Organizational value improvement support system

Abstract

An organizational value improvement support system 1000 capable of supporting an improvement in the value of intangible assets (IACC) created by members of an organization, such as employees of a company, and appropriately managing the intangible assets so as to contribute to the operation of the organization includes at least one processor and a memory, wherein: non-transitory instructions are stored in the memory; the processor is configured such that, when the instructions are executed by the processor, the processor controls an input information generating unit 130, a first inference request generating unit 110, and a first transmitting and receiving unit 120 by executing the instructions; a first input information data group includes IACC information data, intangible resource information data, and performance-related information data; and the input information generating unit 130 includes an IACC information reading unit 131, an intangible resource information reading unit 132, and a performance-related information reading unit 133.

Description

Organizational Value Enhancement Support System

[0001] This disclosure pertains to information technology and artificial intelligence technology for supporting organizational operations, and concerns systems that enhance the value of organizations such as companies. Specifically, this disclosure concerns systems that support the enhancement of intangible assets created by members of an organization, such as employees, and that support the enhancement of organizational value by clarifying the capital classification position of those intangible assets and managing them appropriately within the organization. In this disclosure, "organizational operations" includes "corporate management" as a sub-concept, and "corporate" includes "listed company" as a sub-concept.

[0002] Non-patent document 1 demonstrates the effectiveness of large-scale language models in learning with a few examples as an artificial intelligence technology. In recent years, technologies related to business support using pre-trained generative models, such as large-scale language models, have been rapidly advancing. In this specification, "pre-trained generative models" may sometimes be abbreviated as "generative models." Specific examples of generative models include the large-scale language models mentioned above that generate text, as well as music generation models, image generation models, video generation models, and multimodal models capable of handling multiple data formats.

[0003] Patent Document 1 discloses a matching system that performs matching processing between human resources and projects. The system acquires text data representing the content of the project, identifies one or more project skills related to the project based on the text data, acquires one or more attributes for each of a plurality of human resources, calculates a score for each attribute of each human resource based on each of the project skills and each of the attributes, calculates the score of each human resource based on the scores of the attributes of that human resource, sorts and outputs the plurality of human resources based on the scores of each human resource, and outputs the score of each human resource as a numerical value. The matching system associates one or more normalized skills with each attribute and calculates the score of each attribute based on each of the normalized skills associated with that attribute. Such a matching system may input information including the text data into a large language model and acquire the one or more project skills from the large language model.

[0004] Patent Document 2 discloses an assistance device for real estate management business, which includes a property management unit that manages property information of rental properties in real estate rental, a notification unit that notifies rental staff of rental-related work based on the property information, and a policy proposal unit that proposes measures to promote occupancy of rental properties based on the property information. The property management unit manages property information including the work deadline, rental conditions, and occupancy status related to the rental property, and further includes a guidance unit that displays a guide for the rental property in a virtual space. The property management unit manages property information including the characteristics of the rental property, and the guidance unit generates a response that the guide conveys to the guided person through processing using a language model that includes the inquiry from the guided person to be guided and the characteristics as inputs. This language model has been pre-trained using training data that includes the inquiry and the characteristics as explanatory variables and the response as the target variable.

[0005] Patent Document 3 discloses a program for execution on a computer having a processor and memory, the program causing the processor to perform the following steps: receiving input of an episode experienced by a user and numerical information that quantifies the degree of a predetermined emotion felt by the user at the time of the experience; storing the received episode and numerical information in the memory; using the episode stored in the memory to generate a second prompt for a large-scale language model to generate a question to enrich the episode; inputting the generated second prompt into the large-scale language model to generate the question; outputting the question; receiving the episode modified by the user's operation; storing the received modified episode in the memory; generating a first prompt for a large-scale language model to generate text about the user's strengths using the modified episode and numerical information stored in the memory; inputting the created first prompt into the large-scale language model to generate text about the user's strengths; and outputting the text about the user's strengths.

[0006] Patent Document 4 discloses an information processing system characterized in that it provides instructions to a generator that generates answers based on a trained language model to generate a string extracted from report data including the amount of activity of greenhouse gas emitting activities, as well as the type of activity to be extracted and the scope corresponding to the activity, and the generator is equipped with a generation processing unit that causes the generator to generate the type and the scope.

[0007] Patent Document 5 discloses a back-office support device comprising: a business information management unit that manages business information associated with the attributes of a company and the back-office operations performed by that company; a target attribute acquisition unit that acquires target attributes which are the attributes of a target company; and a business proposal unit that proposes back-office operations to the target company based on a plurality of business information managed by the business information management unit and the target attributes, wherein the business information management unit is configured to manage business information related to the attributes of a company, including the size of the company, and business information related to the attributes of a company, including the fiscal year end month; the target attribute acquisition unit is configured to acquire target attributes of a company, including the size of the company, and target attributes of a company, including the fiscal year end month; and the business proposal unit proposes back-office operations associated with the attributes that match the target attributes in the business information.

[0008] Patent Document 6 discloses an information providing device comprising: a question receiving unit that receives questions; an answer generation unit that causes a language model to generate answers to the questions; a report generation unit that generates a report including the answers generated by the answer generation unit; an information acquisition unit that acquires various information relating to the questions; and a ratio setting unit that sets the proportion of various information relating to the questions in the report generated by the report generation unit, wherein the report generation unit generates a report including the various information at the proportion set by the ratio setting unit.

[0009] Patent Document 7 discloses a control system comprising a control device for controlling an object to be controlled and a language model, wherein the control device comprises a transmission means for transmitting metadata of a function for controlling the object to be controlled to the language model, and a notification means for notifying the language model of a prompt for controlling the object to be controlled, the language model comprises a determination means for determining whether or not to respond to the prompt using the function based on the metadata transmitted by the transmission means and the prompt notified by the notification means, and a presentation means for presenting response information including identification information for identifying the function to the control device when the determination means determines to respond to the prompt using the function, the control device further comprises a control means for controlling the object to be controlled using the response information presented by the presentation means, the object to be controlled includes one of a robot, a sensor, and a plant.

[0010] Patent Document 8 describes a large-scale language model that combines one or more processes in natural language processing, such as morphological analysis, syntactic analysis, semantic analysis, contextual analysis, and intent analysis, to probabilistically predict how likely a word or sentence given as a prompt is to occur in natural language, analyzes the prompt, and predicts and generates a document based on the content of the analyzed prompt. A business support document creation device is disclosed, comprising: a model unit; a document creation prompt generation unit that outputs a prompt to the large-scale language model unit containing content instructing the creation of the business support document as a document based on the classification results; a business pattern formation unit that forms a business pattern for a certain period of time of business performed on the monitored terminal based on the classification results in the operation log classification unit; a business change detection unit that detects qualitative changes in the business performed on the monitored terminal based on the amount of change between the business patterns that are repeatedly formed at each of the certain periods; and a warning information output unit that, when a qualitative change in the business is detected, outputs the monitored terminal that caused the qualitative change, along with the content of the qualitative change, as warning information to the administrator terminal.

[0011] Non-Patent Document 2 provides the <IR> framework as principle-based guidance for companies and other organizations preparing integrated reports. In the <IR> framework, the resources and relationships that an organization uses and influences are collectively referred to as "capital." In the <IR> framework, this capital is classified into "financial capital," "manufacturing capital," "intellectual capital," "human capital," "social and relational capital," and "natural capital." In Non-Patent Document 2, the role of capital is defined as follows: - To serve as part of the theoretical basis for the concepts of value creation, preservation, or impairment. - To serve as a guideline to ensure that an organization considers all forms of capital that it uses or influences.

[0012] Furthermore, Non-Patent Document 2 contains the following description regarding organizations: The core of an organization lies in its business model. In a business model, various forms of capital are used as inputs and transformed into outputs (products, services, by-products, and waste) through business activities. An organization's business activities and outputs produce outcomes as an impact on capital. The adaptability of a business model to change (e.g., in terms of the availability, quality, and economics of inputs) can influence the long-term continuity of an organization.

[0013] Patent No. 7574522 Patent No. 7573923 Patent No. 7573330 Patent No. 7569125 Patent No. 7557812 Patent No. 7519138 Patent No. 7576729 Patent No. 7572760

[0014] Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei, Language Models are Few-Shot Learners, https: / / arxiv.org / pdf / 2005.14165, arXiv:2005.14165, 22 Jul 2020.IntegratedReporting#Framework#061024.pdf(https: / / integratedreportingsa.org / ircsa / wp-content / uploads / 2021 / 01 / InternationalIntegratedReportingFramework.pdf)

[0015] This disclosure aims to provide an organizational value enhancement support system that uses pre-trained generative models, such as large-scale language models, to help enhance the value of intangible assets created by members of an organization, such as employees, and to enable the appropriate management of such intangible assets to contribute to the operation of the organization. This disclosure also aims to clarify the relationship between the five types of capital (human capital, intellectual capital, manufactured capital, social / relational capital, and natural capital; hereinafter, these types of capital are collectively referred to as "non-financial capital" in this disclosure) and the intangible assets created by members, from the perspective of appropriately managing the above. Furthermore, this disclosure also aims to provide a means of quantitatively evaluating non-financial capital.

[0016] The disclosure provided to solve the above problems includes the following aspects.

[0017] (1) The present disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control, by the execution of the instruction, an input information generation unit that collects data constituting a first input information data group, a first inference request generation unit that automatically generates first inference request data using data of a plurality of pieces of information included in the first input information data group as input, and a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model. The first input information data set comprises: IACC information data stored in the IACC information database, which includes IACC information, which is intangible assets created by members belonging to the organization; intangible resource information data stored in the intangible resource information database, which includes information on intangible resources belonging to the same type of non-financial capital as the type of non-financial capital to which the IACC belongs, among the intangible resources owned by the organization to which the member belongs; and performance-related information data stored in the performance-related information database, which includes target values ​​for the organization's financial and performance indicators. The first inference request included in the first inference request data improves the financial and performance indicators included in the performance-related information data based on the IACC information data and the intangible resource information data. The first proposal is generated, and the input information generation unit includes an IACC information reading unit that identifies which of the IACC information data stored in the IACC information database will be read and reads the identified IACC information data from the IACC information database; an intangible resource information reading unit that identifies which of the intangible resource information data stored in the intangible resource information database will be read based on the identified IACC information data and reads the identified intangible resource information data from the intangible resource information database; and a performance-related information reading unit that identifies the financial and performance indicators that have been determined to be targets for improvement and generates performance-related information data including target values ​​for the identified financial and performance indicators.

[0018] In this disclosure, “Organization” refers to a group of people or resources formed to achieve a specific purpose, and includes a variety of forms, such as corporations, non-profit organizations like hospitals, and public institutions like national university corporations. In this disclosure, “Constituent members” refers to the personnel belonging to an organization, and if the organization is a corporation, it includes employees and directors, and may also include external contractors under contract with the organization.

[0019] In this disclosure, "individual skills" refers to the intellectual assets created by members, including knowledge, skills, and abilities (also referred to as "KSAs" in this specification), and ideas conceived based on these KSAs. Furthermore, intangible assets created by members, such as useful intangible things like KSAs possessed by employees, or ideas conceived based on these intangible things, are referred to as "Intangible Assets Created by Constituent Members," a concept that includes the above-mentioned "individual skills," and are abbreviated as "IACC" in this disclosure. The person who creates an IACC is the inventor if the IACC is an invention, the inventor if the IACC is a utility model, and the creator if the IACC is a design or copyrighted work, but in this disclosure, they are collectively referred to as the "Creator."

[0020] In this disclosure, "intangible resources" refers to non-physical information and knowledge used by an organization to create value (specific examples include technical information, know-how, data, algorithms, design information, brands, etc.), regardless of whether or not they are recognized as intangible assets for accounting purposes. These intangible resources mostly consist of IACC created by members within the organization, but may also be acquired through licensing or purchase. Such internal valuations (monetary indicators) that are clearly defined and recognized as "intangible assets" for accounting purposes may be included in the explanation of financial capital in the capital classification described in Non-Patent Literature 2.

[0021] In this disclosure, “intangible resource information” refers to an intangible object that represents an intangible resource, and may include information describing the organization’s contents, information indicating the type of non-financial capital to which the intangible resource belongs, and metadata such as identifiers, origins, versions, authority, and confidentiality levels. An example of how intangible resource information is displayed is shown in Figure 7. “Intangible resource information data” is a data structure that makes intangible resource information mechanically storable, transmittable, and processable. Intangible resource information can be directly referenced, generated, updated, and deleted (CRUD) as a data structure, recorded on a storage medium, transmitted over a communication channel, and processed by a processing device.

[0022] (2) The input information generation unit may have a data group generation unit that generates the first input information data group, which includes the read IACC information data, the read intangible resource information data, and the read performance-related information data. The first inference request generation unit may have a first information identification unit that takes the first input information data group generated by the data group generation unit as input and identifies the plurality of information included in the first input information data group.

[0023] (3) The first inference request generation unit may include a first prompt generation unit that automatically generates the first inference request data, including the execution of a process that automatically places each of the plurality of pieces of information included in the first input information data group into a predetermined target field and generates management data.

[0024] (4) The IACC information reading unit may include: an authorization confirmation unit that identifies an operator attempting to access the IACC information data and confirms the access authority of the identified operator; an access control unit that enables the operator to access the IACC information data stored in the IACC information database within the scope of the access authority confirmed by the authorization confirmation unit; and a reading unit that identifies the IACC information data that the operator has decided to include in the first input information data group from the IACC information data that the operator can access, and reads the identified IACC information data from the IACC information database.

[0025] (5) In the organizational value improvement support system described in (4) above, the access control unit may generate display filter instruction data that allows the IACC information database to display to the operator the self-IACC created by the identified operator and other IACCs not created by the identified operator but which the operator is permitted to view, and transmit the display filter instruction data to the IACC information database.

[0026] (6) In the organizational value improvement support system described in (5) above, the input information generation unit may have a citation notification generation unit that generates citation notification data to notify the creator of the other party's IACC of the decision when the operator decides to include the other party's IACC in the first input information data group.

[0027] (7) The organizational value improvement support system described in (6) above may have a citation notification count unit that records how many of the citation notification data have been generated for each of the IACC information data.

[0028] (8) The IACC information data may include information indicating the type of non-financial capital to which the IACC belongs.

[0029] (9) In the organizational value improvement support system described in (8) above, the intangible resource information reading unit may take the identified IACC information data as input to identify the type of non-financial capital to which the IACC belongs, and read from the performance-related information database the performance-related information data of the same type as the identified type of non-financial capital from the performance-related information database.

[0030] (10) The first input information data group may include personal emotion information data that includes information indicating a first emotion which is an emotion that the member expects when performing their duties. The first inference request may include generating suggestions for behavioral indicators that are in line with the first emotion and contribute to improving the financial and performance indicators. The input information generation unit may include an emotion information identification unit that identifies the first emotion included in the personal emotion information data. The first inference request generation unit may take data including the first emotion identified by the emotion information identification unit as input.

[0031] (11) In the organizational value improvement support system described in (10) above, the emotion information identification unit may include an emotion display unit that generates emotion display data that allows for the selection of a predetermined number of emotions, and an emotion determination unit that determines which of the number of emotions displayed in the emotion display unit has been selected as the first emotion.

[0032] (12) The first input information data set may further include auxiliary information data stored in an auxiliary information database, which includes current information of the organization. The first inference request may refer to the auxiliary information data when generating the first proposal. The input information generation unit may have an auxiliary information reading unit that identifies which of the auxiliary information data stored in the auxiliary information database will be read, and reads the identified auxiliary information data from the auxiliary information database.

[0033] (13) The auxiliary information reading unit described in (12) above may include a reading request generation unit that determines which of the auxiliary information data stored in the auxiliary information database will be read, generates a reading request to the auxiliary information database, and transmits the reading request to the auxiliary information database, and a data reading unit that receives the auxiliary information data prepared in accordance with the reading request from the auxiliary information database.

[0034] (14) In the organizational value improvement support system described in (13) above, the IACC information data includes data indicating the type of non-financial capital to which the IACC belongs, and the read request generation unit may determine that the auxiliary information data, which includes auxiliary information of the same type as the type of non-financial capital to which the IACC belongs included in the IACC information data, is the target of the read request.

[0035] (15) The Disclosure includes an organizational value improvement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input by the execution of the instruction, a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model, and a comparative display generation unit. The first input information data group includes IACC information data which includes information in which IACC, which is an intangible asset created by a member of the organization, is described in a predetermined first format. The first inference request included in the first inference request data includes generating a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group. The comparative display generation unit takes the first inference result data and the IACC information data as input, generates comparative display data that displays the information contained in the first inference result data in a first format, makes it possible to compare it with the information contained in the IACC information data, and outputs the comparative display data.

[0036] (16) The Disclosure includes an organizational value improvement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input by the execution of the instruction, a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model, and a first IACC information registration unit. The first input information data group is data stored in an IACC information database and includes IACC information data in which IACC, which is an intangible asset created by a member of the organization, is described in a predetermined first format. The first inference request included in the first inference request data generates a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group. The first IACC information registration unit generates draft IACC information data in which the information contained in the first inference result data is described in the first format, and, on the condition that an acceptance instruction for the draft IACC information data is entered, it performs a process that includes replacing the draft IACC information data with the IACC information data and saving it in the IACC information database.

[0037] (17) In the organizational value improvement support system described in (16) above, when a correction instruction is input for the first inference result data, the first IACC information registration unit reflects the correction instruction in the information contained in the first inference result data, generates corrected IACC information data in which the reflection result is written in a format corresponding to the display of the IACC information data, and, subject to the condition that an acceptance instruction is input for the corrected IACC information data, the corrected IACC information data may be replaced with the IACC information data and saved as draft IACC information data.

[0038] (18) In the organizational value improvement support system described in (16) above, the first inference request may generate publicly known proposal information including the result of examining whether the first proposal is publicly known or not. The system may also include a confidentiality management setting unit that takes as input the IACC information data to be replaced and stored in the IACC information database generated by the first IACC information registration unit and the first inference result data, determines from the publicly known proposal information whether the first proposal is publicly known or not, and if it is determined that the first proposal is not publicly known, performs processing including setting the management attribute of the IACC information data to data including a candidate for the object of industrial property rights.

[0039] (19) The organizational value improvement support system described in (18) above may include an information management unit that generates information management instruction data for classifying and managing the IACC information database and transmits it to the IACC information database. The information management instruction data may include a first instruction for classifying and managing the IACC information data based on the management attributes.

[0040] (20) In the organizational value improvement support system described in (19) above, the IACC information data includes data indicating the type of non-financial capital to which the IACC belongs, and the information management instruction data may also include a second instruction for classification and management based on the type of non-financial capital to which the IACC belongs.

[0041] (21) In the organizational value enhancement support system described in (20) above, the first instruction may be an instruction that classifies from the perspective of the confidentiality level of the IACC. The second instruction may be an instruction that classifies from the perspective of the type of non-financial capital to which the IACC belongs.

[0042] (22) In the organizational value enhancement support system described in (21) above, the first instruction may include classification in terms of whether it belongs to the category of a candidate subject of industrial property rights, a trade secret, or information that does not require confidentiality protection.

[0043] (23) The organizational value improvement support system described in (8) above may further include an initial inference request generation unit that automatically generates initial inference request data using the IACC basic information data as input, and an initial transmission / reception unit that transmits the initial inference request data to an initial generation model, which is a pre-trained generation model, and receives initial inference result data from the initial generation model. The IACC basic information data is the basic data of the IACC information data and may include a plurality of partial information constituting the information of the IACC. The initial inference request included in the initial inference request data may include generating a proposal regarding the type of non-financial capital to which the IACC should belong as a result of analyzing the IACC basic information data. The initial inference request generation unit includes an IACC partial information identification unit that receives the IACC basic information data and identifies the plurality of partial information, and an initial prompt generation unit that executes a process of automatically arranging the corresponding plurality of partial information in each of the target fields of an initial format, where the target fields in which each of the plurality of partial information should be arranged are pre-specified format data, and automatically generates the initial inference request data.

[0044] (24) In the organizational value improvement support system described in (23) above, the initial inference request generation unit may further include an input display generation unit that executes a process including generating input display data having a plurality of input fields corresponding to the plurality of partial information and outputs the input display data. The IACC partial information identification unit may receive, as input, data including the plurality of partial information input into the plurality of input fields, generate a plurality of data corresponding to each of the plurality of partial information, and output a group of data sets including the plurality of data to the initial prompt generation unit.

[0045] (25) In the organizational value improvement support system described in (1) above, the intangible resource information data includes data indicating the type of non-financial capital to which the intangible resource belongs, and the system further comprises: an intangible resource inference request generation unit that generates intangible resource inference request data as input to intangible resource basic information data which is basic information of the intangible resource information data and includes information on the intangible resource; and an intangible resource transmission / reception unit that transmits the intangible resource inference request data to an intangible resource generation model which is a pre-trained generation model and receives intangible resource inference result data from the intangible resource generation model. The intangible resource inference request included in the intangible resource inference request data may generate a proposal regarding the type of non-financial capital to which the intangible resource should belong as a result of analyzing the intangible resource basic information data. The intangible resource inference request generation unit may include an intangible resource information input unit that receives the intangible resource basic information data and identifies the information of the intangible resource included in the intangible resource basic information data, and an intangible resource prompt generation unit that automatically generates the intangible resource inference request data, including the execution of a process to automatically place the information of the intangible resource into the target field of an intangible resource format, which is a format data in which the target field where the information of the intangible resource should be placed is predetermined.

[0046] (26) In the organizational value improvement support system described in (8) above, the first reasoning request may include, in the first proposal, an improvement proposal from the perspective of increasing human capital if the IACC information data includes human capital-related information relating to systems and institutions for developing the knowledge, skills, and abilities of the members (first case), and in the first proposal, an improvement proposal from the perspective of increasing at least one of the manufacturing capital, social and relational capital, and natural capital if the IACC information data does not include the human capital-related information (second case). In the first case above, the first proposal may include an improvement proposal from the perspective of increasing non-financial capital other than human capital (intellectual capital, manufacturing capital, social and relational capital, and natural capital), or an improvement proposal from the perspective of increasing the organization's management assets, such as know-how including trade secrets.

[0047] (27) In the organizational value improvement support system described in (1) above, the first inference requirement may include generating public knowledge proposal information including the examination result of whether the first proposal is publicly known.

[0048] (28) In the organizational value improvement support system described in (27) above, when the public knowledge proposal information has a proposal that it is publicly known, the first inference requirement indicates public knowledge information determined to include the first proposal, and when the public knowledge proposal information has a proposal that it is not publicly known, it may include indicating public knowledge information determined to be closest to the first proposal.

[0049] (29) In the organizational value improvement support system described in (1) above, at least a part of the data stored in the IACC information database may be positioned as data stored in the intangible resource information database.

[0050] (30) In the organizational value improvement support system described in (29) above, the IACC information database and the intangible resource information database may be integrated.

[0051] (31) In the organizational value improvement support system described in (29) above, it may include an information management unit that generates information management instruction data for classifying and managing the IACC information data and transmits it to the IACC information database. The information management instruction data may include an applicability instruction indicating whether the IACC information data may be stored in the intangible resource information database as the intangible resource information data.

[0052] (32) In the organizational value improvement support system described in (31) above, the information management instruction data may include a secrecy management instruction indicating the degree of secrecy management in the intangible resource information database of the information included in the intangible resource information data.

[0053] (33) The organizational value enhancement support system described in (1) above may include an intangible resource information management unit that generates disclosure management instruction data indicating whether or not the intangible resource information data stored in the intangible resource information database can be disclosed to outside the organization and the extent of disclosure, and transmits the disclosure management instruction data to the intangible resource information database.

[0054] (34) The present disclosure includes an organizational value improvement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input upon execution of the instruction, a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model, and a publicly known indication generation unit. The first input information data group is data stored in an IACC information database and includes IACC information data in which IACC, which is an intangible asset created by a member of the organization, is described in a predetermined first format. The first inference request included in the first inference request data includes generating a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group, and generating publicly known proposal information including the results of an examination of whether the first proposal is publicly known or not. The public-private status indication generation unit takes the first inference result data as input, determines from the public-private status proposal information whether the first proposal is public or not, and if it determines that the first proposal is not public, it performs a process that includes generating non-public status indication data that includes a notice indicating that the first proposal may be confidential information.

[0055] (35) The present disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control an initial IACC information registration unit which, upon execution of the instruction, executes a process including storing IACC information data, which includes information describing IACC, an intangible asset created by a member of the organization, in a predetermined first format, in an IACC information database; an initial inference request generation unit which generates initial inference request data, which is basic information of the IACC information data and includes information of the IACC, as input; an initial transmission / reception unit which transmits the initial inference request data to an initial generation model which is a pre-trained generation model and receives initial inference result data from the initial generation model; and an initial publicly known indication generation unit which takes the initial inference result data as input. The initial inference request included in the initial inference request data may generate initial publicly known proposal information which includes the results of an examination of whether or not the IACC is publicly known. The initial public information indication generation unit determines from the initial public information proposal information whether the IACC is public or private, and if it determines that the IACC is private, it performs a process that includes generating initial non-public information indication data that includes a notice indicating that the IACC may be confidential information.

[0056] (36) In the organizational value improvement support system described in (35) above, if the initial public knowledge proposal information has a proposal that it is publicly known, the system may show publicly known information that is determined to include the IACC, and if the initial public knowledge proposal information has a proposal that it is not publicly known, the system may show publicly known information that is determined to be closest to the IACC.

[0057] (37) The present disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control an initial IACC information registration unit which, upon execution of the instruction, executes a process including storing IACC information data, which includes information describing IACC, an intangible asset created by a member of the organization, in a predetermined first format, in an IACC information database; an initial inference request generation unit which generates initial inference request data, which is basic information of the IACC information data and includes information of the IACC, as input; an initial transmission / reception unit which transmits the initial inference request data to an initial generation model which is a pre-trained generation model and receives initial inference result data from the initial generation model; and an initial confidentiality management setting unit which takes the initial inference result data as input. The initial inference request included in the initial inference request data may generate initial publicity proposal information which includes the results of a study on whether or not the IACC is publicly known. The initial confidentiality management setting unit determines from the initial publicly known proposal information whether the IACC is publicly known or not, and if it determines that the IACC is not publicly known, it performs a process that includes setting the management attribute of the IACC information data to data that includes a candidate for the subject of industrial property rights.

