Information processing apparatus and program

Abstract

To provide an information processing apparatus and a program that can seamlessly execute a business strategy planning task and an intellectual property related task.SOLUTION: An information processing apparatus comprises: a business strategy evaluation unit that inputs an input parameter associated with an evaluation object business strategy to a learned model which is obtained by performing machine learning using a data set including the input parameter being an explanatory variable associated with success / failure for a plurality of business strategies and an objective variable indicating a business strategy success probability as teacher data, and obtains an evaluation result which includes an evaluation value indicating the business strategy success probability; and an intellectual property right analysis unit that refers to an intellectual property right database on the basis of an evaluation result output by the business strategy evaluation unit to extract an existing patent related to a business strategy of an evaluation object, and calculates an evaluation value representing a value for the extracted patent.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to an information processing device and a program capable of seamlessly carrying out business strategy planning work and intellectual property-related work. [Background technology]

[0002] Currently, many companies develop their business strategies using strategy-making methods proposed by universities, business schools, consulting companies, etc. For companies, constructing an appropriate business strategy determines the fate of the company, and a universally important issue is how to formulate an appropriate business strategy based on an analysis of the current situation or a prediction of the future.

[0003] In many cases, because strategy formulation methods require advanced knowledge and technology, business strategy formulation is provided as a service by consultants at consultation companies for a fee, and it is not easy for in-house personnel to formulate business strategies easily. In light of this situation, the inventors have proposed a business strategy formulation support device that enables strategy planners to quickly formulate high-quality strategies and enables strategy proposal adoption assessors to improve the accuracy of their decisions on whether to implement a strategy proposal (see Patent Document 1).

[0004] The business strategy planning support device described in Patent Document 1 makes it possible to search for and output parameters that are significant in a positioning strategy (highly important for differentiation from competitors) by using a trained model obtained by machine learning using as training data a data set including input parameters that are explanatory variables regarding the success or failure of multiple business strategies and a target variable that indicates the likelihood of success of the business strategies. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 7073029 Summary of the Invention [Problem to be solved by the invention]

[0006] In the process of reflecting the parameters that are identified as being important for differentiating from competitors using the technology described in Patent Document 1 and other factors in the business strategy as described above, it is extremely important to consider intellectual property rights such as patents related to the parameters in terms of obtaining the rights yourself or avoiding the rights of other companies.

[0007] Business strategy planning, which includes identifying parameters that are important for differentiation, and intellectual property-related tasks, such as obtaining intellectual property rights and evaluating the rights of other companies, are both highly specialized tasks, and it may not be easy to gather personnel capable of performing both tasks within an individual company. Even if personnel capable of performing each task are available, it may not be easy to smoothly consider the important parameters found in the business strategy planning task from the perspective of intellectual property rights.

[0008] The present invention has been made to solve the above problems, and has an object to provide an information processing device and a program that can seamlessly carry out business strategy planning work and intellectual property-related work. [Means for solving the problem]

[0009] In order to solve the above problems, the information processing device of the present invention is equipped with a business strategy evaluation unit that inputs input parameters related to the business strategy to be evaluated into a trained model obtained by machine learning using as training data a dataset including input parameters that are explanatory variables regarding the success or failure of a plurality of business strategies and a target variable that indicates the likelihood of success of the business strategy, and obtains an evaluation result including an evaluation value that indicates the likelihood of success of the business strategy, and an intellectual property analysis unit that, based on the evaluation result output by the business strategy evaluation unit, queries an intellectual property database to extract existing patents related to the business strategy to be evaluated, and calculates the value of the extracted patents if they are acquired and / or an evaluation value that represents the probability of realizing increased corporate value in relation to "strategic items that improve specific items of non-financial information and financial information."

[0010] In the present invention, the business strategy evaluation unit may include axes in the positioning strategy in the evaluation results, and the intellectual property analysis unit may query an intellectual property database using terms or patent classifications related to the axes in the positioning strategy.

[0011] In the present invention, the intellectual property analysis unit may output, for the extracted patent, the axis and coordinates in the IP landscape of the extracted patent.

