System and method

Abstract

To provide a system and method capable of supporting proposal of a more appropriate solution to a customer by referring to knowledge including at least solutions provided in the past and information associated with the solutions.SOLUTION: A system for supporting a business negotiation with a customer desiring provision of a solution to a manufacturing site is provided. A system includes: a database for storing knowledge including at least solutions provided in the past and information associated with the solutions; a reception part for receiving input information including information acquired from a business negotiation with the customer; and a generation part for generating a content necessary to propose a solution to the customer on the basis of knowledge similar to the input information.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present technology relates to a system and method for supporting business negotiations with customers who wish to provide solutions to manufacturing sites. [Background technology]

[0002] A solution business is known in which a customer's needs are listened to and a solution that meets those needs is provided. The following known technologies exist for such a solution business.

[0003] Japanese Patent No. 6390957 (Patent Document 1) discloses a proposal system that can contribute to proposing products, services, etc. that are highly likely to solve the real issues and problems that customers are facing.

[0004] Japanese Patent Application Laid-Open No. 2023-166218 (Patent Document 2) discloses a technique that can propose a type of service that is appropriate for both the customer and the service provider.

[0005] Japanese Patent Publication No. 2019-212082 (Patent Document 3) discloses a technology that accurately identifies and presents digital solutions that are useful for solving customer problems and their customer value, and aims to support the proposal of digital solutions with high accuracy.

[0006] Japanese Patent Publication No. 2021-039636 (Patent Document 4) discloses a technology that, during digital solution proposal activities (sales negotiations), presents sales representatives with actions to take to progress sales negotiations or clarify the degree of match, based on the degree of match between the customer's issues and the solution and the availability of engineering resources, and prompts them to decide whether to continue or terminate the negotiation. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] Patent No. 6390957 [Patent Document 2] Japanese Patent Application Publication No. 2023-166218 [Patent Document 3] Japanese Patent Application Publication No. 2019-212082 [Patent Document 4] Japanese Patent Publication No. 2021-039636 Summary of the Invention [Problem to be solved by the invention]

[0008] In the solutions business, it is important to understand customer needs, but this understanding depends heavily on the skills and experience of the sales representative, and the quality of the information collected from customers varies greatly. As a result, it can take a lot of time to decide on proposal policies, determine priorities, and coordinate within the organization.

[0009] As a result, there were issues such as losing orders due to an inability to propose services that met customer needs, and even after receiving an order, profitability could decline due to the need to redo work or prolonging the work period in the process of realizing the proposed service.

[0010] Another issue was the difficulty of quantitatively evaluating the reasons and grounds for the decision-making regarding the proposals.

[0011] The present technology provides a system and method that can assist in proposing more appropriate solutions to customers by referencing knowledge that includes at least solutions that have been provided in the past and information associated with those solutions. [Means for solving the problem]

[0012] According to one example of the present technology, there is provided a system for supporting business negotiations with customers who wish to provide solutions to manufacturing sites. The system includes a database that stores knowledge including at least solutions that have been provided in the past and information associated with the solutions, a reception unit that receives input information including information obtained through business negotiations with the customers, and a generation unit that generates content necessary to propose the solution to the customers based on knowledge similar to the input information.

[0013] According to this configuration, the content necessary to propose solutions to customers is generated based on a database that stores knowledge including at least solutions that have been provided in the past and information associated with those solutions, thereby helping to propose more appropriate solutions to customers.

[0014] If the database does not contain knowledge similar to the input information regarding the customer's problem, the generation unit may output a message indicating that the current input information does not contain enough information regarding the customer's problem. This configuration allows sales representatives and others to understand why appropriate content cannot be generated and to work on improving the input information. Furthermore, when the input information is insufficient, it is possible to prevent an inappropriate solution from being proposed to the customer based on the insufficient information.

[0015] If knowledge similar to the input information exists in the database regarding the customer's problem, the generation unit may generate content for proposing a solution contained in the similar knowledge. This configuration allows existing solutions existing in the database to be proposed, making it possible to more reliably realize the proposed solution. It also improves the accuracy of predicting information such as resources required to realize the solution.

[0016] If the database does not contain knowledge similar to the input information regarding the customer's problem and the input information does not contain sufficient information regarding the reason why the customer cannot solve the problem and the customer's decision-making and problem recognition, the generation unit may output a message indicating that further interviews are needed to find out why the customer cannot solve the problem and to obtain information regarding the customer's decision-making and problem recognition. This configuration allows sales representatives and others to understand why appropriate content cannot be generated and to work to improve the input information. Furthermore, even if the database does not contain knowledge similar to the input information, knowledge can be utilized as much as possible to provide a solution.

[0017] The generation unit may output a decision to withdraw in at least one of the following cases: when the reason why the customer cannot solve the problem and further information regarding the customer's decision-making and problem recognition cannot be added within a predetermined period of time, and when it is determined that the proposed solution is unlikely to be accepted based on the customer's decision-making and problem recognition. This configuration reduces the possibility of wasting human resources and time resources when an appropriate solution cannot be provided even if an order is received and / or when the proposed solution is likely to be unacceptable.

[0018] If there is no knowledge in the database that is similar to the input information regarding the customer's problem, and the input information contains sufficient information regarding the reason why the customer cannot solve the problem, as well as the customer's decision-making and problem recognition, the generation unit may determine the difficulty of the project based on the countermeasures and customer expectations contained in the input information. With this configuration, it is possible to present an index for determining whether to proceed with the business negotiations based on the difficulty level.

[0019] When the generation unit determines that the project is not difficult, the generation unit may generate content including a solution that is an adaptation of a solution included in knowledge similar to the input information for the customer's problem. With this configuration, when there is a high possibility that a solution based on an existing solution can be proposed, the necessary content can be provided to the customer, etc.

[0020] When the generation unit determines that the job is difficult, the generation unit may generate content that includes proposals based on knowledge other than that stored in the database. With this configuration, even when existing solutions cannot be used, there are jobs that require proactive efforts to win orders, and content that can be used in such cases can be generated.

[0021] The content may include service proposal content for explaining the solution to be provided to the customer, content for partners requesting cooperation in realizing the solution to be provided to the customer, content for the company itself including a proposed scenario for realizing an order for the solution to be provided to the customer and support information for securing the resources necessary to implement the solution, and content for the company itself including information on the risks involved in providing the solution to the customer. With this configuration, it is possible to provide information necessary to realize the implementation of the solution not only to the customer but also to internal stakeholders and partners. This allows necessary information to be shared among stakeholders.

[0022] The generation unit may determine resources required for a solution proposed in the content based on knowledge similar to the input information. The system may further include a resource allocation unit for exchanging data with a resource management system to allocate the determined resources. This configuration can assist in the allocation of resources required to realize the proposed service.

[0023] The system may further include a learning unit that updates the database based on solutions provided to customers and information associated with the solutions. This configuration allows the database to be updated and enriched based on solutions provided to customers, thereby automatically accumulating knowledge, including know-how.

[0024] The weights used to calculate the similarity with the input information may be changed based on information measured at the manufacturing site that is included in the input information. With this configuration, the information measured at the manufacturing site is estimated to be highly accurate, making it possible to propose more appropriate solutions.