[0058] (38) The present disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control an initial IACC information registration unit which, upon execution of the instruction, executes a process including storing IACC information data in an IACC information database, which includes information describing IACC, an intangible asset created by a member of the organization, in a predetermined first format, and information indicating the type of non-financial capital to which the IACC belongs; an initial inference request generation unit which generates initial inference request data as input to IACC basic information data which is basic information of the IACC information data and includes information of the IACC; an initial transmission / reception unit which transmits the initial inference request data to an initial generation model which is a pre-trained generation model and receives initial inference result data from the initial generation model; and a capital representation generation unit which takes the initial inference result data as input. The initial inference request included in the initial inference request data has the function of generating a proposal regarding the type of non-financial capital to which the IACC should belong as a result of analyzing the IACC basic information data. The capital presentation generation unit performs a process that includes identifying the proposed non-financial capital type from the initial inference result data and generating capital presentation data for displaying the identified non-financial capital type. The initial IACC information registration unit performs a process that includes identifying the proposed non-financial capital type from the initial inference result data and generating IACC information data based on the identified non-financial capital type and the IACC basic information data.

[0059] (39) The present disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control an intangible resource information registration unit which, upon execution of the instruction, performs processing including storing intangible resource information data in an intangible resource information database which includes information on intangible resources owned by the organization and data indicating the type of non-financial capital to which the intangible resources should belong; an intangible resource inference request generation unit which generates intangible resource inference request data as input to intangible resource basic information data which is basic information for the intangible resource information data and includes information on the intangible resources; and an intangible resource transmission / reception unit which transmits the intangible resource inference request data to an intangible resource generation model which is a pre-trained generation model and receives intangible resource inference result data from the intangible resource generation model. The intangible resource inference request included in the intangible resource inference request data includes generating a proposal for the type of non-financial capital to which the intangible resources should belong as a result of analyzing the intangible resource basic information data. The intangible resource information registration unit takes the intangible resource inference result data and the intangible resource basic information data as input, identifies the proposed type of non-financial capital from the intangible resource inference result data, and performs a process that includes generating the intangible resource information data based on the identified type of non-financial capital and the intangible resource basic information data.

[0060] (40) In the organizational value improvement support system described in (39) above, the intangible resource information data may include information on SDGs targets related to the intangible resource. The intangible resource inference request may include generating proposals for SDGs targets related to the intangible resource as a result of analyzing the intangible resource basic information data.

[0061] (41) In the organizational value improvement support system described in (40) above, the intangible resource information registration unit may identify the proposed SDGs targets from the intangible resource inference result data and include information on the identified SDGs targets in the intangible resource information data.

[0062] (42) The Disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when such instructions are executed by the processor, the processor is configured to control an intangible resource information utilization management unit by the execution of the instructions, thereby managing the use of intangible resource information contained in intangible resource information data within the organization. The intangible resource information is an intangible object representing an intangible resource owned by the organization, and includes information describing the content of the intangible resource and attribute information indicating whether it belongs to non-financial capital, and the intangible resource information data is a data structure in which the intangible resource information can be mechanically stored, transmitted, and processed.

[0063] (43) In the organizational value improvement support system described in (42) above, the intangible resource information data is stored in an intangible resource information database, and the intangible resource information utilization management unit may obtain the intangible resource information data to be managed from the intangible resource information database.

[0064] (44) In the organizational value improvement support system described in (42) above, the intangible resource information utilization management unit may include a history management unit that performs processing including generating utilization history data including the utilization history of the intangible resource information.

[0065] (45) In the organizational value improvement support system described in (44) above, the history management unit may include a history recording unit that performs processing including recording the used intangible resource information as contributed intangible resource information, and a contribution amount calculation unit that performs processing including calculating the contribution amount of the contributed intangible resource information using the organization's activity record data.

[0066] (46) In the organizational value improvement support system described in (45) above, the contribution amount calculation unit may calculate the contribution amount based on the intangible resource information-derived performance that has been and / or is expected to be generated in connection with the contribution intangible resource information, and the contribution rate of the contribution intangible resource information in the intangible resource information-derived performance.

[0067] (47) In the organizational value improvement support system described in (45) above, the contribution amount calculation unit further comprises a contribution inference request unit, the contribution inference request unit may take the contribution intangible resource information and the organization's activity record data as input to create calculation inference request data including an inference request to a calculation generation model, transmit the calculation inference request data to the calculation generation model, and perform a process including receiving contribution inference result data including a proposed contribution amount.

[0068] (48) In the organizational value improvement support system described in (47) above, the calculation generation model may, at the time of inference, refer to a performance-related information database in which data including information related to the performance of the organization is stored, and / or an intangible resource information database in which the intangible resource information data is stored, as instructed by the contribution inference request unit.

[0069] (49) In the organizational value improvement support system described in (44) above, the intangible resource information utilization management unit may further include a value calculation unit that performs processing including calculating the intangible resource value, which is the internal valuation amount of the intangible resource information, based on the utilization history data.

[0070] (50) In the organizational value enhancement support system described in (49) above, the value calculation unit may calculate the intangible resource value by allocating the amount to be allocated, which is set based on the difference between the market capitalization of the organization and the identifiable net assets, to each intangible resource information.

[0071] (51) In the organizational value enhancement support system described in (50) above, if the organization is a stock company, the total value of shares may be used as the market capitalization and the most recently published balance sheet may be used as the identifiable net assets.

[0072] (52) In the organizational value improvement support system described in (49) above, the intangible resource information utilization management unit may include a classification setting unit that performs processing including classifying the intangible resource information into a plurality of categories, and a category value calculation unit that performs processing including calculating a category value which is the total internal valuation amount for each of the categories based on the intangible resource value calculated by the value calculation unit.

[0073] (53) In the organizational value improvement support system described in (52) above, the classification setting unit may perform classification that includes the degree of confidentiality management of the intangible resource information data and the type of non-financial capital to which the intangible resource information belongs.

[0074] (54) In the organizational value improvement support system described in (53) above, the classification setting unit may classify the intangible resource information data into a category of information that can be disclosed and a category of information that cannot be disclosed, based on the degree of confidentiality management.

[0075] (55) In the organizational value enhancement support system described in (54) above, the intangible resource information utilization management unit may further comprise an organizational value financial statement preparation unit. The organizational value financial statement preparation unit may perform processing that includes generating OV-B / S data for creating an organizational value balance sheet (OV-B / S) defined by displaying a sustainable assets section after the assets section and a non-financial capital section after the capital section in the balance sheet. The sustainable assets section may show the category value of the disclosed information category and the category value of the non-disclosed information category, and the non-financial capital section may show the category value of the category corresponding to each type of non-financial capital.

[0076] (56) In the organizational value enhancement support system described in (42) above, the intangible resource information utilization management unit may include a PBR information provision creation unit that, when the organization is a stock company, performs processing including creating PBR information provision data to notify the organization when the organization's price-to-book ratio (PBR) is less than 1. In this case, if the intangible resource information utilization management unit is greater than 1, it may indicate the non-financial capital and / or sustainable assets that contribute significantly to increasing the price-to-book ratio (PBR).

[0077] (57) In the organizational value improvement support system described in (55) above, the intangible resource information utilization management unit may include an improvement proposal inference request unit. The improvement proposal inference request unit may take the OV-B / S data as input, generate improvement inference request data including an inference request to an improvement generation model, transmit the improvement inference request data to the improvement generation model, and perform processing including receiving improvement inference result data including proposals to increase the sustainable assets and / or the non-financial capital. The improvement inference result data may include proposals indicating the non-financial capital and / or the sustainable assets that contribute most to increasing the price-to-book ratio (PBR).

[0078] (58) In the organizational value improvement support system described in (57) above, the improvement generation model may, at the time of inference, refer to a performance-related information database containing the organization's performance information and the organization's value information, and / or an intangible resource information database storing the intangible resource information data, in accordance with instructions from the improvement proposal inference request unit.

[0079] (59) In the organizational value improvement support system described in (57) above, if the organization is a stock company, the inference request included in the improvement inference request data may be a request for proposals to increase the price-to-book ratio of the organization.

[0080] (60) In the organizational value improvement support system described in (42) above, the intangible resource information utilization management unit may include a utilization proposal unit that performs processing including proposing the use of the intangible resource information to the operator of the utilization input / output device.

[0081] (61) In the organizational value improvement support system described in (60) above, the utilization proposal unit may include a contribution candidate inference request unit. The contribution candidate inference request unit may generate proposal inference request data by taking data including information on the organization's planned activities as input. The proposal inference request data may include an inference request that asks the proposal generation model to propose contribution candidate intangible resource information, which is intangible resource information that is expected to contribute to improving the value of the organization. Processing may be performed which includes transmitting the proposal inference request data to the proposal generation model and receiving inference result data including the contribution candidate intangible resource information.

[0082] (62) In the organizational value improvement support system described in (61) above, the proposal generation model may, at the time of inference, refer to a performance-related information database that stores data including information on the organization's planned activities, and / or an intangible resource information database that stores the intangible resource information data, based on instructions from the contribution candidate inference request unit.

[0083] (63) In the organizational value improvement support system described in (61) above, the intangible resource information utilization management unit may be configured to generate internal management instruction data indicating the degree of confidentiality management of the intangible resource information data, and to manage the intangible resource information data confidentially based on the internal management instruction data.

[0084] (64) In the organizational value improvement support system described in (63) above, the utilization proposal unit may include a proposal restriction setting unit. The proposal restriction setting unit may identify organizational members involved in the activity plan, determine the range of the intangible resource information data that the identified organizational members can access based on the internal management instruction data, and perform processing that enables the utilization proposal unit to select the candidate intangible resource information for contribution using the intangible resource information included within that range as the population.

[0085] (65) In the organizational value improvement support system described in (61) above, the intangible resource information utilization management unit may include a contribution candidate selection unit. The contribution candidate selection unit may generate utilization display data for displaying the contribution candidate intangible resource information on the utilization input / output device and transmit it to the utilization input / output device, input the intangible resource information selected by the operator from the utilization input / output device, generate history management data indicating that the selected intangible resource information is subject to history management, and output the history management data to a history management unit which performs a process that includes generating utilization history data including the utilization history of the intangible resource information.

[0086] (66) The disclosure includes an organizational value enhancement support system comprising at least one processor and memory. The memory stores non-temporary instructions, and when such instructions are executed by the processor, the processor is configured to perform the following processes (i) to (iii) as a value allocation calculation unit upon execution of the instructions: (i) Identifying an operator who requests access to IACC information data, which includes data stored in the IACC information database and contains information on IACCs that are intangible assets created by members belonging to an organization; (ii) For other IACCs that have not been created by the operator but are permitted to be viewed by the operator, determining the number of times the other IACC will be cited in response to input data indicating that the operator will cite the other IACC in order to create a new IACC; (iii) Defining the value points of the other IACC as the number of citations plus 1, and calculating the value allocation of the other IACC by apportioning the total internal valuation of the IACC according to the ratio of the value points to the total value points of the IACCs stored in the IACC information database.

[0087] (67) In the organizational value improvement support system described in (66) above, the processor may be configured to further perform the following (iv) as the value allocation calculation unit: (iv) Create display data for displaying the other party's IACC and the value allocation of the other party's IACC, and output it to a display device.

[0088] (68) In the organizational value improvement support system described in (66) above, the processor may, when executing the processing of (iii) as the value allocation calculation unit, execute the process of setting the total internal valuation of non-financial capital obtained by subtracting the total amount of financial assets from the market capitalization of the organization as the total internal valuation of IACC.

[0089] (69) In the organizational value improvement support system described in (68) above, the processor may be configured to further perform the following process (v) as the value allocation calculation unit: (v) to obtain the average value allocation by dividing the total internal valuation of the non-financial capital by the total value points, which is the sum of the value points of all the IACC information data that may be subject to calculation.

[0090] (70) In the organizational value improvement support system described in (69) above, the processor may be configured to further perform the following (vi) as the value allocation calculation unit: (vi) creating display data for displaying the average value allocation and the total internal valuation of non-financial capital, and outputting it to a display device.

[0091] This disclosure provides a system for supporting organizational value enhancement that increases the value of IACC (Intangible Assets Created by Organizational Members), supports organization members in acting based on such intangible assets, and enables the proper management of intangible assets. Furthermore, according to a preferred embodiment of this disclosure, it is possible to reduce the stress that organization members may experience when using pre-trained generative models, to enable organization members to feel proactive even when using pre-trained generative models, and to allocate and manage intangible assets (intangible resources) within the organization as appropriate non-financial capital.

[0092] This is a block diagram illustrating an organizational value improvement support system having an organizational value improvement support device according to one embodiment of this disclosure. This is a flowchart (1) illustrating the information processing performed by the organizational value improvement support device according to one embodiment of this disclosure. This is a flowchart (2) illustrating the information processing performed by the organizational value improvement support device according to one embodiment of this disclosure. This is a flowchart (3) illustrating the information processing performed by the organizational value improvement support device according to one embodiment of this disclosure. This is a flowchart (4) illustrating the information processing performed by the organizational value improvement support device according to one embodiment of this disclosure. This is a diagram showing an example of IACC information display. This is a diagram showing an example of intangible resource information display. This is a diagram showing a specific example in which the information contained in the first inference result data and the information contained in the IACC information data are displayed in a comparative manner on the image display unit, which is the output unit of the first input / output device. This is an explanatory diagram (1) of one embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (2) of one embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (3) of one embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (4) of one embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (5) of one embodiment of the organizational value improvement support program according to one embodiment of the present disclosure. This is an explanatory diagram (6) of one embodiment of the organizational value improvement support program according to one embodiment of the present disclosure. This is an explanatory diagram (7) of one embodiment of the organizational value improvement support program according to one embodiment of the present disclosure. This is a block diagram illustrating an organizational value improvement support system having an organizational value improvement support device according to one of the other embodiments of the present disclosure. This is a diagram illustrating the functions of the intangible resource information management unit. This is a diagram illustrating the functions of the auxiliary information management unit. This is a diagram illustrating an organizational value improvement support device that executes the entry process. This is a diagram illustrating an organizational value improvement support device that executes the intangible resource management process. This is a block diagram illustrating the functions of the input information generation unit. This is a block diagram illustrating the functions of the initial inference request generation unit. This is a block diagram illustrating the functions of the intangible resource inference request generation unit. This is a block diagram illustrating an organizational value improvement support system having an organizational value improvement support device according to one of the other embodiments of the present disclosure. This is an explanatory diagram of organizational value financial statements.This figure shows a specific example of the display of intangible resource information data, which includes the corresponding IACC value allocation as a display element. This figure shows a specific example of corporate value financial statements. This is an explanatory diagram (1) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (2) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (3) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (4) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (5) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (6) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (7) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (8) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (9) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (10) of another embodiment of the organizational value improvement support program according to one embodiment of this disclosure. This is an explanatory diagram (part 11) of another embodiment of the organizational value improvement support program according to one embodiment of the present disclosure.

[0093] The embodiments of this disclosure will be described below with reference to the drawings.

[0094] Figure 1 is a block diagram illustrating an organizational value improvement support system having an organizational value improvement support device according to one embodiment of this disclosure. In the following description of embodiments, a large-scale language model will be described as an example of a pre-trained generative model.

[0095] As shown in Figure 1, the organizational value improvement support system 1000 according to one embodiment of the present disclosure comprises an organizational value improvement support device 100, a first large-scale language model (first generation model 910), an initial large-scale language model (initial generation model 920), and an intangible resource large-scale language model (intangible resource generation model 930), which are pre-trained generation models, an IACC (Intangible Assets created by Constituent members) information storage IACC information database 300 (in Figure 1, "database" is abbreviated as "DB"), an intangible resource information database 310 for storing intangible resource information, a performance-related information database 320 for storing performance-related information, an auxiliary information database 330 for storing auxiliary information such as current events information, an SDGs database 340 for storing SDGs target information, a first input / output device 400 used by members such as employees, and an initial input / output device 410.

[0096] The organizational value improvement support system 1000 includes at least one processor and memory, the memory which stores non-temporary instructions, and when such instructions are executed by the processor, the processor is configured to perform information processing by the first inference request generation unit 110, etc., as described later, in response to the execution of the instructions. In this embodiment, as one specific example, the organizational value improvement support system 1000 includes an organizational value improvement support device 100 which includes a processor and memory.

[0097] The Organizational Value Improvement Support Device 100 comprises the following parts in relation to information processing (hereinafter referred to as the "brush-up process") for refining IACC information data and saving it in the IACC information database 300: • A first inference request generation unit 110 that generates first inference request data. • A first transmission / reception unit 120 that transmits and receives data with the first generation model 910. • An input information generation unit 130 that generates a first group of input information data to be input to the first inference request generation unit 110. • A comparison display generation unit 140 that generates data for displaying the inference results of the first generation model 910. • A publicly known display generation unit 150 that generates non-public display data based on the inference results of the first generation model 910. • A confidentiality management setting unit 160 that performs confidentiality management information processing based on the inference results of the first generation model 910. • A first IACC information registration unit 170 that performs processing for saving IACC information data in the IACC information database 300 based on the judgment results of the members regarding the inference results of the first generation model 910.

[0098] One specific example of the organizational value enhancement support device 100 is a computer device having a semiconductor device and a control unit that performs information processing, wherein the control unit comprises the above-mentioned parts. For example, the semiconductor device that performs information processing may be a processor. The processor may be one or more single-chip or multi-chip microprocessors designed and / or manufactured by Intel Corporation, Advanced Micro Devices, Inc. (AMD), Arm Holdings (Arm), Apple Computer, etc. Examples of microprocessors include Intel Corporation's CELERON®, PENTIUM®, CORE i3, CORE i5, CORE i7, AMD's AMD OPTERON®, PHENOM, ATHLON, TURION, RYZEN®, and Arm's CORTEX-A, CORTEX-R, CORTEX-M ("CORTEX" is a registered trademark of Arm).

[0099] The first inference request generation unit 110 generates first inference request data using the data of the information included in the first input information data group generated by the input information generation unit 130 as input.

[0100] In this embodiment, the input information generation unit 130 collects specific IACC information data from the IACC information database 300 based on specified data input from the first input / output device 400. The specified data includes an instruction that designates specific IACC information data stored in the IACC information database 300 as the target of information processing performed by the organizational value improvement support device 100.

[0101] The IACC information data includes IACC information, which is information describing IACC, an intangible asset created by a member, in a predetermined first format. In this embodiment, it also includes information indicating the type of non-financial capital to which IACC belongs (hereinafter also referred to as "first non-financial capital"). Since IACC is a useful intangible asset created by a member, it is used in the organization's activities (business activities). Therefore, IACC can also be positioned as capital within the organization. When IACC is used within the organization, it can be classified into one of five types of non-financial capital. If IACC is used as the subject of a license-out or sale, it will take on the characteristics of financial capital.

[0102] The first format includes various forms. An example of the first format that is not limited to this is a format having multiple target fields in which text information and image / video information are placed, and specific examples of multiple target fields that are not limited to this are as follows: (A) Strengths / Selling Points: This target field contains text that concisely describes the characteristics of the IACC, such as the advantages of the IACC over other IACCs. (B) Overview: This target field contains text that describes the specific content of the IACC. (C) Purpose / Aim: This target field contains text that describes the purpose and aim set when conceiving the IACC. (D) Results or Effects: This target field contains text that describes the results or effects brought about by the IACC. (E) Concerns / Challenges: This target field contains text that describes concerns and challenges recognized as a result of conceiving the IACC. (F) Type of Capital: This target field contains text that describes the type of non-financial capital to which the IACC belongs. (G) Status: This field contains text or other information describing the confidentiality management of the IACC. An example of how IACC information described in the first format, which has the target field described in the specific example above, is displayed is shown in Figure 6.

[0103] The creator of the IACC information data (the "initial operator," described later) and the first operator, who creates the specified data, i.e., the person who intends to refine the IACC information, may or may not be the same person. Each piece of IACC information data has a management attribute that sets the level of confidentiality.

[0104] Since any IACC information data contains IACC data that has a certain degree of usefulness within organizations such as companies, the organizational value enhancement support device 100 according to this embodiment implements confidentiality management to the extent that it prevents leakage outside the organization. As a result, if the IACC satisfies the requirement of non-publicity, it can be protected as a trade secret as defined in the Unfair Competition Prevention Act.

[0105] If IACC possesses usefulness and non-public nature, it should be protected as a trade secret and may also be a candidate for industrial property rights such as patents. In this case, the organizational value enhancement support device 100 according to this embodiment provides a high level of confidentiality management for the IACC information data.

[0106] One concrete example of such a high level of confidentiality management is the restriction of permission to access (view or modify) IACC information data related to IACC to a specific scope, such as the creator (initial operator) of the IACC information data and its administrators, and the requirement that the creator (initial operator) of the IACC information data and the creator (first operator) of the designated data be the same person. In the following explanation, it is assumed that the creator of the IACC and the creator (initial operator) of the IACC information data containing that IACC are the same person.

[0107] Furthermore, if the IACC is not confidential and does not require strict confidentiality management, the organizational value enhancement support device 100 according to this embodiment can view IACC information data created by other members of the organization, select predetermined IACC information data, and create new IACC information based on the IACC information derived from this data. Such activities constitute the utilization of the IACC within the organization by members other than its creator. In other words, it constitutes the active utilization of intangible resources, where existing IACC is used as input and new intangible assets (intangible resources) with monetary value are produced as output. Through such activities in which multiple members are involved in growing the IACC, the value, especially its usefulness, is increased. If the IACC grows further as this activity progresses and becomes confidential, the IACC should be protected as a potential subject of trade secrets or industrial property rights. In other words, the organizational value enhancement support device 100 according to this embodiment can enhance the property value of intangible assets, such as intellectual assets, within an organization by supporting their active utilization. As a result, intangible resources are strengthened, and organizational value can be improved.

[0108] In this embodiment, the input information generation unit 130 identifies the type of first non-financial capital from the information contained in the IACC information data collected from the IACC information database 300, specifically, which of the five types of non-financial capital (natural capital, human capital, intellectual capital, manufactured capital, and social / relational capital) it is. Then, it collects intangible resource information data of the same type as the identified first non-financial capital from the intangible resource information database 310.

[0109] In this embodiment, the input information generation unit 130 collects performance-related information data, including target values ​​for the organization's financial and performance indicators, from the performance-related information database 320. Examples of financial and performance indicators include those that constitute the ROIC tree, with the nine indicators that make up the ends of the tree (sales growth rate, cost of goods sold ratio, R&D ratio to sales, personnel cost ratio to sales, accounts receivable turnover ratio, accounts payable turnover ratio, inventory turnover ratio, tangible fixed asset turnover ratio, and intangible fixed asset turnover ratio) being given as specific examples. Target values ​​for these indicators are set, for example, on an annual basis, and data including information showing the latest target values ​​is stored in the performance-related information database 320.

[0110] Financial and performance indicators are not limited to those that directly affect performance, such as the nine indicators mentioned above, which are known as KPIs (Key Performance Indicators). Indicators that affect future performance, such as EIOFs (Early Indicators of Future Success), may also be used. Furthermore, if the organization is a non-profit rather than a corporation, appropriate performance metrics such as objective achievement, results, and activity performance, as well as indicators for evaluating these performance metrics, should be set according to the organization's activities. Performance-related data should include target values ​​for these set indicators.

[0111] In this embodiment, the input information generation unit 130 collects auxiliary information data from the auxiliary information database 330. The auxiliary information includes current events information about the organization, trends in the organization's field of activity (industry trends, if the organization is a company, the field of business the company conducts), organizational philosophy such as corporate philosophy, and basic information related to management and operation within the organization, such as KGI (Key Goal Indicator).

[0112] Current events information is collected, for example, by being provided regularly or irregularly by news providers. The collected current events information data is stored in the auxiliary information database 330. In other examples, an information processing unit related to the auxiliary information database 330 (for example, the auxiliary information management unit 330A, described later in Figure 18) may have a search function for an external information network such as the Internet (ExNW), search for information useful for the brush-up process, and store the search results. If this search function is available, the IACCs that are the target of the brush-up process may be input from the IACC information database 300, and search conditions may be created from the input IACCs.

[0113] In this embodiment, the input information generation unit 130 receives personal emotion information data from a first input / output device 400 operated by a first operator. A specific example of the first input / output device 400 is a personal computer. The personal emotion information data includes information indicating a first emotion, which is the emotion that the member (first operator), who is the creator of the specified data, expects when performing their duties. Specific examples of the first emotion include "feeling happy," "feeling accomplished," and "feeling excited." The first emotion can be any emotion, but from the viewpoint of improving the stability of subsequent information processing, particularly the stability of the analysis results in the first generation model 910, it may be preferable that one of a plurality of pre-set emotions is selected.

[0114] The input information generation unit 130 may, at the stage of collecting data from each database and the first input / output device 400, select only the data that should be input to the first inference request generation unit 110, and generate the first input information data group by only combining the input data in the input information generation unit 130. Alternatively, the input information generation unit 130 may generate the first input information data group by performing processing such as selection and combination of the information contained in the data input from each database and the first input / output device 400 in the input information generation unit 130.

[0115] The first inference request generation unit 110 generates first inference request data using the data included in the first input information data group output by the input information generation unit 130 as input. The first inference request data includes first inference requirements, which are requests to cause the first generation model 910 to generate first inference result data.

[0116] The first transmitting / receiving unit 120 transmits the first inference request data generated by the first inference request generation unit 110 to the first generation model 910, and receives the first inference result data, including the first proposal, generated by the first generation model 910 upon receiving the first inference request data. The data transmitted and received by the first transmitting / receiving unit 120 may be transmitted and received via a storage device (not shown). That is, the first inference request data generated by the first inference request generation unit 110 may be stored in a storage device (not shown), and the first transmitting / receiving unit 120 may read this stored first inference request data from the storage device (not shown) and transmit it to the first generation model 910. In this specification, the input and output of data to each unit includes the exchange of data via such a storage device.

[0117] The first generation model 910 may or may not be a component of the organizational value improvement support system 1000 according to this embodiment. In the former case, considerable costs will be incurred for acquisition and maintenance, but the confidentiality management of the first generation model 910 can be proactively handled. In the latter case, the burden of acquisition and maintenance is reduced, but it becomes difficult to proactively manage the first generation model 910, so the level of confidentiality management of the first generation model 910 will be set by contract with the owner of the first generation model 910.

[0118] In this embodiment, the first inference request involves generating a first proposal to improve financial and performance indicators included in performance-related information data, based on IACC information data and intangible resource information data. For example, if one of the target values ​​for financial and performance indicators is set to increase the sales growth rate to 15%, the first proposal will include the result of refining the IACC from the perspective of achieving this target.

[0119] While there are many approaches to refining IACC, including such requirements in the first reasoning requirement allows for directing the improvement of IACC towards achieving a 15% sales growth rate. Improvement of financial and performance indicators may not only mean achieving the set target values, but also exceeding them. Setting higher targets may increase the likelihood of more effective proposals being included in the first proposal.