[0012] In the present invention, the intellectual property analysis unit preferably identifies areas that are highly worth patenting based on the coordinates of the extracted patents in the IP landscape, and more preferably identifies blank areas within the areas that are highly worth patenting where competitor patents are sparse.

[0013] The information processing device according to the present invention may further include a patent document drafting section that generates and outputs a draft of a patent document that is highly worthy of being patented.

[0014] A program according to another embodiment of the present invention causes a computer to function as any one of the information processing devices described above. [Brief description of the drawings]

[0015] [Figure 1] 1 is a schematic diagram showing an information processing device 1 together with devices connected to the information processing device 1. FIG. [Diagram 2] 1 is a schematic diagram showing a hardware configuration of an information processing device 1. FIG. [Diagram 3] 1 is a functional block diagram of an information processing device 1. FIG. [Figure 4] FIG. 13 is a diagram showing an example of a presentation of evaluation results (scores). [Diagram 5] FIG. 13 is a diagram showing an example of a presentation of evaluation results (coordinates in a positioning strategy). [Figure 6] 4 is a flowchart showing an operation process of the information processing device 1. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] An information processing device 1 according to an embodiment of the present invention will now be described with reference to the drawings.

[0017] [System Configuration] 1 is a schematic diagram showing an information processing device 1 according to an embodiment of the present invention together with an intellectual property right database 4, an external information server 5, and a user terminal 6 connected to the information processing device 1 via a network NW. The information processing device 1 supports a user in formulating an event strategy based on information input by the user and information on the market, business environment, and the like, and provides information on intellectual property rights (e.g., patent rights, utility model rights, etc.) that contribute to the user's business strategy. The information on intellectual property rights includes, for example, information on existing patents that may be related to the business strategy, areas where intellectual property rights are highly valuable in the analysis of patent maps and IP landscapes, and draft application documents (draft specifications) for patent applications.

[0018] The intellectual property right database 4 is a database relating to intellectual property rights used by the information processing device 1. The intellectual property right database 4 may be a public database such as the Patent Information Platform (J-Platpat) or a commercial database. It may also be a database that independently accumulates data relating to intellectual property rights. The information processing device 1 queries the intellectual property right database 4 for information relating to intellectual property rights using keywords, patent classifications, etc.

[0019] The external information server 5 is an external device that provides information indicating the external environment and the like used by the information processing device 1. The information processing device 1 is configured to be able to acquire, for example, news, market information, corporate financial statement information, legal amendment information, and the like from the external information server 5.

[0020] The user terminal 6 is a terminal device used by a user of the information processing device 1. The user terminal 6 may be, for example, a computer, a mobile information terminal, or the like that can communicate with the information processing device 1 via the network NW. The user uses the user terminal 6 to input operations and information for causing the information processing device 1 to execute an evaluation, and to receive evaluation results, notifications, and the like from the information processing device 1. [Hardware configuration of information processing device]

[0021] Fig. 2 is a schematic diagram showing a hardware configuration of the information processing device 1. The information processing device 1 is realized as, for example, a computer. That is, the information processing device 1 includes a processor 101, a RAM 102, a HDD 103, a graphics processing unit 104, an input interface 105, and a network interface 106. Note that, while Fig. 2 shows an example in which the information processing device 1 is realized by one computer as a so-called stand-alone type, the information processing device 1 can also be realized by a mode in which a plurality of computers (for example, one server computer and a plurality of client computers connected to a LAN) connected to each other via a network line such as a LAN work together.

[0022] The information processing device 1 is entirely controlled by a processor 101. The processor 101 may be a multiprocessor. The processor 101 is, for example, a central processing unit (CPU), a micro processing unit (MPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a graphics processing unit (GPU), or a programmable logic device (PLD). The processor 101 may also be a combination of two or more elements of a CPU, an MPU, a DSP, an ASIC, or a PLD.

[0023] A RAM 102 (Random Access Memory) is used as a main storage device of the information processing device 1. The RAM 102 temporarily stores at least a part of an OS (Operating System) program and application programs to be executed by the processor 101. The RAM 102 also stores various data necessary for processing by the processor 101.