[0025] The generation unit may lower the similarity of the input information when the input information includes information indicating that the information cannot be measured from the manufacturing site. With this configuration, when the input information is estimated to include uncertain information, it is possible to prevent an increase in the similarity based on the input information.

[0026] According to another example of the present technology, there is provided a computer-implemented method for supporting negotiations with a customer who wishes to provide a solution to a manufacturing site, the method including the steps of: storing knowledge in a database, the knowledge including at least solutions provided in the past and information associated with the solutions; accepting input information including information obtained through negotiations with the customer; and generating content necessary to propose the solution to the customer based on knowledge similar to the input information. [Effects of the Invention]

[0027] This technology can help propose more appropriate solutions to customers. [Brief explanation of the drawings]

[0028] [Figure 1] FIG. 1 is a diagram illustrating an overview of a system according to an embodiment of the present invention. [Figure 2]FIG. 2 is a schematic diagram showing an example of a functional configuration of a system according to the present embodiment. [Figure 3] FIG. 2 is a schematic diagram showing an example of a hardware configuration of a support server in the system according to the present embodiment. [Figure 4] FIG. 2 is a schematic diagram showing an example of a hardware configuration of a terminal in the system according to the present embodiment. [Figure 5] FIG. 1 is a diagram illustrating an example of a usage form of a system according to an embodiment of the present invention. [Figure 6] FIG. 6 is a schematic diagram showing an example of the policy-rationale document shown in FIG. 5. [Figure 7] FIG. 6 is a schematic diagram showing an example of a confirmation item document shown in FIG. 5. [Figure 8] FIG. 6 is a schematic diagram illustrating an example of a required resource document shown in FIG. 5. [Figure 9] 6 is a schematic diagram illustrating an example of an additional resource required document shown in FIG. 5. [Figure 10] FIG. 6 is a schematic diagram showing an example of the policy-rationale document shown in FIG. 5. [Figure 11] FIG. 6 is a schematic diagram showing an example of a confirmation item document shown in FIG. 5. [Figure 12] FIG. 6 is a schematic diagram illustrating an example of a required resource document shown in FIG. 5. [Figure 13] FIG. 6 is a schematic diagram showing an example of the customer interaction risk shown in FIG. 5. [Figure 14] FIG. 2 is a schematic diagram showing an example of a processing procedure of the system according to the present embodiment. [Figure 15] FIG. 10 is a diagram illustrating an example of a policy determination logic for generating a proposed policy and an execution procedure using the system according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0029] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail with reference to the accompanying drawings, in which the same or corresponding parts in the drawings are designated by the same reference numerals and the description thereof will not be repeated.

[0030] <A. Application Examples> First, an example of the scenario to which the present invention is applied will be described.

[0031] The system 1 according to the present embodiment supports negotiations with customers who wish to receive solutions for the manufacturing site.

[0032] In this specification, a "solution" includes at least a standardized off-the-shelf offering that achieves functional requirements and an offering (co-creation) that is updated as needed while consulting with the customer other than the off-the-shelf offering. There are several types of customers to whom solutions are provided, and the weighting may vary for each type. For example, the types of customers include, for example, on-site operators, on-site managers, production technology engineers, and facility managers.

[0033] In this specification, a "manufacturing site" means a site where products or semi-finished products are actually manufactured and manufacturing-related operations are performed in the manufacturing industry. A manufacturing site is a place where manufacturing equipment (for example, manufacturing machinery, control devices such as PLCs (Programmable Logic Controllers), sensors and actuators associated with the control devices, robots, inspection devices, etc.) exists. The manufacturing site may be, for example, either a line production method and / or a cell production method.

[0034] In this specification, a "solution for the manufacturing site" includes changes and / or additions of hardware and / or software to solve troubles and problems occurring at the manufacturing site and / or troubles and problems that may occur at the manufacturing site.

[0035] FIG. 1 is a diagram for explaining the outline of the system 1 according to the present embodiment. Referring to FIG. 1, the system 1 includes a support server 100 and a knowledge database 200. The system 1 may include a resource management system 300. In the following description, the support server 100 and the knowledge database 200 are also collectively referred to as the "support system".

[0036] The salesperson 2 in charge of business with Customer 4 accesses the support server 100 by operating the terminal 500 to obtain information and necessary documents for supporting business as described later.

[0037] FIG. 2 is a schematic diagram showing a functional configuration example of the system 1 according to the present embodiment. Referring to FIG. 2, the system 1 includes a knowledge database 200. The knowledge database 200 stores knowledge including at least solutions provided in the past and information associated with the solutions.

[0038] The system 1 includes a reception unit 160 for receiving input information 70 including information obtained through negotiations with Customer 4, and a generation unit 170 for generating content 180 necessary for proposing a solution to Customer 4 based on knowledge similar to the input information 70.

[0039] In the system 1, since the content 180 can be generated by referring to knowledge including at least solutions provided in the past and information associated with the solutions, a more appropriate solution can be proposed to Customer 4.

[0040] <B. Hardware Configuration Example> Next, a hardware configuration example of the main devices constituting the system 1 according to the present embodiment will be described.

[0041] (b1: Hardware Configuration Example of Support Server 100) FIG. 3 is a schematic diagram showing a hardware configuration example of the support server 100 of the system 1 according to the present embodiment. Referring to FIG. 3, the support server 100 includes, as hardware components, one or more processors 102, a memory 104, a storage 106, an input unit 108, a display unit 110, a network controller 112, and a DB interface 114.

[0042] The processor 102 reads out a program stored in the storage 106, expands it in the memory 104, and executes it to realize various processes described below. The processor 102 is, for example, a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit).

[0043] The memory 104 is a volatile storage device for holding programs executed by the processor 102, working data, etc. The memory 104 is, for example, a dynamic random access memory (DRAM) or a static random access memory (SRAM).

[0044] The storage 106 is a non-volatile storage device that stores programs executed by the processor 102. The storage 106 is, for example, a hard disk drive (HDD) or a flash solid state drive (SSD).

[0045] The storage 106 stores, for example, a system program 120, a support program 122, and a learning program 124. The system program 120 includes computer-readable instructions for basic processing. The support program 122 includes computer-readable instructions for processing to support the sales activities of the sales representative 2 via the terminal 500. The learning program 124 includes computer-readable instructions for learning processing, such as adding knowledge to the knowledge database 200.

[0046] The input unit 108 accepts user operations. The input unit 108 is, for example, a keyboard or a mouse. The input unit 108 may be an interface with an external input device. In other words, the input device that accepts user operations does not need to be a hardware component of the support server 100.

[0047] The display unit 110 displays or outputs the processing results by the processor 102. The display unit 110 is, for example, a liquid crystal display or an organic EL display. The display unit 110 may also be an interface with an external display device. In other words, the display device that displays or outputs the processing results does not need to be a hardware component of the support server 100.

[0048] The network controller 112 exchanges data with the resource management system 300, the terminal 500, and the like via the network.

[0049] The DB interface 114 exchanges data with the knowledge database 200 .

