Information processing device and program

Abstract

[Problem] To provide technology for assisting in making better use of personnel by utilizing the results of personality tests on other personnel. [Solution] An information processing device 1 is capable of performing personality estimation in various models using answer results from a questionnaire, image data obtained by imaging the face, image data obtained by imaging the upper body or the entire body, and genome analysis results as personal information for personality estimation. Regarding the personality of an arbitrary person among target people for whom the personality estimation was performed, a distribution identification unit 1C and a position calculation unit 1D postulate target people belonging to a group of target people which is postulated for said arbitrary person, for example an organization or a divided unit within an organization (e.g. a department), and calculate a relative position. Thereby, the personality of the arbitrary person can be understood as a relative position within the postulated group.

Description

Information Processing Apparatus and Program

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

[0002] In an organization such as a company, it is necessary to employ human resources useful to the organization and arrange the employed human resources in appropriate departments. The human resources to be employed 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, an information processing apparatus is used to assist the organization in employing the human resources to be employed, including their personalities (see, for example, Patent Document 1).

[0003] Japanese Patent Application Laid-Open No. 2001-297160

[0004] In reality, the desired personality of the human resources to be employed or the department etc. 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 in making better use of human resources.

[0006] According to the present invention, the present invention comprises: 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 the persons belonging to an organization and / or persons wishing to work for the organization as the diagnostic subjects; a plurality of personality estimation units that use the personal information acquired by the information acquisition unit to estimate the level indicating the personality of each person being diagnosed using mutually different estimation methods; a distribution identification unit that uses the level indicating the personality estimated for each person being diagnosed by the plurality of personality estimation units to identify the frequency distribution of the level indicating the personality of a plurality of persons being diagnosed belonging to each division unit assumed to be part of the organization; and a position calculation unit that calculates the relative position in the frequency distribution of the level indicating the personality of a person being diagnosed who is of interest among the diagnostic subjects, based on the frequency distribution identified for each division unit by the distribution identification unit, wherein each personality estimation unit estimates the level indicating the personality of the person being diagnosed for one or more items predetermined for each personality estimation unit. The information processing device is provided, wherein the distribution identification unit determines one level representing the personality for each person to be diagnosed based on the two or more levels representing the personality estimated by the two or more personality estimation units for each item, and then identifies the frequency distribution, and the position calculation unit calculates the relative position of the level representing the personality of the person to be diagnosed in the frequency distribution for each item.

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

[0008] This diagram 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. This diagram 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 diagram shows an example of the functional configuration implemented on the AP server, which is an information processing device according to one embodiment of the present invention. This flowchart shows an example of a questionnaire-based personality estimation process.

[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 personnel 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] The talent matching service provided is, more specifically, 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 personalities that are suited or unsuited to them. 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") whose personality characteristics are estimated through personality assessment 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 a patient terminal 2 used by the person being diagnosed and an administrator terminal 3 used by the administrator, which are information processing devices that communicate directly or indirectly with the information processing device 1. The patient 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, the most common method used by companies and other organizations is the questionnaire, where individuals are presented with a number of options and asked to select the one that best describes them. Examples of this type of personality assessment include the SPI, the Big Five personality test, and the 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 position 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 of the participant's terminal 2. Participants answer by selecting one of the options presented in the question. Participants can select an option using 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 a subject using personal information. To enable compatibility with various types of personal information, the personality estimation unit 1B is equipped with four personality estimation units 1BA to 1BD, each handling different types of personal information. The first personality estimation unit 1BA performs personality estimation using the results of a questionnaire as personal information.

[0018] Currently, other methods exist, such as the facial method, which estimates personality from the contours of the face, the shape of the facial features, and their relative positions; the skeletal method, which estimates personality from the shape of the skeleton; and the genomic method, which estimates personality from the characteristics of the genome. The second to fourth personality estimation units 1BB to 1BD correspond to these methods, respectively.

[0019] In the facial and skeletal methods, image data representing the subject becomes personal information for personality estimation. Such image data can be acquired by taking pictures with a 2D camera. Therefore, the second and third personality estimation units 1BB and 1BC perform personality estimation using the image data received from the subject terminal 2. Thus, the image data is personal information for personality estimation.

[0020] The subject can send a sample of their own cells, such as hair or blood, to the genome analysis company 4 and request genome analysis for personality diagnosis. The subject can then have the results of the genome analysis performed as a result of that request transmitted to the information processing device 1. The genome analysis company 4 can also transmit the analysis results to the information processing device 1. Upon receiving the analysis results, the fourth personality estimation unit 1BD can perform personality estimation using those results. Therefore, the genome analysis results are also personal information for personality estimation.

[0021] The estimation results from the first to fourth personality estimation units 1BA to 1BD may be limited to just one of them. However, two or more estimation results may be combined to obtain an overall estimation result.

