Information processing device and program

Abstract

We provide technology that utilizes the results of personality assessments of other individuals to support the better utilization of talent. [Solution] The information processing device 1 can perform personality estimation using various methods, with the results of questionnaire responses, image data obtained by facial photography, image data obtained by upper body or full body photography, and genome analysis results as personal information for personality estimation. For any of the subjects whose personality has been estimated, the distribution identification unit 1C and the position calculation unit 1D calculate the relative position of that person, assuming that they belong to a group of subjects that they are expected to belong to, such as an organization or a division of an organization (such as a department). Thus, the personality of any given person can be understood as their relative position within the assumed group.

Description

Technical Field

[0006] ,

[0001] The present invention relates to an information processing apparatus and a program.

Background Art

[0002] In an organization such as a company, it is necessary to recruit useful human resources for the organization and arrange the recruited human resources in appropriate departments. The human resources to be recruited need to be determined considering not only their abilities but also their personalities. For this reason, an appropriate examination capable of personality diagnosis such as SPI is carried out, and from the diagnosis results, the organization is assisted using an information processing apparatus so that the organization can recruit the human resources to be recruited including their personalities (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In reality, the desired personality of the human resources to be recruited or the department where the human resources are to be placed is often determined by the image held by the person in charge. In order to make better use of human resources, it is considered that the results of personality diagnosis (personality estimation) in the appropriate examinations conducted on other human resources should be used more effectively. Personality diagnosis is also carried out other than in the appropriate examinations, and the types of personality diagnosis themselves are not particularly limited.

[0005] An object of the present invention is to provide a technique for using the results of personality diagnosis of other human resources and assisting to make better use of human resources.

Means for Solving the Problems

[0006] An information processing apparatus in one aspect of the present invention includes: an information acquisition unit that acquires personal information that allows for the estimation of the personality of each person being diagnosed, with at least one of a person belonging to an organization and a person wishing to work for the organization as the person being diagnosed; a personality estimation unit that estimates the personality of each person being diagnosed using the personal information acquired by the information acquisition unit; a distribution identification unit that identifies the distribution of the personalities of the persons being diagnosed belonging to each division unit of the organization assumed to be divided into division units, using the personalities estimated for each person being diagnosed by the personality estimation unit; and a position calculation unit that calculates the personality position of a person being diagnosed who is of interest among the persons being diagnosed, within the division unit, based on the distribution identified for each division unit by the distribution identification unit. [Effects of the Invention]

[0007] This invention allows for the use of personality assessment results from other individuals to support the better utilization of human resources. [Brief explanation of the drawing]

[0008] [Figure 1] This figure illustrates an information processing device according to one embodiment of the present invention, and an overview of the personnel matching service provided by the information processing device. [Figure 2] This figure shows an example of the hardware configuration of an AP server, which is an information processing device according to one embodiment of the present invention. [Figure 3] This figure shows an example of a functional configuration implemented on an AP server, which is an information processing device according to one embodiment of the present invention. [Figure 4] This flowchart shows an example of a personality estimation process using a questionnaire. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. Figure 1 is a diagram illustrating an overview of an information processing device according to one embodiment of the present invention and a human resource matching service provided by the information processing device.

[0010] Information Processing Device 1 is installed to provide a talent matching service that supports personnel or managers in order to make human resources tasks easier and more appropriate for organizations such as companies. This information processing device 1 is installed, for example, within the company, or implemented using a cloud service. Hereafter, organizations that use the talent matching service will be referred to as "Target Organizations" to distinguish them.

[0011] More specifically, the talent matching service provided is designed to help target organizations more reliably secure suitable personnel, or to more easily assign employees to more appropriate positions within those organizations. Since talent acquisition is also a target of support, users include individuals outside the target organizations. These individuals are primarily those who wish to work for the target organizations (hereinafter referred to as "applicants"). Users within the target organizations are primarily employees, human resources personnel responsible for their personnel, and managers who oversee employees. For convenience, users within the target organizations other than employees will be collectively referred to as "managers" from now on. The talent matching service provided will be hereinafter referred to as "this service." This service is only available to registered users, that is, only to logged-in users.