[0024] The HDD 103 (Hard Disk Drive) is used as an auxiliary storage device of the information processing device 1. The HDD 103 stores an OS program, an application program, and various data. Note that other types of non-volatile storage devices such as SSDs (Solid State Drives) can also be used as the auxiliary storage device.

[0025] A display device 104a is connected to the graphics processing unit 104. The graphics processing unit 104 displays an image on the screen of the display device 104a in accordance with an instruction from the processor 101. As the display device 104a, a liquid crystal display, an organic EL (Electro Luminescence) display, or the like is used.

[0026] An input device 105a is connected to the input interface 105. The input interface 105 transmits a signal output from the input device 105a to the processor 101. The input device 105a may be a keyboard or a pointing device. The pointing device may be a mouse, a touch panel, a tablet, a touch pad, a trackball, or the like.

[0027] The network interface 106 realizes communication with external devices via the network NW. The communication via the network NW by the network interface 106 may be wired communication or wireless communication. As shown in FIG. 1, an intellectual property right database 4, an external information server 5, a user terminal 6, etc. are connected to the network, and the information processing device 1 can communicate with these via the network NW. The information processing device 1 may receive input of operations and information from a user terminal instead of input using the input interface 105.

[0028] The information processing device 1 can be realized by the above hardware configuration.

[0029] [Functional blocks of information processing device 1] FIG. 3 shows a functional block diagram of the information processing device 1. The information processing device 1 includes a machine learning execution unit 11, a business strategy evaluation unit 12, an evaluation result presentation unit 13, an intellectual property right analysis unit 14, and a patent document drafting unit 15. Each of these functional blocks is realized by a processor 101 in the hardware configuration of the information processing device 1 described above executing a program stored in a RAM 102 or a HDD 103.

[0030] The machine learning execution unit 11 generates a trained model (prediction model) M for evaluating a business strategy. The trained model M takes various information that can be explanatory variables for the success or failure (win or loss) of the business as input parameters, and outputs the success or failure (win or loss) of the business. The input parameters of the trained model M may include parameters related to the external environment from the perspectives of PESTLE (Politics, Economy, Society, Technology, Legal, Ecology), parameters related to the 3C (Customer, Competitor, Company) centered on the company, and parameters related to the 4P (Product, Price, Place, Distribution, and Sales Channel, Promotion) for sales, which correspond to analysis items in various frameworks used for analyzing business strategies. In addition, one or more strategy models (e.g., types of initial strategy, mid-stage strategy, and scale strategy) applied to the business may be included in the input parameters. In addition, in order to incorporate information representing the external environment as an input parameter, information such as news may be included in the input parameters. Furthermore, these parameters may be dimensionally compressed and converted into feature quantities and used as input parameters. Specifically, the machine learning execution unit 11 may perform reinforcement learning using the square of business value maximization through investment V = (current existing business assets + source of competitiveness (unimitable advantage)) A × (business decision-making speed + human resource skills + synergy strategy accuracy with A) S as the basis of ValueNet·PolicyNet.

[0031] In addition, the output of the trained model M (i.e., the evaluation result) can be a numerical value (score) that indicates the accuracy of the business strategy (a measure of the possibility of the business succeeding (winning)), and an axis in the positioning strategy (i.e., a parameter of interest) and a coordinate on that axis. For example, the score can be a numerical value between 0 and 1 that represents the output of the trained model M, and the closer to 1, the higher the possibility of synergy with existing assets occurring, exponential change (growth) occurring, and a more advantageous capability positioning resulting in discontinuous growth and success (winning), whereas the closer to 0, the higher the possibility of failure (losing).

[0032] In addition, in order to present the coordinates of the positioning strategy, the trained model M searches for and outputs multiple (e.g., two) axes that are significant in the positioning strategy (i.e., important for transition from the current location to the destination and differentiation from competitors), and outputs the coordinates of the current location of the positioning strategy that can be taken at the moment on the output axes, the location of competitors, and the destination with a high probability of winning. In other words, it presents the conditions for creating synergy between the trends and the company's own assets and realizing innovation (a state in which exponential change (growth) occurs = synergy) through commercialization through investment as economic activity. The current location of the coordinates of the positioning strategy that can be taken at the moment can be calculated from the features of the current PESTLE / 3C / 4P. As a specific example of the axis, it is preferable to output any of the input parameters of the trained model M as an axis that is significant in the positioning strategy.