[0120] Here, when refining the IACC, the first reasoning requirement includes comparing the first type of non-financial capital with intangible resources and supporting information of the same type. This ensures that when specific proposals for improving the IACC are generated, the use of the organization's intangible resources and the latest trends indicated by the supporting information are taken into consideration. As a result, the first proposal will include suggestions that align the direction of IACC improvement with the direction of the organization's growth. This is equivalent to aligning the IACC creation vectors of each member of the organization with the organization's growth vector, thereby increasing the efficiency of the organization's human capital utilization and, consequently, promoting the improvement of organizational value.

[0121] Furthermore, since financial and performance indicators are parameters related to financial capital, improving IACC, which belongs to non-financial capital, from the perspective of improving financial and performance indicators means increasing the relationship between financial capital and non-financial capital. Consequently, such improvements make it easier for investors familiar with information related to financial capital to grasp the capabilities of non-financial capital more directly (making non-financial capital more visible), and as its utilization and economic evaluation are further strengthened, the capabilities of non-financial capital are more easily reflected in financial capital.

[0122] In this embodiment, the first inference request involves generating a proposal for behavioral indicators that contribute to improving financial and performance indicators, in line with the first emotion included in the personal emotional information data. Aligning the creation vector of IACC with the growth vector of the organization is desirable from the perspective of organizational growth, but if the emotional burden on members is not adequately considered, there is a concern that members may be excessively burdened with unwanted stress for the sake of organizational growth. Therefore, by including a proposal for behavioral indicators that incorporate the first emotion as an element in the first inference request, the first proposal generated by the first generation model 910 will include content that realizes the emotional satisfaction of members, and it will be less likely to generate a proposal that excessively burdens members with unwanted stress. For members, an organization that is a place where they can obtain emotional satisfaction increases their engagement with the organization and contributes to improving the stability of organizational growth.

[0123] In this embodiment, the first inference request includes, if the IACC information data includes human capital-related information, which is information about systems and institutions for developing the knowledge, skills, and abilities (KSAs) of members (first case), then including improvement suggestions from the perspective of increasing human capital in the first proposal; and if the IACC information data does not include human capital-related information (second case), then adding improvement suggestions from the perspective of increasing at least one of the following: manufactured capital, social and relational capital, and natural capital, to the first proposal. In the first case described above, if improvement suggestions related to human capital are included in the first proposal, then improvement suggestions from the perspective of increasing non-financial capital other than human capital (intellectual capital, manufactured capital, social and relational capital, and natural capital) may also be included in the first proposal. Alternatively, improvement suggestions from the perspective of increasing the organization's management assets, such as know-how including trade secrets, may also be included in the first proposal.

[0124] In the organizational value improvement support device 100 according to this embodiment, as will be described later, an initial large-scale language model (initial generative model 920, sometimes referred to as the "second large-scale language model" in this specification) is used when setting the type of non-financial capital to which IACC belongs (first non-financial capital). Even when using information with a certain degree of objectivity, it is not easy in practice to appropriately set the first non-financial capital. In particular, since IACC is an intangible asset that includes intellectual assets, and the entity that created IACC is "people", it is common for the first operator to set intellectual capital or human capital as the first non-financial capital.

[0125] Therefore, in this embodiment, the first inference request includes prompting the system to propose improvements that can be determined to belong to one of the five types of non-financial capital other than intellectual capital and human capital, namely natural capital, manufactured capital, or social / relational capital. This optimizes the allocation of IACC to the appropriate type of non-financial capital, making it easier to more appropriately evaluate the value of an organization, such as corporate value.

[0126] Furthermore, if the IACC includes human capital-related information concerning systems and institutions for developing the knowledge, skills, and abilities (KSAs) of its members, then the IACC should be considered to belong to human capital. Therefore, the first generative model 910 is instructed to propose improvements to the mechanism for improving the IACC from the perspective of increasing human capital.

[0127] Therefore, the first inference result indicates that, with respect to IACC, except for those that should be judged to belong to human capital, improvement proposals will include those that belong to natural capital, manufactured capital, or social / relational capital, and the number of IACC belonging to intellectual capital tends to be small. IACC proposed to belong to intellectual capital in this process may have characteristics different from other IACC, such as being difficult to classify into a specific type of non-financial capital, as they affect multiple types of non-financial capital. By consolidating such IACC into intellectual capital, the management (allocation) of non-financial capital may become easier.

[0128] In this embodiment, the first inference result data received by the first transmitting / receiving unit 120 is input to the comparative display generation unit 140. As previously mentioned, the first inference result data received by the first transmitting / receiving unit 120 is stored in a storage device (not shown) before being input to each part of the organizational value improvement support device 100, and the case where each part, such as the comparative display generation unit 140, reads this stored data is included in the statement that "the first inference result data is input to the comparative display generation unit 140."

[0129] The comparative display generation unit 140 receives IACC information data in addition to the first inference result data. The comparative display generation unit 140 may directly access the IACC information database 300 to obtain the IACC information data, or it may obtain the IACC information data from the input information generation unit 130. The IACC information data collected by the input information generation unit 130 may be stored in a storage device (not shown), and the comparative display generation unit 140 may read this data.

[0130] The comparative display generation unit 140 performs a process that includes generating comparative display data that displays the information contained in the first inference result data in a first format, making it possible to compare it with the information contained in the IACC information data. By displaying the two pieces of information in a comparative manner in this way, members can easily confirm what kind of refinements have been made to the first generated model 910. In addition, by displaying the information before and after the refinement in a comparative manner, it becomes easier to judge the validity of the information after the refinement.

[0131] The comparative display data may be a signal directly displayed on the output unit of the first input / output device 400 operated by a member, such as an image display signal or a print signal, or the data necessary for comparative display may be input to the first input / output device 400, and a display signal to the output unit may be generated in the first input / output device 400. The comparative display data may be encrypted data. Figure 8 is a specific example in which the information contained in the first inference result data and the information contained in the IACC information data are displayed in a comparative manner on the image display unit, which is the output unit of the first input / output device 400.

[0132] In this embodiment, the first inference request includes generating publicity proposal information, which includes the results of an examination of whether or not the first proposal is publicly known. The first generation model 910, upon receiving this first inference request, may, for example, perform an internet search to confirm whether or not the first proposal generated by the first generation model 910 is publicly available on the internet.

[0133] If the publicly known proposal information has a proposal that it is publicly known, the first inference request may further include indicating the publicly known information that is determined to contain the first proposal. In this case, the first inference result data will include publicly known information that is determined to have the same content as the first proposal. A specific example of publicly known information is the URL of a web page.

[0134] If the publicly known proposed information has a proposal that it is not publicly known, the first inference request may further include indicating the publicly known information (nearest publicly known information) that it has determined to be the closest to the first proposal. In this case, the first inference result data includes publicly known information that is not the same as the first proposal, but which the first generative model 910 has determined to be the closest to the first proposal among the search results.

[0135] Thus, when the information that forms the basis for determining public knowledge is included in the first inference result data, it becomes easier for the first operator and other members of the organization to consider whether the proposed public knowledge information included in the first inference result data is valid. This makes it less likely that the problem of blindly trusting information from the first generative model 910 will occur.

[0136] The public knowledge indication generation unit 150 takes first inference result data from the first generation model 910 as input, checks the content of the public knowledge proposal information contained in the data, and determines whether the first proposal is public or private. If it determines that the first proposal is private, it performs a process that includes generating private knowledge indication data that includes a notice indicating that the first proposal may be confidential information. Private knowledge indication data is, for example, data that enables the image display unit, which is the output unit of the first input / output device 400, to display the text, "This IACC may be private information and will be managed as confidential information. Please be careful not to disclose it to anyone outside the organization." In this way, by informing members that the information they are currently handling may be confidential information and encouraging confidentiality management, it is possible to prevent problems such as IACC information losing novelty or private status. This contributes to the appropriate protection of potential subjects of industrial property rights such as patent inventions and trade secrets within the organization.

[0137] Figure 2 is a flowchart (part 1) illustrating the information processing (brush-up process) performed by an organizational value improvement support device according to one embodiment of the present disclosure. Specifically, it is a flowchart of the information processing performed by the first inference request generation unit 110, the first transmission / reception unit 120, the input information generation unit 130, the comparison display generation unit 140, and the publicly known display generation unit 150, which are included in the organizational value improvement support device 100 as described above.

[0138] First, the input information generation unit 130 collects input information, including accessing each database and obtaining data from the first input / output device 400 (step S101), and generates a first input information data set (step S102). Next, the first inference request generation unit 110 generates first inference request data using the first input information data set as input (step S103), and outputs the first inference request data to the first transmission / reception unit 120. Subsequently, the first transmission / reception unit 120 transmits the first inference request data to the first generation model 910 (step S104).

[0139] The first inference result data generated by the first generation model 910 is received by the first transmission / reception unit 120 (step S105). Based on the first proposal contained in the received first inference result data, the comparison display generation unit 140 generates comparison display data (step S106).

[0140] Furthermore, the public knowledge display generation unit 150 confirms the public knowledge proposal information contained in the first inference result data (step S107), and determines whether the first proposal is not public based on this information (step S108). If the public knowledge display generation unit 150 determines that the first proposal is not public, it generates non-public display data (step S109), and the comparison display data and non-public display data are transmitted (output) to the first input / output device 400 as data for display (step S110). If the public knowledge display generation unit 150 determines that the first proposal is public, the comparison display data is transmitted (output) to the first input / output device 400 as data for display (step S110).

[0141] In this embodiment, the first IACC information registration unit 170 generates draft IACC information data in a format corresponding to the display of IACC information data, i.e., the first format, where the information contained in the first inference result data is written. Then, conditional on receiving an acceptance instruction for the draft IACC information data, it executes a process that includes replacing the draft IACC information data with IACC information data and saving it in the IACC information database 300.

[0142] As mentioned above, the first generation model 910 generates suggestions for refining the IACC information data included in the first input data set. By replacing the original IACC information data with the IACC information data based on these suggestions, the consistency with the organization's growth is enhanced, and the IACC information, with its increased asset value, is accumulated as an intangible resource within the organization. Furthermore, since consideration is given to individual emotions when generating the refined IACC information data, it is expected that the motivation of IACC creators for their activities within the organization will increase.

[0143] On the other hand, although consideration is given to the personal feelings of the members, there are concerns that simply using the IACC information data based on the proposals generated by the first generative model 910 as refined IACC information data, regardless of the intentions of the member who created the IACC related to that data, may affect the motivation of the members. In particular, since the IACC information data includes information such as behavioral indicators that could become constraints on the members' activities within the organization afterward, there are concerns that members may feel that their actions are being controlled by so-called "AI". Such feelings could lead to a decline in engagement with the organization, and even with society. For example, if a member intended to refine their IACC in order to feel "excited," but ultimately felt that they were merely being manipulated by calculated proposals from a cold, calculating machine, this could lead to a strong distrust of the process of refining the IACC.

[0144] Therefore, in the organizational value improvement support device 100 according to this embodiment, instead of simply replacing and saving the IACC information data based on the proposal of the first generation model 910 in the existing IACC information database 300, the data is updated in a manner that appropriately reflects the intentions of the first operator who operates the first input / output device 400.

[0145] Figure 3 is a flowchart (part 2) illustrating the information processing (brush-up process) performed by an organizational value improvement support device according to one embodiment of the present disclosure. It is a flowchart of the information processing in which the first IACC information registration unit 170 uses the brushed-up IACC information proposed by the first generation model 910 to store the IACC information in the IACC information database 300.

[0146] Specifically, first, the first IACC information registration unit 170 collects the first inference result data generated by the first generation model 910 (step S201), generates draft IACC information data written in a first format based on the collected data (step S202), and performs a transmission process to display the draft IACC information data on the first input / output device 400 (step S203). This draft IACC information data may be based on data generated by the comparison display generation unit 140. Alternatively, that data may be used as is as the draft IACC information data, in which case the comparison display generation unit 140 is responsible for a part of the processing that the first IACC information registration unit 170 should perform, specifically the execution of step S220, which is enclosed by a dotted line in Figure 3.

[0147] In this way, the draft IACC information data is displayed on the first input / output device 400 and becomes recognizable by the first operator. The first operator checks the contents of the draft IACC information data and determines whether the contents of the draft IACC information data can be used as their own IACC information or whether there are any items that need to be corrected. If there are items that need to be corrected in the contents of the draft IACC information data, a correction instruction is sent to the first IACC information registration unit 170 through the first input / output device 400.

[0148] The first IACC information registration unit 170 determines whether or not there is a correction instruction in the input signal from the first input / output device 400 (step S204). If it is determined in step S204 that a correction instruction has been input, the first IACC information registration unit 170 reflects the correction instruction in the information contained in the first inference result data, and the reflection result generates corrected IACC information data written in a format corresponding to the display of IACC information data, i.e., the first format (step S205), and performs a transmission process to display the data on the first input / output device 400 (step S206).

[0149] The IACC information data being modified is then displayed on the first input / output device 400 and becomes recognizable by the first operator. The first operator checks the contents of the IACC information data being modified and determines whether the contents of the IACC information data being modified can be used as their own IACC information, or whether there are any further items that need to be modified. If the first operator determines that there are no items that need to be modified in the contents of the IACC information data being modified, they send an acceptance instruction to the first IACC information registration unit 170 through the first input / output device 400.

[0150] The first IACC information registration unit 170 determines whether or not there is an acceptance instruction in the input signal from the first input / output device 400 (step S207). If it is determined in step S207 that an acceptance instruction has been input, the first IACC information registration unit 170 sets the IACC information data being modified as the IACC information data to be saved, replacing the existing IACC information data (step S208).

[0151] If it is determined in step S204 that no correction instruction has been input, the first IACC information registration unit 170 determines whether or not there is an acceptance instruction in the input signal from the first input / output device 400 (step S209). If it is determined in step S209 that an acceptance instruction has been input, the first IACC information registration unit 170 sets the draft IACC information data as the IACC information data to be saved, replacing the existing IACC information data (step S210). If it is determined in step S209 that no acceptance instruction has been input, the process returns to step S204. This puts the system in a state of waiting for input from the first input / output device 400. A predetermined interval (for example, 1 second) may be provided between step S209 and the subsequent step S204.

[0152] If it is determined in step S207 that no acceptance instruction has been entered, the first IACC information registration unit 170 determines whether there is another correction instruction in the input signal from the first input / output device 400 (step S211). If there is a correction instruction in step S211, step S205 is executed to generate corrected IACC information that reflects the new correction instruction, and steps S206 onwards are re-executed. If it is determined in step S211 that no further correction instruction has been entered, the process returns to step S207. This puts the system into a state of waiting for input from the first input / output device 400. A predetermined interval (for example, 1 second) may be provided between step S211 and the subsequent step S207.

[0153] Through the above process, the data reflecting the intentions of the first operator is set as IACC information data to be replaced and saved in the IACC information database 300. While it is possible to process this data directly for saving in the IACC information database 300, the organizational value improvement support device 100 according to this embodiment further determines whether or not it should be managed as confidential information and, if so, performs processing to do so.

[0154] As described above, in the organizational value improvement support device 100 according to this embodiment, the first inference request included in the first inference request data generated by the first inference request generation unit 110 generates public-publicity proposal information that includes the results of an examination of whether or not the first proposal is publicly known. Therefore, the first inference result data includes public-publicity proposal information. Accordingly, the organizational value improvement support device 100 includes a confidentiality management setting unit 160 that takes as input the IACC information data to be stored in the IACC information database 300, which is generated by the first IACC information registration unit 170, and the first inference result data, determines from the public-publicity proposal information whether the first proposal is publicly known or not, and if it is determined that the first proposal is not publicly known, executes a process that includes setting the management attribute of the IACC information data to be stored in the IACC information database 300 to data that includes a candidate for the object of industrial property rights.

[0155] For IACC information data whose management attribute is set to include data containing potential subjects of industrial property rights, different data management is performed in the IACC information database 300 compared to IACC information data that does not have such a management attribute. Specifically, a high level of access restriction is implemented to prevent the loss of novelty and non-publicity, thereby preventing unforeseen information leaks. Furthermore, when changes are made to IACC information data, a log including the person who made the change and the details of the change is recorded. In addition, if necessary, measures are taken to prevent data loss even if there is an unexpected failure in the storage device that constitutes the database, such as data storage redundancy.

[0156] Steps S212 and S213 in Figure 3 show the information processing performed by the confidentiality management setting unit 160. In step S212, the confidentiality management setting unit 160 determines whether the first proposal is confidential or not. If it is determined to be confidential in step S212, it sets management attributes in step S213, and the first IACC information registration unit 170 performs a transmission process to save the IACC information data with these management attributes set to the IACC information database 300 (step S214). In Figure 3, as a specific example, separate from the transmission of the IACC information data, the information management unit 260 generates information management instruction data that includes information on the management attributes of the data, and performs a transmission process for that data (step S215). The IACC information database 300 stores the IACC information data while appropriately managing it according to the management attributes included in the information management instruction data.

[0157] Note that the processing in step S212 is performed by the publicly known information generation unit 150 in step S108 (Figure 2). Therefore, if the determination result of step S108 is stored in a storage device (not shown), the secret management setting unit 160 may, instead of executing the processing in step S212, read the determination result of step S108 from the storage device (not shown) and perform subsequent processing based on that determination result.

[0158] If it is determined in step S212 that the information is publicly known, the first IACC information registration unit 170 performs processing to save the IACC information data to the IACC information database 300 without setting any special management attributes (step S214). In this case, the management attribute information included in the information management instruction data generated in step S215 includes, for example, access restrictions equivalent to confidentiality within the organization. The IACC information database 300 stores the IACC information data while appropriately managing it according to its management attributes.

[0159] The organizational value improvement support device 100 includes the following parts in relation to information processing (in this specification, this information processing is also referred to as the "entry process") for generating IACC information data that can also be subject to refinement and storing it in the IACC information database 300: - Initial inference request generation unit 180 (second inference request generation unit) that generates initial inference request data (second inference request data) - Initial transmission / reception unit 190 (second transmission / reception unit) that transmits and receives data with the initial large-scale language model (initial generation model 920, which may also be referred to as the "second large-scale language model" in this specification) - Capital display generation unit 200 that generates data for displaying the inference results of the initial generation model 920 - Initial IACC information registration unit 210 (second information registration unit) that performs processing for storing IACC information data, which includes the inference results of the initial generation model 920, in the IACC information database 300

[0160] An initial operator (second operator), who is a member who intends to create IACC information data by executing the entry process, inputs IACC basic information data, which is the basic information for IACC information data and includes IACC information, from the initial input / output device 410 (second input / output device) to the organizational value improvement support device 100. The initial inference request generation unit 180 generates initial inference request data as this IACC basic information data. The initial inference requirements included in the initial inference request data have the function of generating proposals for the types of non-financial capital to which IACC should belong, as a result of analyzing the IACC basic information data. The initial operator may or may not be the same as the first operator who performs the brush-up process. Also, the initial input / output device 410 may be physically the same as the first input / output device 400. In this specification, for the sake of facilitating understanding of the disclosed content, the devices used in the brush-up process (first input / output device 400) and the devices used in the entry process (initial input / output device 410) are described separately.

[0161] As mentioned above, IACC information data includes information indicating the type of non-financial capital (first non-financial capital) to which the IACC belongs in one specific example. However, it is not easy for members without special knowledge to determine which type of non-financial capital their IACC belongs to. Therefore, in the organizational value improvement support device 100 according to this embodiment, the initial generation model 920 is made to analyze the IACC basic information data based on the input information of the initial operator and propose the type of first non-financial capital.

[0162] The initial inference result data, which is the result of analyzing the initial inference request data transmitted from the initial transmission / reception unit 190, is received by the initial transmission / reception unit 190. The capital representation generation unit 200 performs processing that includes identifying the proposed non-financial capital type and generating capital representation data to display the identified non-financial capital type, based on the initial inference result data received from the initial transmission / reception unit 190. The capital representation data is output to the initial input / output device 410, and the initial operator can use this capital representation data to determine the type of non-financial capital (first non-financial capital) to which their IACC belongs, taking into account the type of non-financial capital proposed by the initial generation model 920, and complete the IACC information.

[0163] The capital display data, like the comparative display data, may be a signal directly displayed on the output unit of the initial input / output device 410, such as an image display signal or a print signal, or the data necessary for display may be input to the initial input / output device 410, and the initial input / output device 410 may generate a display signal for the output unit. The capital display data may also be encrypted data.

[0164] In this embodiment, the organizational value improvement support device 100 includes, as an example, an initial IACC information registration unit 210 that performs a process including automatically generating IACC information data from the non-financial capital and IACC basic information data proposed by the initial generation model 920, and saving that data in the IACC information database 300.

[0165] The initial IACC information registration unit 210 identifies the proposed non-financial capital type from the initial inference result data and generates IACC information data based on the identified non-financial capital type and the IACC basic information data. The initial inference result data may be input directly to the initial IACC information registration unit 210 from the initial transmission / reception unit 190, or it may be input via a storage device (not shown). The IACC basic information data should be stored in a storage device (not shown) when it is input to the initial inference request generation unit 180. In this case, the initial IACC information registration unit 210 reads this stored data.

[0166] Figure 4 is a flowchart (part 3) illustrating the information processing performed by an organizational value improvement support device according to one embodiment of the present disclosure. It is a flowchart of the information processing in which the initial IACC information registration unit 210 stores IACC information in the IACC information database 300 using the proposed types of non-financial capital proposed by the initial generation model 920.

[0167] Specifically, first, the initial inference request generation unit 180 collects IACC basic information data from the initial input / output device 410 and the like (step S301), and generates initial inference request data based on the collected data (step S302). Next, the initial transmission / reception unit 190 transmits the initial inference request data to the initial generation model 920 (step S303).

[0168] The initial transmission / reception unit 190 receives the initial inference result data generated by the initial generation model 920 (step S304). Based on the initial proposal contained in the received initial inference result data, the capital presentation generation unit 200 confirms the proposed type of non-financial capital (step S305), generates capital presentation data containing the confirmed non-financial capital information, and transmits the data to the initial input / output device 410 (step S306).

[0169] The initial IACC information registration unit 210 generates IACC information data from the non-financial capital information confirmed by the capital presentation generation unit 200 and the IACC basic information data read from a storage device (not shown) (step S307), and performs a transmission process to save the generated IACC information data to the IACC information database 300 (step S308).

[0170] As shown in step S215 of Figure 3, the information management unit 260 generates information management instruction data for the IACC information database 300 to classify and manage IACC information data, and transmits it to the IACC information database 300. The following describes one possible information processing performed by the information management unit 260.

[0171] The information management instruction data generated by the information management unit 260 may include a first instruction for classification and management based on the management attributes of the IACC information data. A specific example of the first instruction is an instruction that classifies the IACC in terms of whether it belongs to a candidate subject of industrial property rights, a trade secret, or information that does not require confidentiality protection.

[0172] When an IACC is classified as a potential subject of industrial property rights such as a patented invention, it is treated as strictly confidential information to prevent the loss of novelty. Access to the IACC is limited even within the organization, and those who have exceptional access by contract are subject to strong confidentiality obligations.

[0173] If an IACC is classified as a trade secret, it will be managed confidentially in accordance with the requirements for a trade secret as defined in the Unfair Competition Prevention Act. Furthermore, it will be marked in a way that allows viewers of the IACC to recognize that the information they are viewing is confidential. If classified as a trade secret, the level of confidentiality management may be further classified according to the economic value of the IACC (lost profits if lost). The first instruction may contain information regarding this classification.

[0174] When IACC is classified as non-confidential information, its value as an intangible asset is expected to increase, as mentioned above, by being actively shared with other members of the organization. Therefore, it may be preferable to make it accessible to the member who will be the first operator. Even when such internal sharing is preferable, it may be preferable to appropriately set the scope of sharing depending on the importance of the information. The first instruction may contain information regarding classification from this perspective.

[0175] The information management instruction data generated by the information management unit 260 may include a second instruction for classifying and managing IACCs based on the type of non-financial capital to which the IACCs included in the IACC information data belong. A specific example of the second instruction is an instruction to classify IACCs in terms of whether they belong to human capital, intellectual capital, manufactured capital, social / relational capital, or natural capital. By performing such management, it becomes easy to identify IACCs within the organization that belong to a specific type of non-financial capital, and it also becomes possible to perform more detailed classification management within that scope. For example, among IACCs belonging to social / relational capital, it is possible to classify and manage IACCs related to customers and IACCs related to shareholders, creditors, society, and other stakeholders.

[0176] If the IACC information data includes both a first and a second instruction, the IACC included in the IACC information data will be classified from two perspectives: the level of confidentiality and the type of non-financial capital. Consequently, in the IACC information database 300, the IACC information data will be managed in a two-dimensional matrix classified from the above two perspectives. In this case, each element of the matrix will be independent of the others, as they will be managed under fundamentally different rules.

[0177] In other words, the IACC information database 300 appropriately separates and manages potential subjects of industrial property rights, such as patented inventions, from other information, and also appropriately separates and manages trade secrets from other information. Therefore, because it appropriately manages this information, the IACC information database 300 is positioned as a patent and trade secret management database.

[0178] In this regard, if the IACC information data stored in the IACC information database 300 has appropriate usefulness, the IACC information included in it will be stored in the intangible resource information database 310 as a management resource. In other words, the IACC information database 300 and the intangible resource information database 310 are related databases. Figure 1 shows that among the IACC information data stored in the IACC information database 300, the data that should become intangible resource information data is output to the intangible resource information database 310 and stored in that database as well.

[0179] The intangible resources information database 310 may be part of the IACC information database 300. In this case, the classification in the IACC information database 300 at the level of confidentiality management can be further subdivided at the level of usefulness and non-publicity (novelty) that underlies the classification, thereby allowing for the extraction of data to be preserved in the intangible resources information database 310.

[0180] As described above, the organizational value improvement support device 100 according to this embodiment realizes the refinement of IACC. Therefore, a portion of the IACC included in the IACC information data stored in the IACC information database 300 is appropriately refined and becomes an intangible resource that is stored in the intangible resource information database 310. From this perspective, the IACC information database 300 is positioned as the cradle of intangible resources.

[0181] Furthermore, among the IACC information data stored in the IACC information database 300, those that are candidates for being subject to industrial property rights may be transferred to a database managed by, for example, the intellectual property department within the organization, and become the subject of specific business flows for obtaining rights, such as patent applications.

[0182] The organizational value improvement support device 100 comprises the following parts in relation to information processing for generating intangible resource information data and storing it in the intangible resource information database 310 (in this specification, this information processing is also referred to as the "intangible resource management process"): ・An intangible resource inference request generation unit 230 (third inference request generation unit) that generates intangible resource inference request data (third inference request data) ・An intangible resource transmission / reception unit 240 (third transmission / reception unit) that transmits and receives data with an intangible resource large-scale language model (intangible resource generation model 930, which may also be referred to as the "third large-scale language model" in this specification) ・An intangible resource information registration unit 250 that generates intangible resource information data based on the inference results of the intangible resource generation model 930 and performs processing for storing it in the intangible resource information database 310 These parts are part of the information processing performed by the intangible resource management process and are specifically related to the generation of intangible resource information data.