[0012] The types of work in which people can perform at their best depend largely on their personality. In other words, certain tasks have personality traits that make them more or less suitable. Furthermore, personality compatibility with employees belonging to organizational divisions (divisions based on assigned tasks and responsibilities) can also be an important factor. For this reason, this service supports more appropriate responses to personnel based on personality. Accordingly, the subjects of the personality assessment (hereinafter abbreviated as "subjects") are mainly employees and those who wish to participate. Managers with personnel authority are provided with information that enables them to respond to personnel more appropriately.

[0013] Therefore, Figure 1 shows the subject terminal 2, used by the person being diagnosed, and the administrator terminal 3, used by the administrator, as terminals that are information processing devices that communicate directly or indirectly with the information processing device 1. The subject terminal 2 is, for example, a desktop PC (Personal Computer) to which a display 2A, keyboard 2B, mouse 2C, and camera 2D are connected. The administrator terminal 3 also has, for example, a display and keyboard installed or connected to it.

[0014] Personality assessments, or methods for estimating personality, can be broadly categorized into several types. Currently, many organizations, such as companies, use questionnaires where individuals select the option that best describes them from a set of choices presented for multiple questions. Examples of this type of personality assessment include SPI, the Big Five personality test, and MBTI (Myers-Briggs Type Indicator).

[0015] In Figure 1, the information processing device 1 includes, as an example of its functional configuration, a questionnaire implementation unit 1A, a personality estimation unit 1B, a distribution identification unit 1C, and a location calculation unit 1D. The questionnaire implementation unit 1A is used to conduct a questionnaire with subjects for personality diagnosis, i.e., personality estimation, in order to obtain personal information for personality estimation.

[0016] The survey questions are displayed on the display 2A via the participant's terminal 2. Participants answer by selecting one of the options presented in the question. Participants can select an option using either the keyboard 2B or the mouse 2C. The responses are managed by the survey administration unit 1A.

[0017] The personality estimation unit 1B estimates the personality of the target person using personal information. In order to be compatible with various types of personal information, the personality estimation unit 1B includes first to fourth personality estimation units 1BA to 1BD with different types of target personal information. The first personality estimation unit 1BA estimates personality using the implementation results of a questionnaire as personal information.

[0018] Currently, there are also other methods such as a face method that estimates personality from the facial contour, part shapes, their positional relationships, etc., a skeleton method that estimates personality from the shape of the skeleton, and a genome method that estimates personality from genomic characteristics. The second to fourth personality estimation units 1BB to 1BD correspond to those methods respectively.

[0019] In the face method and the skeleton method, the image data representing the target person becomes the personal information for personality estimation. Such image data can be obtained by shooting with a camera 2D. Therefore, the second and third personality estimation units 1BB and 1BC perform personality estimation using the image data received from the target person terminal 2. From this, the image data is the personal information for personality estimation.

[0020] The target person can send their own cells, such as hair or blood, etc. as samples to the genome analysis company 4 and request a genome analysis for personality diagnosis. The results of the genome analysis performed based on that request can be sent by the target person themselves to the information processing device 1. The analysis results can also be sent from the genome analysis company 4 to the information processing device 1. When the information processing device 1 receives the analysis results, the fourth personality estimation unit 1BD can perform personality estimation using the analysis results. From this, the results of the genome analysis are also the personal information for personality estimation.

[0021] Regarding the estimation results by the first to fourth personality estimation units 1BA to 1BD, only one of them may be made valid. However, it is also possible to integrate two or more estimation results to obtain a comprehensive estimation result.

[0022] The first to fourth personality estimation units 1BA to 1BD estimate (evaluate) the personality of the target person for each predetermined item. Among the items, there are those that are common to two or more personality estimation units, those that have a relatively high influence on the items estimated by other personality estimation units, and so on. For example, when the third personality estimation unit 1BC of the skeletal method estimates (evaluates) the personality of the target person as follows. · Prudent · Studious · Listen carefully to what is said and then act · Keep one's word · There are parts that lack flexibility · Have analytical ability · A leader type who is good at gathering people

[0023] The estimation of such each item or similar items is also performed by the first personality estimation unit 1BA. From this, it is also possible to integrate two or more estimation results to obtain a comprehensive estimation result. The method of obtaining the comprehensive estimation result is not particularly limited. As an example of the method, for example, a base method is determined, and depending on whether the directionality of the same item or related items obtained by another method matches the estimation result of each item obtained by that method, the estimation result of the item in the base method is manipulated. For example, from the estimation result of the item obtained by another method, the reliability of the estimation result of the item obtained by the base method is evaluated, and the estimation result of the item obtained by the base method is manipulated according to the evaluation result.