[0022] The first to fourth personality estimation units 1BA to 1BD each estimate (evaluate) the subject's personality for each predetermined item. Some items are common to two or more personality estimation units, while others have a relatively high influence on items estimated by other personality estimation units. For example, the third personality estimation unit 1BC of the skeletal method may estimate (evaluate) the subject's personality as follows: • Cautious • Studious • Listens carefully and acts accordingly • Follows instructions • Can be inflexible • Analytical • A good leader who can bring people together

[0023] The estimation of each of these items, or similar items, is also performed in the first personality estimation unit 1BA. Therefore, it is also possible to integrate two or more estimation results to obtain an overall estimation result. The method for obtaining the overall estimation result is not particularly limited. For example, one could determine a base method and then manipulate the estimation results of each item obtained using that method based on whether the direction of the same item or related items obtained using another method matches. For example, the reliability of the estimation results of items obtained using the base method could be evaluated from the estimation results of items obtained using another method, and the estimation results of items obtained using the base method could be manipulated according to the evaluation results.

[0024] This service assumes that all employees belonging to the target organization will be included as subjects for personality estimation. Based on this assumption, the service identifies the distribution of personalities of each subject belonging to the entire target organization or to each division of the target organization, and then calculates and identifies the personality position of any one of the subjects (the HR subject) on that distribution. The distribution identification unit 1C identifies the distribution, and the position calculation unit 1D calculates the personality position of that one person. Hereafter, the division unit will be assumed to be a "department".

[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 is a diagram showing 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 facility 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 a bus 29. VRAM (video RAM) 24A is connected to the 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 the 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] ROM 22 is also a device capable of permanently storing data, such as firmware and various other data. The CPU 21 reads the firmware stored in ROM 22 into RAM 23 and executes it. Subsequently, the firmware reads the OS stored in auxiliary storage device 26 into RAM 23 and executes it. Various application programs, including some matching service applications, are read into RAM 13 by the OS and executed. The GPU 24 can execute various application programs, including some matching service applications, that are stored in auxiliary storage device 26 and read into VRAM 24A.

[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. The functional configuration is not particularly limited, and various modifications are possible.

[0038] As shown in Figure 3, the CPU 21 of the 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 tendency identification unit 220, a recommended personality identification unit 221, and a recommended assignment identification unit 222.

[0039] On the GPU 24, 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 are implemented as functional components. Artificial Intelligence (AI) is used in all of these. While such functional components are implemented on the CPU 21 and the GPU 24, the auxiliary storage device 26 has a storage area reserved for data, consisting of an estimation result storage unit 261, a departmental tendency information storage unit 262, a recommended personality information storage unit 263, and an 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 here is, for example, identification information assigned by this service to each subject for service provision, i.e., login. Even within the same department, the work content that a subject is engaged in may be divided. For example, in a sales department, the work content is usually subdivided into tasks such as actual sales work and sales administration work. For this reason, in addition to the department ID that uniquely identifies the department, the type of work content within the department is also included in the estimation result information. The method type is, for example, information representing one of the following: questionnaire method, face method, skeletal method, genome method, and comprehensive.

[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 secured for storing recommended personality information representing the personality recommended for engaging in the assumed business content, for example, for each department or for each type of business content within a department (intra-department business content type). The recommended personality information is generated, for example, by extracting subjects (role models) who have achieved high results among the subjects engaging in the assumed business content. Thereby, the recommended personality information is information including, for example, the ID of the subject who is the role model, the department ID, the type of intra-department business content, and the estimated results of each item for that subject. The estimated result of each item is extracted from the estimated result information of that subject.

[0044] The achievement information storage unit 264 is a storage area secured for storing achievement information representing the achievements achieved in the business content engaged in by each subject. The achievement information is information including, for example, the ID of the subject, the department ID, the type of intra-department business content, and achievement-specific information. The achievement-specific information is information including, for example, the content of the achievements cited by the subject, the department ID of the department to which the subject was assigned when citing the achievements, the type of intra-department business content, the date of year, month, and day when the subject cited the achievements, and the evaluation, etc. Whether the subject has cited excellent achievements can be confirmed by evaluation for each achievement.

[0045] The various data stored in each of the storage units 261 to 264 are actually read out to the RAM 23 or the VRAM 24A and processed. Also, the data transfer between the CPU 21 and the GPU 24 is actually performed via the RAM 23. The communication with the subject terminal 2 and the administrator terminal 3 is performed via the NIC 25. In FIG. 3, for the sake of convenience, these are ignored. This is the same in the following description.