[0183] As described above, in order to align the vector of IACC information refinement with the growth vector of the organization, in this embodiment, the first inference request included in the first inference request data requires that, when generating the first proposal, intangible resources belonging to the same non-financial capital as the first non-financial capital be taken into consideration. Therefore, the intangible resource information data stored in the intangible resource information database 310 includes information indicating which non-financial capital the intangible resources included in the data belong to.

[0184] There are various methods for preparing intangible resource information data. One of them is, as described above, the intangible resource conversion of IACC information data stored in the IACC information database 300. In this case, since the non-financial capital to which the IACC included in the IACC information data belongs is identified during the generation of the IACC information data, the non-financial capital to which the intangible resource belongs can be easily identified. However, in processes other than this, it may not be clear which non-financial capital the intangible resource belongs. In such cases, as will be explained below, a pre-trained generative model, such as a large-scale language model, can be made to propose which non-financial capital the intangible resource included in the intangible resource information data belongs to.

[0185] The intangible resource inference request generation unit 230 takes intangible resource basic information data, which is basic information for intangible resource information data and includes information about intangible resources, as input and generates intangible resource inference request data. In this embodiment, as an example, the intangible resource information database 310 stores the intangible resource basic information data, but it is not limited to this, and other databases may also store it.

[0186] The creator of the intangible resource basic information data is not limited. The creator of the data may belong to an organization, and a specific example of this would be a person with management responsibility at the manager level or higher. The creator of the data does not have to belong to an organization, and a specific example of this would be a business operator such as a management consultant commissioned by an organization, and their members. The method of creating the intangible resource basic information data is arbitrary, and the creator may input the intangible resource basic information data into the organizational value improvement support device 100 or the intangible resource information database 310 from an input / output device (not shown). Alternatively, as will be described later, IACC information data stored in the IACC information database 300 that meets certain conditions may be stored in the intangible resource information database 310 as intangible resource basic information data.

[0187] The Resource Inference Requirements included in the Intangible Resource Inference Requirements data involve generating proposals for the type of non-financial capital to which the intangible resource should belong, as a result of analyzing the intangible resource basic information data.

[0188] The intangible resource transmission / reception unit 240 transmits the intangible resource inference request data generated by the intangible resource inference request generation unit 230 to the intangible resource generation model 930 and receives intangible resource inference result data from the intangible resource generation model 930.

[0189] The processing performed by the Intangible Resource Information Registration Unit 250 includes the following: It takes intangible resource inference result data and intangible resource basic information data as input and identifies the proposed type of non-financial capital from the intangible resource inference result data. It generates intangible resource information data based on the identified type of non-financial capital and the intangible resource basic information data. It stores the generated intangible resource information data in the intangible resource information database 310.

[0190] The intangible resource information data may include information on SDGs targets related to the intangible resource. In this case, the intangible resource inference request generated by the intangible resource inference request generation unit 230 generates a proposal for an SDGs target related to the intangible resource as a result of analyzing the intangible resource basic information data. The intangible resource information registration unit 250 identifies the proposed SDGs target from the intangible resource inference result data and includes information on the identified SDGs target in the intangible resource information data.

[0191] From the perspective of facilitating the setting of SDGs target information, an SDGs database 340 containing information on SDGs targets may be provided. In this case, the intangible resource inference request may include information stored in the SDGs database 340 as text, for example, or it may include an instruction to take into account the information stored in the SDGs database 340 when generating proposals for SDGs targets related to intangible resources. In some cases, the intangible resource generation model 930 may provide information on SDGs targets. In this case, there is no need to specifically prepare the SDGs database 340, and it is sufficient to generate proposals for SDGs targets related to the intangible resource inference request generated by the intangible resource inference request generation unit 230.

[0192] Figure 5 is a flowchart (part 4) illustrating the information processing (intangible resource management process) performed by an organizational value improvement support device according to one embodiment of this disclosure. It is a flowchart of the information processing in which the intangible resource information registration unit 250 stores IACC information in the intangible resource information database 310 using the proposed types of non-financial capital proposed by the intangible resource generation model 930.

[0193] Specifically, first, the intangible resource inference request generation unit 230 collects intangible resource basic information data from the intangible resource information database 310 and the like (step S401), and collects SDGs data related to SDGs targets from the SDGs database 340 (step S402). Based on the collected data, the intangible resource inference request generation unit 230 generates intangible resource inference request data (step S403). Next, the intangible resource transmission / reception unit 240 transmits the intangible resource inference request data to the intangible resource generation model 930 (step S404).

[0194] The intangible resource inference result data generated by the intangible resource generation model 930 is received by the intangible resource transmission / reception unit 240 (step S405). Based on the intangible resource proposals contained in the received intangible resource inference result data, the intangible resource information registration unit 250 confirms the proposed type of non-financial capital (step S406) and confirms the proposed SDGs target (step S407). The intangible resource information data is generated by adding the confirmed non-financial capital and SDGs target information to the intangible resource basic information data (step S408). The intangible resource information registration unit 250 performs a transmission process to save the generated intangible resource information data to the intangible resource information database 310 (step S409).

[0195] Another embodiment of the present disclosure includes a program executed by the organizational value improvement support device 100. The program according to this embodiment is an organizational value improvement support program that transmits first inference request data generated based on a first input information data group to a first generation model 910 and receives first inference result data from the first generation model 910. Figures 9 to 15 are explanatory diagrams of one embodiment of the organizational value improvement support program according to one embodiment of the present disclosure.

[0196] The program according to this embodiment specifically includes the following processes: First, it collects data that should be included in the first input information data group. Next, it generates first inference request data based on the first input information data group. Subsequently, it transmits the first inference request data to the first generation model 910. Furthermore, it receives first inference result data from the first generation model 910.

[0197] The first input information data set handled in the program according to this embodiment includes IACC information data, which in one example includes IACC information in which the IACC is described in a predetermined first format; intangible resource information data, which includes information on intangible resources belonging to the same type of non-financial capital as the non-financial capital to which the IACC belongs, among the intangible resources owned by the organization to which the member belongs; and performance-related information data, which includes target values ​​for the organization's financial and performance indicators. The first inference request included in the first inference request data generated in the program according to this embodiment includes generating a first proposal to improve the financial and performance indicators included in the performance-related information data, based on the IACC information data and the intangible resource information data.

[0198] Another embodiment of the present disclosure is an organizational value enhancement support system comprising a plurality of devices as components.

[0199] One specific example of such a system is an organizational value enhancement support system comprising a first device having input / output functions, an initial device (second device) consisting of at least one device having a data storage function, and an intangible resource device (third device) equipped with a control unit, wherein the first device is capable of communicating with the initial device and the intangible resource device.

[0200] The initial equipment of the system includes an IACC information database 300, an intangible resources information database 310, and a performance-related information database 320. The IACC information database 300 stores IACC information data, including IACC information of members, for example, IACC information in which the IACC is described in a predetermined first format. The intangible resources information database 310 stores data including information on intangible resources owned by the organizations to which the members belong. The performance-related information database 320 stores performance-related information data, including target values ​​for the organization's financial and performance indicators.

[0201] The control unit of the intangible resource device in the system includes a first inference request generation unit 110 that generates first inference request data to be input to a pre-trained generative model based on data input from the first device.

[0202] The first device of the system comprises an input / output unit and a transmit / receive unit. The input / output unit receives a first input information data group from the initial device, which includes IACC information data, intangible resource information data, and performance-related information data, and outputs the first input information data group to the intangible resource device. Here, the intangible resource information data is a part of the data stored in the intangible resource information database 310 and includes information on intangible resources belonging to the same type of non-financial capital as the non-financial capital to which IACC belongs. The transmit / receive unit transmits the first inference request data input from the intangible resource device to a pre-trained generative model and receives the first inference result data from the pre-trained generative model.

[0203] The first inference request included in the first inference request data generated by the first inference request generation unit 110 of the intangible resource device includes generating a first proposal to improve financial and performance indicators included in performance-related information data, based on IACC information data and intangible resource information data.

[0204] In the above system, at least two of the first device, the initial device, and the intangible resource device may be integrated. The aforementioned organizational value improvement support device 100 is an integrated first device and intangible resource device. In the above system, each of the first device, the initial device, and the intangible resource device may consist of multiple devices. For example, the multiple databases provided by the initial device may each consist of a separate storage device, and furthermore, a single database may also consist of multiple storage devices. As a specific example, when the aforementioned IACC information database 300 is used as a patent and trade secret management database, if the storage devices that store the information groups that form each element of the matrix are independent of each other, it becomes easier to properly manage each information group.

[0205] Another concrete example of such a system is an organizational value enhancement support system that has multiple computer devices constituting a peer-to-peer network.

[0206] At least one of the multiple computer devices has a first inference request generation unit 110 that generates first inference request data to be input to a pre-trained generative model based on input data. At least one of the multiple computer devices has a transmitting / receiving unit that transmits the first inference request data to the pre-trained generative model and receives first inference result data from the pre-trained generative model. At least one of the multiple computer devices has an input information generation unit 130 that collects data from multiple databases to generate a first input information data set. The computer device having the first inference request generation unit 110, the computer device having the transmitting / receiving unit, and the computer device having the input information generation unit 130 may be different from each other, or any two of them may be the same computer device.

[0207] In this system, the multiple databases include an IACC information database 300 that stores IACC information data, including, for example, IACC information in which the IACC is described in a predetermined first format; an intangible resource information database 310 that stores data including information on intangible resources owned by the organization to which the member belongs; and a performance-related information database 320 that stores performance-related information data including target values ​​for the organization's financial and performance indicators.

[0208] The first inference request included in the first inference request data generated by the computer device having the first inference request generation unit 110 includes generating a first proposal to improve financial and performance indicators included in the performance-related information data, based on IACC information data and intangible resource information data. As described above, the intangible resource information data is part of the data accumulated by the intangible resource information database 310 and includes information on intangible resources belonging to the same type of non-financial capital as the non-financial capital to which IACC belongs.

[0209] In the refinement process, IACC information data is essential as data input to the input information generation unit 130, while input of other information data is optional. Therefore, the first inference request included in the first inference request data can be expressed as generating a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group which includes at least IACC information data.

[0210] Other embodiments of this disclosure will be described below. Figure 16 is a block diagram illustrating an organizational value improvement support system having an organizational value improvement support device according to one of the other embodiments of this disclosure.

[0211] As shown in Figure 16, the organizational value improvement support system 1000A according to one of the other embodiments of the present disclosure has a configuration common to the organizational value improvement support system 1000 according to one embodiment of the present disclosure. Specifically, the organizational value improvement support system 1000A is capable of executing a brush-up process using the first generation model 910, an entry process using the initial generation model 920, and an intangible resource management process using the intangible resource generation model 930.

[0212] The following are the differences in configuration between the organizational value improvement support system 1000A shown in Figure 16 and the organizational value improvement support system 1000 shown in Figure 1. Configuration 1: The organizational value improvement support device 100A in the organizational value improvement support system 1000A shown in Figure 16 includes a pre-trained generative model, including a large-scale language model, as a component. Configuration 2: The organizational value improvement support device 100A includes an intangible resource information management unit 251 that manages intangible resource information data stored in the intangible resource information database 310. Configuration 3: The organizational value improvement support system 1000A has an auxiliary information management unit 330A that manages the auxiliary information database 330.

[0213] The following provides a detailed explanation of the differences in the configuration of the organizational value improvement support system 1000A.

[0214] With respect to Configuration 1, in the Organization Value Improvement Support Device 100, the first generation model 910, the initial generation model 920, and the intangible resource generation model 930 were not components of the Organization Value Improvement Support Device 100. However, the Organization Value Improvement Support Device 100A, as an example without limitation, includes at least one of these pre-trained generation models as a component.

[0215] With advancements in hardware technology such as increased functionality of semiconductor devices (miniaturization, reduced power consumption, and improved processing speed) and advancements in software technology such as federated learning, it is possible to implement pre-trained generative models at a practical level in organizational value enhancement support devices, such as personal computers and smartphones. Embodiments of this disclosure include such cases. The organizational value enhancement support device 100A includes all of the first generative model 910, the initial generative model 920, and the intangible resource generative model 930 as components, but is not limited to this, and may include at least one pre-trained generative model as a component.

[0216] Configuration 2 will be described with reference to Figure 17. Figure 17 is a diagram illustrating the functions of the intangible resource information management unit of an organizational value improvement support system having an organizational value improvement support device according to one of the other embodiments of this disclosure. It consists of a block diagram drawn by extracting a part of the configuration of the organizational value improvement support system 1000A shown in Figure 16, and a diagram (data management relationship diagram) shown above it, which shows the relationship between IACC information data stored in the IACC information database 300 and intangible resource information data stored in the intangible resource information database 310, and further, the relationship with the guidelines for disclosing intangible resource information data to outside the organization. In the explanation using Figure 17, a company, which is a for-profit organization, may be used as a specific example.

[0217] In the organizational value enhancement support system 1000A, at least a portion of the data stored in the IACC information database 300 (such as IACC information data) is positioned as data stored in the intangible resource information database 310 (intangible resource information data). Since the data positioned as intangible resource information data includes all the information contained in the corresponding IACC information data, it includes information about the type of non-financial capital to which the corresponding IACC information data belongs. Therefore, intangible resource information data also includes information about the type of non-financial capital to which the intangible resource information contained in the data belongs.

[0218] The specific methods for changing the data's location are not limited. For example, a copy of the data stored in the IACC information database 300 may be stored in the intangible resources information database 310, so that the IACC information database 300 and the intangible resources information database 310 store data that is equivalent in content. Alternatively, data may be effectively transferred between databases (IACC information database 300 → intangible resources information database 310) by deleting the data stored in the IACC information database 300 once data has been stored in the intangible resources information database 310.

[0219] Furthermore, if the IACC information database 300 and the intangible resource information database 310 are essentially composed of a single database, and the database to which data belongs is determined by the setting of data management classifications, then it is possible to position the IACC information data as intangible resource information data by changing the management classification from the IACC information database 300 to the intangible resource information database 310.

[0220] In this case, the IACC information database 300 may be retained as a management category for the IACC information data that has become intangible resource information data. In this case, the data that is stored in the IACC information database 300 and the intangible resource information database 310 may have information added to indicate that it is stored in both databases.

[0221] Thus, the IACC information database 300 and the intangible resources information database 310 only need to be functionally separate; physically, the two databases may or may not be separate. In other words, the IACC information database 300 is primarily established for the purpose of managing the creation of IACC by its members, while the intangible resources information database 310 is primarily established for the purpose of safely (with appropriate confidentiality management) utilizing (including disclosure of) intangible resources. Therefore, as long as each database can fulfill its respective purpose, the physical configuration of the two databases is not limited.

[0222] The information management instruction data generated by the information management unit 260 may include an applicability instruction indicating whether or not the IACC information data may be stored in the intangible resource information database 310 as intangible resource information data. The data indicating the applicability instruction may be attached to individual IACC information data, or it may exist as data that manages the applicability instructions for all IACC information data.

[0223] The first instruction (classification instruction from the perspective of confidentiality management level) of the information management instruction data generated by the information management unit 260 of the organizational value improvement support device 100A has more types than the organizational value improvement support device 100, as shown in the data management relationship diagram in Figure 17. Specifically, in the organizational value improvement support device 100, the confidentiality management levels of IACC in the first instruction were three types: candidate subject matter of industrial property rights, trade secrets, and information that does not require confidentiality management. However, in the organizational value improvement support device 100A, in addition to these three types, there are three more types.

[0224] - Unpublished information with pending applications: This refers to information about potential subjects of industrial property rights for which the necessary requirements for the procedure have been met and an application or application procedure has been filed with the Japan Patent Office or other relevant institution for the creation of the rights. The level of confidentiality required is not as high as that for potential subjects of industrial property rights or trade secrets before the application procedure, but the confidential status will be maintained unless actively disclosed, meaning that each disclosure will result in the information leaking outside the organization.

[0225] ・Published but unpatented information: This refers to information that has been filed with the Japan Patent Office or similar authorities and subsequently made public by them. As it falls under the category of publicly known information, the level of confidentiality is low, and much of the information's content can be disclosed. However, it is important to note that since the corresponding industrial property rights are not yet established, i.e., in the process of obtaining rights, actively disclosing information belonging to the category of published but unpatented information may also disclose unpublished information associated with that information (e.g., technical know-how).

[0226] • Registered information: This is information that has been registered as the subject of industrial property rights by the Japan Patent Office, etc., and therefore does not require any substantial confidentiality.

[0227] If IACC information data includes information that is classified as a candidate subject of industrial property rights, the applicability instruction corresponding to the IACC information data will be an instruction not to allow the IACC information data to be stored in the intangible resource information database 310. This ensures that candidate subject of industrial property rights does not leak out of the intangible resource information database 310. Intangible resource information data stored in the intangible resource information database 310 should be actively utilized within the organization as an intangible asset; therefore, the intangible resource information database 310 is accessed more frequently by members of the organization than the IACC information database 300. For this reason, from the standpoint of managing the confidentiality of information, information stored in the intangible resource information database 310 tends to leak out more easily than information stored in the IACC information database 300.

[0228] If the IACC information data does not include information classified as a candidate subject of industrial property rights, but includes information classified as trade secrets, or information that has been filed but not yet published, published but not yet patented, or patented, the applicability instruction corresponding to the IACC information data will be an instruction to allow the IACC information data to be stored in the intangible resource information database 310, provided that the IACC information data does not include information that is highly relevant to information that could be the subject of industrial property rights. This makes it possible to utilize useful information as intangible assets within the organization.

[0229] If the IACC information data contains only information that does not require confidentiality management among the six categories classified by the first instruction, then that information does not reach the level of an organization's intangible asset and is therefore outside the scope of management of the intangible resource information database 310. Accordingly, the applicability instruction corresponding to that IACC information data will be an instruction that does not permit its storage in the intangible resource information database 310. This prevents the storage of data containing only worthless or low-value information in the intangible resource information database 310. Furthermore, since the information contained in the data stored in the intangible resource information database 310 becomes an organization's asset (intangible asset), preventing worthless or low-value information from being positioned as an intangible asset makes it easier to improve the ease of valuation of intangible assets within the organization and the validity of the valuation results.

[0230] Furthermore, the information management instruction data generated by the information management unit 260 may include confidentiality instructions indicating the degree of confidentiality management of the information contained in the intangible resource information data in the intangible resource information database 310. The confidentiality instructions should be set in accordance with the first instruction regarding the confidentiality level of the IACC included in the IACC information data positioned as intangible resource information data. Specifically, the intangible resource information data can be classified into four types: trade secrets, unpublished information for which applications have been filed, unpatented information for which patents have been published, and patented information.

[0231] The organizational value enhancement support device 100A includes an intangible resource information management unit 251 that generates disclosure management instruction data indicating whether or not intangible resource information data stored in the intangible resource information database 310 can be disclosed to outside the organization and the extent of disclosure, and transmits the disclosure management instruction data to the intangible resource information database 310. Since the information contained in the intangible resource information data stored in the intangible resource information database 310 is the organization's intangible asset, members of the organization can access such information relatively freely.

[0232] However, since this information includes confidential information, it is necessary to manage whether or not it can be disclosed outside the organization and to what extent it is disclosed. The Intangible Resources Information Management Department 251 is responsible for this management. The Intangible Resources Information Database 310 receives disclosure management instruction data generated by the Intangible Resources Information Management Department 251 and manages the information stored in the Intangible Resources Information Database 310 based on the instructions contained in the disclosure management instruction data.

[0233] Under the management of the Intangible Resources Information Management Department 251, the Intangible Resources Information Database 310 outputs information for external disclosure. This external disclosure information is disclosed to external parties, such as information included in the integrated report, if the organization is a company. The integrated report discloses financial statements such as the balance sheet and income statement, and there is consideration to adding intangible resources to these financial statements, i.e., on-booking them. For example, a corporate value balance sheet has been proposed in which an intangible assets column is added after the assets column in the balance sheet, and a non-financial capital column is added to the right of the intangible assets column, below the capital column, to show intangible assets and capital that cannot be displayed in conventional balance sheets. The total internal valuation of intangible resources (monetary equivalent index) is derived by subtracting the net assets from the market capitalization of the company, if the organization is a company. Here, instead of managing (market capitalization) - (net assets) collectively as "goodwill," clarifying the constituent elements makes it possible to individually value intangible resources that were previously unvaluable. This is expected to lead to a fairer valuation of a company's true value.

[0234] Thus, while intangible resources need to be made known to stakeholders, some lose value if disclosed to the extent that their confidentiality cannot be maintained, such as trade secrets. Therefore, it is extremely important to appropriately classify and manage intangible resources according to the level of confidentiality required.

[0235] Furthermore, by indicating which of the five non-financial capital components included in non-financial information an intangible resource corresponds to, it becomes possible to specifically evaluate the operational policies and operational status (management in the case of a company) of an organization such as a company.

[0236] The leftmost part of the data management diagram in Figure 17 shows an example of information management by the Intangible Resources Information Management Department 251. If intangible resource information data includes trade secrets, the content is not disclosed because disclosing it outside the organization would eliminate the value of the intangible resources. When trade secrets are disclosed, one specific example is to disclose only the type of capital to which the trade secrets belong, specifically the number of trade secrets belonging to a particular type of capital (such as manufacturing capital).

[0237] If intangible resource information data contains only filed but unpublished information, industrial property rights based on the filed but unpublished information can still arise even if the confidentiality is lifted by disclosing the contents. However, if the filed but unpublished information is treated as publicly known information, the legal stability of industrial property rights based on priority applications related to the filed but unpublished information may decrease. Therefore, when disclosing filed but unpublished information, one specific example is to disclose only the title of the subject matter if it is an invention.

[0238] If intangible resource information data consists only of publicly available, unpatented information and / or patented information, it is considered publicly known information, and therefore there is no need to restrict its disclosure. Rather, it is preferable to actively disseminate this information and widely inform stakeholders of the existence of valuable intangible resources based on this information. For this reason, disclosing the content as well is one specific example.

[0239] Furthermore, information including potential trade secrets before applications are filed is stored only in the IACC information database 300 and not in the intangible resources information database 310, thus reliably preventing accidental disclosure from the intangible resources information database 310.

[0240] The process performed by the intangible resource information management unit 251 described above may be positioned as part of the intangible resource management process.

[0241] Here, we will explain the relationship between the refinement process and IACC information data shown on the right side of the data management diagram in Figure 17. If the IACC included in the IACC information data includes a candidate subject of industrial property rights, access to that IACC information data will be strictly restricted. Specifically, it is exemplified that only the creator of that IACC and the manager of the intellectual property will be allowed access. IACC information data that includes an IACC classified as a candidate subject of industrial property rights may, in principle, be excluded from the refinement process. In that case, the creator of that IACC may perform the refinement under appropriate confidentiality management during the process leading up to the application or other procedures.

[0242] Other IACCs, i.e., IACC information data including IACCs classified into one or more categories selected from the group consisting of trade secrets, information not requiring confidentiality management, filed but unpublished information, published but unpatented information, and patented information, may also be subject to the refinement process. When IACC information data including IACCs classified as trade secrets is subject to the refinement process, it is preferable to indicate on the first input / output device 400, such as a member's PC which is the interface for the refinement process, that it is subject to high confidentiality management. When IACC information data including IACCs classified as information not requiring confidentiality management is subject to the refinement process, it is preferable to actively include it in the refinement process and enhance its value by adding non-publicity. When IACC information data including IACCs classified as filed but unpublished information is subject to the refinement process, it is preferable to indicate on the first input / output device 400 that it is confidential to the organization to prevent information leakage. When IACC information data, including IACC classified as publicly available but unpatented information or patented information, is subject to the refinement process, the first input / output device 400 may indicate that the patenting process is in progress or that the information has been patented, respectively.

[0243] Configuration 3 will be described with reference to Figure 18. Figure 18 is a diagram illustrating the functions of the auxiliary information management unit of an organizational value improvement support system having an organizational value improvement support device according to one of the other embodiments of the present disclosure. The organizational value improvement support system 1000A has an auxiliary information management unit 330A that manages the auxiliary information database 330.

[0244] The auxiliary information management unit 330A has an IACC information analysis unit 331 that inputs IACC information data subject to the brush-up process from the IACC information database 300 and analyzes the IACC information contained in the IACC information data. Since IACC information is information described in a first format in a specific example, the IACC information analysis unit 331 can automatically extract an overview of IACC, the type of capital, etc. from the IACC information data by extracting predetermined target fields of the first format in the IACC information data.

[0245] The auxiliary information management unit 330A has a search condition generation unit 332 that automatically generates search conditions based on information obtained from the IACC information analysis unit 331. When the IACC information is information described in a first format, the search conditions can be automatically generated by structuring the search conditions in a format consisting of multiple target fields and associating those target fields with the target fields in the first format. In this case, as enclosed by the dashed line in Figure 18, the IACC information analysis unit 331 and the search condition generation unit 332 function as a substantially integrated unit.

[0246] Specific examples of search conditions generated by the search condition generation unit 332 include an overview of IACC, information on non-financial capital of the same type as the non-financial capital to which the IACC information belongs, information on the organization or department to which the member who created the IACC information belongs, information on trends in the field (technology field, industry, etc.) to which the IACC belongs, current events information from the time the IACC information was created until the time of the refinement process, the management and operational philosophy of a company or other organization, management and operational policies, internal organizational information different from financial and performance indicators such as KGI, and combinations thereof.

[0247] The auxiliary information management unit 330A includes an external information retrieval unit 333 that performs searches on an external information network such as the Internet (ExNW) using the search conditions generated by the search condition generation unit 332, and an internal information retrieval unit 334 that performs searches on the auxiliary information database 330. In one example, the search results of the external information retrieval unit 333 are stored in the auxiliary information database 330. The external information retrieval unit 333 and the internal information retrieval unit 334 may both be executed, or only one of them may be executed. Depending on the search conditions, only one may be executed. For example, if the search conditions consist only of information within the organization, only the internal information retrieval unit 334 is executed.

[0248] The auxiliary information management unit 330A has a search result generation and transmission unit 335 that integrates the search results of the external information retrieval unit 333 and / or the internal information retrieval unit 334 and automatically generates data to be sent to the input information generation unit 130. If integration of search results is not required, the search result generation and transmission unit 335 only performs the task of sending the search results to the input information generation unit 130.

[0249] The entry process, which includes the execution of the initial IACC information registration unit 210, and the intangible resource management process, which includes the execution of the intangible resource information registration unit 250, may be configured independently of the brush-up process.