[0024] In this service, it is assumed that all employees belonging to the target organization are made to have their personalities estimated as target persons. Based on this assumption, in this service, for the entire target organization or for each divided unit of the target organization, the distribution of the personalities of each target person belonging to it is specified, and on that distribution, the personality position of any one person (personnel target person) among the target persons is calculated and specified. The distribution specifying unit 1C specifies that distribution, and the position calculating unit 1D calculates the personality position of that one person. Hereinafter, it is assumed that the "department" is the divided unit.

[0025] The results of this personality-based positioning calculation can be viewed by the administrator at any time. The example output shown in Figure 1 presents the estimated results for each item of the subject, along with the Japanese average and the test average, in a table format for easy review. The test average is the average for all subjects in the entire organization or in any single department. In organizations with multiple departments, it is often the average for any single department. Therefore, unless otherwise specified, the test average refers to the average for any single department. Such calculation results may be made available for viewing by the subjects.

[0026] In the example output shown in Figure 1, the estimated results for each item of the subject are represented by a numerical value between 0 and 100. In the estimated results for each item of the subject, two different shaded areas are used for item A and item C. This shading is done based on the calculated position of each item. Shading is applied to the estimated result of item A if, for example, it falls within the top 5%. Shading is applied to the estimated result of item C if, for example, it falls within the bottom 20%. In this embodiment, the position of the estimated result for each item is made visible by the presence or absence of shading and the type of shading.

[0027] Based on these output results, administrators can check the personality relationships of personnel targets within any given department, item by item. By utilizing the results of personality estimations (personality assessments) for other targets, the personality of the personnel target can be evaluated relatively.

[0028] For example, in a department with high performance, unless the high performance is due to individual factors, it can be assumed that the department has a group of employees with personalities suited to the work. Therefore, it can be considered desirable to assign personnel with similar personalities to the majority of employees to that department. On the other hand, in a department with low performance, unless the low performance is due to individual factors, it can be assumed that there are few or no personnel with personalities suited to the work of that department. Therefore, it can be considered desirable to assign personnel with different personalities to that department.

[0029] Therefore, managers can more appropriately and easily identify suitable candidates from among applicants for departments that are understaffed or underperforming. Employees can more easily identify departments that are more suitable for them. Therefore, presenting the estimated personality of a personnel candidate in conjunction with the results of personality assessments (personality tests) for other individuals is effective in supporting better utilization of human resources. This result also has the effect of improving work efficiency for managers.

[0030] Hereafter, embodiments of the present invention will be described in detail with further reference to the drawings. Figure 2 shows an example of the hardware configuration of an AP server, which is an information processing device according to one embodiment of the present invention. This hardware configuration example is just one example and is not particularly limited. For example, only one CPU (Central Processing Unit) 21 and one GPU (Graphics Processing Unit) 24 are shown, but multiple units of each may be installed.

[0031] Information processing device 1 is implemented, for example, as an AP server installed by the target organization within its management facilities for the purpose of providing this service, or installed using a cloud service. Therefore, the AP server is assigned the code "1". For this reason, "information processing device" will also be referred to as "AP server" from now on. It can communicate with target terminals 2 used by target users (e.g., employees) and administrator terminals 3 via network 30. Network 30 is, for example, a LAN (Local Area Network) or a composite network including the Internet.

[0032] As shown in Figure 2, AP Server 1 has a configuration in which a CPU 21, ROM (Read Only Memory) 22, RAM (Random Access Memory) 23, GPU 24, NIC (Network Interface Card) 25, auxiliary storage device 26, media drive 27, and I / FC (Interface Controller) group 28 are connected to bus 29. VRAM (video RAM) 24A is connected to GPU 24.

[0033] The auxiliary storage device 26 is a device capable of permanently storing data, such as a hard disk drive or an SSD (Solid State Drive). The media drive 27 is a device on which the recording medium 27A can be attached and detached. The media 27A is such as a CD (Compact Disc)-ROM, DVD-ROM, DVD-RAM, etc.

[0034] The I / FC group 28 includes various I / FCs that enable communication with various peripheral devices, including the input device 28A and the display device 28B, or with external devices. The input device 28A and the display device 28B are temporarily connected to the I / FC group 28 as needed. The auxiliary storage device 26 stores the OS (Operating System) and various application programs that run on that OS as programs. Among these various application programs is an application program that enables the provision of this service. Hereafter, this application will be referred to as the "matching service app".

