STRATEGY PLANNING SUPPORT DEVICE, COMMUNICATION SYSTEM, STRATEGY PLANNING SUPPORT METHOD, AND PROGRAM

Abstract

The purpose of the present disclosure is to provide a technology that makes it easy for even a non-expert to identify a driving force (DF), in order to support the creation of a scenario which matches the actual composition of an organization.　This strategic planning support device has: an EPU analysis unit for subjecting a word in a written social conditions examination to EPU analysis by using a word which appears frequently in a financial document of an organization as a policy classification term; an uncertainty calculation unit for calculating the uncertainty of each class analyzed by the EPU analysis unit by using the Latent Dirichlet allocation method; an association calculation unit for detecting a prescribed word which appears around the word analyzed by the EPU analysis unit in a specific class which is most uncertain according to the calculations by the uncertainty calculation unit, and calculating the degree of association of the prescribed word by using the cosine similarity thereof; a selection unit for selecting a higher specific word having a high degree of association according to the calculations by the association calculation unit to be an element on the DF coordinate axes; and an output unit for outputting the specific word selected by the selection unit.

Description

[Technical field]

[0001] The present disclosure relates to a strategy planning support device, a communication system, a strategy planning support method, and a program. [Background technology]

[0002] There are many uncertain events (hereafter referred to as "events") that could affect people's lives and business activities, such as infectious diseases and climate change. In order to develop policies and strategies to deal with such events, the impact of events is analyzed by creating possible scenarios. In particular, companies are required to analyze the impact of events on their business and disclose information as risks and opportunities, and use this information as a basis for formulating management strategies.

[0003] When creating scenarios for corporate strategy planning, it is common to investigate factors related to the subject of analysis, set two axes (DF: driving forces) that could significantly influence future outcomes, and then draw up multiple scenarios based on the DF.

[0004] Figure 11 is a conceptual diagram of scenario creation using general scenario planning. As shown in Figure 11, "diversity" is set as an element on the X-axis, with greater diversity toward the + direction and greater uniformity toward the - direction. Additionally, "connections with the community" is set as an element on the Y-axis, with stronger community connections toward the + direction and weaker community connections toward the - direction. To make effective use of scenarios, it is important to decide what to set for each element (word) on the DF coordinate axis.

[0005] Conventionally, DFs were determined manually by experts familiar with the field based on their experience, etc. (See Non-Patent Document 1.) In this example, to examine the state of a sustainable society from the perspective of lifestyles, a workshop was held by experts, DFs were selected, and scenarios related to multiple lifestyles were drawn up. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] Masahiro Kadokawa, 2014, Practical methods for "Shell-style" scenario planning, Journal of LCA Society of Japan, vol.10, pages 254-260<https: / / www.nies.go.jp / kanko / news / 28 / 28-2 / 28-2-02.html> Summary of the Invention [Problem to be solved by the invention]

[0007] However, conventional scenario creation has problems such as the need for expertise to select DF and the time required for information analysis. Furthermore, in order to apply scenario creation methods to the strategic planning of organizations such as companies, there is also the problem that in addition to knowledge about the subject of analysis, it is also necessary to reflect the situation of the company.

[0008] The present invention has been made in consideration of the above points, and aims to propose a technology that enables even non-experts to easily identify driving forces in order to support the creation of scenarios for corporate strategy planning that are in line with the actual circumstances of the company. [Means for solving the problem]

[0009] In order to solve the above problem, the invention of claim 1 is a strategy planning support device that supports strategic planning for an organization, comprising: an EPU analysis unit that performs EPU analysis on words in a social survey document by using frequently occurring words in the organization's financial statements as terms for policy classification; an uncertainty calculation unit that calculates the uncertainty of each classification analyzed by the EPU analysis unit by using a latent Dirichlet allocation; a relevance calculation unit that detects predetermined words that appear around the words analyzed by the EPU analysis unit in a specific classification with the highest uncertainty as calculated by the uncertainty calculation unit, and calculates the relevance of the predetermined words using cosine similarity; a determination unit that determines specific words with the highest relevance values ​​calculated by the relevance calculation unit as elements of each coordinate axis of a driving force; and an output unit that outputs the specific words determined as the elements by the determination unit. Effect of the Invention