[0250] Figure 19 is a diagram illustrating an organizational value enhancement support device that performs an entry process, relating to another embodiment of the present disclosure. As shown in Figure 19, the organizational value enhancement support device 100B according to this embodiment comprises, as a minimum set of components, an initial IACC information registration unit 210, an initial inference request generation unit 180, an initial transmission / reception unit 190, and a capital statement generation unit 200.

[0251] The initial IACC information registration unit 210 performs a process that includes storing IACC information, for example, IACC information in which the IACC is described in a predetermined first format, and IACC information data that indicates which of the five non-financial capitals the IACC belongs to, in the IACC information database 300.

[0252] The initial inference request generation unit 180 takes IACC basic information data, which is basic information for IACC information data and includes IACC information, as input and generates initial inference request data.

[0253] The initial transmission / reception unit 190 transmits initial inference request data to the initial generation model 920 and receives initial inference result data from the initial generation model 920. The initial inference request included in the initial inference request data is to generate a proposal on which of the five non-financial capitals the IACC should belong to, as a result of analyzing the IACC basic information data.

[0254] The capital presentation generation unit 200 takes initial inference result data as input, identifies proposed non-financial capital types from the initial inference result data, and performs a process that includes generating capital presentation data for displaying the identified non-financial capital types.

[0255] The initial IACC information registration unit 210 also performs processing that includes identifying proposed non-financial capital types from the initial inference result data, and generating IACC information data based on the identified non-financial capital types and IACC basic information data.

[0256] The initial inference request generated by the initial inference request generation unit 180 of the organizational value improvement support device 100B generates initial public knowledge proposal information that includes the results of an examination of whether or not IACC is publicly known. Furthermore, if the initial public knowledge proposal information proposes that it is publicly known, the initial inference request will indicate publicly known information that is determined to include IACC, and if the initial public knowledge proposal information proposes that it is not publicly known, it will indicate publicly known information that is determined to be the closest to IACC.

[0257] In this way, the organizational value enhancement support device 100B makes a determination of public knowledge at the entry process stage, making it easier to manage the confidentiality of non-public information. Specifically, the organizational value enhancement support device 100B includes an initial public knowledge display generation unit 280 and an initial confidentiality management setting unit 290.

[0258] The initial public information indication generation unit 280 takes the initial inference result data as input and determines whether the IACC is public or private based on the initial public information proposal information. If it determines that the IACC is private, it performs a process that includes generating initial non-public information indication data that includes a notice indicating that the IACC may be confidential information.

[0259] The initial non-public information display data generated by the initial public information display generation unit 280 makes it possible to inform the initial operator performing the entry process that the IACC being targeted may contain non-public information.

[0260] The initial confidentiality management setting unit 290 takes the initial inference result data as input and determines whether the IACC is public or private based on the initial public knowledge proposal information. If it determines that the IACC is private, it performs a process that includes setting the management attribute of the IACC information data to data that includes a candidate for the subject of industrial property rights.

[0261] The initial confidentiality management setting unit 290 and the information management unit 260 enable proper confidentiality management of the IACC that is the target of the entry process.

[0262] The initial public information display generation unit 280 and the initial confidentiality management setting unit 290 may also be present in organizational value improvement support devices 100, 100A according to embodiments other than this embodiment.

[0263] Figure 20 illustrates an organizational value enhancement support device that performs an intangible resource management process, relating to another embodiment of the present disclosure. The organizational value enhancement support device 100C according to this embodiment comprises, as a minimum set of components, an intangible resource information registration unit 250, an intangible resource inference request generation unit 230, and an intangible resource transmission / reception unit 240.

[0264] The intangible resource information registration unit 250 performs a process that includes storing intangible resource information data in the intangible resource information database 310, which includes information on the intangible resources owned by the organization and data indicating the type of non-financial capital to which these intangible resources should belong.

[0265] The intangible resource inference request generation unit 230 takes intangible resource basic information data, which is basic information for intangible resource information data and includes information about intangible resources, as input and generates intangible resource inference request data.

[0266] The intangible resource transmission / reception unit 240 transmits intangible resource inference request data to the intangible resource generation model 930 and receives intangible resource inference result data from the intangible resource generation model 930.

[0267] The intangible resource inference request included in the intangible resource inference request data involves generating a proposal for the type of non-financial capital to which the intangible resource should belong, as a result of analyzing the intangible resource basic information data.

[0268] The intangible resource information registration unit 250 takes intangible resource inference result data and intangible resource basic information data as input, identifies the proposed type of non-financial capital from the intangible resource inference result data, and performs a process that includes generating intangible resource information data based on the identified type of non-financial capital and the intangible resource basic information data.

[0269] Furthermore, the intangible resource basic information data may include types of non-financial capital. If the intangible resource basic information data includes IACC information data stored in the IACC information database 300, then the types of capital in IACC are included, and therefore the types of non-financial capital of intangible resources are included. Even in this case, since the types of capital in IACC are based on the proposed results of the first generative model 910 and the initial generative model 920, if the intangible resource generative model 930 differs from these pre-trained generative models, different proposals may be made. Since pre-trained generative models usually continue to be retrained, the degree of learning is constantly changing. Therefore, even if the pre-trained generative models are outwardly identical, if the access timing differs, strictly speaking, an inference request has been made to a pre-trained generative model with a different degree of learning. For this reason, it is meaningful to check the types of non-financial capital multiple times in this manner.

[0270] In the organizational value enhancement support device 100C, similar to the organizational value enhancement support device 100, the intangible resource information data may include information on SDGs targets related to intangible resources. Furthermore, the intangible resource inference request may include generating proposals for SDGs targets related to intangible resources as a result of analyzing the intangible resource basic information data.

[0271] The intangible resource generation model 930 is not limited in its sources of information for SDGs targets when it includes proposed SDGs targets related to intangible resources in the intangible resource inference result data. As shown in Figure 20, SDGs data, which is data about SDGs targets, is stored in the SDGs database 340, and when the intangible resource inference request generation unit 230 generates an intangible resource inference request, it may use the SDGs data stored in the SDGs database 340, thereby making the intangible resource inference request a source of information for SDGs targets. Alternatively, the intangible resource inference request does not need to specify a source of information for SDGs targets. In that case, the intangible resource generation model 930 searches for information on SDGs targets based on the inference request and generates appropriate proposals for SDGs targets.

[0272] The intangible resource information registration unit 250, similar to the organizational value improvement support device 100, identifies proposed SDGs targets from the intangible resource inference result data, includes information on the identified SDGs targets in the intangible resource information data, and stores the intangible resource information data with the added information in the intangible resource information database 310.

[0273] Figure 21 is a block diagram illustrating the functions of the input information generation unit. As shown in Figure 1, the input information generation unit 130 reads data from the IACC information database 300 and generates a first input information data set. Figure 20 is a block diagram illustrating the generation process of this first input information data set and related processes.

[0274] The input information generation unit 130 includes an IACC information reading unit 131, an intangible resource information reading unit 132, a performance-related information reading unit 133, an emotion information identification unit 136, and an auxiliary information reading unit 137, as well as a data group generation unit 134, and further includes a citation notification generation unit 135. The organizational value improvement support device 100 includes a citation notification counting unit 270 in relation to the citation notification generation unit 135.

[0275] Since the IACC information reading unit 131 reads data from the IACC information database 300, which stores data subject to high-level confidentiality management, it has an access control verification unit 131A, an access control unit 131B, and a reading unit 131C in relation to access control.

[0276] The authorization verification unit 131A identifies a first operator attempting to access the IACC information data stored in the IACC information database 300 for the purpose of refinement, and verifies the access rights of the identified first operator. The method for identifying the first operator is not limited; in Figure 21, operator identification data is received from the first input / output device 400, and access rights are verified based on the information contained in this data. A specific example of operator identification data is a set of user ID and passcode.

[0277] For example, if the IACC information data to be accessed includes an IACC that is a candidate for the subject of an industrial property right, access rights to that data are granted only to the creator of that IACC and the manager of the candidate for the subject of the industrial property right, such as the intellectual property department. Therefore, if the first operator is neither the creator of that IACC nor the manager of the candidate for the subject of the industrial property right, the authorization verification unit 131A confirms that the first operator does not have the authority to access the IACC information data to be accessed.

[0278] The access control unit 131B allows the first operator to access the IACC information data stored in the IACC information database 300, within the scope of the access rights confirmed by the authorization verification unit 131A. To further explain using the previous example, the access control unit 131B does not permit the first operator to access the IACC information data to be accessed if the first operator does not have the necessary access rights to that data. If the first operator is the creator (initial operator) of the IACC, or otherwise has the necessary access rights to the IACC information data to be accessed, the access control unit 131B permits the first operator to access the data.

[0279] If the first operator wishes to access multiple data items in a single operation, the access control unit 131B sets the accessible data based on the confirmation result of the authorization confirmation unit 131A. The multiple data items authorized by the access control unit 131B become available for display on the first input / output device 400, and by recognizing this display, the first operator accesses the desired IACC information data. In Figure 21, the first input / output device 400 receives IACC information display data from the IACC information database 300, and based on the IACC information display data, multiple data items are displayed on the first input / output device 400. Here, the IACC information display data is instruction data that causes the first input / output device 400 to display the information contained in the IACC information data that has become available for display on the first input / output device 400. In this case, since the predetermined information is displayed on the first input / output device 400 without directly leaking IACC information data from the IACC information database 300, the possibility of information leakage can be reduced.

[0280] The access control unit 131B may grant the first operator, identified by the authorization verification unit 131A, access to multiple data sets. A specific example of such a case is when the access control unit 131B allows the first operator to display their own IACC (in this case, the first operator and the initial operator are the same person) and other IACCs. Here, other IACCs refer to IACCs that are not created by the accessing first operator but are permitted to be viewed.

[0281] In this case, the access control unit 131B may generate display filter instruction data that is permitted for the IACC information database 300 and transmit the display filter instruction data to the IACC information database 300. Upon receiving this display filter instruction data, the IACC information database 300 generates IACC information display data, including information on its own IACC and other IACCs, based on the instructions in the display filter instruction data, and makes the predetermined information available for display on the first input / output device 400.

[0282] The reading unit 131C identifies the IACC information data that the first operator has decided to include in the first input information data group from the IACC information data accessible to the first operator, and reads the identified IACC information data from the IACC information database 300.

[0283] As described above, if we take the case where a predetermined set of information is displayed on the first input / output device 400 without directly leaking IACC information data from the IACC information database 300 as a specific example, the first operator selects, for example, one desired piece of information from the set of information displayed on the first input / output device 400. Since the IACC information data corresponding to this selected information is the IACC information data that has been decided to be included in the first input information data group, the reading unit 131C identifies this data and reads the identified IACC information data from the IACC information database 300. In Figure 21, as an example, a read request is output from the IACC information reading unit 131, which includes the reading unit 131C, and the predetermined IACC information data is output from the IACC information database 300, which receives this request, to the IACC information reading unit 131.

[0284] The intangible resource information reading unit 132 takes as input the IACC information data identified by the IACC information reading unit 131 and read from the IACC information database 300. Based on this IACC information data, the intangible resource information reading unit 132 identifies which of the intangible resource information data stored in the intangible resource information database 310 should be read. The intangible resource information reading unit 132 then reads this identified intangible resource information data from the intangible resource information database 310. In this way, information processing, including data transmission and reception, is performed in the IACC information reading unit 131 and the intangible resource information reading unit 132, thereby enabling the automatic generation of a first inference request that includes performance-related information data belonging to the same type of non-financial capital as the IACC information data targeted for the brush-up process.

[0285] The performance-related information reading unit 133 identifies the financial and performance indicators that the first operator has decided to improve, and reads performance-related information data, including the target values ​​of these identified financial and performance indicators, from the performance-related information database 320. Specifically, as shown in Figure 21, the first operator receives data indicating the financial and performance indicators to be targeted through input from the first input / output device 400 operated by the first operator, and creates read request data from the received data indicating the financial and performance indicators. The read request data is sent to the performance-related information database 320, and based on the data received from the performance-related information database 320, predetermined performance-related information data is generated, and that performance-related information data is output to the data group generation unit 134.

[0286] In the embodiment shown in Figure 13, data including all target values ​​for financial and performance indicators is pre-loaded into the organizational value improvement support device 100 and displayed. In this case, the performance-related information loading unit 133 does not need to create loading request data and can generate performance-related information data including the desired target values ​​for financial and performance indicators from the pre-loaded data.

[0287] The input information generation unit 130 of the organizational value improvement support device 100 may have an emotion information identification unit 136 in relation to the first emotion. The emotion information identification unit 136 identifies the first emotion included in the personal emotion information data. As a result, the first inference request generation unit 110 can take data including the first emotion identified by the emotion information identification unit 136 as input.

[0288] The specific configuration of the emotion information identification unit 136 can take various forms. For example, the emotion information identification unit 136 may be configured to receive the first emotion directly, which is input by the first operator performing the brush-up process using the first input / output device 400. In this case, since the expression format of the first emotion can vary widely, the influence of the first emotion on the first proposal depends on the expression format of the first emotion, which can become an instability factor for the first proposal.

[0289] Therefore, as a concrete example, the emotion information identification unit 136 may have an emotion display unit 136A that generates emotion display data that allows the user to select and display a predetermined number of emotions. For example, the emotion display unit 136A prepares several expressions that represent emotions such as "excited" and "feeling accomplished," and displays these expressions on the first input / output device 400 in a selectable manner. The first operator selects one of these expressions as the first emotion, and the data including the selection result is output from the first input / output device 400 to the emotion information identification unit 136.

[0290] The emotion display unit 136A includes an emotion determination unit 136B that determines which of the multiple emotions displayed on the emotion display unit 136A has been selected as the first emotion, thereby identifying the first emotion.

[0291] The input information generation unit 130 of the organizational value improvement support device 100 may also have an auxiliary information reading unit 137 in relation to auxiliary information such as current events information. The auxiliary information reading unit 137 identifies which of the auxiliary information data stored in the auxiliary information database 330 is to be read, and reads the identified auxiliary information data from the auxiliary information database 330.

[0292] The auxiliary information reading unit 137 includes a read request generation unit 137A. The read request generation unit 137A determines which of the auxiliary information data stored in the auxiliary information database 330 to read, generates a read request to the auxiliary information database 330, and transmits the read request to the auxiliary information database 330. As mentioned above, there are various types of auxiliary information (current events information, industry trends, basic management information, etc.), so the auxiliary information reading unit 137 may first identify what type of information to read and then determine the subsequent processing according to the type of information to be read.

[0293] More specifically, the auxiliary information database 330 may consist of multiple databases corresponding to different types of information. In that case, a read request will determine which of the multiple databases to access depending on the type of information to be read. In this case, access restrictions may prevent the read request from being accepted. The access control unit 131B may be responsible for handling these access restrictions.

[0294] The auxiliary information reading unit 137 includes a data reading unit 137B that receives auxiliary information data prepared in accordance with a reading request from the auxiliary information database 330.

[0295] When reading auxiliary information such as current events information from the auxiliary information database 330, it is sometimes preferable to set a certain level of filter to alleviate the load on subsequent processing (generation of the first input information data group and generation of the first inference request). From this perspective, the read request generation unit 137A may determine that the target of the read request is auxiliary information data that includes auxiliary information belonging to non-financial capital equivalent to the non-financial capital to which the IACC subject to the brush-up process belongs, which is included in the IACC information data.

[0296] The input information generation unit 130 includes read IACC information data, read intangible resource information data, and read performance-related information data. In a preferred example, it further includes a data group generation unit 134 that generates a first input information data group from data including a first emotion and read auxiliary information data. The specific format of the first input information data group generated by the data group generation unit 134 is not limited. Any format is acceptable as long as the first inference request generation unit 110, which uses the first input information data group as input data, can perform appropriate processing.

[0297] From the perspective of developing IACC, it is sometimes preferable to focus the refinement process on other people's IACC rather than one's own. When refining an IACC created by oneself, the context in which it was created can act as a limitation, making it difficult to incorporate free thinking beyond the original creation. In contrast, when using other people's IACC as the target of the refinement process, it is less constrained by the context in which it was created, making it easier to incorporate free thinking.

[0298] From the perspective of promoting the combination of such ideas and increasing the incentive to create IACCs, the input information generation unit 130 has a citation notification generation unit 135 that generates citation notification data to notify the creator of another person's IACC of the decision when the first operator performing the brush-up process decides to include another person's IACC in the first input information data group.

[0299] Specifically, for example, when a member who has created a certain IACC accesses the organizational value improvement support device 100 as an initial operator via the initial input / output device 410 to create initial IACC information data, the citation notification generation unit 135 displays that the IACC previously created by the member has been cited by other members as another member's IACC and is subject to a refinement process. This allows the member to know that the IACC they created was at a level that was also valued by other members. As a result, the initial operator gains a sense of accomplishment by knowing that they have effectively contributed to increasing the organization's intangible assets. This feeling contributes to increasing the initial operator's level of engagement with the organization.

[0300] The citation notification generation unit 135 may generate data to display to the creator of the IACC, not only that other members have cited it, but also information about the affiliation of the citing member, such as their department. For example, by knowing that the IACC created by the creator has been cited as a subject for the refinement process by a member of a department less relevant to their own work, the creator can re-evaluate the value of the IACC they have created. As a result, they may realize that the limitations they felt when creating the IACC were not valid, and such realization can strongly contribute to the further growth of the IACC.

[0301] From the perspective of particularly increasing the incentive to create IACCs, the organizational value improvement support device 100 may have a citation notification count unit 270 that records how many citation notification data have been generated for each IACC information data. By recording the number of times it has been cited by other members, it becomes possible to provide creators with a quantitative incentive for citation. In addition, since the degree of citation can be compared with other IACCs (which may be other IACCs created by the user or IACCs created by others), a game element is incorporated into the refinement process. This is expected to contribute to the revitalization of the refinement process.

[0302] A specific example of the citation notification sent to the IACC creator by the citation notification generation unit 135 and the citation notification count unit 270 is the information displayed in the lower left area of ​​Figure 6 (employee number, name, team affiliation) and the number indicated by the "selection points" above it.

[0303] The processing performed by the first inference request generation unit 110 will be explained in detail using Figure 21. The first inference request generation unit 110 includes a first information identification unit 111 and a first prompt generation unit 112. The first information identification unit 111 takes as input the first input information data group generated by the data group generation unit 134 of the input information generation unit 130, and identifies multiple pieces of information included in the first input information data group. Even if the first input information data group consists of IACC information data, since IACC information data contains multiple pieces of information, the first input information data group will contain multiple pieces of information.

[0304] The first prompt generation unit 112 automatically generates first inference request data, including the execution of a process to generate management data by automatically placing each of the multiple pieces of information included in the first input information data group into a predetermined target field.

[0305] In Figures 1 and 21, the input information generation unit 130 and the first inference request generation unit 110 are shown as independent functional blocks. The input information generation unit 130 forms the first input information data group, and the first inference request generation unit 110 receives the first input information data group output from the input information generation unit 130. However, this information processing is just one example, and this embodiment is not limited to this example. For example, the data constituting the first input information data group does not necessarily have to be bundled as the first input information data group in the input information generation unit 130. The first information identification unit 111 or the first prompt generation unit 112 may collect the desired data individually from each database. In this case, the first inference request generation unit 110 has the function of the data group generation unit 134, and this is included as one specific example of this embodiment. Therefore, the first inference request generation unit 110 may include the function of the input information generation unit 130.

[0306] The process by which the first prompt generation unit 112 automatically generates the first inference request data will be explained below using a specific example.

[0307] In one example, the first prompt generation unit 112 has the following automatically generated resources.

[0308] In order to achieve (and improve) our company's " & [RO] Global-KPI Rate-Type & " goals, && "Our company's [corporate selling points] (each point is separated by a line break) and && "Team members' [specific behavioral indicators]" && "in light of the following "current events", && " & [RO] Reflection-Name & " proposes a summary of specific actions", && " & [RO] Global-Action Items & " " proposes a summary of specific actions", && " & [RO] Global-Action Items & " " proposes a summary of specific actions", && " & [RO] Global-Action Items & " " proposes a summary of specific actions", && "In light of the following "current events", && " & [RO] Reflection-Name & " proposes a summary of specific actions", && "In light of the following three capital types", && " " Manufacturing capital, social and relational capital, and natural capital. && "If the specific actions proposed by " & [RO] Reflection-Name & " proposes a summary of specific actions", && "in light of specific actions", && "Provide advice on how to improve them as "human capital" only if they relate to people's KSAs (knowledge, skills, abilities, etc.)". && "Provide advice on how to improve them as "human capital". "&& "Finally, please indicate whether the content of the analysis response is generally "publicly known" or "not publicly known." "&& "If it is publicly known, please also include the web information (URL, etc.) where the content is described. If it is not publicly known, please include the web information (URL, etc.) that is closest to the content. "&&& "When describing the analyzed response, be sure to write it at the very beginning (beginning of the line) as follows ((α)・(β)・(γ))." " &&& "(α)" & "Improvement Proposal" & [RO] Reflection - Name & "Specific Behavioral Indicators" && [" Strengths] ●●●●●●●●●●●●●●" && [" Objective] ●●●●●●●●●●●●●●" && [" Overview] ●●●●●●●●●●●●●●" & [" Results / Effects] ●●●●●●●●●●●●●●" && [" Capital Type] ●● Capital" &&& "(β) [" & [RO] Global - Sentiment / Indicators & "] Behavioral Indicators Incorporating These Elements" & " " ●●●●●●●●●●●●●●●●●●●●●●●●●●●●" &&& "(γ) (Content of (α)) is publicly known or not" && " " ●●●●●●" &&& "When writing your answer, please be sure to write (α), (β), and (γ) first." && "Please write any other reasons after (α), (β), and (γ)."" &&& "Now, I will provide you with the following analysis information. Thank you." &&& "-------------------------------------------------------------" && "Below, "Current Events"" &&& "<Title>:" & [RO] News Title - Rel & ¶ & "<Body>:" & [NE] Current Events / News Library [NE] News Content && "-------------------------------------------------------------" &&& "-------------------------------------------------------------" && "Below, [Company Selling Points]" &&& [RO] [S2] Settings - Company - Non-Financial Capital [S2] ● Part 2 - Aggregation - Capital Items - Trade Secrets / ROIC Analysis && "-------------------------------------------------------------" &&& "-------------------------------------------------------------" && "Below, Team Members' [Specific Behavioral Indicators]" &&& [RO] Team Capital [S1] Settings - Person - Non-Financial Capital [S1] Aggregation - ROIC Display - List - B - Overview - Capital Set && "-------------------------------------------------------------".

[0309] In the automatically generated resources above, characters or strings enclosed in double quotes, such as "our company" (in the example above, this would be "our company"), indicate that they are part of the text describing the first inference request in the first inference request data. The "&" indicates that the characters or strings before and after it are joined together without any breaks.

[0310] In the example "[RO]Global-KPI-Rate-Type", "[RO]" and the string that follows it (in the example above, "Global-KPI-Rate-Type") are the "target fields," and this is an instruction to place a predetermined string representing the information entered by the first operator into this target field. The relationship (linking) between the target field and the information (string) is set separately.

[0311] Therefore, if the string associated with the target field "[RO] Global-KPI Rate-Type" is "Sales Growth Rate", the automatically generated resource consisting of "Our Company's " & [RO] Global-KPI Rate-Type will automatically generate the text "Our Company's Sales Growth Rate".

[0312] "&&" is an instruction to insert a line break in automatically generated text, and "&&&" is an instruction to insert a line break and then an additional blank line in automatically generated text.

[0313] The first prompt generation unit 112 first reads the automatically generated resources from the storage device, and then prepares a string corresponding to each target field. To prepare this string, it may obtain information from the first information identification unit 111, which has information generated by the input information generation unit 130, or it may directly access the IACC information database 300 or the like to collect the necessary information. When obtaining information from the first information identification unit 111, the information obtained will be appropriately managed by the access control unit 131B, and when directly accessing the IACC information database 300, separate access management will be performed.

[0314] An example of text automatically generated by the first prompt generation unit 112 from the above automatically generated resources is as follows:

[0315] To achieve our sales growth rate target (including improvement), please describe the following advice for refining the specific action outline proposed by Kunihiro Katagiri, "01-B [Trade Secret Candidate / Personal Skill] ★★★," based on our company's [Corporate Selling Points] (each point is separated by a line break) and the team members' [Specific Action Indicators], in relation to the "Current Events" below, into the following three capital types: "Manufacturing Capital," "Social / Relational Capital," and "Natural Capital." If the specific action proposed by Kunihiro Katagiri that is being analyzed is an institution or system and relates to people's KSAs (Knowledge, Skills, Abilities, etc.), please describe the advice for refining it as "Human Capital." Finally, please indicate whether the content of your analysis is generally "publicly known" or "not publicly known." If it is publicly known, please provide the web information (URL, etc.) where the content is described; if it is not publicly known, please provide the web information (URL, etc.) that is closest to the content. When writing your analyzed response, be sure to write it at the very beginning (at the start of the line) as follows ((α)・(β)・(γ)). (α) Improvement proposal Katagiri Kunihiro's [Specific action indicators] [Strengths] ●●●●●●●●●●●●●● [Purpose] ●●●●●●●●●●●●●● [Overview] ●●●●●●●●●●●●●● [Results / effects] ●●●●●●●●●●●●●● [Type of capital] ●● capital (β) Action indicators that incorporate elements that [make you feel happy] "●●●●●●●●●●●●●●●●●●●●●●●●●●●●●" (γ) Is (the content of (α)) publicly known or not "●●●●●●" When writing your response, be sure to write (α)・(β)・(γ) first. Other reasons should be written after (α)・(β)・(γ). Now, I will provide you with the analysis information below. Thank you.------------------------------------------------------------- Below is "Current Events" <Title>: 01 [Current Events Title Regarding Sales Growth Rate] <Body>: 01 [Current Events Regarding Sales Growth Rate] ★★★ ------------------------------------------------------------- ------------------------------------------------------------- Below is [Company Selling Points] [Company Selling Points] ★★★ [Company Selling Points] ★★★ ------------------------------------------------------------- ------------------------------------------------------------- Below are [Specific Behavioral Indicators] of Team Members [Specific Behavioral Indicators] ★★★ [Specific Behavioral Indicators] ★★★ -------------------------------------------------------------.

[0316] In the automatically generated text above, the string consisting of 01-B[Trade Secret Candidates / KSAs]★★★ actually corresponds to a string indicating specific action summary information linked to the target field [RO]Global-Action Items, which is placed after 01-B[Trade Secret Candidates / KSAs]. The same applies to other "★★★" in the automatically generated text, meaning that in reality, strings indicating specific information will be placed there.

[0317] In the example above, the first inference request data automatically generated by the first prompt generation unit 112 includes text, but is not limited to this. The first inference request data may also include sonic / vocal information, such as voice or music, or it may include images or videos. In such cases, when the first inference request data includes data other than text, other pre-trained generative models (such as music generation models, video generation models, or image generation models) may be used as the generated data instead of, or in conjunction with, the large-scale language model, or a multimodal model may be used.