[0050] (b2: Example of hardware configuration for Knowledge Database 200) The knowledge database 200 may have the hardware configuration of a general-purpose database, and therefore the hardware configuration of the knowledge database 200 will not be described in detail.

[0051] (b3: Example of hardware configuration of terminal 500) 4 is a schematic diagram showing an example of a hardware configuration of terminal 500 of system 1 according to the present embodiment. Terminal 500 may be, for example, a general-purpose personal computer or a tablet.

[0052] Referring to FIG. 4, the terminal 500 includes, as hardware components, one or more processors 202, a memory 204, a storage 206, an input unit 208, a display unit 210, a network controller 212, a microphone 216, and a speaker 218.

[0053] The processor 202 reads out a program stored in the storage 206, expands it in the memory 204, and executes it to realize various processes described below. The processor 202 is, for example, a CPU or a GPU.

[0054] The memory 204 is a volatile storage device for storing programs executed by the processor 202, working data, and the like.

[0055] The storage 206 is a non-volatile storage device that stores programs executed by the processor 202. The storage 206 stores, for example, a system program 220 and a browser program 222. The system program 220 includes computer-readable instructions for basic processing. The browser program 222 includes computer-readable instructions for accessing the support server 100, etc.

[0056] The input unit 208 receives user operations and is, for example, a keyboard, a mouse, or a touch panel.

[0057] The display unit 210 displays or outputs the results of processing by the processor 202. The display unit 210 is, for example, a liquid crystal display or an organic EL display.

[0058] The network controller 212 exchanges data with the support server 100 and the like via the network.

[0059] The microphone 216 generates a digital signal corresponding to the collected audio signal. The speaker 218 generates an audio signal according to the results of processing by the processor 202 .

[0060] (b4: Example of hardware configuration of resource management system 300) The resource management system 300 has the same hardware configuration as the support server 100 shown in Fig. 3 (however, the DB interface 114 is not necessarily required). Therefore, the hardware configuration of the resource management system 300 will not be described in detail.

[0061] (b5:Other) In this specification, the "processor" includes at least a part of a processing circuit that sequentially processes computer-readable instructions such as a CPU or a GPU, a hard-wired circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array), and a semiconductor such as an AI chip.

[0062] In this specification, the term "memory" includes memory and storage. At least a part of the support server 100, the knowledge database 200, and the resource management system 300 may be realized using computing resources existing on the cloud.

[0063] At least a part of the support server 100, the knowledge database 200, and the resource management system 300 may be composed of a plurality of physical servers. Alternatively, at least a part of the support server 100, the knowledge database 200, and the resource management system 300 may be composed of the same physical server.

[0064] A part of the processing described below that the support server 100 executes may be executed by the terminal device 500. In this case, the terminal device 500 may store an application program for executing the processing.

[0065] The programs (computer-readable instructions) executed by the support server 100, the knowledge database 200, the resource management system 300, and the terminal device 500 may be installed by downloading from an application server, or may be installed via a recording medium such as an optical disk.

[0066] <C. System Usage Forms> Next, an example of the usage form of the system 1 according to this embodiment will be described.

[0067] 5 is a diagram illustrating an example of a usage form of system 1 according to the present embodiment. Referring to FIG. 5, the support system receives input information 70 (corresponding to receiving unit 160 in FIG. 2). Input information 70 includes customer information and competitor information (hereinafter also referred to as "competitor information"), as well as information obtained by sales representative 2 through negotiations with customer 4 (hereinafter also referred to as "negotiation results 60").

[0068] The support system generates content necessary for proposing a solution to the customer 4 based on knowledge similar to the input information 70 (corresponding to the generation unit 170 in FIG. 2). The content necessary for proposing a solution to the customer 4 outputs information for external use (the customer 4 and external partner companies) and information for internal use. More specifically, the content necessary for proposing a solution to the customer 4 includes service proposal content 10, partner response plans 20, proposed scenarios 30, support information 40, and customer response risk information 50.

[0069] As will be described later, the information output by the support system will differ depending on the degree of satisfaction of the negotiation result 60. Also, if necessary information is insufficient, some or all of the information may not be output.

[0070] The information for external use output by the support system includes, for example, service proposal content 10 related to the solution system. The service proposal content 10 is mainly information intended for the customer 4. The service proposal content 10 includes content for explaining the solution to be provided to the customer 4.

[0071] The service proposal content 10 includes a policy and reason document 12 , a check item document 14 , and a required resource document 16 .

[0072] The policy and reason document 12 includes the policy (solution) for solving the needs of the customer 4 and the reasons for deciding on that policy. The confirmation item document 14 includes items for confirming information necessary for proposing a service. The required resource document 16 includes information on the resources necessary to realize the proposed service (solution).

[0073] Fig. 6 is a schematic diagram showing an example of the policy and reason document 12 shown in Fig. 5. Referring to Fig. 6, the policy and reason document 12 includes items such as the customer name, factory / department, customer representative, customer needs, proposal policy, approach, expected effects, schedule, and rough estimate. For each item, the content is described, and, if necessary, the reason why the content was decided is also described.

[0074] Fig. 7 is a schematic diagram showing an example of the check item document 14 shown in Fig. 5. Referring to Fig. 7, the check item document 14 includes items such as approach, budget and constraints, and customer expectations. The contents of each item are described.

[0075] Fig. 8 is a schematic diagram showing an example of the required resources document 16 shown in Fig. 5. Referring to Fig. 8, the required resources document 16 includes items such as a lead sales representative, a lead engineer, an assistant engineer, equipment used, and others. For each item, the content is described, and, if necessary, the reason for determining the content is also described.

[0076] Referring again to FIG. 5 , the external information output by the support system may include a partner response plan 20. The partner response plan 20 may be output when it is determined that additional response is necessary. The partner response plan 20 is primarily information intended for external partner companies (e.g., system integrators and staffing agencies). The partner response plan 20 includes content for partners requesting cooperation in realizing a solution to be provided to the customer 4. The partner response plan 20 includes an alert 22 indicating precautions, etc.

[0077] For example, the alert 22 includes an additional resource required document 24. The additional resource required document 24 corresponds to a portion of the required resources and includes information on resources that are required to realize the proposed service (solution) and that are to be additionally provided by an external partner company.

[0078] Fig. 9 is a schematic diagram showing an example of the additional resource required document 24 shown in Fig. 5. Referring to Fig. 9, the additional resource required document 24 includes items such as technical qualifications, required quantity, past performance, and others. For each item, the content is described, and, if necessary, the reason for determining the content is also described.

[0079] 5, the in-house information output by the support system includes, for example, a proposed scenario 30 relating to a service proposal and support information for securing resources 40. The proposed scenario 30 and the support information for securing resources 40 are primarily intended for in-house users of the system 1 (i.e., sales representative 2, etc.).

[0080] The proposed scenario 30 includes information such as the reasons for deciding on a policy (solution) to solve the needs of the customer 4. The proposed scenario 30 is content for the company itself, including a proposed scenario for realizing an order for the solution to be provided to the customer 4. The proposed scenario 30 includes a policy and reason document 32 and a confirmation item document 34.