[0035] ROM22 is also a device capable of permanently storing data, such as firmware and various other data. The CPU21 reads the firmware stored in ROM22 into RAM23 and executes it. Subsequently, the firmware reads the OS stored in auxiliary storage device 26 into RAM23 and executes it. Various application programs, including some matching service applications, are read into RAM13 by the OS and executed. The GPU24 can execute various application programs, including some matching service applications, that are stored in auxiliary storage device 26 and read into VRAM24A.

[0036] The matching service application may be stored on media 27A and distributed. If network 30 is a composite network, it may also be distributed via network 30. When distributed via network 30, the matching service application should be stored on a recording medium that can be directly or indirectly accessed by the information processing device distributing it. In other words, the storage medium may be directly or indirectly accessible by another information processing device that can communicate with the information processing device distributing it.

[0037] Figure 3 shows an example of a functional configuration implemented on an AP server, which is an information processing device according to one embodiment of the present invention. This example of a functional configuration is mainly implemented by having the CPU 21 and GPU 24 execute different parts of the matching service application, respectively. Note that the functional configuration is not particularly limited, and various modifications are possible.

[0038] As shown in Figure 3, the CPU 21 of AP Server 1 is functionally configured to include a transmission / reception processing unit 211, a screen generation unit 212, a questionnaire implementation unit 213, a face feature extraction unit 214, a skeletal feature extraction unit 215, a genome feature extraction unit 216, a comprehensive estimation unit 217, a target result extraction unit 218, a position calculation unit 219, a departmental trend identification unit 220, a recommended personality identification unit 221, and a recommended assignment identification unit 222.

[0039] On the GPU24, the following functional configurations are implemented: a first personality estimation unit 241, a second personality estimation unit 242, a third personality estimation unit 243, and a fourth personality estimation unit 244. All of these utilize AI (Artificial Intelligence). While this functional configuration is realized on the CPU 21 and GPU 24, the auxiliary storage device 26 has a data storage area reserved for the estimation result storage unit 261, the departmental trend information storage unit 262, the recommended personality information storage unit 263, and the achievement information storage unit 264.

[0040] The estimation result storage unit 261 is a storage area reserved for storing estimation result information that represents the results of personality estimation for each subject. The estimation result information includes, for example, the subject's name, an ID (IDentification) that uniquely identifies the subject, a department ID, the type of work content within the department, the estimated implementation date and time, the method type, and the estimation results for each item. The ID used here refers to identification information assigned by this service to each user for service provision purposes, i.e., for login. Even within the same department, the specific tasks performed by the individuals involved may be categorized. For example, in a sales department, tasks are typically subdivided into areas such as actual sales activities and sales administration. Therefore, in addition to a department ID that uniquely identifies a department, the type of work performed within that department is included in the estimation results. The method type represents one of the following: questionnaire method, facial method, skeletal method, genome method, and comprehensive method.

[0041] The departmental tendency information storage unit 262 is a storage area reserved for storing departmental tendency information that represents the personality tendencies of the individuals assigned to each department. Departmental tendency information includes, for example, department ID, type of work, type of work content within the department, specific date and time, and the results of the identification of each item.

[0042] The results for each item include, for example, an estimated mean or an estimated median. Even within the same department, the tasks performed by the subjects may be categorized as described above. Therefore, in this embodiment, departmental trend information is generated and stored for each department and each type of task.

[0043] The recommended personality information storage unit 263 is a storage area reserved for storing recommended personality information that represents the personality traits recommended for engaging in a given job, for example, for each department or for each job (type of job within a department). The recommended personality information is generated by extracting, for example, high-performing individuals (role models) among those engaged in the given job. As a result, the recommended personality information includes information such as the ID of the role model, department ID, type of job within the department, and the estimated results for each item for that individual. The estimated results for each item are extracted from the estimated result information of that individual.

[0044] The results information storage unit 264 is a storage area reserved for storing results information that represents the results achieved by each individual in the work they are engaged in. The results information includes, for example, the individual's ID, department ID, type of work within the department, and results-specific information. The results-specific information includes, for example, the content of the results achieved by the individual, the department ID of the department to which they were assigned when the results were achieved, the type of work within the department, the date the results were achieved, and the evaluation. Whether or not an individual has achieved outstanding results can be confirmed by evaluation for each result.