[0318] The functions of the initial inference request generation unit 180 will be described below. Figure 22 is a block diagram illustrating the functions of the initial inference request generation unit. The initial inference request generation unit 180 includes an IACC partial information identification unit 181, an initial prompt generation unit 182, and an input display generation unit 183.

[0319] The IACC partial information identification unit 181 receives IACC basic information data, which is the basic information data for IACC information data, from the initial input / output device 410, and identifies multiple partial information contained in the IACC basic information data. These multiple partial information are the basic data for IACC information data and constitute IACC information.

[0320] The input display generation unit 183 performs a process that includes generating input display data having multiple input fields corresponding to multiple partial information to be included in the IACC information data, and outputs the input display data to the initial input / output device 410. An example of the display (graphical user interface) output to the initial input / output device 410 using the input display data generated by the input display generation unit 183 is shown in Figure 6.

[0321] Specifically, the display (graphical user interface) shown in Figure 6 has multiple input fields for text, etc. These input fields correspond to the multiple target fields of the first format, namely, (A) Strengths / selling points, (B) Overview, (C) Objectives / goals, (D) Results or effects, (E) Concerns / issues, (F) Type of capital, and (G) Status. The text data etc. entered into each input field by the initial input / output device 410 is saved as the value of the corresponding target field. In addition to these input fields, Figure 6 also shows an input field labeled "Notes for improvement during AI analysis" in which a string equivalent to the name of IACC can be entered.

[0322] The capital type (F) included in the first format can be entered from the input field by the initial input / output device 410. When the entry process shown in Figure 19, etc., is executed and a capital type is proposed from the initial generation model 920, the capital type related to that proposal is overwritten in this input field, allowing the first operator to confirm the proposed capital type. The first operator may adopt the proposed capital type or enter a different capital type into the input field. The capital type that is finally displayed in the input field becomes the value of the target field corresponding to the capital type (F) in the first format.

[0323] The (G) status included in the first format is also shown as an input field, but by executing the entry process, the processing result of the initial publicly known information generation unit 280, which is executed based on the proposed initial generation model 920, is overwritten and displayed, allowing the first operator to confirm the publicly known information of the IACC.

[0324] When a first operator inputs multiple partial pieces of information into multiple input fields of the graphical user interface displayed on the initial input / output device 410, the IACC partial piece of information identification unit 181 takes the data containing the input multiple partial pieces of information as input, generates multiple pieces of data corresponding to each of the multiple pieces of information, and outputs a set of datasets containing these multiple pieces of data to the initial prompt generation unit 182.

[0325] The initial prompt generation unit 182 receives a set of datasets output by the IACC partial information identification unit 181 and identifies multiple partial information from the datasets. The initial prompt generation unit 182 has an initial format in which the target fields to which each of the identified multiple partial information should be placed are predetermined. The initial prompt generation unit 182 automatically generates initial inference request data, including the execution of a process to automatically place the corresponding multiple partial information into each of the target fields of the initial format. The automatically generated initial inference request data is output from the initial prompt generation unit 182 to the initial transmission / reception unit 190 and transmitted to the initial generation model 920.

[0326] An example of an automatically generated resource possessed by the initial prompt generation unit 182 is shown below. This automatically generated resource corresponds to the initial format described above. The rules for string manipulation in the automatically generated resource are the same as those for the first prompt generation unit 112. In the automatically generated resource below, "[S1] ● Part 1 - Cal - Capital Item" etc. are the target fields set in the initial format, and a string representing partial information entered by the initial operator is automatically placed in this target field. The text thus automatically generated constitutes at least a part of the initial inference request data.

[0327] "Please compare the following text [Subject of Analysis] with [Analysis Material Text 1 (Definition of Capital by Team Members)] and [Analysis Material Text 2 (Definition of Capital by Our Company)], and determine which of the five non-financial capitals—"Human Capital," "Intellectual Capital," "Manufacturing Capital," "Social Capital," and "Natural Capital"—it falls under, and also determine whether its content is generally "publicly known" or "not publicly known." Please answer accordingly. "The format for writing your answer should be as follows: "Answer" "Capital Type: ●● Capital / Patent Characteristics: Publicly Known or Not Publicly Known" "Please be sure to begin your answer with this statement, followed by the reason. "Please be sure to summarize the request and your answer policy afterwards. " Please write everything in Japanese. " &&& "───────────────────────────────"&& ["Target of Analysis]↓" &&& [S1] ● Part 1 - Cal - Capital Items && "───────────────────────────────"&&& "───────────────────────────────"&& ["Analysis Material Document 1 (Definition of Capital for Team Members)]↓" &&& Self-Relation [S1] Team - For Analysis [S1] ● Part 2 - Aggregation - Capital Items - For ROIC Analysis && "───────────────────────────────"&&& "───────────────────────────────"&& ["Analysis Material Document 2 (Definition of Capital for Our Company)]↓" &&& [S2] Settings - Company - Non-Financial Capital [S2] ● Part 2 - Aggregation - Capital Items - For Trade Secrets and ROIC Analysis && "────────────────────────────────"

[0328] An example of text automatically generated by the initial prompt generation unit 182 from the above-mentioned automatically generated resources is as follows:

[0329] Please compare the following text under [Analysis Subject] with [Analysis Material Text 1 (Definition of Capital by Team Members)] and [Analysis Material Text 2 (Definition of Capital by Our Company)], and determine which of the five non-financial capitals—"Human Capital," "Intellectual Capital," "Manufacturing Capital," "Social Capital," and "Natural Capital"—it falls under. Also, please determine whether its content is generally "publicly known" or "not publicly known." Please write your answer in the following format: Answer Capital Type: ●● Capital / Patent Characteristics: Publicly known or Not Publicly Known. Please state your answer at the beginning of your response, followed by your reasoning. Please also include a summary of the request and your response strategy afterwards. Please write everything in Japanese. ─────────────────────────────────── [Target of Analysis]↓ [Company Sales Points]01-A [Candidate Trade Secrets / Individual Skills]★★★ <Overview>01-B [Candidate Trade Secrets / Individual Skills]★★★ <Objective>01-C [Candidate Trade Secrets / Individual Skills]★★★ Objective / Objective <Results / Effects>01-D [Candidate Trade Secrets / Individual Skills] Results or Effects★★★ ─────────────────────────────────── ─────────────────────────────────── [Analysis Material Text 1 (Definition of Team Members' Capital)]↓ [Company Sales Points]★★★ [Company Sales Points]★★★ [Company Sales Points]★★★ ─────────────────────────────────── ─────────────────────────────────── [Analysis Material Text 2 (Definition of Our Company's Capital)]↓ [Company Sales Points] ★★★ [Company Sales Points] ★★★ [Company Sales Points] ★★★ ───────────────────────────────────

[0330] In the example above, the initial inference request data automatically generated by the initial prompt generation unit 182 includes text, but is not limited to this. The initial inference request data may also include sonic / vocal information, such as voice or music, or it may include images or video.

[0331] The functions of the intangible resource inference request generation unit 230 will be described below. Figure 23 is a block diagram illustrating the functions of the intangible resource inference request generation unit. The intangible resource inference request generation unit 230 includes an intangible resource information input unit 231 and an intangible resource prompt generation unit 232.

[0332] The intangible resource information input unit 231 receives intangible resource basic information data from the intangible resource information database 310 and identifies the intangible resource information contained in the intangible resource basic information data. The intangible resource prompt generation unit 232 automatically generates intangible resource inference request data, including the execution of a process to automatically place the intangible resource information into the target field of the intangible resource format, which is a format data in which the target field where the intangible resource information should be placed is predetermined. The generated intangible resource inference request data is output to the intangible resource transmission / reception unit 240, and upon receiving this data, the intangible resource transmission / reception unit 240 transmits the intangible resource inference request data to the intangible resource generation model 930 and receives intangible resource inference result data from the intangible resource generation model 930.

[0333] An example of an automatically generated resource possessed by the intangible resource prompt generation unit 232 is shown below. This automatically generated resource corresponds to the intangible resource format described above. The rules for string manipulation in the automatically generated resource are the same as those for the first prompt generation unit 112. In the automatically generated resource below, "[S2] Capital - Description / Remarks" is the target field set in the intangible resource format, and a string corresponding to the information contained in the intangible resource basic information data is automatically placed in this target field. The text thus automatically generated constitutes at least a part of the initial inference request data.

[0334] Please analyze the following text and tell us the corresponding item and target number in the SDGs. Also, please explain the reason and answer in the format "Target 1.1" at the end. (All in Japanese) Furthermore, please tell us which of the following five categories it falls under: "Human Capital," "Intellectual Capital," "Manufacturing Capital," "Social Capital," or "Natural Capital." Please write your answer in the format "●● Capital / Target 0.0" with a line break at the end. " &&& [S2] Capital - Explanation / Remarks

[0335] Please analyze the following text and identify the corresponding SDG item and target number. Please also include your reason and conclude with "Target 1.1" (in Japanese). Furthermore, please indicate which of the following five capitals it falls under: Human Capital, Intellectual Capital, Manufacturing Capital, Social Capital, or Natural Capital. Please write your answer on a new line at the end, like this: ●● Capital / Target 0.0. Five Non-Financial Capitals from a Corporate Perspective ★★★

[0336] In the example above, the intangible resource inference request data automatically generated by the intangible resource prompt generation unit 232 includes text, but is not limited to this. The intangible resource inference request data may also include sonic / vocal information, such as voice or music, or it may include images or video.

[0337] An organizational value improvement support program according to one embodiment of this disclosure transmits first inference request data generated based on a first input information data set to a first generative model which is a pre-trained generative model, and receives first inference result data from the first generative model.

[0338] The organizational value enhancement support program comprises the following processes: (a) collecting data that should be included in the first input information data group; (b) generating first inference request data based on the first input information data group; (c) sending the first inference request data to the first generative model; and (d) receiving first inference result data from the first generative model.

[0339] The first input information data set includes IACC information data containing IACC information, intangible resource information data containing information on intangible resources belonging to the same type of non-financial capital as the non-financial capital to which the IACC belongs among the intangible resources owned by the organizations to which the members belong, and performance-related information data containing target values ​​for the organization's financial and performance indicators. The first inference request included in the first inference request data includes generating a first proposal to improve the financial and performance indicators contained in the performance-related information data, based on the IACC information data and the intangible resource information data.

[0340] An organizational value improvement support system according to one embodiment of the present disclosure comprises a first device having input / output functions, a second device consisting of at least one device having a data storage function, and a third device equipped with a control unit. The first device is capable of communicating with the second and third devices.

[0341] The second device includes an IACC information database that stores IACC information data, including IACC information; an intangible resource information database that stores data including information on intangible resources owned by the organizations to which the members belong; and a performance-related information database that stores performance-related information data, including target values ​​for the organization's financial and performance indicators.

[0342] The control unit of the third device has a first inference request generation unit that generates first inference request data to be input to a pre-trained generative model based on data input from the first device.

[0343] The first device comprises an input / output unit and a transmit / receive unit. The input / output unit receives a first input information data set from the second device, which includes IACC information data, intangible resource information data which is part of the data stored in the intangible resource information database and includes information on intangible resources belonging to the same type of non-financial capital as the non-financial capital to which IACC belongs, and performance-related information data, and outputs the first input information data set to the third device. The transmit / receive unit transmits the first inference request data input from the third device to a pre-trained generative model and receives the first inference result data from the pre-trained generative model.

[0344] The first inference request included in the first inference request data includes generating a first proposal to improve financial and performance indicators contained in the performance-related information data, based on IACC information data and intangible resource information data.

[0345] In the organizational value enhancement support system described above, at least two of the first device, the second device, and the third device may be integrated into a single unit.

[0346] Another embodiment of the organizational value improvement support system of this disclosure comprises a plurality of computer devices constituting a peer-to-peer network. At least one of the plurality of computer devices has a first inference request generation unit that generates first inference request data to be input to a pre-trained generative model based on input data. At least one of the plurality of computer devices has a transmission / reception unit that transmits the first inference request data to the pre-trained generative model and receives first inference result data from the pre-trained generative model. At least one of the plurality of computer devices has an input information generation unit that collects data from a plurality of databases to generate a first input information data set.

[0347] The multiple databases include an IACC information database that stores IACC information data, which includes IACC information; an intangible resources information database that stores data including information on intangible resources owned by the organizations to which the members belong; and a performance-related information database that stores performance-related information data, which includes target values ​​for the organization's financial and performance indicators.

[0348] The first inference request included in the first inference request data includes generating a first proposal to improve financial and performance indicators included in the performance-related information data, based on IACC information data and intangible resource information data, which is part of the data accumulated in the intangible resource information database and includes information on intangible resources belonging to the same type of non-financial capital as the non-financial capital to which IACC belongs.

[0349] Another embodiment of the present disclosure will be described below. Figure 24 is a block diagram illustrating an organizational value improvement support system having an organizational value improvement support device according to one of the other embodiments of the present disclosure.

[0350] The following describes the outline of the organizational value improvement support system according to this embodiment.

[0351] In Japan, financial information (balance sheet: B / S, income statement: P / L, cash flow statement: C / F), which represents the "past" financial results of companies and other organizations, has been criticized for lacking information necessary to calculate the future value of an organization. In other words, for a joint-stock company, it lacks information that investors can use to decide whether to invest further or sell their shares, based on what will happen to that company in the future. Particularly due to strong requests from institutional investors, including activist investors, to the government, it was recognized that the disclosure of information regarding what the future value of a company will be and what kind of capital other than financial capital (the initial investment for the business) exists has been insufficient. Based on this recognition, the Tokyo Stock Exchange has requested the disclosure of information other than financial information (non-financial information) as "soft law." The Corporate Governance Code (CGC) is cited as an example of such soft law, and its second revised version was officially published and implemented on June 11, 2021.

[0352] In response to these demands, listed companies needed both "financial information," which represents the results of past performance, and "non-financial information," which serves as a basis for judging future stock price trends. Therefore, a "combined" document of both types of information was required. This led to the demand for disclosure documents called "integrated reports."

[0353] The disclosure requirements for capital (initial capital) included in non-financial information were finalized when the IIRC defined five types of non-financial capital (Non-Patent Literature 2). Furthermore, the "legal nature" of these five types of non-financial capital can become industrial property rights such as patents or trade secrets through the rights acquisition process. However, in the case of self-development, under current accounting standards, the "objective acquisition consideration" is unclear, unlike in sales or licensing acquisitions. Therefore, there is a risk of falsification if it is left to the company's "estimate," and for this reason, Japanese accounting standards do not allow asset recognition. Consequently, it is not included in financial information. On the other hand, under International Financial Reporting Standards (IFRS), asset recognition is permitted based on similar cases.

[0354] In this regard, the organizational value improvement support systems 1000 and 1000A according to the embodiments of the present disclosure described above make the capital included in non-financial information "visible," (I) ensuring the three requirements for trade secrets as assets, and (II) clarifying the ledger function of the five types of non-financial capital, thereby solving the above problem (clarification of the object of capital (initial capital) included in non-financial information).

[0355] In addition to (I) and (II) above, the organizational value enhancement support system 1000B according to this embodiment contributes to solving management and operational challenges in relation to organizational value such as corporate value. Specifically, (III) it solves the problem of the so-called "PBR below 1x problem" that the Tokyo Stock Exchange has adopted at the request of institutional investors, including activists, and is pursuing from listed companies, and as a result contributes to improving corporate value.

[0356] PBR stands for Price-to-Book Ratio, which indicates how many times the price of a stock is compared to the net assets per share. It is one of the criteria used to evaluate a company. In other words, PBR is calculated as stock price ÷ net assets actually owned by the company per share, and the answer is the ratio of the two. When the two amounts are equal, the PBR is 1, so the baseline value is 1. When PBR = 1, market valuation (= stock price × total number of outstanding shares) = net assets. When PBR > 1, market valuation is higher than net assets → non-financial capital is high. When PBR < 1, market valuation is lower than net assets → non-financial capital is low.

[0357] The "PBR below 1 problem" refers to a situation where a listed company's market valuation (stock price x total number of outstanding shares) falls below its net asset value. In this situation, activist investors would prefer that the company immediately cease operations, sell all its assets, and distribute the entire amount as dividends, rather than continuing its business activities. In other words, a PBR below 1 indicates that the company is unable to achieve "sustainable growth," and this is the point that the "PBR below 1 problem" focuses on.

[0358] From the perspective of solving this problem alone, reducing the denominator in the PBR calculation (specifically, by lowering equity through share buybacks or increased dividends, the net asset value in the denominator can be reduced) would also be a solution to the problem of PBRs below 1. However, the Tokyo Stock Exchange states that such measures do not fundamentally solve the problem of PBRs below 1, and recommends promoting measures that contribute to the sustainable growth of companies.

[0359] For listed companies, while stock prices fluctuate constantly, both the stock price and the total number of outstanding shares are publicly available. Furthermore, the net asset value of listed companies is disclosed through their balance sheet (B / S), a key piece of financial information. In other words, since all the information necessary to calculate the PBR—stock price, number of shares, and net asset value—is publicly available, it's possible to obtain the PBR of listed companies in real time by searching online for "[company name] PBR".

[0360] In this way, by appropriately incorporating publicly available information from the internet and other sources, it is possible to determine the ever-changing "corporate value (= stock price × total number of outstanding shares)" and, from that corporate value, calculate the "total amount of the five non-financial capitals (= corporate value - net assets)." Furthermore, the "balance sheet (B / S)," one of the traditional financial information documents, is readily available.

[0361] Therefore, in the corporate value financial statements according to this embodiment, five non-financial capital items other than financial capital, which are non-financial information, are placed under "financial capital," which is the capital section shown on the right side of a conventional balance sheet. In addition, intellectual assets, which are non-financial information and include self-developed patents and trade secrets that have been "visualized" as shown in other embodiments of this disclosure (hereinafter referred to as "self-developed intellectual assets"). The total amount of these self-developed intellectual assets balances out to the same amount as the amounts allocated to the five non-financial capital items placed on the capital side (corporate value - net asset value).

[0362] As shown in the embodiments described above in this disclosure, it is clarified which category of non-financial capital each of the "visualized" self-developed intellectual assets belongs to. Furthermore, in this embodiment, self-developed intellectual assets are positioned as intangible resource information, and as will be described later, the relative valuation (monetary equivalent) of each intangible resource information within the organization (company) is clarified.Therefore, in the corporate value financial statements according to this embodiment, the internal valuation (monetary equivalent) of each non-financial capital can be calculated by multiplying the sum of the relative values ​​of the intangible resource information (self-developed intellectual assets) belonging to each non-financial capital by the total internal valuation (monetary equivalent) of the non-financial capital allocated as corporate value minus net assets.

[0363] Thus, the organizational value enhancement support system according to this embodiment makes it possible to disclose organizational value financial statements (which become "corporate value balance sheets" if the organization is a company) that clearly show self-developed intellectual assets and non-financial capital included in non-financial information, in addition to the conventional balance sheet (B / S). Furthermore, in the case of listed companies, the total amount of non-financial capital (total internal valuation) changes from time to time due to fluctuations in stock prices. In the specific example of this embodiment, warnings can be issued to the company as needed, and it is possible to guide them to increase or reduce negative non-financial capital (i.e., the capital for future business). This can encourage solutions to the "PBR below 1 problem" and contribute to the sustainable growth of companies.

[0364] The organizational value improvement support system 1000B according to this embodiment includes at least one processor and memory. Non-temporary instructions are stored in the memory, and when these instructions are executed by the processor, the organizational value improvement support system 1000B is configured such that the processor controls the intangible resource information utilization management unit 500 by executing the instructions.

[0365] Here, intangible resource information data is a data structure that provides intangible resource information in a form that can be mechanically stored, transmitted, and processed. Intangible resource information is an intangible object that represents the intangible resources held by an organization, and includes information describing the content of the intangible resource, as well as attribute information indicating which of the five non-financial capitals included in non-financial information it belongs to.

[0366] Intangible resource information data is stored in the intangible resource information database 310, as in other embodiments.

[0367] The Intangible Resource Information Utilization Management Unit 500 acquires intangible resource information data to be managed from the Intangible Resource Information Database 310. Here, the Intangible Resource Information Database 310 may be a different database from the IACC Information Database 300 (see Figure 1, etc.), or it may share parts with it.

[0368] In this embodiment, the intangible resource information utilization management unit 500 includes, in one specific example, a history management unit 510, a value calculation unit 520, a classification setting unit 530, a category value calculation unit 540, an organizational value financial statement preparation unit 550, a utilization proposal unit 580, a contribution candidate selection unit 590, a PBR information provision and preparation unit 560, and an improvement proposal inference request unit 570.

[0369] The history management unit 510 performs processing that includes generating usage history data, which includes the usage history of intangible resource information. The history management unit 510 includes a history recording unit 511 that performs processing that includes recording the used intangible resource information as contributed intangible resource information, and a contribution amount calculation unit 512 that performs processing that includes calculating the contribution amount of the contributed intangible resource information using the organization's activity record data.

[0370] Specifically, the history recording unit 511 records that the intangible resource information was used in the tag data portion of the intangible resource information data, including the intangible resource information that was used. If, in addition to the fact that it was used, information such as the department or person who decided to use it, the purpose of use (for example, the project on which it will be used), the date of the decision to use it, and the period of use is also recorded, it may be easier for the contribution amount calculation unit 512 to calculate the contribution amount.

[0371] The contribution amount calculation unit 512 may calculate the contribution amount based on the intangible resource information-derived performance that has occurred and / or is expected to occur as a result of the contribution intangible resource information, and the contribution rate of the contribution intangible resource information in the intangible resource information-derived performance.

[0372] Identifying achievements derived from intangible resource information can be done, for example, as follows: First, the tag data portion of the intangible resource information data, including the contribution intangible resource information recorded by the history recording unit 511, is referenced to identify the purpose of use of the contribution intangible resource information (for example, a specific task or project). By reading the achievement information corresponding to that purpose of use from, for example, the achievement-related data stored in the achievement-related information database 320, achievements derived from intangible resource information can be identified.

[0373] The contribution rate of contributing intangible resource information in performance derived from intangible resource information can be identified, for example, as follows: First, access the intangible resource information database 310 to identify other contributing intangible resource information (hereinafter referred to as "second contributing intangible resource information") that is used for the same purpose as the contributing intangible resource information (hereinafter referred to as "first contributing intangible resource information") for which the contribution rate is to be calculated. This step can also be performed by referring to the tag data portion of the intangible resource information data stored in the intangible resource information database 310.

[0374] Once the first and second contributing intangible resource information are identified, the degree of contribution of these contributing intangible resource information to the intended use is evaluated, and the relative contribution rate (normalized apportionment coefficient) of the first contributing intangible resource information is set. If there is no second contributing intangible resource information and only one contributing intangible resource information contributes to the target intended use, this relative contribution rate will be 1.

[0375] Furthermore, the extent to which the combined first and second contribution intangible resource information contributes to the performance for the purpose of use is determined. Here, the so-called three-part or four-part classification may be used. The three-part classification is a model that classifies all resources held by an organization, including tangible and intangible things, into three types: (A) physical resources consisting of tangible things such as manufacturing equipment, (B) human resources including tacit knowledge and labor that are not formalized and are integrated with the members of the organization, and (C) intangible things consisting of formalized information that has monetary value, specifically intangible resources related to intangible resource information contained in the intangible resource information data accumulated in the intangible resource information database 310, and assumes that each of these contributes 1 / 3 to business profits. The four-part classification model assumes the existence of intangible resources that are not managed by the intangible resource information database 310, such as business strategies, business structures, and distribution channels, and treats their contributions on par with the other three types of resources. In this model, the contribution ratio of intangible resource information accumulated in the intangible resource information database 310 is 1 / 4. The degree of contribution may be set individually depending on the purpose of use. For example, if the purpose of use is licensing, the contribution ratio of intangible resource information should be higher than 1 / 3 or 1 / 4, and may be set to, for example, 2 / 3.

[0376] The product of the relative contribution rate thus established and the degree of contribution becomes the contribution rate of the first contributing intangible resource information. The contribution amount of the first contributing intangible resource information is calculated from the product of this contribution rate and the performance derived from the intangible resource information.

[0377] As explained above, calculating the contribution amount requires identifying not only the first contributing intangible resource information but also other contributing intangible resource information (second contributing intangible resource information) that contribute to the purpose of use, and it is also necessary to set the overall contribution level of the intangible resource information to the purpose of use. In order to perform these processes, it is necessary to grasp a lot of information related to the purpose of use, in particular the contents of many documents with different formats. From the viewpoint of performing such processes efficiently, as will be explained below, the contribution amount calculation unit 512 has a contribution inference request unit 513 that, as one specific example, performs a process that includes generating inference request data to a pre-trained generative model.

[0378] The contribution inference request unit 513 takes contribution intangible resource information (first contribution intangible resource information) and organizational activity record data as input and creates calculation inference request data that includes an inference request to the calculation generative model 940, which is a pre-trained generative model used for this purpose. It then performs processing that includes sending the inference request data to the calculation generative model 940 and receiving contribution inference result data, including a proposal for the contribution amount, from the calculation generative model 940. The inference request included in the calculation inference request data includes a request for a proposal for the contribution amount.

[0379] In the example shown in Figure 24, the organization's activity record data, including the performance of the purpose of use of the first contributing intangible resource information, is stored in the performance-related information database 320. In one example, the calculation generation model 940, at the instruction of the contribution inference request unit 513, refers to the performance-related information database 320 and the intangible resource information database 310, which stores intangible resource information data, during inference. The performance-related information database 320 also stores data that includes information related to the organization's performance. In one specific example, the inference request data includes requesting a proposal for the calculation result of performance derived from intangible resource information, a proposal for the identification result of the second contributing intangible resource information and the calculation result of the relative contribution rate, a proposal for the degree of contribution, and a proposal for the calculation result of the contribution amount of the first contributing intangible resource information. If the relative contribution rate of the first contributing intangible resource information is prerequisite information in the inference request, the calculation generation model 940 may be able to generate the inference result without accessing the intangible resource information database 310.

[0380] The calculation generation model 940 may continuously or intermittently access the performance-related information database 320 and / or the intangible resource information database 310, and the calculation generation model 940 may be retrained at appropriate times. In this case, it becomes easier to quickly output appropriate inference results in response to inference requests from the contribution inference request unit 513.