[0081] The resource securing support information 40 includes information for securing resources to realize a policy (solution) for resolving the needs of the customer 4. The resource securing support information 40 is content for the company to secure resources required to realize the implementation of the solution provided to the customer 4. The resource securing support information 40 includes a required resource document 46.

[0082] Fig. 10 is a schematic diagram showing an example of the policy and reason document 32 shown in Fig. 5. Referring to Fig. 10, the policy and reason document 32 includes the policy and reason document 12 shown in Fig. 6, but information based on knowledge stored in the knowledge database 200 has been added.

[0083] More specifically, the policy and reason document 32 includes items such as the customer name, factory / department, customer representative, customer needs, proposal policy, past similar cases, solution, expected effect, schedule, and rough estimate. The content of each item is described, and, if necessary, the reason for the content being decided is also described.

[0084] The information in bold in the policy and reason document 32 shown in Figure 10 is knowledge-based.

[0085] Fig. 11 is a schematic diagram showing an example of the check item document 34 shown in Fig. 5. Referring to Fig. 11, the check item document 34 includes, as items, an approach, budget / constraints, and customer expectations. The contents of each item are described.

[0086] In the confirmation item document 34 shown in FIG. 11, the information shown in bold is based on knowledge.

[0087] Fig. 12 is a schematic diagram showing an example of the required resources document 46 shown in Fig. 5. Referring to Fig. 12, the required resources document 46 includes items such as a lead sales representative, a lead engineer, an assistant engineer, equipment used, and others. For each item, the content is described, and, if necessary, the reason for determining the content is also described.

[0088] The information in bold in the required resource document 46 shown in FIG. 12 is based on knowledge.

[0089] Referring again to FIG. 5, the in-house information output by the support system may include the customer-facing response risk information 50. The customer-facing response risk information 50 may be output when it is determined that additional response is necessary. The customer-facing response risk information 50 is in-house content that includes information on the risks when providing solutions to customer 4. The customer-facing response risk information 50 is mainly information for in-house resource managers (such as those responsible for managing the utilization of in-house resources) and procurement staff (such as those responsible for arranging equipment, etc.). The customer-facing response risk information 50 includes an alert 52 indicating precautions and the like.

[0090] For example, the alert 52 includes a required additional resource document 54 and a customer-facing response risk 56. The required additional resource document 54 includes information similar to the required additional resource document 24 shown in FIG. 9. The customer-facing response risk 56 includes, for example, the sufficiency of the proposed content for the needs of customer 4.

[0091] FIG. 13 is a schematic diagram showing an example of the customer-facing response risk 56 shown in FIG. 5. Referring to FIG. 13, the customer-facing response risk 56 includes, as items, approach, budget / constraints, and customer expectations. For each item, an estimated probability is described.

[0092] <D. Processing Procedures of the System> Next, an example of the processing procedure of the system 1 according to the present embodiment will be described.

[0093] FIG. 14 is a schematic diagram showing an example of the processing procedure of the system 1 according to the present embodiment. Referring to FIG. 14, in the system 1 according to the present embodiment, there are an operation phase 130 (steps S20 to S80) in which negotiations are advanced using the output information and processing necessary for realizing the solution is advanced, and a learning phase 140 (steps S100 and S110) in which knowledge is added to the knowledge database 200 using the results after the solution determined by the negotiations is realized.

[0094] (d1: Support for Negotiations) First, the phase (steps S10 to S80) in which the output information is used to advance negotiations and the processing required to realize a solution is described. The processing of steps S30 to S80 may be realized by, for example, the processor 102 of the support server 100 executing the support program 122.

[0095] During business negotiations with the customer 4, the sales representative 2 listens to the customer 4's problems and issues (step S10). The initial listening may be performed on a document basis.

[0096] During and / or after the negotiation, the sales representative 2 inputs the negotiation results 60, such as minutes, into the terminal 500. The text information, such as the negotiation results 60, input into the terminal 500 is input into the support server 100 (step S20).

[0097] The support server 100 executes processes such as negotiation analysis and customer needs extraction based on the input information (step S30). The input information 70 output by the process of step S30 includes, for example, the troubles and problems of the customer 4, the reasons why the customer 4 cannot solve them, the decision-making and problem recognition of the customer 4, measures to address the problems, and the expectations of the customer 4.

[0098] The support server 100 evaluates the input information 70 by referring to the knowledge database 200 (step S40). The evaluation in step S40 determines whether the input information 70 has sufficient information, and also evaluates the similarity between the input information 70 and past cases.

[0099] If the input information 70 contains insufficient information to propose a service and it is determined that the predetermined requirements are not met (NO in step S50), the support server 100 determines that additional measures are necessary. Then, the support server 100 generates a proposal policy and an execution procedure (step S60). The processing in step S60 corresponds to the generation unit 170 in FIG. 2.

[0100] If additional measures are required, the process of generating a proposed policy and execution procedure (step S60) outputs a policy and reason document 12 and a check item document 14 as information for external use, and also outputs a policy and reason document 32 and a check item document 34 as information for internal use. However, these output documents are insufficient for proposing a service.

[0101] Furthermore, the support server 100 outputs an alert 52 including a customer response risk 56 and the like in response to the determination that additional response is necessary.

[0102] Salesperson 2 conducts business negotiations based on the output document and alert 52 (step S10).

[0103] On the other hand, if it is determined that the information contained in the input information 70 is sufficient to propose a service and satisfies the predetermined requirements (YES in step S50), the support server 100 generates a proposal policy and an execution procedure (step S60). More specifically, the support server 100 outputs the policy and reason document 12 and the check item document 14 as information for external use, and outputs the policy and reason document 32 and the check item document 34 as information for internal use.

[0104] The support server 100 refers to the resource management system 300 and determines whether the resources required to realize the proposed service (solution) can be secured (step S70). In this way, the support server 100 (generation unit) determines the resources required for the solution proposed in the content based on knowledge similar to the input information 70. Then, the support server 100 (resource securing unit) exchanges data with the resource management system 300 to secure the determined resources.

[0105] If the necessary resources can be secured (YES in step S70), the support server 100 generates an external required resource document 16 and an internal required resource document 46. The sales representative 2 conducts final negotiations based on the output documents (step S10).

[0106] On the other hand, if the required resources cannot be secured (NO in step S80), the support server 100 presents an alert 52 including an additional resource required document 54 and a customer response risk 56 to the internal resource manager 6, and / or presents an alert 22 including an additional resource required document 24 to the external partner company 8 (step S90). Upon receiving notification from the resource manager 6 and / or the external partner company 8 that resources can be secured, the support server 100 generates an external required resource document 16 and an internal required resource document 46.

[0107] In this way, by providing the information necessary for negotiations between sales representative 2 and customer 4 based on the knowledge stored in knowledge database 200, it is possible to propose a more appropriate solution to resolve customer 4's needs.

[0108] It is rare that everything is decided in one negotiation, and multiple negotiations are conducted. The content required as input information 70 may change depending on the progress of the negotiation (negotiation phase). The determination process (step S50) and the process for generating proposal policies and execution procedures (step S60) may change depending on the negotiation phase. An example of such processing will be described in detail later.