[0033] The machine learning execution unit 11 performs machine learning and re-learning of the trained model M using a data set that corresponds input parameters for various past and current business models with the success or failure of the business (a value of 1 for a successful business (win) and a value of 0 for an unsuccessful business (loss)) as training data.

[0034] The trained model M may be configured to include a decision tree regarding the relationship between input parameters (i.e., explanatory variables) and output values ​​(i.e., objective variables), and the trained model M performs decision tree learning on this decision tree. The trained model M may be configured to include multiple decision trees with different characteristics, and the final output may be determined by taking a majority vote or averaging the outputs of the multiple decision trees.

[0035] When the trained model M includes multiple decision trees, it is preferable that each (some of) the individual decision trees correspond to various frameworks used in analyzing business strategies. For example, the trained model M may be configured to include a decision tree that takes as input parameters corresponding to 3C analysis, a decision tree that takes as input parameters corresponding to 4P analysis, a decision tree that takes as input parameters corresponding to SWOT analysis, and the like, and the combined output value of these decision trees may be the final output of the trained model M. It is preferable that the trained model M also outputs the output value of each decision tree in association with the information on that decision tree.

[0036] It is preferable that the trained model M is a model in which the process leading to the predicted or estimated result can be explained and understood by humans (so-called XAI (Explainable AI)). The configuration including the decision tree described above is an example of a model in which the process leading to the predicted or estimated result can be explained and understood by humans.

[0037] The business strategy evaluation unit 12 obtains an evaluation result for the business strategy by inputting various input parameters (i.e., the same type of input parameters as those used in learning) related to the business strategy (business plan) to be evaluated to the trained model M generated by the machine learning execution unit 11. Note that the input parameters related to the business strategy input to the trained model M do not need to cover all the types used in learning, and some parameters may be missing. The business strategy evaluation unit 12 may supplement the missing input parameters and execute the evaluation. For example, the business strategy evaluation unit 12 may use a predetermined value (e.g., an average value in the industry, etc.) for the missing input parameters, or may randomly determine the values.

[0038] The evaluation result presentation unit 13 presents to the user the evaluation result obtained by the business strategy evaluation unit 12 inputting the input parameters into the trained model M. For example, as shown in FIG. 4, the evaluation result presentation unit 13 may present to the user an overall evaluation value and multiple intermediate evaluation values ​​corresponding to the framework of the business strategy as the evaluation result for the business strategy to be evaluated. When the trained model M outputs multiple evaluation values ​​corresponding to various frameworks used for analyzing the business strategy, the evaluation result presentation unit 13 may present the evaluation values ​​of the various frameworks as intermediate evaluation values ​​in a standard order in which the consultation company advances the review when evaluating the business strategy. In this way, the user can recognize at a glance how far the review of the business strategy has progressed. In addition, the evaluation result presentation unit 13 may present input parameters (explanatory variables) that have a high influence on the evaluation result, input parameters that should be improved or changed to improve the evaluation value (explanatory variables that are the main cause of the evaluation result being calculated low) and the contents of the change (for example, increase or decrease in numerical value, proposed changes to the strategy model, etc.) together with the evaluation value. For example, the business strategy evaluation unit 12 may perform an evaluation when each input parameter is changed, and may grasp the input parameters that have a high influence or that should be improved based on the change in the evaluation result (overall evaluation value or intermediate evaluation value). In this way, it is possible to easily grasp the weaknesses and improvements of the strategy. In addition, the business strategy evaluation unit 12 may repeatedly execute the evaluation when the input parameters are changed in order for a plurality of input parameters, and may identify the optimal value that maximizes the evaluation result for each input parameter. In this case, when the optimal value for one input parameter is determined, the business strategy evaluation unit 12 may use the determined optimal value in the evaluation performed by changing another input parameter thereafter. In this way, by sequentially specifying the optimal value for each input parameter, it is possible to finally specify the optimal value for all input parameters and the evaluation result that can be expected from the combination of the optimal input parameters. Then, the evaluation result presentation unit 13 may present the identified optimal value and evaluation result for each parameter to the user.