[0381] The valuation unit 520 performs processing that includes calculating the intangible resource value, which is the internal valuation amount (monetary conversion index) of the intangible resource information, based on the usage history data generated by the history management unit 510. In one specific example, the valuation unit 520 calculates the intangible resource value by allocating the apportionment amount set based on the difference between the organization's market capitalization and identifiable net assets (hereinafter, this amount is also referred to as the "first difference") to each intangible resource information. More specifically, the valuation unit 520 obtains the contribution amount of the intangible resource information (calculated by the contribution amount calculation unit 512 as described above) from the usage history data of the intangible resource information, and sets a contribution rate (normalized apportionment coefficient) for all intangible resource information based on this contribution amount. Identifiable net assets can basically be any assets associated with tangible things, and assets associated with intangible things can be valued as part of the first difference in relation to the intangible resource information. If assets associated with intangible assets are included as part of identifiable net assets, the link between those intangible assets and the intangible resource information should be removed to prevent double counting of intangible resources.

[0382] The amount subject to apportionment may be the entirety of the first difference, or it may be a portion of the first difference. In the latter case, a specific example of a non-financial asset that does not constitute the amount subject to apportionment is the unrealized gains on held assets (especially real estate). In the first difference, the present value of growth opportunities (PVGO), such as the contribution of ongoing projects, can be appropriately evaluated by the valuation unit 520, which considers the business plan, discounts the results to their present value, and apportions them to the corresponding intangible resource information.

[0383] If the organization is a corporation, the total value of shares may be used as the market capitalization, and the total value of financial assets listed in the most recently published balance sheet may be used as the identifiable net assets. In this case, since the total value of shares fluctuates in real time, the market capitalization also fluctuates in real time, but the valuation of identifiable net assets remains constant over a specified period, such as a quarter. An example of the market capitalization of an organization that is not a corporation is the acquisition price if the organization were to be acquired.

[0384] As explained above, the value calculation unit 520 sets a contribution rate (normalized allocation coefficient) for all intangible resource information. Based on this contribution rate (normalized allocation coefficient), the evaluation and management of intangible resource information may be performed. For example, the contribution rate (normalized allocation coefficient) may be used as the basis for calculating compensation for creators of intangible resource information. Alternatively, it may be used as an evaluation criterion when inventorying intangible resource information. To give a specific example, intangible resource information for which the contribution rate (normalized allocation coefficient) remains low for a certain period of time may be subject to licensing out or excluded from management in the intangible resource information database 310.

[0385] The classification setting unit 530 performs processing that includes classifying intangible resource information into multiple categories. The method of classifying intangible resource information in the classification setting unit 530 is not particularly limited, and categorization can be performed using various classifications, and it is also possible to categorize from multiple perspectives. By categorizing from multiple perspectives, it is possible to evaluate the intangible resource information stored in the intangible resource information database 310 from multiple angles.

[0386] One specific example of categorization is to classify the data based on the degree of confidentiality of the intangible resource information data and the five types of non-financial capital to which the intangible resource information belongs. Although the object to be kept confidential is intangible resource information, the specific management, such as password setting and access control, applies to the intangible resource information data, including the intangible resource information itself. The classification setting unit 530 may classify the intangible resource information data into a category of information that can be disclosed and a category of information that cannot be disclosed, based on the degree of confidentiality.

[0387] The category valuation unit 540 calculates the category value, which is the total internal valuation (monetary conversion index), for each category set by the classification setting unit 530, based on the intangible resource value (value of intangible resource information) calculated by the valuation unit 520. As described above, when categorizing from two perspectives (degree of confidentiality and five types of non-financial capital), for example, the category value of the Disclosable Information category is the sum of the intangible resource values ​​belonging to this category, and for example, the category value of the Human Capital category is the sum of the intangible resource values ​​belonging to this category. Furthermore, when categorizing by the type of organizational activity, the category value of individual activities can be determined. Specifically, if the organization is a company, the category value of a business unit can be determined by summing the values ​​of the intangible resource information belonging to a given business unit.

[0388] The Organization Value Financial Statement Preparation Unit 550 performs processing that includes generating OV-B / S data for creating an Organization Value Balance Sheet, which is defined in a conventional balance sheet by displaying a Sustainable Assets section following an Assets section (hereinafter referred to as "Financial Assets" to indicate that it is shown in conventional financial statements) and a Non-Financial Capital section following an Equity section (hereinafter referred to as "Financial Capital" to indicate that it is shown in conventional financial statements).

[0389] In a typical balance sheet, although it varies depending on the accounting standards, assets are listed on the left side, and capital (including liabilities) that balances those assets is listed on the right side. In an organizational value balance sheet, a section for sustainable assets is added after the asset (financial asset) section of a typical balance sheet, and the category value of the disclosable information category and the category value of the non-disclosable information category are shown in the sustainable assets section. As mentioned above, the total value of intangible resource information is the difference (first difference) between the organization's market capitalization and identifiable net assets (total amount of the financial capital section), so the total of the financial assets section and sustainable assets in the organizational value balance sheet is the organization's market capitalization.

[0390] Furthermore, the organizational value balance sheet includes a non-financial capital section following the equity (financial capital) section of a general balance sheet. This section shows the category value for each of the five categories of non-financial capital. The sum of these category values ​​is equal to the sum of the category values ​​of the non-disclosed information category and the category value of the disclosed information category that constitutes sustainable assets. In other words, sustainable assets and non-financial capital are balanced in the organizational value balance sheet.

[0391] Figure 25 illustrates the above organizational value balance sheet. In Figure 25, unrealized gains on real estate and other assets are listed under financial assets at their revaluation amount, and the revaluation difference is shown in the financial capital section. In other words, in Figure 25, only intangible resources are shown within the scope of non-financial information.

[0392] In this case, if the organization is a stock company, the market capitalization of the organization is the market capitalization of the company, which is equivalent to the total value of shares (= share price × total number of shares issued). As mentioned above, in recent years, it has become common to value a stock company using the PBR (price-to-book ratio), and stock companies are required to disclose to investors, etc., measures to increase the potential (future) value of the company in order to maintain a PBR of more than 1.

[0393] In this regard, the above-mentioned organizational value financial statements (hereinafter, if the organization is a stock company, also referred to as "corporate value financial statements" as mentioned above) apply intangible resource information contained in the intangible resource information data stored in the intangible resource information database 310 as the object of the first difference, which is positioned as the potential value of the company that is not expressed in the financial statements. Furthermore, it makes it possible to relatively evaluate the value of individual intangible resource information (intangible resource value) and the value of a category consisting of multiple intangible resource information (category value). In other words, the amount obtained by subtracting the total amount of financial assets from the total amount of shares becomes the total amount of sustainable assets, and this is the total internal evaluation of the intangible resource information contained in the intangible resource information data stored in the intangible resource information database 310. Non-financial capital listed under the financial capital section in the corporate value financial statements is equal to the amount of sustainable assets. In other words, intangible resource information corresponds to money in a general balance sheet, and when evaluated as capital it becomes non-financial capital, and when evaluated as an asset it becomes a sustainable asset. This ensures that non-financial capital and sustainable assets are balanced in the company's financial statements.

[0394] From the perspective of notifying when to evaluate the value of such intangible resource information, the Intangible Resource Information Utilization Management Unit 500 includes a PBR Information Provision Creation Unit 560 that, when the organization is a stock company, performs processing including creating PBR information provision data to notify when the organization's price-to-book ratio (PBR) is less than 1. The specific configuration of the notification shown by the PBR information provision data is not limited. For example, if the PBR is 1 or greater, the PBR may be displayed in black text, and when the PBR falls below 1, the color of the text indicating the PBR may be changed to red. Alternatively, when the PBR falls below 1, a notification (such as an email) may be sent to the department that should take countermeasures.

[0395] By collecting stock prices for calculating the PBR in real time, an alert can be issued promptly when the PBR falls below 1. By using the average stock price over a certain period as the basis for calculating the PBR, the impact of instantaneous fluctuations can be mitigated. The PBR information provision and creation unit 560 may also generate PBR information provision data that notifies of the PBR trend, even when the PBR is not less than 1. For example, when the PBR is 1 or greater but a downward trend occurs and the PBR approaches 1, or when a downward trend in the PBR becomes apparent (including detection of an inflection point), PBR information provision data indicating that fact may be created.

[0396] When considering improvements to PBR, information on non-financial information is necessary, so organizational value financial statements, which allow for the relative evaluation of the value of non-financial information by category, are extremely useful. From the perspective of supporting such considerations based on organizational value financial statements, the intangible resource information utilization management unit 500 is equipped with an improvement proposal inference request unit 570.

[0397] The improvement proposal inference request unit 570 takes the OV-B / S data prepared by the organizational value financial statement preparation unit 550 as input and generates improvement inference request data that includes inference requests to the improvement generative model 950, which is a pre-trained generative model used for this purpose. The inference requests included in the improvement inference request data include soliciting proposals to increase sustainable assets and / or five non-financial capitals. If the organization is a corporation, the inference request may also include soliciting proposals to increase the organization's PBR (price-to-book ratio), and such proposals may include identifying intangible resources that have a significant impact on PBR.

[0398] The improvement suggestion inference request unit 570 transmits the created improvement inference request data to the improvement generation model 950 and performs processing that includes receiving improvement inference result data, including a predetermined suggestion, from the improvement generation model 950. As described above, when identifying intangible resources that have a significant impact on PBR, the improvement suggestion inference request unit 570 may refer to the intangible resource information database 310 to read intangible resource information data corresponding to the identified intangible resource, identify the type of non-financial capital to which the identified intangible resource belongs, and output improvement suggestion display data for display on an output device such as the improvement suggestion input / output device 430, along with the improvement inference result data, indicating the type of non-financial capital that was identified.

[0399] If the intangible resource information data also contains information regarding the activity status and planned activities of the intangible asset (for example, information such as which department (more specifically, which member) in the organization is using it, for what purpose, and for how long, or plans to use it; the same applies hereinafter), the improvement suggestion inference request unit 570 may output improvement suggestion display data for displaying that information on the improvement suggestion input / output device 430 or the like.

[0400] If the improvement suggestion inference request unit 570 receives data from the improvement suggestion input / output device 430 that includes information identifying a predetermined intangible resource, it may generate improvement inference request data such that the improvement inference result data from the improvement generation model 950 includes suggestions to increase sustainable assets and / or non-financial capital, focusing on the utilization of that intangible resource.

[0401] The timing at which the improvement suggestion inference request unit 570 starts execution is arbitrary, but it may start execution in relation to other elements constituting the organizational value improvement support system 1000B according to this embodiment. For example, the improvement suggestion inference request unit 570 may start execution when the PBR information provision creation unit 560 creates PBR information provision data.

[0402] In the example shown in Figure 24, the performance-related information database 320 stores information on the organization's performance and value (including financial information), as well as information on its shares. In one example, the improvement generation model 950, upon instruction from the improvement suggestion inference request unit 570, refers to the performance-related information database 320 and the intangible resource information database 310, which stores intangible resource information data, during inference. The improvement generation model 950 may refer to only one of the performance-related information database 320 or the intangible resource information database 310.

[0403] The improvement generation model 950 may continuously or intermittently access the performance-related information database 320 and / or the intangible resource information database 310, and the improvement generation model 950 may be retrained at appropriate times. In this case, it becomes easier to quickly output appropriate inference results in response to inference requests from the improvement suggestion inference request unit 570.

[0404] The utilization suggestion unit 580 performs processing that includes suggesting the use of intangible resource information to the operator of the utilization input / output device 440 (specifically, a member of the organization). If the organization's activities continue for a predetermined period, a large amount of intangible resource information will be accumulated in the intangible resource information database 310. In this case, it is not easy for the organization's members to determine which intangible resource information is expected to contribute to improving the organization's value.

[0405] Therefore, in one specific example, the utilization proposal unit 580 causes the proposal generation model 960, which is a pre-trained generation model, to propose intangible resource information (hereinafter, this intangible resource information is referred to as "contributing candidate intangible resource information") that is expected to contribute to improving the value of the organization when used by the organization's members. The contributing candidate intangible resource information has a type of non-financial capital to which the intangible resource belongs, and may also have information regarding the activity status and planned activities of the intangible asset (for example, information such as which department (more specifically, which member) in the organization is using it, for what purpose, and for how long, or plans to use it).

[0406] In other words, in one specific example, the utilization proposal unit 580 includes a contribution candidate inference request unit 581. The contribution candidate inference request unit 581 takes data including information on the organization's planned activities (activity plan data) as input and generates proposal inference request data. Here, the proposal inference request data includes an inference request that asks the proposal generation model 960 to propose contribution candidate intangible resource information, which is intangible resource information that is expected to contribute to improving the organization's value. Information on the organization's planned activities includes information including the future planned activities of the organization's members, such as business plans, sales plans, and development plans. The contribution candidate inference request unit 581 transmits the generated proposal inference request data to the proposal generation model 960 and performs processing that includes receiving proposal inference result data including contribution candidate intangible resource information generated by the proposal generation model 960 from the proposal generation model 960.

[0407] As described above, the improvement suggestion inference request unit 570 receives a predetermined intangible resource via the improvement suggestion input / output device 430 and outputs data to the improvement suggestion input / output device 430 for displaying an organization's improvement suggestion (action plan) that focuses on that intangible resource. In contrast, the utilization suggestion unit 580 receives activity plan data including an action plan via the utilization input / output device 440 and outputs data to the utilization input / output device 440 via the contribution candidate selection unit 590 for displaying intangible resources that can contribute to that activity plan data.

[0408] In the example shown in Figure 24, the activity schedule data is stored in the performance-related information database 320 along with information related to the organization's performance. In one example, the proposal generation model 960, upon instruction from the contribution candidate inference request unit 581, refers to the performance-related information database 320 and the intangible resource information database 310, which stores intangible resource information data, during inference. The proposal generation model 960 may refer to only one of the performance-related information database 320 or the intangible resource information database 310.

[0409] The proposal generation model 960 may continuously or intermittently access the performance-related information database 320 and / or the intangible resource information database 310, and the proposal generation model 960 may be retrained at appropriate times. In this case, it becomes easier to quickly output appropriate inference results in response to inference requests from the contribution candidate inference request unit 581.

[0410] Thus, when generating a proposal model 960 to propose candidate intangible resource information, it is necessary from the standpoint of proper management of confidential information to restrict the intangible resource information that forms the population to a range accessible to the operator of the input / output device 440. Therefore, in this embodiment, as a specific example, the intangible resource information utilization management unit 500 generates internal management instruction data indicating the degree of confidentiality management of the intangible resource information data, and manages the intangible resource information data stored in the intangible resource information database 310 confidentially based on the internal management instruction data. This internal management instruction data may be generated directly by the intangible resource information utilization management unit 500, or it may be generated by acquiring information generated by the intangible resource information management unit 251 shown in Figure 16.

[0411] The utilization proposal unit 580 may also include a proposal restriction setting unit 582 that uses internal management instruction data. The proposal restriction setting unit 582 identifies organizational members involved in the above-mentioned activity plan (such as a business plan) and determines the range of intangible resource information data that the identified organizational members can access, based on the internal management instruction data. Then, using the intangible resource information included within this range as a population, the utilization proposal unit 580 performs processing that enables it to select candidate intangible resource information for contribution.

[0412] In Figure 24, the proposal restriction setting unit 582 generates data representing the population and outputs this data to the contribution candidate inference request unit 581. Upon receiving this data, the contribution candidate inference request unit 581 includes an instruction to specify the population in the inference request. As a result, even if the proposal generation model 960 has access to all the intangible resource information stored in the intangible resource information database 310, it can select appropriate intangible resource information from the range of the population specified in the inference request and propose it as contribution candidate intangible resource information.

[0413] Thus, the proposed intangible resource information for contributions proposed by the proposal generation model 960 may include multiple intangible resource information, depending on the settings of the inference requests included in the proposal inference request data generated by the candidate contribution inference request unit 581. In this case, the intangible resource information utilization management unit 500 may include a candidate contribution selection unit 590 that performs processing including assisting the operator of the utilization input / output device 440 in deciding which intangible resource information to actually use, and managing the intangible resource information that has been decided to be used.

[0414] The contribution candidate selection unit 590 generates usage display data for displaying the contribution candidate intangible resource information on the usage input / output device 440 and transmits it to the usage input / output device 440. Next, it receives the intangible resource information selected by the operator of the usage input / output device 440 as input from the usage input / output device 440, generates history management data indicating that this selected intangible resource information will be subject to history management, and outputs the generated history management data to the history management unit 510. The history management unit 510 takes the history management data as input and performs processing that includes generating usage history data, which includes the usage history of the intangible resource information.

[0415] The following describes the value allocation with respect to the citation notification counting unit 270. As mentioned above, the citation notification counting unit 270 records how many citation notification data were generated for each IACC information data. This recorded information can be used to evaluate the individual value of IACC.

[0416] The value allocation calculation unit 271 shown in Figure 21 is provided for this purpose, and sets the value points of the IACC included in the IACC information data from the citation notification data recorded by the citation notification count unit 270. The value points are set by setting the value points to "1" when there are no citations and to "n+1" when there are n citations. By using the IACC value points set in this way and apportioning the total internal valuation amount (monetary conversion index) of the IACC, the value allocation of each IACC can be calculated.

[0417] In a specific example, the value allocation calculation unit 271 calculates the sum of the value points of all IACC information (total value points). Here, when calculating the total value points, IACCs that are positioned as potential subjects of industrial property rights and are in the process of being prepared for application may be excluded from the calculation because they are subject to a high level of confidentiality. IACCs that have been excluded from the calculation in this way may be included in the calculation once the application procedure is completed.

[0418] Then, the value points of the IACC subject to value allocation calculation are divided by the sum of these value points to obtain the allocation ratio, and this allocation ratio is multiplied by the internal valuation amount (monetary equivalent) of the IACC subject to value allocation calculation to calculate the value allocation of the IACC subject to value allocation. As the total internal valuation amount (monetary equivalent) of the IACC, the total internal valuation amount (monetary equivalent) of non-financial capital obtained by subtracting the total amount of financial assets from the market capitalization (total amount of shares in the case of a corporation) may be used.

[0419] Here, among the IACC information data, the data stored in the intangible resource information database 310 as intangible resource information data contains information indicating its relationship to the original IACC information data. Therefore, the IACC value allocation contained in the corresponding IACC information data can be used as the individual value of the intangible resource contained in the intangible resource information data stored in the intangible resource information database 310.

[0420] Figure 26 shows a specific example in which the display of intangible resource information data includes the corresponding IACC value allocation as a display element. In Figure 26, to the right of the display column for the name of the "practitioner" (Makio Inoue), "3" is shown as the IACC value point corresponding to the intangible resource information being displayed. This means that this IACC has been cited 2 times to generate other IACCs. Below that display, "42.957 billion yen" is shown as the "management capital allocation value," indicating the value allocation.

[0421] The value allocation calculation unit 271 may calculate the average value allocation by dividing the total internal valuation of non-financial capital (monetary conversion index) by the sum of value points. The average value allocation can be used as a baseline value for the value of each non-financial capital. To explain specifically using the example in Figure 26, the intangible resource information data displayed in Figure 26 has a value of 3, so the average value allocation corresponds to the case where the value is 1, which is 14.319 billion yen. This average value allocation may be displayed in the organizational value financial statements (corporate value financial statements). Figure 27 shows a specific example of corporate value financial statements in which this average value allocation is displayed as "Value Allocation".

[0422] The value allocation calculation unit 271 may be configured to perform the following processes (i) to (iii): (i) Identify an operator requesting access to IACC information data stored in the IACC information database 300, which includes information on IACCs that are intangible assets created by members of the organization; (ii) For other IACCs that were not created by the operator but are permitted to be viewed by the operator, determine the number of times the other IACCs are cited in response to input data indicating that the operator will cite the other IACCs in order to create new IACCs; (iii) Determine the value points of the other IACCs by adding 1 to the number of citations, and calculate the value allocation of the other IACCs by apportioning the total internal valuation of the IACCs according to the ratio of the value points to the total value points of the IACCs stored in the IACC information database 300.

[0423] The value allocation calculation unit 271 may be configured to further perform at least one of the following processes: (iv) creating display data for displaying other IACCs and the value allocation of other IACCs and outputting it to a display device. A specific example of the display of this display data is shown in Figure 26. (v) calculating the average value allocation by dividing the total internal valuation of non-financial capital by the total value points, which is the sum of the value points of all IACC information data that may be subject to calculation. (vi) creating display data for displaying the average value allocation and the total internal valuation of non-financial capital and outputting it to a display device. A specific example of the display of this display data is shown in Figure 27.

[0424] The embodiments described above are provided to facilitate understanding of this disclosure and are not intended to limit it. Accordingly, each element disclosed in the embodiments is intended to include all design changes and equivalents that fall within the technical scope of this disclosure. Figures 28 to 38 are illustrative diagrams (1 to 11) of another embodiment of the organizational value enhancement support program according to one embodiment of this disclosure.

[0425] This disclosure includes the following embodiments. In the following embodiments, "management resources" is used as a term meaning "intangible resources." (1) A corporate value improvement support device comprising: a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input; and a first transmission / reception unit that transmits the first inference request data to a first large-scale language model that has been trained on machine learning and receives first inference result data from the first large-scale language model, wherein the first input information data group comprises: data stored in a personal skill information database, including personal skill information data including information describing an employee's personal skills in a predetermined first format; management resource information data including information on management resources belonging to the same type of management capital as the management capital to which the personal skills belong among the management resources owned by the company to which the employee belongs; and performance-related information data including target values ​​of the company's financial and performance indicators, wherein the first request included in the first inference request data generates a first proposal to improve the financial and performance indicators included in the performance-related information data based on the personal skill information data and the management resource information data.

[0426] (2) The corporate value enhancement support device described in (1) above, wherein the personal skill information data includes information indicating which of the five management capitals included in non-financial information the personal skill belongs to.

[0427] (3) The corporate value enhancement support device according to (1) or (2) above, wherein the first input information data group has personal emotion information data including information indicating a first emotion which is an emotion that the employee expects when performing their duties, and the first request generates a proposal for behavioral indicators that are in line with the first emotion and contribute to improving the financial and performance indicators.

[0428] (4) The corporate value enhancement support device according to (1) or (2) above, wherein the first input information data group further comprises current events data including current events information of the company, and the first request refers to the current events information when generating the first proposal.

[0429] (5) The corporate value enhancement support device according to (1) or (2) above, further comprising a comparison display generation unit that takes the first inference result data and the personal skill information data as input, performs a process that includes generating comparison display data which displays the information contained in the first inference result data in a first format and makes it possible to compare it with the information contained in the personal skill information data, and outputs the comparison display data.

[0430] (6) The corporate value enhancement support device according to (1) or (2) above, comprising a first personal skill information registration unit that generates draft personal skill information data in which the information contained in the first inference result data is described in the first format, and, on the condition that an acceptance instruction for the draft personal skill information data is entered, performs a process that includes replacing the draft personal skill information data with the personal skill information data and saving it in the personal skill information database.

[0431] (7) The corporate value enhancement support device according to (6) above, wherein the first personal skill information registration unit, when a correction instruction is input for the first inference result data, reflects the correction instruction in the information contained in the first inference result data, generates personal skill information data being corrected as described in the first format as a result of the reflection, and, subject to the condition that an acceptance instruction is input for the personal skill information data being corrected, replaces the personal skill information data being corrected with the personal skill information data and saves it as the draft personal skill information data.

[0432] (8) The corporate value enhancement support device according to (2) above, further comprising: a second inference request generation unit that generates second inference request data as input to personal skill basic information data which is basic information of personal skill data and includes information on personal skills; and a second transmission / reception unit that transmits the second inference request data to a second large-scale language model that has been trained and receives second inference result data from the second large-scale language model, wherein the second request included in the second inference request data generates a proposal as a result of analyzing the personal skill basic information data on which of the five management capitals the personal skills should belong.

[0433] (9) The corporate value enhancement support device according to (8) above, comprising a capital representation generation unit that takes the second inference result data as input, identifies the proposed type of management capital from the second inference result data, and generates capital representation data for displaying the identified type of management capital.

[0434] (10) The corporate value enhancement support device according to (9) above, comprising a second personal skill information registration unit that performs a process including identifying the proposed type of management capital from the second inference result data, generating personal skill information data based on the identified type of management capital and the personal skill basic information data, and storing the generated personal skill information data in the personal skill information database.

[0435] (11) The corporate value enhancement support device according to (1) or (2) above, wherein the management resource information data includes data indicating the type of management capital to which the management resource should belong, and further comprises a third inference request generation unit that generates third inference request data using basic management resource information data, which is basic information of the management resource information data and includes information on the management resource, as input, and a third transmission / reception unit that transmits the third inference request data to a machine-learned third large-scale language model and receives third inference result data from the third large-scale language model, wherein the third request included in the third inference request data generates a proposal for the type of management capital to which the management resource should belong as a result of analyzing the basic management resource information data.

[0436] (12) The corporate value enhancement support device according to (11), further comprising a business resource information registration unit that takes the third inference result data and the basic business resource information data as inputs, identifies the proposed type of business capital from the third inference result data, generates the business resource information data based on the identified type of business capital and the basic business resource information data, and performs a process that includes storing the generated business resource information data in a business resource information database.

[0437] (13) The corporate value enhancement support device according to (12) above, wherein the management resource information data includes information on SDGs targets related to the management resources, and the third request comprises generating proposals for SDGs targets related to the management resources as a result of analyzing the management resource basic information data.

[0438] (14) The business resource information registration unit identifies the proposed SDGs target from the third inference result data, and includes information on the identified SDGs target in the business resource information data, as described in (13) above, a business value enhancement support device.

[0439] (15) The corporate value enhancement support device according to (2) above, wherein the first requirement includes, if the personal skills information data includes human capital-related information relating to systems and institutions for developing the knowledge, skills, and abilities of the employees, the first proposal includes improvement suggestions from the perspective of increasing human capital, and if the personal skills information data does not include the human capital-related information, the first proposal includes improvement suggestions from the perspective of increasing at least one of the following: manufacturing capital, social and relational capital, and natural capital.

[0440] (16) The corporate value enhancement support device according to (1) above, wherein the first request generates publicly known proposal information including the results of an examination of whether or not the first proposal is publicly known.

[0441] (17) The corporate value enhancement support device according to (16) above, wherein the first request indicates publicly known information that is determined to include the first proposal if the publicly known proposal information has a proposal that it is publicly known, and indicates publicly known information that is determined to be closest to the first proposal if the publicly known proposal information has a proposal that it is not publicly known.

[0442] (18) The corporate value enhancement support device according to (16), comprising a public information indication generation unit that takes the first inference result data as input, determines from the public information indication information whether the first proposal is public or not, and if it is determined that the first proposal is not public, performs a process that includes generating non-public indication data including a notice indicating that the first proposal may be confidential information. (19) The corporate value enhancement support device according to (6), comprising a confidentiality management setting unit that takes the first request as input, the personal skill information data to be replaced and saved in the personal skill information database generated by the first personal skill information registra...