[0109] (d2: Learning Knowledge Database 200) Next, a description will be given of the phase (steps S100 and S110) of adding knowledge to the knowledge database 200. The processing of steps S100 to S110 may be realized by the processor 102 of the assistance server 100 executing the learning program 124, for example.

[0110] The knowledge database 200 stores knowledge including at least solutions provided in the past and information associated with the solutions. The support system (learning unit) updates the knowledge database 200 based on the solutions provided to the customers 4 and the information associated with the solutions. More specifically, the support server 100 receives input of completed project information 80, which is the result after the solutions decided in business negotiations have been realized.

[0111] The completed project information 80 includes, as text information, for example, examples of problem-solving cases at manufacturing sites, in-house knowledge (negotiation know-how, procedure manuals, etc.), customer information, competitive information (web information), past negotiation materials, etc. Past negotiation materials include, for example, proposals, question lists, minutes, estimates, organizational structures, equipment lists, plans and progress charts, work procedures, and test design documents.

[0112] The support server 100 extracts business negotiation knowledge 90 from the input completed project information 80 (step S100). The business negotiation knowledge 90 includes, for example, (1) industry / business type, process, manufactured product, (2) issues, question items, and (3) resources used (man-hours, skills, equipment).

[0113] The extraction of business negotiation knowledge 90 may be achieved, for example, by converting the text information contained in the completed project information 80 into a numerical vector representation by embedding, and then extracting sentences and words that have a meaning similar to that which should be included in the business negotiation knowledge 90.

[0114] Next, the support server 100 associates the extracted negotiation knowledge 90 (step S110). That is, the support server 100 converts the extracted negotiation knowledge 90 into knowledge.

[0115] In the process of knowledge conversion, the support server 100 structures the elements included in the negotiation knowledge 90. That is, it converts them into knowledge while maintaining the relationships between the elements included in the negotiation knowledge 90. For example, the support server 100 extracts the content corresponding to the following order: industry → business type → process → manufactured product → needs → countermeasures → procedures → technologies → skills → products → estimate (man-hours · labor man-hours) → verification items, and associates them with each other.

[0116] More specifically, the support server 100 converts the text information included in the negotiation knowledge 90 into a numerical vector representation by embedding, extracts sentences and words that are similar for each item, and then adds hierarchical structure information to the content of each item.

[0117] Finally, the support server 100 adds the extracted information (knowledge) to the knowledge database 200. Since the negotiation knowledge 90 is independent for each case, basically there is no need to consider the relevance between cases. However, if there is a relevance between cases, the relevance between the cases may also be added to the knowledge database 200.

[0118] Note that the information on completed cases 80 is not limited to those implemented using the system 1 according to this embodiment, and can include information on any service (solution). For example, the information on completed cases 80 may include newly developed solutions, know-how of other departments, and know-how of acquired companies.

[0119] Furthermore, the knowledge database 200 may include, as knowledge, information on social situations such as market information with trends and government subsidies. By including such information as knowledge, it is possible to make more realistic service proposals.

[0120] <E. Policy Decision Logic (Steps S40 to S60)> Next, an example of the logic (steps S40 to S60) for generating the proposed policy and execution procedure shown in FIG. 14 (hereinafter also referred to as "policy decision logic 150") will be described.

[0121] FIG. 15 is a diagram illustrating an example of policy determination logic 150 for generating a proposed policy and an execution procedure using system 1 according to the present embodiment.

[0122] Referring to FIG. 15, the support system outputs three main types of proposed policies ("strong", "semi-strong", and "strategic learning") as output information.

[0123] A proposal policy classified as "specialty" proposes a standard service (standard solution) with a proven track record. A proposal policy classified as "semi-specialty" proposes individual responses by arranging past cases based on knowledge. A proposal policy classified as "strategic learning" proposes cases for which there has been no experience. "Strategic learning" is aimed at solutions that require new development. The policy determination logic 150 determines which proposal policy should be adopted based on the input information 70.

[0124] If the information contained in the input information 70 is sufficient but does not satisfy the predetermined requirements, "preparation" is output as the proposed policy. In "preparation," instructions for enriching the input information 70 are output.

[0125] As described above, the input information 70 includes the troubles and problems of the customer 4, the reasons why the customer 4 cannot solve the problem, the customer 4's decision-making and problem recognition, measures to address the problem, and the customer 4's expectations.

[0126] Customer 4's troubles and problems are information used to structure customer needs and determine the initial service response policy. Customer 4's reasons for not being able to resolve the problem and their decision-making and problem recognition are information used to clarify the customer's capabilities and organization and are used to determine the feasibility of providing value to the customer. Customer 4's countermeasures for the problem and their expectations are information that indicates Customer 4's intention to resolve the problem and are used to determine the likelihood and priority of closing the deal.

[0127] More specifically, the policy determination logic 150 executes the following process.

[0128] First, it is determined whether the content of the problem contained in the input information 70 satisfies predetermined requirements (step S200). For example, if the information about the problem itself is insufficient or if the items described as the problem are vague, it is determined that the predetermined requirements are not met (NO in step S200), and a return is output (step S202). In response to the return output, the sales representative 2 reorganizes or confirms the problem of the customer 4. Using the input information 70 that has been improved by the reorganization or confirmation, the processing from step S200 onwards is executed again.

[0129] If the enriched input information 70 is not obtained after the return is output (after step S202), a message to that effect is input to the support system, which then decides on a withdrawal policy.

[0130] If it is determined that the content of the problem satisfies the predetermined requirements (YES in step S200), it is determined whether the content of the problem included in the input information 70 satisfies the predetermined requirements (step S204). If it is determined that the content of the problem does not satisfy the predetermined requirements (NO in step S204), a standard service response (standard response) is decided as the proposal policy (step S206). The sales representative 2 negotiates with the customer 4 using service proposal content 10 (see FIG. 5) based on the standard service response. Ideally, it would be necessary to hear not only about the content of the problem but also about content beyond the problem, but the sales representative 2 is forced to propose a standard service to solve the problem.

[0131] If the service proposal cannot be agreed with the customer 4 (NO in step S208), a policy of withdrawing from the business negotiation is decided (step S210). On the other hand, if the service proposal can be agreed with the customer 4 (YES in step S208), a policy of accepting the order for the proposed service is decided (step S212).

[0132] On the other hand, if it is determined that the content of the problem satisfies the predetermined requirements (YES in step S204), it is determined whether the reason why the problem cannot be solved by customer 4 and the decision-making and problem recognition by customer 4 contained in the input information 70 satisfy the predetermined requirements (step S214). In other words, if the problem is understood, it is determined whether (3) the reason why the problem cannot be solved and (4) the decision-making and problem recognition are satisfied.

[0133] If it is determined that the reason for the inability to solve the problem and the decision-making / problem recognition do not satisfy the predetermined requirements (NO in step S214), an interview is instructed to the sales representative 2 (step S216). In response to the interview instruction, the sales representative 2 interviews the customer 4 again to find out why the customer 4 cannot solve the trouble or problem, whether the customer 4 recognizes the trouble or problem as an issue, whether the customer 4 wants to solve it, etc. Using the input information 70 that has been enriched by the second interview, the processing from step S214 onwards is executed again.