[0045] The various data stored in each memory unit 261-264 are actually read out and processed in RAM 23 or VRAM 24A. Data transfer between CPU 21 and GPU 24 is also actually performed via RAM 23. Communication with the user terminal 2 and administrator terminal 3 is performed via NIC 25. These are conveniently ignored in Figure 3. This will also be the case in subsequent explanations.

[0046] The parts 241-244 implemented on GPU24 have the following functions. The first personality estimation unit 241 estimates the personality of the subject based on the results of the questionnaire. The second personality estimation unit 242 estimates the personality of the subject using features extracted from the face represented by the image data. The third personality estimation unit 243 estimates the personality of the subject using feature quantities extracted from the subject's upper body or whole body represented by the image data. The fourth personality estimation unit 244 estimates the subject's personality using features extracted from the genome analysis results. These personality estimation techniques are all well-known. Therefore, a more detailed explanation will be omitted.

[0047] The parts 221 to 227 implemented on the CPU 21 have the following functions. The transmission / reception processing unit 211 performs processing for sending and receiving various data, including requests, between the target terminal 2, the administrator terminal 3, and the genome analysis company 4 (or its terminal). The screen generation unit 212 generates screens to be sent to the target terminal 2, the administrator terminal 3, and the genome analysis company 4 (or its terminal). The transmission / reception processing unit 211 enables the sending of various requests and the display of responses by sending the screens generated by the screen generation unit 212 to the target terminal 2, the administrator terminal 3, and the genome analysis company 4 (or its terminal). The example output result shown in Figure 1 is placed within the screen generated by the screen generation unit 212.

[0048] The survey implementation unit 213 uses the screen generation unit 212 to conduct a survey with the target individuals. The survey implementation unit 213 manages the responses of the target individuals to each question. After the survey is completed, the survey implementation unit 213 instructs the first personality estimation unit 241 to perform personality estimation using the response results, for example. As a result, the first personality estimation unit 241 functions and obtains personality estimation results using the survey method. These estimation results are stored in the estimation result storage unit 261 reserved in the auxiliary storage device 26.

[0049] The facial feature extraction unit 214 functions, for example, when a person who has sent image data instructs (requests) a facial-based personality estimation. The facial feature extraction unit 214 extracts features from the face represented by the transmitted image data and instructs the second personality estimation unit 242 to perform personality estimation using the extracted features. As a result, the second personality estimation unit 242 functions and obtains the facial-based personality estimation result.

[0050] The skeletal feature extraction unit 215 functions, for example, when the subject who has sent the image data instructs (requests) skeletal-based personality estimation. The skeletal feature extraction unit 215 extracts features from the subject's upper body or whole body represented by the image data and instructs the third personality estimation unit 243 to perform personality estimation using the extracted features. As a result, the third personality estimation unit 243 functions and obtains the personality estimation result using the skeletal method.

[0051] The genome feature extraction unit 216 functions, for example, when a subject who has sent genome analysis results instructs (requests) genome-based personality estimation, or when genome analysis results are received from genome analysis company 4. The genome feature extraction unit 216 extracts features from the genome analysis results and instructs the fourth personality estimation unit 244 to perform personality estimation using the extracted features. As a result, the fourth personality estimation unit 244 functions and obtains genome-based personality estimation results.

[0052] As described above, in this embodiment, personality estimation can be performed using multiple methods. Therefore, if a personality estimation method is instructed, there is a possibility that results from other personality estimation methods already exist. The integrated estimation unit 217 is designed to address this possibility. For this purpose, the integrated estimation unit 217 functions after the results of personality estimation using the instructed method have been obtained.

[0053] The comprehensive estimation unit 217 extracts data with the same ID from the estimation result information stored in the estimation result storage unit 261 by searching using the ID of the subject for whom the personality estimation result has been obtained. After extraction, the comprehensive estimation unit 217 further extracts only the valid data from the extracted estimation result information. In cases where multiple pieces of estimation result information obtained using the same method exist, only one of them is extracted, for example, the most recent one with the latest date and time.

[0054] If only one estimation result is ultimately extracted, the comprehensive estimation unit 217 does not generate any new estimation result information. However, if multiple estimation result information exists, the comprehensive estimation unit 217 may, as described above, determine a base method, evaluate the estimation results of each item obtained using that method using the estimation results of items obtained using other methods, and perform operations according to the evaluation results. After performing such operations as necessary, the estimation results of each item are newly stored in the estimation result storage unit 261 as estimation result information where the method type is comprehensive.