Claims

1. An organizational value improvement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control, by the execution of the instruction, an input information generation unit that collects data constituting a first input information data group, a first inference request generation unit that automatically generates first inference request data using data of multiple pieces of information included in the first input information data group as input, and a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model, wherein the first input information data group comprises: IACC information data stored in an IACC information database, which includes IACC information, which is intangible assets created by members belonging to the organization; and intangible resource information data stored in an intangible resource information database, which includes intangible resource information belonging to the same type of non-financial capital as the type of non-financial capital to which the IACC belongs, among the intangible resources owned by the organization to which the member belongs. The input information generation unit comprises: data stored in a performance-related information database, including performance-related information data that includes target values ​​for the financial and performance indicators of the organization; the first inference request included in the first inference request data generates a first proposal to improve the financial and performance indicators included in the performance-related information data based on the IACC information data and the intangible resource information data; the input information generation unit comprises: an IACC information reading unit that identifies which of the IACC information data stored in the IACC information database will be read and reads the identified IACC information data from the IACC information database; an intangible resource information reading unit that identifies which of the intangible resource information data stored in the intangible resource information database will be read based on the identified IACC information data and reads the identified intangible resource information data from the intangible resource information database; and a performance-related information reading unit that identifies the financial and performance indicators determined to be targets for improvement and generates performance-related information data that includes target values ​​for the identified financial and performance indicators. A system for supporting the improvement of organizational value, characterized by having the following features.

2. The organizational value improvement support system according to claim 1, wherein the input information generation unit has a data group generation unit that generates the first input information data group including the read IACC information data, the read intangible resource information data, and the read performance-related information data, and the first inference request generation unit has a first information identification unit that takes the first input information data group generated by the data group generation unit as input and identifies the plurality of information included in the first input information data group.

3. The organizational value improvement support system according to claim 1, wherein the first inference request generation unit includes a first prompt generation unit that automatically generates the first inference request data, including the execution of a process that automatically places each of the plurality of pieces of information included in the first input information data group into a predetermined target field to generate management data.

4. The organizational value improvement support system according to claim 1, wherein the IACC information reading unit comprises: an authority confirmation unit that identifies an operator attempting to access the IACC information data and confirms the access authority of the identified operator; an access control unit that enables the operator to access the IACC information data stored in the IACC information database within the scope of the access authority confirmed by the authority confirmation unit; and a reading unit that identifies the IACC information data that the operator has decided to include in the first input information data group from the IACC information data accessible to the operator, and reads the identified IACC information data from the IACC information database.

5. The organizational value improvement support system according to claim 4, wherein the access control unit generates display filter instruction data that allows the IACC information database to display to the operator the self-IACC created by the identified operator and other IACCs not created by the identified operator but which the operator is permitted to view, and transmits the display filter instruction data to the IACC information database.

6. The organizational value improvement support system according to claim 5, wherein the input information generation unit has a citation notification generation unit that generates citation notification data to notify the creator of the other party's IACC of the decision when the operator decides to include the other party's IACC in the first input information data group.

7. The organizational value improvement support system according to claim 6, further comprising a citation notification count unit that records how many of the citation notification data have been generated for each of the IACC information data.

8. The organizational value enhancement support system according to claim 1, wherein the IACC information data includes information indicating the type of non-financial capital to which the IACC belongs.

9. The organizational value improvement support system according to claim 8, wherein the intangible resource information reading unit takes the identified IACC information data as input, identifies the type of non-financial capital to which the IACC belongs, and reads from the performance-related information database the performance-related information data of the same type as the identified type of non-financial capital from the performance-related information database.

10. The organizational value improvement support system according to claim 1, wherein the first input information data group includes personal emotion information data that includes information indicating a first emotion which is an emotion that the member expects when performing their duties, the first inference request generates a proposal for behavioral indicators that are in line with the first emotion and contribute to improving the financial and performance indicators, the input information generation unit includes an emotion information identification unit that identifies the first emotion included in the personal emotion information data, and the first inference request generation unit also takes data including the first emotion identified by the emotion information identification unit as input.

11. The organizational value improvement support system according to claim 10, wherein the emotion information identification unit comprises: an emotion display unit that generates emotion display data that allows for the selection of a predetermined number of emotions; and an emotion determination unit that determines which of the number of emotions displayed in the emotion display unit has been selected as the first emotion.

12. The organizational value improvement support system according to claim 1, wherein the first input information data group is data stored in an auxiliary information database and further includes auxiliary information data including current information of the organization, the first inference request includes referring to the auxiliary information data when generating the first proposal, and the input information generation unit has an auxiliary information reading unit that identifies which of the auxiliary information data stored in the auxiliary information database is to be read, and reads the identified auxiliary information data from the auxiliary information database.

13. The organizational value improvement support system according to claim 12, wherein the auxiliary information reading unit comprises: a reading request generation unit that determines which of the auxiliary information data stored in the auxiliary information database to be read, generates a reading request to the auxiliary information database, and transmits the reading request to the auxiliary information database; and a data reading unit that receives the auxiliary information data prepared in accordance with the reading request from the auxiliary information database.

14. The organizational value improvement support system according to claim 13, wherein the IACC information data includes data indicating the type of non-financial capital to which the IACC belongs, and the read request generation unit determines that the auxiliary information data, which includes auxiliary information of the same type as the type of non-financial capital to which the IACC included in the IACC information data belongs, is the target of the read request.

15. An organizational value improvement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control: a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input; a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model; and a comparative display generation unit, wherein the first input information data group has IACC information data including information in which IACC, which is an intangible asset created by a member of the organization, is described in a predetermined first format; the first inference request included in the first inference request data generates a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group; and the comparative display generation unit takes the first inference result data and the IACC information data as input. An organizational value improvement support system characterized by performing a process that includes displaying the information contained in the first inference result data in a first format, generating comparative display data that can be compared with the information contained in the IACC information data, and outputting the comparative display data.

16. An organizational value improvement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control: a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input; a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model; and a first IACC information registration unit, wherein the first input information data group is data stored in an IACC information database and includes IACC information data in which IACC, which is an intangible asset created by a member of the organization, is described in a predetermined first format; the first inference request included in the first inference request data generates a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group; and the first IACC information registration unit controls: A system for supporting the improvement of organizational value, characterized by generating draft IACC information data in which the information contained in the first inference result data is described in the first format, and, on the condition that an acceptance instruction for the draft IACC information data is entered, performing a process that includes replacing the draft IACC information data with the IACC information data and saving it in the IACC information database.

17. The organizational value improvement support system according to claim 16, wherein the first IACC information registration unit, when a correction instruction is input for the first inference result data, reflects the correction instruction in the information contained in the first inference result data, generates corrected IACC information data in which the reflection result is described in a format corresponding to the display of the IACC information data, and, conditional on an acceptance instruction being input for the corrected IACC information data, replaces the corrected IACC information data with the IACC information data and saves it as draft IACC information data.

18. The organizational value enhancement support system according to claim 16, comprising: a first inference request which generates publicly known proposal information including the results of an examination of whether the first proposal is publicly known; a confidentiality management setting unit which takes as input the IACC information data to be replaced and stored in the IACC information database generated by the first IACC information registration unit and the first inference result data; determines from the publicly known proposal information whether the first proposal is publicly known or not; and if it is determined that the first proposal is not publicly known, performs a process which includes setting the management attribute of the IACC information data to data including a candidate for the object of industrial property rights.

19. The organizational value improvement support system according to claim 18, comprising an information management unit which generates information management instruction data for classifying and managing the IACC information data and transmits it to the IACC information database, wherein the information management instruction data includes a first instruction for classifying and managing the IACC information data based on the management attributes.

20. The organizational value improvement support system according to claim 19, wherein the IACC information data includes data indicating the type of non-financial capital to which the IACC belongs, and the information management instruction data also includes a second instruction for classification and management based on the type of non-financial capital to which the IACC belongs.

21. The organizational value enhancement support system according to claim 20, wherein the first instruction is an instruction to classify the IACC in terms of its level of confidentiality management, and the second instruction is an instruction to classify the IACC in terms of the type of non-financial capital to which it belongs.

22. The organizational value enhancement support system according to claim 21, wherein the first instruction includes classification in terms of whether it belongs to the category of a candidate subject of industrial property rights, a trade secret, or information that does not require confidentiality protection.

23. The organizational value improvement support system according to claim 8, further comprising: an initial inference request generation unit that automatically generates initial inference request data with IACC basic information data as input; an initial transmission / reception unit that transmits the initial inference request data to an initial generation model which is a pre-trained generation model and receives initial inference result data from the initial generation model, wherein the IACC basic information data is basic data of the IACC information data and includes a plurality of partial information that constitutes the information of the IACC; the initial inference request included in the initial inference request data generates a proposal about the type of non-financial capital to which the IACC should belong as a result of analyzing the IACC basic information data; and the initial inference request generation unit includes: an IACC partial information identification unit that accepts the IACC basic information data and identifies the plurality of partial information; and an initial prompt generation unit that automatically generates the initial inference request data, including the execution of a process to automatically place the corresponding plurality of partial information in each of the target fields of an initial format which is a pre-identified format data, where each of the target fields to which each of the plurality of partial information should be placed is a pre-identified format data.

24. The organizational value improvement support system according to claim 23, wherein the initial inference request generation unit further comprises an input display generation unit that performs a process including generating input display data having a plurality of input fields corresponding to the plurality of partial information and outputs the input display data, and the IACC partial information identification unit takes data including the plurality of partial information entered in the plurality of input fields as input, generates a plurality of data corresponding to each of the plurality of partial information, and outputs a set of datasets including the plurality of data to the initial prompt generation unit.

25. The intangible resource information data includes data indicating the type of non-financial capital to which the intangible resource belongs, and further comprises: an intangible resource inference request generation unit that generates intangible resource inference request data as input to intangible resource basic information data which is basic information of the intangible resource information data and includes information on the intangible resource; an intangible resource transmission / reception unit that transmits the intangible resource inference request data to an intangible resource generation model which is a pre-trained generation model and receives intangible resource inference result data from the intangible resource generation model, wherein the intangible resource inference request included in the intangible resource inference request data generates a proposal regarding the type of non-financial capital to which the intangible resource should belong as a result of analyzing the intangible resource basic information data, and an intangible resource information input unit that accepts the intangible resource basic information data and identifies information on the intangible resource included in the intangible resource basic information data, The organizational value improvement support system according to claim 1, comprising: an intangible resource prompt generation unit that automatically generates intangible resource inference request data, including the execution of a process to automatically place the information of the intangible resource into the target field of an intangible resource format, which is a format data in which the target field where the information of the intangible resource should be placed is predetermined; and an intangible resource prompt generation unit that automatically generates the intangible resource inference request data.

26. The organizational value improvement support system according to claim 8, wherein the first inference request includes, if the IACC information data includes human capital-related information relating to systems and institutions for developing the knowledge, skills and abilities of the members, an improvement proposal from the perspective of increasing human capital in the first proposal, and if the IACC information data does not include the human capital-related information, an improvement proposal from the perspective of increasing at least one of manufacturing capital, social and relational capital, and natural capital in the first proposal.

27. The organizational value enhancement support system according to claim 1, wherein the first inference request comprises generating publicity proposal information including the results of an examination of whether or not the first proposal is publicly known.

28. The organizational value enhancement support system according to claim 27, wherein the first inference request includes indicating publicly known information that is determined to contain the first proposal if the publicly known proposal information includes a proposal that it is publicly known, and indicating publicly known information that is determined to be closest to the first proposal if the publicly known proposal information includes a proposal that it is not publicly known.

29. The organizational value enhancement support system according to claim 1, wherein at least a portion of the data stored in the IACC information database is positioned as data stored in the intangible resource information database.

30. The organizational value enhancement support system according to claim 29, wherein the IACC information database and the intangible resource information database are integrated.

31. The organizational value improvement support system according to claim 29, comprising an information management unit which generates information management instruction data for classifying and managing the IACC information database and transmits it to the IACC information database, wherein the information management instruction data includes an applicability instruction indicating whether or not the IACC information data may be stored in the intangible resource information database as intangible resource information data.

32. The organizational value enhancement support system according to claim 31, wherein the information management instruction data includes a confidentiality instruction indicating the degree of confidentiality management of the information contained in the intangible resource information data in the intangible resource information database.

33. The organizational value enhancement support system according to claim 1, comprising an intangible resource information management unit that generates disclosure management instruction data indicating whether or not the intangible resource information data stored in the intangible resource information database can be disclosed to an outside party and the extent of disclosure, and transmits the disclosure management instruction data to the intangible resource information database.

34. An organizational value improvement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to control: a first inference request generation unit that generates first inference request data using data of information included in a first input information data group as input; a first transmission / reception unit that transmits the first inference request data to a first generation model which is a pre-trained generation model and receives first inference result data from the first generation model; and a publicly known indication generation unit, wherein the first input information data group is data stored in an IACC information database and includes IACC information data in which IACC, which is an intangible asset created by a member of the organization, is described in a predetermined first format; the first inference request included in the first inference request data comprises generating a first proposal to improve the financial and performance indicators of the organization to which the member belongs, based on the first input information data group, and generating publicly known proposal information including the results of an examination of whether the first proposal is publicly known; and the publicly known indication generation unit Organizational value enhancement support system characterized by taking the first inference result data as input, determining from the publicly known proposal information whether the first proposal is publicly known or not, and if it is determined that the first proposal is not publicly known, performing a process that includes generating non-public indication data including a notice indicating that the first proposal may be confidential information.

35. An organizational value enhancement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor executes a process that includes saving IACC information data, which includes information describing IACC, an intangible asset created by a member of the organization, in a predetermined first format, to an IACC information database; an initial inference request generation unit that takes IACC basic information data, which is basic information for the IACC information data and includes information about the IACC, as input and generates initial inference request data; an initial transmission / reception unit that transmits the initial inference request data to an initial generation model, which is a pre-trained generation model, and receives initial inference result data from the initial generation model; and an initial publicness display generation unit that takes the initial inference result data as input, wherein the initial inference request included in the initial inference request data generates initial publicness proposal information, which includes the result of examining whether the IACC is publicly known or not; and the initial publicness display generation unit controls An organizational value enhancement support system characterized by performing a process that includes determining whether the IACC is public or private based on the initial public information proposal, and, if it is determined that the IACC is private, generating initial non-public indication data that includes a notice indicating that the IACC may be confidential information.

36. The organizational value enhancement support system according to claim 35, wherein if the initial public knowledge proposal information has a proposal that it is publicly known, it displays publicly known information that is determined to include the IACC, and if the initial public knowledge proposal information has a proposal that it is not publicly known, it displays publicly known information that is determined to be closest to the IACC.

37. An organizational value enhancement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor executes a process that includes saving IACC information data, which includes information describing IACC, an intangible asset created by a member of the organization, in a predetermined first format, to an IACC information database; an initial inference request generation unit that takes IACC basic information data, which is basic information for the IACC information data and includes information about the IACC, as input and generates initial inference request data; an initial transmission / reception unit that transmits the initial inference request data to an initial generation model, which is a pre-trained generation model, and receives initial inference result data from the initial generation model; and an initial confidentiality management setting unit that takes the initial inference result data as input, wherein the initial inference request included in the initial inference request data generates initial publicity proposal information, which includes the result of examining whether the IACC is publicly known or not; and the initial confidentiality management setting unit controls An organizational value enhancement support system characterized by determining whether the IACC is public or private based on the initial public-priority proposal information, and, if it is determined that the IACC is private, performing a process that includes setting the management attribute of the IACC information data to data that includes a candidate for the object of industrial property rights.

38. An organizational value enhancement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor executes a process that includes saving IACC information data, which includes information describing IACC, an intangible asset created by a member of the organization, in a predetermined first format, and information indicating the type of non-financial capital to which the IACC belongs, to an IACC information database; an initial IACC information registration unit, which takes IACC basic information data, which is basic information for the IACC information data and includes information for the IACC, as input, and generates initial inference request data; an initial transmission / reception unit, which transmits the initial inference request data to an initial generation model, which is a pre-trained generation model, and receives initial inference result data from the initial generation model; and a capital representation generation unit, which takes the initial inference result data as input, wherein the initial inference request included in the initial inference request data generates a proposal regarding the type of non-financial capital to which the IACC should belong as a result of analyzing the IACC basic information data. Organizational value enhancement support system characterized in that the capital representation generation unit performs a process including identifying the proposed non-financial capital type from the initial inference result data and generating capital representation data for displaying the identified non-financial capital type, and the initial IACC information registration unit performs a process including identifying the proposed non-financial capital type from the initial inference result data and generating IACC information data based on the identified non-financial capital type and the IACC basic information data.

39. An organizational value improvement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor executes a process that includes storing intangible resource information data, which includes information on intangible resources possessed by the organization and data indicating the type of non-financial capital to which the intangible resources should belong, in an intangible resource information database; an intangible resource inference request generation unit that takes intangible resource basic information data, which is basic information for the intangible resource information data and includes information on the intangible resources, as input and generates intangible resource inference request data; and an intangible resource transmission / reception unit that transmits the intangible resource inference request data to an intangible resource generation model, which is a pre-trained generation model, and receives intangible resource inference result data from the intangible resource generation model, wherein the intangible resource inference request included in the intangible resource inference request data generates a proposal for the type of non-financial capital to which the intangible resources should belong as a result of analyzing the intangible resource basic information data. The organizational value enhancement support system is characterized in that the intangible resource information registration unit takes the intangible resource inference result data and the intangible resource basic information data as input, identifies the proposed type of non-financial capital from the intangible resource inference result data, and performs a process that includes generating the intangible resource information data based on the identified type of non-financial capital and the intangible resource basic information data.

40. The organizational value enhancement support system according to claim 39, wherein the intangible resource information data includes information on SDGs targets related to the intangible resource, and the intangible resource inference request generates a proposal for SDGs targets related to the intangible resource as a result of analyzing the intangible resource basic information data.

41. The organizational value enhancement support system according to claim 40, wherein the intangible resource information registration unit identifies the proposed SDGs target from the intangible resource inference result data, and includes information on the identified SDGs target in the intangible resource information data.

42. An organizational value enhancement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when such instructions are executed by the processor, the processor is configured to control an intangible resource information utilization management unit by the execution of the instructions to manage the use of intangible resource information contained in intangible resource information data within the organization, wherein the intangible resource information is an intangible object representing an intangible resource owned by the organization, and includes information describing the content of the intangible resource and attribute information indicating whether it belongs to non-financial capital, and the intangible resource information data is a data structure in which the intangible resource information can be mechanically stored, transmitted, and processed.

43. The organizational value enhancement support system according to claim 42, wherein the intangible resource information data is stored in an intangible resource information database, and the intangible resource information utilization management unit obtains the intangible resource information data to be managed from the intangible resource information database.

44. The organizational value improvement support system according to claim 42, wherein the intangible resource information utilization management unit comprises a history management unit that performs processing including generating utilization history data including the utilization history of the intangible resource information.

45. The organizational value improvement support system according to claim 44, wherein the history management unit comprises a history recording unit that performs processing including recording the used intangible resource information as contributed intangible resource information, and a contribution amount calculation unit that performs processing including calculating the contribution amount of the contributed intangible resource information using the organization's activity record data.

46. ​​The organizational value improvement support system according to claim 45, wherein the contribution amount calculation unit calculates the contribution amount based on the intangible resource information-derived performance that has occurred and / or is expected to occur as a result of the contribution intangible resource information, and the contribution rate of the contribution intangible resource information in the intangible resource information-derived performance.

47. The organizational value improvement support system according to claim 45, wherein the contribution amount calculation unit further comprises a contribution inference request unit, the contribution inference request unit takes the contribution intangible resource information and the organization's activity record data as input to create calculation inference request data including an inference request to a calculation generation model, transmits the calculation inference request data to the calculation generation model, and performs a process including receiving contribution inference result data including a proposed contribution amount.

48. The organizational value improvement support system according to claim 47, wherein, at the time of inference, the calculation generation model refers to a performance-related information database in which data including information related to the performance of the organization is stored, and / or an intangible resource information database in which the intangible resource information data is stored, as instructed by the contribution inference request unit.

49. The organizational value improvement support system according to claim 44, wherein the intangible resource information utilization management unit further comprises a value calculation unit that performs processing including calculating the intangible resource value, which is an internal valuation amount of the intangible resource information, based on the utilization history data.

50. The organizational value enhancement support system according to claim 49, wherein the valuation unit calculates the intangible resource value by allocating an amount to be allocated based on the difference between the organization's market capitalization and identifiable net assets to each piece of intangible resource information.

51. The organizational value enhancement support system according to claim 50, wherein, if the organization is a stock company, the total value of shares is used as the market capitalization and the most recently published balance sheet is referred to as the identifiable net assets.

52. The organizational value improvement support system according to claim 49, wherein the intangible resource information utilization management unit comprises: a classification setting unit that performs processing including classifying the intangible resource information into a plurality of categories; and a category value calculation unit that performs processing including calculating a category value which is the total internal valuation amount for each of the categories based on the intangible resource value calculated by the value calculation unit.

53. The organizational value improvement support system according to claim 52, wherein the classification setting unit performs classification with respect to the degree of confidentiality management of the intangible resource information data and the type of non-financial capital to which the intangible resource information belongs.

54. The organizational value improvement support system according to claim 53, wherein the classification setting unit classifies the intangible resource information data into a category of information that can be disclosed and a category of information that cannot be disclosed, based on the degree of confidentiality management.

55. The organizational value enhancement support system according to claim 54, wherein the intangible resource information utilization management unit further comprises an organizational value financial statement preparation unit, the organizational value financial statement preparation unit performs processing including generating OV-B / S data for preparing an organizational value balance sheet defined by displaying a sustainable assets section after the assets section and a non-financial capital section after the capital section in the balance sheet, the sustainable assets section shows the category value of the disclosed information category and the category value of the non-disclosed information category, and the non-financial capital section shows the category value of the category corresponding to each type of non-financial capital.

56. The organizational value enhancement support system according to claim 42, wherein the intangible resource information utilization management unit includes a PBR information provision creation unit that performs processing including creating PBR information provision data to notify the organization when the organization's price-to-net-book ratio is less than 1, in the case that the organization is a stock company.

57. The organizational value improvement support system according to claim 55, wherein the intangible resource information utilization management unit comprises an improvement proposal reasoning request unit, the improvement proposal reasoning request unit takes the OV-B / S data as input and generates improvement reasoning request data including a reasoning request to an improvement generation model, transmits the improvement reasoning request data to the improvement generation model, and performs processing including receiving improvement reasoning result data including a proposal to increase the sustainable assets and / or the non-financial capital.

58. The organizational value improvement support system according to claim 57, wherein the improvement generation model, upon instruction from the improvement proposal inference request unit, refers during inference to a performance-related information database containing the organization's performance information and the organization's value information, and / or an intangible resource information database storing the intangible resource information data.

59. The organizational value enhancement support system according to claim 57, wherein, in the case where the organization is a stock company, the inference request included in the improvement inference request data is to request a proposal for increasing the price-to-book ratio of the organization.

60. The organizational value improvement support system according to claim 42, wherein the intangible resource information utilization management unit includes a utilization proposal unit that performs processing including proposing the use of the intangible resource information to the operator of the utilization input / output device.

61. The organizational value improvement support system according to claim 60, wherein the utilization proposal unit comprises a contribution candidate inference request unit, the contribution candidate inference request unit generates proposal inference request data as input, the proposal inference request data includes an inference request that the proposal generation model proposes contribution candidate intangible resource information, which is intangible resource information that is expected to contribute to improving the value of the organization, the proposal inference request unit transmits the proposal inference request data to the proposal generation model, and performs a process that includes receiving inference result data including the contribution candidate intangible resource information.

62. The organizational value improvement support system according to claim 61, wherein the proposal generation model, upon instruction from the contribution candidate inference request unit, refers at the time of inference to a performance-related information database that stores data including information on the organization's planned activities, and / or an intangible resource information database that stores the intangible resource information data.

63. The organizational value improvement support system according to claim 61, wherein the intangible resource information utilization management unit is configured to generate internal management instruction data indicating the degree of confidentiality management of the intangible resource information data, and to manage the intangible resource information data confidentially based on the internal management instruction data.

64. The organizational value enhancement support system according to claim 63, wherein the utilization proposal unit comprises a proposal restriction setting unit, the proposal restriction setting unit identifies organizational members involved in the activity plan, determines the range of the intangible resource information data that the identified organizational members can access based on the internal management instruction data, and performs a process that enables the utilization proposal unit to select the candidate intangible resource information for contribution using the intangible resource information included within that range as the population.

65. The organizational value improvement support system according to claim 61, wherein the intangible resource information utilization management unit comprises a contribution candidate selection unit, the contribution candidate selection unit generates utilization display data for displaying the contribution candidate intangible resource information on the utilization input / output device and transmits it to the utilization input / output device, inputs the intangible resource information selected by the operator from the utilization input / output device, generates history management data indicating that the selected intangible resource information is subject to history management, and performs a process that includes outputting the history management data to a history management unit which performs a process that includes generating utilization history data including the utilization history of the intangible resource information.

66. Organizational value enhancement support system comprising at least one processor and memory, wherein the memory stores non-temporary instructions, and when an instruction is executed by the processor, the processor is configured to perform the following processes as a value allocation calculation unit upon execution of the instruction: (i) Identifying an operator who requests access to IACC information data, which includes data stored in an IACC information database and which contains information on IACCs that are intangible assets created by members belonging to the organization; (ii) Determining the number of times an external IACC is cited in response to input data indicating that the operator will cite an external IACC that was not created by the operator but is permitted to be viewed by the operator, for the purpose of creating a new IACC. (iii) The value of the other party's IACC is determined by adding 1 to the number of citations, and the value allocation of the other party's IACC is calculated by apportioning the total internal valuation of the IACC according to the ratio of the value of the value of the value of the IACC to the total value of the IACC stored in the IACC information database.

67. The organizational value improvement support system according to claim 66, wherein the processor is configured to further perform the following (iv) as the value allocation calculation unit: (iv) creating display data for displaying the other party's IACC and the value allocation of the other party's IACC, and outputting it to a display device.

68. The organizational value improvement support system according to claim 66, wherein the processor, as the value allocation calculation unit, performs the process of setting the total internal valuation of non-financial capital obtained by subtracting the total amount of financial assets from the market capitalization of the organization as the total internal valuation of the IACC.

69. The organizational value improvement support system according to claim 68, wherein the processor is configured to further perform the following process (v) as the value allocation calculation unit: (v) obtaining the average value allocation by dividing the total internal valuation of the non-financial capital by the total value points, which is the sum of the value points of all the IACC information data that may be subject to calculation.

70. The organizational value improvement support system according to claim 69, wherein the processor is configured to further perform the following (vi) as the value allocation calculation unit: (vi) creating display data for displaying the average value allocation and the total internal valuation of non-financial capital, and outputting it to a display device.

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