[0010] As described above, the present invention has the effect of supporting the creation of scenarios for corporate strategy planning that are in line with the actual circumstances of the company, thereby enabling even non-experts to easily identify driving forces. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic diagram of a communication system. [Diagram 2] FIG. 2 is a hardware configuration diagram of a strategy planning support device and a communication terminal according to the embodiment. [Diagram 3] FIG. 2 is a functional configuration diagram of the strategy planning support device. [Figure 4] 13 is a flowchart showing a process of setting driving forces when creating possible future scenarios for corporate strategy planning. [Diagram 5] FIG. 13 is a diagram showing the breakdown of frequently used words in Company B's financial statements. [Figure 6] FIG. 13 is a diagram showing survey contents in a social situation survey document. [Figure 7]FIG. 1 is a diagram showing survey results in a social situation survey document. [Figure 8] This figure shows a breakdown of frequently occurring words in documents from Country A regarding changes in lifestyle after COVID-19. [Figure 9] FIG. 13 is a diagram showing a list of related words of EPU. [Figure 10] FIG. 2 is a conceptual diagram of scenario creation by scenario planning according to the present embodiment. [Figure 11] FIG. 1 is a conceptual diagram of scenario creation using general scenario planning. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0013] [System configuration of the embodiment] First, an outline of the configuration of a communication system according to the present embodiment will be described with reference to Fig. 1. Fig. 1 is a schematic diagram of a communication system according to an embodiment of the present invention.

[0014] 1, a communication system 1 of this embodiment is constructed by a strategy planning support device 3 and a communication terminal 5. The communication terminal 5 is managed and used by a user Y.

[0015] Furthermore, the strategy planning support device 3 and the communication terminal 5 can communicate with each other via a communication network 100 such as the Internet. The connection form of the communication network 100 may be either wireless or wired.

[0016] The strategy planning support device 3 is configured with one or more computers. When the strategy planning support device 3 is configured with multiple computers, it may be indicated as a "strategy planning support device" or a "strategy planning support system."

[0017] The strategy planning support device 3 is a device that supports strategy planning for a company by setting driving forces (DFs) used to create a scenario for strategy planning for an organization such as a company. Organizations include, in addition to companies, for example, incorporated associations, NPOs (Non-Profit Organizations), and NGOs (Non-Governmental Organizations).

[0018] The communication terminal 5 is a computer, and a notebook computer is shown as an example in Fig. 1. In Fig. 1, a user Y operates the communication terminal 5. Note that the strategy planning support device 3 may perform processing alone without using the communication terminal 5.

[0019] [Hardware configuration of the strategy planning support device and communication terminal] Next, the hardware configuration of the strategy planning support device 3 and the communication terminal 5 will be described with reference to Fig. 2. Fig. 2 is a hardware configuration diagram of the strategy planning support device and the communication terminal according to this embodiment. As shown in Fig. 2, the strategy planning support device 3 has a processor 301, a memory 302, an auxiliary storage device 303, a connection device 304, a communication device 305, and a drive device 306. The hardware components constituting the strategy planning support device 3 are connected to each other via a bus 307.

[0020] The processor 301 serves as a control unit that controls the entire strategy planning support device 3, and includes various arithmetic devices such as a CPU (Central Processing Unit). The processor 301 reads various programs onto the memory 302 and executes them. The processor 301 may include a GPGPU (General-purpose computing on graphics processing units).

[0021] The memory 302 includes a main storage device such as a read only memory (ROM) and a random access memory (RAM). The processor 301 executes various programs read onto the memory 302 to realize various functional units, which will be described later.

[0022] The auxiliary storage device 303 stores various programs and various information used when the various programs are executed by the processor 301 (such as financial statements of Company B and social situation survey documents, which will be described later).

[0023] The connection device 304 is a connection device that connects an external device (for example, a display device 310, an operation device 311) and the strategy planning support device 3.

[0024] The communication unit 305 is a communication device for transmitting and receiving various types of information to and from other units.

[0025] The drive device 306 is a device for setting the recording medium 330. The recording medium 330 here includes media that record information optically, electrically, or magnetically, such as a CD-ROM (Compact Disc Read-Only Memory), a flexible disk, a magneto-optical disk, etc. The recording medium 330 may also include semiconductor memories that record information electrically, such as a ROM (Read Only Memory), a flash memory, etc.