[0039] As shown in Fig. 5, the evaluation result presenting unit 13 may present a graph plotting the coordinates of the current location of the positioning strategy that can be taken at the present time on the axis included in the output of the trained model M and the coordinates of the destination with a high winning rate. The positions of competitors may also be plotted and presented on the graph. As a result, it is preferable that the strategic dimensions are reduced and the competitive landscape of AS IS and TO BE in which significant and characteristic factors are identified can be specifically grasped.

[0040] As a method for the evaluation result presentation unit 13 to present the evaluation results to the user, for example, the evaluation results may be displayed on the display device 104a. Furthermore, the evaluation result presentation unit 13 may present the evaluation results in a manner other than displaying them on the display device 104a. For example, the evaluation result presentation unit 13 may print the evaluation results as a report, or store electronic data of the report in a storage means such as the HDD 103. Furthermore, the evaluation result presentation unit 13 may send the report to the user terminal 6 or other delivery destinations by email or the like.

[0041] The intellectual property right analysis unit 14 queries the intellectual property right database 4 using the evaluation result obtained by the business strategy evaluation unit 12 inputting the input parameters into the trained model M, and extracts existing patents related to the business strategy to be evaluated. The intellectual property right analysis unit 14 may query the intellectual property right database 4, for example, by using the "axis in the positioning strategy" or a term related thereto output by the business strategy evaluation unit 12 as the evaluation result, as a keyword, or by using a patent classification related to the "axis in the positioning strategy". The intellectual property right analysis unit 14 outputs bibliographic information such as, for example, a patent number and an application number as a result of the query.

[0042] Furthermore, the intellectual property right analysis unit 14 calculates an evaluation value representing the value of the extracted patents when they are acquired and / or the probability of realizing an increase in enterprise value in relation to "strategic matters that improve specific items of non-financial information and financial information." This evaluation value may be obtained, for example, by processing the feature quantities of the patents of improvements that give an advantage over competitors, and scoring them based on the relevance to issues and problems that are likely to contribute greatly to business success. In addition, the intellectual property right analysis unit 14 may list patents that are likely to generate synergy based on a SWOT analysis of the business strategy to be evaluated, and present the list of patents to be purchased to the user. At this time, the listed patents may be displayed in association with the evaluation values ​​of the patents.

[0043] The intellectual property analysis unit 14 may output, for the extracted patents, instead of or in addition to the above evaluation values, a score indicating the degree of affinity with the business, the probability of obtaining a patent, the probability that the patent will be valuable, coordinates (axes and coordinates) in the IP landscape, etc.

[0044] The intellectual property analysis unit 14 may further identify areas that are worth patenting in the future based on the coordinates (axes and coordinates) of the extracted patents in the IP landscape, and may further identify patent blank areas within those areas (areas where competitor patents are sparse).

[0045] The patent document drafting unit 15 generates and outputs a draft of a patent document that is highly valuable to be granted rights, taking into account the high-value areas and patent blank areas identified by the intellectual property analysis unit 14. Here, the patent document refers to various documents that contribute to the patent granting process, including the specification, claims, drawings, and abstract used in the patent application. The patent document drafting unit 15 may generate a draft of the patent document, for example, by inputting terms corresponding to the high-value areas and patent blank areas identified by the intellectual property analysis unit 14 into a large-scale natural language processing model. It is particularly preferable that the patent document drafting unit 15 generates a draft of the patent document by inputting, into the large-scale natural language processing model, terms related to the strengths and opportunities in the SWOT analysis of the business strategy to be evaluated, as well as the company's own assets related to these, in addition to the terms corresponding to the high-value areas and patent blank areas identified by the intellectual property analysis unit 14. The patent document for which the patent document drafting unit 15 generates a draft document may be related to an application patent of an existing patent extracted by the intellectual property rights analysis unit 14, or it may be a new patent that is unrelated to the existing patent extracted by the intellectual property rights analysis unit 14.

[0046] Next, a description will be given of the operation of the information processing device 1. FIG 6 is a flowchart showing an operation process of the information processing device 1.