[0055] The target result extraction unit 218 extracts the necessary estimated result information from the estimated result storage unit 261. For example, this extraction is performed by specifying conditions that include at least the department ID and the type of work content within the department. These conditions are intended for situations such as when an administrator is considering where to assign a target person.

[0056] The position calculation unit 219 assumes the target individuals of each estimated result information extracted by the target result extraction unit 218, and calculates the position of the personality traits of the assumed target individuals for each item. This position is expressed as a positional relationship within the entire group of target individuals (e.g., within the top 5), or as a standard score, etc. By calculating such positions, shading can be applied as shown in the example output result in Figure 1.

[0057] The departmental trend identification unit 220 identifies the personality tendencies of the target individuals by department and by type of work content within each department, generates departmental trend information using the identification results, and stores the generated departmental trend information in the departmental trend information storage unit 262. The personality tendencies to be identified are, for example, the average of each item, or the desirable values ​​of each item for performing the work. The desirable values ​​of each item can be estimated by regression analysis or the like.

[0058] This kind of departmental trend information is useful for managers in identifying the most suitable department for a given employee. This is because it makes it easier and more appropriate to assign employees with personalities that are considered to match the overall personality tendencies of the employees in each department. As a result, for example, it becomes easier and more appropriate to assign an employee who is in a mentally vulnerable state to a department that is more suitable for them.

[0059] The recommended personality identification unit 221 identifies, for example, individuals who have achieved excellent results among those engaged in the specified tasks for each department and each type of work content within a department, and generates the recommended personality information using the identified individuals as role models. This recommended personality information is generated using the estimated result information of the identified individuals. The generated recommended personality information is stored in the recommended personality information storage unit 263. Verification of whether or not an individual has achieved excellent results is performed by referring to the results information stored in the results information storage unit 264.

[0060] The recommended placement identification unit 222 identifies placements that are considered appropriate for the personnel target designated by the administrator. Placement identification may be performed, for example, by calculating the similarity between the estimated results of each item represented by the estimated personality information stored in the recommended personality information storage unit 263 and the estimated results of each item for the personnel target. The similarity may be, for example, the difference between them, or the similarity obtained by considering the estimated results of each item as a vector. When recommending placements where there are personnel with a high similarity, personnel who are suitable as role models for the personnel target can also be recommended to the personnel target.

[0061] Figure 4 is a flowchart illustrating an example of a questionnaire-based personality estimation process. This process is executed, for example, when a subject operating subject terminal 2 requests personality estimation using a questionnaire. This process itself is implemented by the execution of the matching service application described above. Next, we will refer to Figure 4 and explain this process in detail.

[0062] As described above, part of the matching service application is executed by GPU24, and the rest is executed by CPU21. The flowchart shown in Figure 4 is an example of the processing to be executed by CPU21. Therefore, CPU21 is the main entity that executes the processing.

[0063] First, in step S11, the CPU 21 conducts a questionnaire, sequentially presenting the questionnaire questions and answer choices to the subject. In step S12, which follows the completion of the questionnaire, the CPU 21 instructs the system to perform personality estimation using the answers to each question. This instruction activates the first personality estimation unit 241, which then obtains the results of the personality estimation using the questionnaire method.

[0064] In the following step S13, the CPU 21 determines whether there are other personality estimation results for the subject who answered the questionnaire. If the subject had undergone personality estimation using another method, the estimation result information obtained using that other method is stored in the estimation result storage unit 261. In this case, the determination in step S13 is YES and the process proceeds to step S14. Otherwise, the determination in step S13 is NO and the process proceeds to step S15.

[0065] In step S14, the CPU 21 generates and saves new estimation result information by integrating the already existing estimation result information. In the following step S15, the CPU 21 determines whether the subject is an employee or not. If the subject is an employee, the determination in step S15 is YES and the process proceeds to step S16. If the subject is a volunteer, the determination in step S15 is NO and the process proceeds to step S19.

[0066] If the subject is an employee, they will be assigned to one of the departments. As a result, the content of at least one of the departmental tendency information and estimated personality information generated in that department may change based on the personality estimation results. Therefore, steps S16 to S18 are performed to address such possibilities.