[0026] The various programs to be installed in the auxiliary storage device 303 are installed, for example, by setting the distributed recording medium 330 in the drive device 306 and reading out the various programs recorded in the recording medium 330 by the drive device 306. Alternatively, the various programs to be installed in the auxiliary storage device 303 may be installed by being downloaded from a network via the communication device 305.

[0027] FIG. 2 also shows the hardware configuration of the communication terminal 5. However, the only difference is that the reference numerals have changed from the 300s to the 500s, and the configuration is the same, so the description thereof will be omitted.

[0028] [Functional configuration of the strategy planning support device] Next, the functional configuration of the strategy planning support device will be described with reference to Fig. 3. Fig. 3 is a functional configuration diagram of the strategy planning support device in the embodiment of the present invention.

[0029] 3, the strategy planning support device 3 has a financial report processing unit 10, a social situation survey document processing unit 20, an uncertainty calculation unit 31, a relevance calculation unit 32, a determination unit 33, and an output unit 34. Each of these units is a function realized by an instruction from the processor 301 in FIG. 2 based on the above-mentioned program.

[0030] Furthermore, the financial report processing unit 10 has an input unit 11, a morphological analysis unit 12, and a frequent word extraction unit 13. Moreover, the social survey text processing unit 20 has an input unit 21, a morphological analysis unit 22, and an EPU analysis unit .

[0031] Of these, the input unit 11 inputs data indicating a social situation survey document from the auxiliary storage device 303 or the like. The morphological analysis unit 12 extracts words by morphologically analyzing the data of the financial statements input by the input unit 11. The frequent word extraction unit 13 extracts frequent words that appear a predetermined number of times (e.g., five times) or more by counting the same words related to the organization's current business field or future prospects extracted by the morphological analysis unit 12. For example, if the same word appears twice in the financial statements, the frequent word extraction unit 13 counts it as two times.

[0032] Furthermore, the input unit 21 inputs data indicating a social situation survey document from the auxiliary storage device 303 or the like. The morphological analysis unit 22 extracts words by morphologically analyzing the data of the social situation survey document input by the input unit 21. The EPU analysis unit 23 performs EPU analysis on the words extracted by the morphological analysis unit 22 by using the frequent words (see FIG. 5) acquired from the frequent word extraction unit 13 as terms of the Policy classification among the three classifications of the policy uncertainty index EPU (Economy, Policy, Uncertainty) (by entering them into the Policy dictionary). Note that the morphological analysis unit 12 and the morphological analysis unit 22 may be the same or different.

[0033] Here, examples of words included in "Economy" include "economy" or "business climate." Examples of words included in "Policy" include words (terms) related to company policies, such as "production," "demand," "supply," or "profit." Examples of words included in "Economy" include "opaque," "uncertain," "uncertain," and "anxiety."

[0034] Next, the uncertainty calculation unit 31 calculates the uncertainty U for each category (Economy, Policy, Uncertainty) analyzed by the EPU analysis unit 23 using Latent Dirichlet Allocation (LDA) (see Reference 1).

[0035] <Reference 1> Andres Azqueta-Gavaldon, 2017. "Developing news-based Economic Policy Uncertainty index with unsupervised machine learning", Economics Letters, Volume 158. The relevance calculation unit 32 detects specified words that appear around the words used in the EPU analysis (e.g., "production," "demand," and "IP development") in the classification of the EPU with the highest uncertainty U calculated by the uncertainty calculation unit 31, and calculates the relevance of this specified word using cosine similarity (see Reference 2).

[0036] <Reference 2> https: / / www.cse.kyoto-su.ac.jp / ~g0846020 / keywords / cosinSimilarity.html The determination unit 33 analyzes a group of words with high relevance, and determines predetermined words with high relevance as elements of each coordinate axis of the driving force.

[0037] The output unit 34 outputs, for example, each data of the word "online" and the word "moving" as elements of each coordinate axis of the driving force. Examples of the output method include transmitting the data of the words as driving forces to the communication terminal 5, displaying it, or printing it.