[0134] Alternatively, if it is determined that the reason for the inability to solve the problem and the decision-making / problem recognition do not satisfy the predetermined requirements (NO in step S214), a decision may be made to withdraw from the business negotiation (step S218). For example, if the reason for the inability to solve the problem is fatal or if there is a fatal problem in the decision-making / problem recognition of the customer 4, it is expected that it will be difficult to propose a service, and in such cases, a decision may be made to withdraw.

[0135] If it is determined that the reasons for inability to resolve the problem and the decision-making / problem recognition meet the specified requirements (YES in step S214), it is determined whether the case is difficult or not based on the measures for the problem contained in the input information 70 and the expectations of customer 4 (step S220).

[0136] If it is determined that the case is not of high difficulty (NO in step S220), past case arrangement (individual response) is decided as the proposal policy (step S222). Service proposal content 10 (see FIG. 5) based on past case arrangement is created by referring to knowledge stored in knowledge database 200. If it is determined that the case is not of high difficulty, the support system (generation unit 170) generates content including a solution (past case arrangement) that is an arrangement of a solution included in knowledge similar to input information 70 for the problem of customer 4.

[0137] The sales representative 2 negotiates with the customer 4 using the service proposal content 10 (see FIG. 5) based on an arrangement of past cases. If the sales representative 2 and the customer 4 cannot agree on the service proposal (NO in step S224), the sales representative 2 is instructed to interview the customer 4 about the reasons why the problem cannot be solved and about their decision-making and problem recognition (step S226). In response to the interview instruction, the sales representative 2 again interviews the customer 4 about the reasons why the problem cannot be solved and about their decision-making and problem recognition. Using the input information 70 that has been enriched by the second interview, the processing from step S222 onwards is executed again.

[0138] Alternatively, if the service proposal cannot be agreed with the customer 4 (NO in step S224), a decision may be made to withdraw from the business negotiation (step S228).

[0139] Furthermore, when an agreement cannot be reached with the customer 4 regarding the service proposal based on the past case arrangement, if the measures and the expectations of the customer 4 are satisfied in the interview with the customer 4 (step S226), the process may return to step S220.

[0140] On the other hand, if an agreement can be reached with Customer 4 regarding the service proposal (YES in Step S224), a policy to accept the project with the proposed service is determined (Step S230).

[0141] If it is determined that the project is of high difficulty (YES in Step S220), a policy of handling new development (unexperienced project) is determined as the proposal policy (Step S232). When it is determined that the difficulty of the project is high, the support system (generation unit 170) generates content including a proposal (unexperienced project) based on something other than the knowledge stored in the knowledge database 200.

[0142] The salesperson 2 negotiates with Customer 4 using the service proposal content 10 based on handling new development (see FIG. 5). If an agreement cannot be reached with Customer 4 regarding the service proposal (NO in Step S234), an interview regarding countermeasures and Customer 4's expectations is instructed to the salesperson 2 (Step S236). Upon receiving the interview instruction, the salesperson 2 interviews Customer 4 again regarding countermeasures and Customer 4's expectations, etc. Using the input information 70 enriched by the re-interview, the processes from Step S232 onward are executed again. <Q

[0143] Alternatively, if an agreement cannot be reached with Customer 4 regarding the service proposal (NO in Step S234), a policy of withdrawing from the target negotiation may be determined (Step S238). For example, when it is determined that the risk is too high in handling new development (unexperienced project), a policy of withdrawal may be determined.

[0144] On the other hand, if an agreement can be reached with Customer 4 regarding the service proposal (YES in Step S234), a policy to accept the project with the proposed service is determined (Step S240).

[0145] <F. Use of the Knowledge Database 200> The knowledge database 200 is used to determine whether the input information 70 satisfies predetermined requirements and to generate information for internal and external use. As described above, the knowledge database 200 stores structured knowledge. The stored knowledge is converted into a numerical vector representation, making it easy to search for and extract sentences or words with similar meanings.

[0146] The determination of whether the content of the problem included in the input information 70 satisfies predetermined requirements (step S200 shown in FIG. 15) may be based on, for example, determining whether text similar to the problem included in the input information 70 exists in text information to which a need attribute has been assigned. If the similarity of the extracted text exceeds a predetermined threshold, it may be determined that the predetermined requirements are satisfied. The calculated similarity may be described in information for internal use (see, for example, FIG. 10).

[0147] In this way, if there is no knowledge similar to the input information 70 in the knowledge database 200 regarding the problem of customer 4, the support system (generation unit 170) outputs a message indicating that the current input information 70 does not contain enough information regarding the problem of customer 4.

[0148] The determination of whether the content of the problem included in the input information 70 satisfies predetermined requirements (step S204 shown in FIG. 15) may be based on, for example, determining whether text similar to the problem included in the input information 70 exists in text information to which a need attribute has been assigned. If the similarity of the extracted text exceeds a predetermined threshold, it may be determined that the predetermined requirements are satisfied. The calculated similarity may be described in internal company information (see, for example, FIG. 10).

[0149] If knowledge similar to the input information 70 exists in the knowledge database 200 regarding the problem of customer 4, the support system (generation unit 170) generates information for external and internal use based on standard service responses (standard responses) as content for proposing solutions contained in the similar knowledge (step S206 shown in Figure 15).

[0150] Large language models (LLMs) may be used to generate information for external and internal use based on the standard service response (standard response) (step S206 shown in FIG. 15). For example, the support server 100 extracts knowledge of cases similar to the troubles and problems included in the input information 70 (past similar cases shown in FIG. 10) from the knowledge database 200, and provides the extracted knowledge and a prompt for generating information for external and internal use to the LLM, thereby outputting a desired document from the LLM. The prompt provided to the LLM may include, for example, specifications for items and formats to be included in the document to be output.

[0151] The support server 100 may calculate the similarity (match degree) between the troubles and problems included in the input information 70 and past similar cases stored in the knowledge database 200. Alternatively, the troubles and problems included in the input information 70 and knowledge of past similar cases may be input to the LLM, and the LLM may calculate the similarity (match degree).

[0152] The determination of whether the reasons for inability to solve the problem and the decision-making / problem recognition contained in the input information 70 satisfy predetermined requirements (step S214 shown in FIG. 15) may be based on an evaluation of whether any knowledge stored in the knowledge database 200 contains text information similar to the text of the reasons for inability to solve the problem and the decision-making / problem recognition contained in the input information 70. If the similarity of the extracted text exceeds a predetermined threshold, it may be determined that the predetermined requirements are satisfied. The calculated similarity may be described in internal company information (see, for example, FIG. 10).

[0153] When the degree of sufficiency of the input information 70 is low, an instruction to conduct interviews (step S216) is decided to be given to the sales representative 2. That is, if there is no knowledge similar to the input information 70 in the knowledge database 200 regarding the problem of the customer 4, and the input information 70 does not contain sufficient information regarding the reason why the problem cannot be solved by the customer 4 and the decision-making and problem recognition by the customer 4, the support system (generation unit 170) outputs a message indicating that further interviews are necessary to obtain information regarding the reason why the problem cannot be solved by the customer 4 and the decision-making and problem recognition by the customer 4.