[0067] First, in step S16, the CPU 21 extracts estimated result information, identified by the department to which the subject belongs and the type of work performed (type of work within the department), from the estimated result storage unit 261 as the target result. In the following step S17, the CPU 21 uses the extracted estimated result information to generate new departmental trend information and stores the generated departmental trend information in the departmental trend information storage unit 162. In the subsequent step S18, the CPU 21 identifies subjects who have achieved outstanding results among those performing the same work in the department to which the subject belongs, and generates recommended personality information. The generated recommended personality information is stored in the recommended personality information storage unit 263. Note that recommended personality information may not be generated.

[0068] In this embodiment, the personality estimation process also updates information that may have different content as needed. Therefore, departmental tendency information and recommended personality information are always kept up-to-date.

[0069] In step S19, following step S18, the CPU 21 calculates the subject's position within the personality distribution represented by each estimated result information extracted in step S16. After calculating the position, the questionnaire-based personality estimation process ends. Even when personality estimation using methods other than questionnaires is requested, the same processing as the questionnaire-based personality estimation process described above is performed. Therefore, regardless of the method used for personality estimation, departmental tendency information and recommended personality information are always kept up-to-date.

[0070] In this embodiment, the position of a personnel subject is indicated by their rank in each item representing the assumed personality space, or by an index (standard score) representing that rank; however, the method of expressing the position is not particularly limited. Furthermore, the methods for using the results of personality estimation for other personnel (subjects) are also not particularly limited, and various modifications are possible. The method used for personality estimation is also not particularly limited. When supporting multiple methods, there are no particular limitations on how the results of personality estimation for each method are handled. The group of subjects used to calculate the position of a personnel subject is not limited to an organization or a division of that organization. It is also possible to assume a hypothetical group of subjects and calculate the position of the personnel subject.

[0071] Furthermore, in this embodiment, both applicants who wish to work for the target organization and employees currently working for the target organization are considered targets, but it is also possible to consider only one of them as the target. Also, there may be more than one target organization. The division units, such as departments, may also be groups of division units within multiple target organizations where the work content is the same or nearly the same. When multiple target organizations are assumed in this way, it becomes possible to relatively understand the position of the personnel target individuals in terms of their characteristics across all of the target organizations. [Explanation of symbols]

[0072] 1. Information processing device (AP server), 1A. Questionnaire implementation unit, 1B. Personality estimation unit, 1BA. First personality estimation unit, 1BB. Second personality estimation unit, 1BC. Third personality estimation unit, 1BD. Fourth personality estimation unit, 1C. Distribution identification unit, 1D. Location calculation unit, 2. Participant terminal, 3. Administrator terminal, 4. Genome analysis company

Claims

1. An information acquisition unit acquires personal information that allows for the estimation of the personality of each individual, with at least one of the following being individuals belonging to an organization and individuals wishing to work for the said organization as the individuals to be assessed. A personality estimation unit uses the personal information acquired by the information acquisition unit to estimate the personality of each person being diagnosed, A distribution identification unit uses the personality estimated for each person being diagnosed by the personality estimation unit to identify the distribution of the personalities of the persons being diagnosed that belong to each division unit of the organization assumed to be part of the organization, A position calculation unit calculates the position of the personality of the personnel subject who is of interest among the persons to be diagnosed, based on the distribution identified for each division unit by the distribution identification unit, An information processing device equipped with the following features.

2. The personality estimation unit estimates the personality of the person to be diagnosed for each predetermined item, The position calculation unit calculates the position of the personality of the person being represented in the distribution for each item. The information processing apparatus according to claim 1.

3. The division unit in which the position is calculated is one of the division unit to which the person subject to personnel matters belongs, and the division unit that is a candidate for the person subject to personnel matters to be assigned. The information processing apparatus according to claim 1 or 2.

4. In an information processing device, At least one of the persons belonging to the organization and the persons wishing to work for the said organization will be selected as subjects for diagnosis, and for each of the said subjects, personal information that allows for the estimation of the said subject's personality will be obtained. Using the acquired personal information, the personality of each person to be diagnosed is estimated. Using the personality estimated for each person to be diagnosed, the distribution of the personalities of the persons to be diagnosed belonging to each division unit of the organization assumed to exist within the organization is identified. Based on the distribution identified for each division unit, the personality position of the personnel subject who is of interest among the persons to be diagnosed is calculated within the division unit. A program that executes a process.

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