[0038] [Processing or Operation of the Embodiment] Next, the processing or operation of this embodiment will be described in detail with reference to Figs. 4 to 10. Fig. 4 is a flowchart showing the processing of setting driving forces when creating a scenario that may occur in the future for corporate strategy planning. Fig. 5 is a diagram showing the breakdown of frequently occurring words in Company B's financial statements. Fig. 6 is a diagram showing the survey contents in a social situation survey document. Fig. 7 is a diagram showing the survey results in a social situation survey document. Fig. 8 is a diagram showing the breakdown of frequently occurring words in a country A document regarding changes in lifestyle after COVID-19. Fig. 9 is a diagram showing a list of EPU-related words. Fig. 10 is a conceptual diagram of scenario creation by scenario planning of this embodiment.

[0039] As shown in FIG. 4, first, in response to a command from the communication terminal 5 by the user Y, the input unit 11 inputs data showing the latest financial statements of a specific organization (here, Company B in Country A) (S11). Then, the morphological analysis unit 12 extracts words by morphologically analyzing the data of the financial statements input by the input unit 11 (S12). Next, the frequent word extraction unit 13 extracts frequent words by counting the same words based on the words extracted by the morphological analysis unit 12 (S13). Specifically, the frequent word extraction unit 13 extracts frequent words that have appeared a predetermined number of times (for example, 5 times) or more by counting the same words related to the current business field or future prospects of the organization (here, Company B) extracted by the morphological analysis unit 12. For example, as shown in FIG. 5, the same word "IP development" that appeared 13 times, the same word "E-commerce" that appeared 12 times, and the same word "Country C" that appeared 7 times are extracted.

[0040] Next, the input unit 21 inputs data showing the social condition survey document shown in Figures 6 and 7 (S21). Then, the morphological analysis unit 22 extracts words by morphologically analyzing the data of the social condition survey document input by the input unit 21 (S22). Next, the EPU analysis unit 23 performs an EPU analysis on the words extracted by the morphological analysis unit 22 by using the frequent words (see Figure 5) acquired from the frequent word extraction unit 13 as terms of the Policy classification out of the three classifications of EPU (Economy, Policy, Uncertainty) (by entering them into the Policy dictionary) (S23). For example, by the EPU analysis, the number of occurrences of words for each EPU classification is obtained, as shown in the two left columns of Figure 8.

[0041] Next, the uncertainty calculation unit 31 uses Latent Dirichlet Allocation (LDA) (see Reference 1) to calculate (S31) the uncertainty U for each classification (Economy, Policy, Uncertainty) analyzed by the EPU analysis unit 23. As a result, for example, the uncertainty U is calculated for each EPU classification, as shown in the rightmost column of FIG.

[0042] Next, the relevance calculation unit 32 detects predetermined words that appear around the words used in the EPU analysis (e.g., "production", "demand", "IP development") in the specific classification of the EPU with the highest uncertainty U calculated by the uncertainty calculation unit 31, and calculates the relevance of the predetermined words using the above-mentioned cosine similarity (S32). As a result, for example, as shown in Fig. 9, the number of occurrences and the relevance are obtained for each of the predetermined words that appear around the above-mentioned surrounding words (e.g., "online", "infectious disease", "relocation") as related words of the EPU.

[0043] Next, the determination unit 33 analyzes the word group with high relevance values ​​calculated by the relevance calculation unit 32, and determines specific words with high relevance as elements of each coordinate axis of the driving force (S33). Then, the output unit 34 outputs each data of the specific words, for example, the word "online" and the word "relocation", as elements of each coordinate axis of the driving force.

[0044] As a result, as shown in Figure 10, when creating a scenario using scenario planning, "online" is set as an element on the Y axis, with the value increasing in the + direction as the number of people moving online increases, and the value increasing in the - direction as the number of people returning to offline increases. Also, "relocation" is set as an element on the X axis, with the number of people moving to the suburbs increasing in the + direction and the number of people moving to one-sided (in urban areas) increasing in the - direction. In this way, when creating a scenario using scenario planning, the word "offline" is set, which has the opposite meaning to "online," and with regard to "relocation," "one-sided" is set, which is contrasted in social life with "moving to the suburbs."