[0154] The policy of withdrawing from the target business negotiation (step S238) may be decided, for example, when it is determined that it is difficult to deal with the situation by arranging past cases. That is, when it is difficult to deal with the situation by arranging past cases, it is expected that it will be difficult to realize the proposed service.

[0155] Furthermore, if it is assessed based on the decision-making and problem recognition included in the input information 70 that the customer 4 has no intention of considering the service proposal, a policy of withdrawing from the target business negotiation may be decided. In this way, the support system (generation unit 170) may output a decision to withdraw when it is determined that the solution proposal is unlikely to be accepted based on the decision-making and problem recognition of the customer 4. The assessment that the customer 4 has no intention of considering the service proposal may be automatically generated by providing the LLM with the decision-making and problem recognition included in the input information 70 and a prompt for assessing the willingness to consider.

[0156] Furthermore, if necessary information has not been added as input information 70 when a predetermined time has elapsed since the start of the business negotiation (registration of the case in the support server 100), a decision to withdraw from the business negotiation may be automatically decided. In this way, the support system (generation unit 170) may output a decision to withdraw if the reason why the problem cannot be solved by the customer 4 and further information regarding the customer 4's decision-making and problem recognition cannot be added within a predetermined period of time.

[0157] The determination of whether or not the case is of high difficulty based on the countermeasures and expectations of customer 4 included in the input information 70 (step S220 shown in FIG. 15) may be based on an evaluation of whether or not any knowledge stored in the knowledge database 200 contains text information similar to the text of the countermeasures and expectations of customer 4. Alternatively, the countermeasures and expectations of customer 4 included in the input information 70 and a prompt for evaluating determination toward a solution may be input into the LLM, and whether or not the case is of high difficulty may be determined based on the level of determination toward a solution that is output.

[0158] For example, multiple similar past cases may be extracted based on the text of the countermeasures and customer 4's expectations, and if none of the extracted similar past cases has a similarity to the problems of the similar past cases that is equal to or exceeds a predetermined threshold (e.g., 60%), the case may be determined to be of high difficulty.

[0159] In this way, if there is no knowledge similar to the input information 70 in the knowledge database 200 regarding customer 4's problem, and if the input information 70 contains sufficient information regarding the reasons why customer 4 cannot solve the problem, as well as customer 4's decision-making and problem recognition, the support system (generation unit 170) may determine the difficulty of the case based on the countermeasures and customer 4's expectations contained in the input information 70.

[0160] In generating information for internal and external use based on past case arrangement (individual response) (step S222 shown in FIG. 15), knowledge of multiple cases that are somewhat similar to the difficulties, problems, reasons for inability to solve, and decision-making / issue recognition contained in the input information 70 is extracted from the knowledge database 200. The extracted cases may include cases with a relatively low degree of similarity. The extracted knowledge and a prompt for generating information for internal and external use are provided to the LLM, which outputs the desired document.

[0161] Additionally, knowledge for arranging similar past cases may be searched for. In this case, cases similar to the troubles and problems contained in the input information 70 may be searched for from the knowledge database 200.

[0162] External and internal information based on new development responses may be created using output from the LLM, but as it may be a management decision, it may also be generated after evaluation by the organization. Therefore, the support server 100 may generate a policy and reason document 32 (internal information) that includes the reasons why the project was judged to be difficult and the information currently lacking.

[0163] In addition, information on similar past cases that are extracted based on the text of countermeasures and customer 4's expectations and that have a predetermined number of similarities in terms of problems (for example, the top three) may be output as information for consideration.

[0164] Furthermore, the content of the information contained in the input information 70 may be taken into consideration when calculating the similarity. For example, if the input information 70 includes data acquired by a sensor or the like that can measure information from the manufacturing site, the weight of the similarity for that data may be set higher. In this way, the weight for calculating the similarity with the input information 40 may be changed based on the information measured from the manufacturing site that is included in the input information 40. Information from the manufacturing site includes, for example, the arrival and completion status of products, production quantities, on-site worker allocation, inspection results, and operation information of manufacturing equipment.

[0165] On the other hand, when there are circumstances where information at the manufacturing site cannot be measured by sensors or the like, information indicating that it cannot be measured may be added to the input information 70. By providing the input information 70 with the added indication that it cannot be measured, the calculated similarity may be decreased. The degree of decreasing the similarity may depend on the absolute number or ratio of points that cannot be measured. Thus, when the input information 70 includes information indicating that it cannot measure information from the manufacturing site, the support system (generation unit 170) may decrease the similarity for the input information 70.

[0166] <G. Supplementary Note> The present embodiment as described above includes the following technical ideas. [Configuration 1] A system (1) for supporting negotiations with a customer (4) who wishes to receive a solution for a manufacturing site, a database (200) that stores knowledge including at least solutions provided in the past and information associated with the solutions, a reception unit (100; 160) for receiving input information (70) including information obtained through negotiations with the customer, and a generation unit (100; 170) for generating content (180; 10, 20, 30, 40, 50) necessary for proposing a solution to the customer based on knowledge similar to the input information. [Configuration 2] The system according to Configuration 1, wherein when there is no knowledge similar to the input information in the database regarding the customer's problem, the generation unit outputs that the current input information lacks information regarding the customer's problem (S200, S202). [Configuration 3] The system according to Configuration 1 or 2, wherein when there is knowledge similar to the input information in the database regarding the customer's problem, the generation unit generates content for proposing the solution included in the similar knowledge (S204, S206). [Configuration 4] The system described in any one of configurations 1 to 3, wherein if there is no knowledge similar to the input information in the database regarding the customer's problem and the input information does not contain sufficient information regarding the reason why the customer cannot solve the problem and the customer's decision-making and problem recognition, the generation unit outputs a message indicating that further information regarding the reason why the customer cannot solve the problem and the customer's decision-making and problem recognition is needed (S214, S216). [Configuration 5] The system described in configuration 4, wherein the generation unit outputs a decision to withdraw (S214, S218) in at least one of the following cases: when the reason why the problem cannot be solved by the customer and further information regarding the customer's decision-making and problem recognition cannot be added within a specified period of time; and when it is determined that the proposed solution is unlikely to be accepted based on the customer's decision-making and problem recognition. [Configuration 6] The system described in configuration 4 or 5, wherein if there is no knowledge in the database that is similar to the input information regarding the customer's problem and the input information contains sufficient information regarding the reason why the customer cannot solve the problem, as well as the customer's decision-making and problem recognition, the generation unit determines the difficulty of the case based on the countermeasures and the customer's expectations contained in the input information (S220). [Configuration 7] The system described in configuration 6, wherein when the generation unit determines that the difficulty level of the case is not high, the generation unit generates content including a solution that is an adaptation of a solution contained in knowledge similar to the input information regarding the customer's problem (S222). [Configuration 8] The system according to configuration 6 or 7, wherein the generation unit generates content including suggestions based on knowledge other than that stored in the database when it is determined that the difficulty level of the case is high (S232). [Configuration 9] The content is: Service proposal content (10) for explaining the solution provided to the customer; Contents (20) for partners who request cooperation in realizing the solutions provided to said customers; Contents (30, 40) for the company, including a proposal scenario for realizing an order for a solution to be provided to the customer and support information for securing resources necessary to realize the implementation of the solution; and a content (50) for the company that includes information on risks involved in providing a solution to the customer. [Configuration 10] the generation unit determines resources required for a solution proposed in the content based on knowledge similar to the input information; The system according to any one of configurations 1 to 9, further comprising a resource securing unit (100) for exchanging data with a resource management system (300) in order to secure the determined resources. [Configuration 11] The system according to any one of configurations 1 to 10, further comprising a learning unit (100; 140) that updates the database based on the solution provided to the customer and information associated with the solution. [Configuration 12] 9. The system according to any one of configurations 1 to 8, wherein a weight for calculating the similarity with the input information is changed based on information measured at a manufacturing site that is included in the input information. [Configuration 13] 13. The system according to claim 12, wherein the generation unit reduces the similarity of the input information when the input information includes information indicating that the information cannot be measured from the manufacturing site. [Configuration 14] A method executed by a computer (100) for supporting business negotiations with a customer (4) who wishes to provide a solution to a manufacturing site, comprising: Storing in a database knowledge that includes at least a solution provided in the past and information associated with the solution (S100, S110); Receiving input information that includes information obtained through negotiation with the customer (S20); A method comprising: generating content necessary for proposing a solution to the customer based on knowledge similar to the input information (S60).