[0047] At the start of operation, the information processing device 1 generates a trained model M by performing machine learning using a large number of training data sets inputted by the machine learning execution unit 11 (step S01). Note that the information processing device 1 may add a new training data set and perform re-learning as appropriate.

[0048] Next, input parameters for the business strategy to be evaluated are input, and the business strategy evaluation unit 12 executes evaluation based on the input parameters and outputs the evaluation result of the business strategy (step S02). At this time, some or all of the input parameters may be acquired from the external information server 5 via the network NW.

[0049] Next, the evaluation result presentation unit 13 presents the evaluation result output by the business strategy evaluation unit 12 to the user as necessary (step S03). Note that, if there is no need to check the evaluation result, step S03 may be omitted. After that, using the evaluation result output by the business strategy evaluation unit 12, the intellectual property right analysis unit 14 queries the intellectual property right database 4 and extracts existing patents related to the business strategy to be evaluated (step S04). Next, the intellectual property right analysis unit 14 calculates an evaluation value representing the value of the extracted patent (step S05). In addition, the intellectual property right analysis unit 14 presents a list of patents to be purchased (step S06). In addition, the intellectual property right analysis unit 14 performs IP landscape analysis (step S07). The IP landscape analysis performed here includes determining the evaluation axis and coordinates for the extracted patent, identifying areas with high value to patent and patent blank areas for the determined axis, and the like. The above steps S05 to S07 may be performed sequentially in any order, or may be performed in parallel.

[0050] Next, the patent document drafting unit 15 generates and outputs a draft of the patent document (step S08). At this time, the patent document drafting unit 15 generates a draft of the patent document that is highly valuable for patent protection, taking into account the high-value areas and patent blank areas identified in step S07.

[0051] With the configuration and procedures described above, the information processing device 1 of this embodiment and the program that causes a computer to function as the information processing device make it possible to seamlessly carry out business strategy planning work and intellectual property-related work.

[0052] Although the present embodiment has been described above, the present invention is not limited to these examples. Furthermore, those in which a person skilled in the art appropriately adds or removes components or modifies the design of the above-described embodiment, or those in which the features of each embodiment are appropriately combined, are also included within the scope of the present invention as long as they include the gist of the present invention. [Explanation of symbols]

[0053] 1. Information processing device 11 Machine Learning Execution Department 12 Business Strategy Evaluation Department 13 Evaluation result presentation section 14 Intellectual Property Rights Analysis Department 15 Patent Document Drafting Department

Claims

1. a business strategy evaluation unit that inputs input parameters related to a business strategy to be evaluated into a trained model obtained by machine learning using a data set including input parameters that are explanatory variables related to the success or failure of a plurality of business strategies and a target variable that indicates the likelihood of success of the business strategy as training data, and obtains an evaluation result including an evaluation value that indicates the likelihood of success of the business strategy; and an intellectual property analysis unit that, based on the evaluation results output by the business strategy evaluation unit, queries an intellectual property database to extract existing patents related to the business strategy to be evaluated, and calculates an evaluation value representing the value of the extracted patents if they are acquired and / or the probability of realizing an increase in corporate value in relation to "strategic items that improve specific items of non-financial information / financial information."

2. The business strategy evaluation unit includes an axis in the positioning strategy in the evaluation result, 2 . The information processing apparatus according to claim 1 , wherein the intellectual property analysis unit queries the intellectual property database using terms or patent classifications related to axes in the positioning strategy.

3. 3 . The information processing apparatus according to claim 1 , wherein the intellectual property analysis unit outputs, for the extracted patent, axes and coordinates in an IP landscape of the extracted patent.

4. The information processing apparatus according to claim 3 , wherein the intellectual property right analysis unit identifies an area that is highly worth patenting based on coordinates in the IP landscape of the extracted patent.

5. 5. The information processing apparatus according to claim 4, wherein the intellectual property right analysis section identifies a blank area where there are few patents from competitors in an area that is highly worth patenting.

6. 3. The information processing apparatus according to claim 1, further comprising a patent document drafting unit that generates and outputs a draft of a patent document that is highly worth patenting.

7. A business strategy evaluation program that causes a computer to function as the information processing device according to claim 1 or 2.

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