[0045] [Effects of the embodiment] As described above, according to this embodiment, the creation of a scenario that is in line with the actual situation of a company is supported, and therefore even a non-expert can easily identify the driving forces.

[0046] 〔supplement〕 The present invention is not limited to the above-described embodiment, and may have the following configurations or processes (operations). (1) The strategy planning support device 3 can be realized by a computer and a program, but this program can also be recorded on a (non-transitory) recording medium or provided via the communication network 100. (2) In the communication between the strategy planning support device 3 and the communication terminal 5, other devices (such as a server or a router) may relay data. (4) In the above embodiment, a notebook computer is shown as an example of the communications terminal 5, but this is not limited to this and may be, for example, a desktop computer, a tablet terminal, a smartphone, a smart watch, a car navigation device, a refrigerator, a microwave oven, etc. (5) At least one of the calculations performed by the uncertainty calculation unit 31 and the relevance calculation unit 32 may use a neural network. [Explanation of symbols]

[0047] 1. Communication Systems 3. Strategic planning support device 5. Communication terminals 10. Financial Report Processing Section 11 Input section 12 Morphological analysis unit (an example of a first morphological analysis unit) 13 Frequent word extraction section 20 Social Survey Document Processing Department 21 Input section 22 Morphological analysis unit (an example of a second morphological analysis unit) 23 EPU Analysis Department 31 Uncertainty Calculation Section 32 Relevance calculation unit 33 Decision Section 34 Output section

Claims

1. A strategy planning support device that supports strategic planning for an organization, comprising: an EPU analysis unit that performs EPU analysis on words in a social survey document by using frequently occurring words in the financial statements of the organization as terms of policy classification; an uncertainty calculation unit for calculating the uncertainty of each classification analyzed by the EPU analysis unit by using a Latent Dirichlet Allocation method; a relevance calculation unit that detects a predetermined word that appears around the word analyzed by the EPU analysis unit in a specific classification with the highest uncertainty calculated by the uncertainty calculation unit, and calculates the relevance of the predetermined word using cosine similarity; a determination unit that determines specific words with high relevance values ​​calculated by the relevance calculation unit as elements of each coordinate axis of a driving force; an output unit that outputs the specific word determined as the element by the determination unit; A strategy planning support device having the above structure.

2. 2. The strategy planning support device according to claim 1, The strategy planning support device has a frequent word extraction unit that counts the occurrence of the same word in the financial statements of the organization and extracts the frequent words that appear a predetermined number of times or more.

3. 3. The strategy planning support device according to claim 2, A first morphological analysis unit extracts words by performing morphological analysis on data of the financial statements of the organization; A strategy planning support device, wherein the frequent word extraction unit extracts the frequent words by counting the same words based on the words extracted by the first morphological analysis unit.

4. 4. The strategy planning support device according to claim 3, wherein the identical words are words related to a current business field or a future outlook of the organization.

5. 2. The strategy planning support device according to claim 1, a second morphological analysis unit that performs morphological analysis on data of the social survey document to extract words; The EPU analysis unit performs EPU analysis on the words in the social survey document extracted by the second morphological analysis unit, in the strategy planning support device.

6. A strategy planning support device according to any one of claims 1 to 5, a communication terminal for receiving the data of the specific word output from the strategy planning support device; A communication system having the above configuration.

7. A computer-implemented strategy planning support method for supporting strategy planning for an organization, comprising: The computer includes: an EPU analysis step of performing an EPU analysis on words in a social survey document by using frequently occurring words in the financial statements of the organization as terms of policy classification; an uncertainty calculation step for calculating the uncertainty of each classification analyzed by said EPU analysis step by using a Latent Dirichlet Allocation method; a relevance calculation step of detecting a predetermined word that appears around the word analyzed in the EPU analysis step in a specific classification having the highest uncertainty calculated in the uncertainty calculation step, and calculating the relevance of the predetermined word using cosine similarity; a determining step of determining specific words having high relevance values ​​calculated by the relevance calculation step as elements of each coordinate axis of the driving force; an output step of outputting the specific word determined as the element by the determination step; A method to support strategy planning to implement the above.

8. A program causing a computer to execute the method according to claim 7.

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