[0167] <H. Advantages> System 1 according to the present embodiment can accumulate knowledge including in-house know-how, and support negotiations and generate necessary content required for solution business based on the accumulated knowledge. Further, System 1 can secure resources necessary for realizing the service (solution) to be proposed.

[0168] System 1 according to the present embodiment provides information necessary for providing services such as service proposal, support for conducting negotiations, various arrangements, and resource enhancement strategies by referring to the knowledge database 200.

[0169] The knowledge database 200 stores customer information, competitive information, negotiation results, in-house know-how, resource information, etc. Therefore, in-house know-how is automatically accumulated and updated. Since the knowledge database 200 is additionally learned based on the information 80 of completed cases, System 1 itself evolves autonomously. Thereby, the accuracy of the information output by System 1 can be improved.

[0170] System 1 according to the present embodiment is quantitatively determined according to a business process in which a proposal policy, etc. are predetermined in response to needs heard from the customer 4, etc. In the decision-making process, the sufficiency and difficulty level, etc. of the input information 70 are also quantitatively determined, so that more appropriate proposals, etc. can be made without depending on the skills and experience of the salesperson 2. Thereby, even a salesperson 2 with little skill and experience can ensure service quality.

[0171] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0172] 1 System, 2 Sales representative, 4 Customer, 6 Resource manager, 8 External partner company, 10 Service proposal content, 12, 32 Reason document, 14, 34 Check item document, 16, 46 Required resource document, 20 Partner response plan, 22, 52 Alert, 24, 54 Additional resource document required, 30 Proposal scenario, 40 Support information, 50 Customer response risk information, 56 Customer response risk, 60 Negotiation result, 70 Input information, 80 Completed case information, 90 Negotiation knowledge, 100 Support server, 102, 202 Processor, 104, 204 Memory, 106, 206 Storage, 108, 208 Input unit, 110, 210 Display unit, 112, 212 Network controller, 114 Interface, 120, 220 System program, 122 Support program, 124 Learning program, 130 Operation phase, 140 learning phase, 150 policy decision logic, 160 reception unit, 170 generation unit, 180 content, 200 knowledge database, 216 microphone, 218 speaker, 222 browser program, 300 resource management system, 500 terminal.

Claims

1. A system for supporting business negotiations with customers who wish to provide solutions to manufacturing sites, a database that stores knowledge including at least solutions provided in the past and information associated with the solutions; a reception unit for receiving input information including information obtained through business negotiations with the customer; A generation unit for generating content necessary to propose a solution to the customer based on knowledge similar to the input information.

2. The system according to claim 1 , wherein the generation unit outputs a message indicating that the current input information does not contain enough information about the customer's problem if there is no knowledge similar to the input information in the database regarding the customer's problem.

3. The system according to claim 2 , wherein if knowledge similar to the input information exists in the database regarding the customer's problem, the generation unit generates content for proposing a solution contained in the similar knowledge.

4. The system of claim 3, wherein if there is no knowledge in the database similar to the input information regarding the customer's problem and the input information does not contain sufficient information regarding the reason why the customer cannot solve the problem and the customer's decision-making and problem recognition, the generation unit outputs a message indicating that further interviews are needed to obtain information regarding the reason why the customer cannot solve the problem and the customer's decision-making and problem recognition.

5. The system described in claim 4, wherein the generation unit outputs a decision to withdraw in at least one of the following cases: when the reason why the problem cannot be solved for the customer and further information regarding the customer's decision-making and problem recognition cannot be added within a specified period of time; and when it is determined that the proposed solution is unlikely to be accepted based on the customer's decision-making and problem recognition.

6. The system described in claim 4, wherein if there is no knowledge in the database similar to the input information regarding the customer's problem and the input information contains sufficient information regarding the reason why the customer cannot solve the problem, as well as the customer's decision-making and problem recognition, the generation unit determines the difficulty of the case based on the countermeasures and the customer's expectations contained in the input information.

7. The system according to claim 6, wherein the generation unit generates content including a solution for the customer's problem that is an adaptation of a solution contained in knowledge similar to the input information when it is determined that the difficulty level of the case is not high.

8. The system according to claim 6 , wherein the generation unit generates content including suggestions based on knowledge other than knowledge stored in the database when the difficulty level of the case is determined to be high.

9. The content is: service proposal content to explain a solution to be provided to the customer; Content for partners requesting cooperation in realizing solutions provided to said customers; Content for the company, including a proposal scenario for realizing an order for a solution to be provided to the customer and support information for securing resources necessary to realize the implementation of the solution; The system according to any one of claims 1 to 8, further comprising content for the company that includes information on risks involved in providing a solution to the customer.

10. the generation unit determines resources required for a solution proposed in the content based on knowledge similar to the input information; The system according to any one of claims 1 to 8, further comprising a resource reserving unit for exchanging data with a resource management system in order to reserve the determined resources.

11. The system according to any one of claims 1 to 8, further comprising a learning unit that updates the database based on solutions provided to the customer and information associated with the solutions.

12. The system according to any one of claims 1 to 8, wherein the weight for calculating the similarity with the input information is changed based on information measured from a manufacturing site included in the input information.

13. The system according to claim 12 , wherein the generation unit reduces the similarity of the input information when the input information includes information indicating that information cannot be measured from a manufacturing site.

14. 1. A computer-implemented method for supporting negotiations with a customer who wishes to provide a solution to a manufacturing site, comprising: storing knowledge in a database including at least previously provided solutions and information associated with the solutions; receiving input information including information obtained through business negotiations with the customer; and generating content necessary to propose a solution to the customer based on knowledge similar to the input information.

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