[0046] Each of the units 241 to 244 implemented on the GPU 24 has the following functions. The first personality estimation unit 241 estimates the personality of the subject from the results of the implementation of the questionnaire. The second personality estimation unit 242 estimates the personality of the subject using the feature amount extracted from the face represented by the image data. The third personality estimation unit 243 estimates the personality of the subject using the feature amount extracted from the upper body or the whole body of the subject represented by the image data. The fourth personality estimation unit 244 estimates the personality of the subject using the feature amount extracted from the analysis result of the genome. Note that all of these personality estimation techniques are well-known. Therefore, a more detailed description is omitted.

[0047] Each of the units 221 to 227 implemented on the CPU 21 has the following functions. The transmission / reception processing unit 211 performs processing for the transmission and reception of various data including requests between the subject terminal 2, the administrator terminal 3, and the genome analysis company 4 (terminal). The screen generation unit 212 generates a screen to be transmitted to the subject terminal 2, the administrator terminal 3, and the genome analysis company 4 (terminal). The transmission / reception processing unit 211 enables the transmission of various requests and the display of responses, etc., by transmitting the screen generated by the screen generation unit 212 to the subject terminal 2, the administrator terminal 3, and the genome analysis company 4 (terminal). The output result example shown in FIG. 1 is arranged in the screen generated by the screen generation unit 212.

[0048] The questionnaire implementation unit 213 is for implementing a questionnaire for the subject using the screen generation unit 212. The questionnaire implementation unit 213 manages the responses of the subject to each question. After the completion of the questionnaire, the questionnaire implementation unit 213 instructs, for example, the first personality estimation unit 241 to perform personality estimation using the response results. Thereby, the first personality estimation unit 241 functions, and the personality estimation result in the questionnaire method is obtained. This estimation result is stored in the estimation result storage unit 261 secured in the auxiliary storage device 26.

[0049] The facial feature extraction unit 214 functions, for example, when the person who sent the 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 person who sent the image data instructs (requests) skeletal-based personality estimation. The skeletal feature extraction unit 215 extracts feature quantities from the upper body or the whole body of the person represented by the image data and instructs the third personality estimation unit 243 to perform personality estimation using the extracted feature quantities. 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 personnel target individual's personality among the assumed target individuals for each item. This position is expressed as a positional relationship within the entire target group (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 excellent results have been achieved 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 showing an example of a questionnaire-based personality estimation process. This process is executed, for example, when a subject operating the subject terminal 2 requests personality estimation using a questionnaire. This process itself is realized 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 the GPU 24, and the rest is executed by the CPU 21. The flowchart shown in Figure 4 is an example of the processing to be performed by the CPU 21. From this, it can be seen that the CPU 21 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 the 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. If personality estimation using a method other than the questionnaire method is requested, a similar process to the questionnaire-based personality estimation process is executed. 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, but the method of expressing the position is not particularly limited. Also, the methods of using the results of personality estimation for other personnel (subjects) are just examples, 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 for which the position of a personnel subject is calculated 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 understand the relative position of the personnel target individuals in terms of their characteristics across all of the target organizations.

[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. Target user terminal, 3. Administrator terminal, 4. Genome analysis company

Claims

1. The system comprises: 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 the persons belonging to the organization and / or persons wishing to work for the organization as the diagnostic subjects; a plurality of personality estimation units that use the personal information acquired by the information acquisition unit to estimate the level of personality of each person being diagnosed using mutually different estimation methods; a distribution identification unit that uses the level of personality estimated for each person being diagnosed by the plurality of personality estimation units to identify the frequency distribution of the level of personality of a plurality of persons being diagnosed belonging to each division unit assumed to be part of the organization; and a position calculation unit that calculates the relative position in the frequency distribution of the level of personality of a person being diagnosed who is of interest among the diagnostic subjects, based on the frequency distribution identified for each division unit by the distribution identification unit, wherein each personality estimation unit estimates the level of personality of the person being diagnosed for one or more items predetermined for each personality estimation unit. Information processing device, wherein the distribution identification unit determines one level representing personality for each person to be diagnosed based on the two or more levels representing personality estimated by the two or more personality estimation units for items in which the level of personality of the person to be diagnosed has been estimated by the two or more personality estimation units, and then identifies the frequency distribution, and the position calculation unit calculates the relative position of the level representing the personality of the person to be diagnosed in the frequency distribution for each item.

2. The information processing apparatus according to claim 1, further comprising: a recommended personality identification unit that identifies estimated levels for each item indicating the characteristics of high-performing role models for each department or type of work content within a department; and a recommended placement identification unit that identifies the placement of the person to be diagnosed based on the similarity between the estimated levels for each item indicating the characteristics of role models for each department or type of work content within a department and the estimated levels for each item indicating the characteristics of the person to be diagnosed.

3. The mutually different estimation methods include a questionnaire-based method and at least one of a face method, a skeletal method, and a genome method, and the distribution identification unit, for items in which the level of the personality of the person to be diagnosed has been estimated by the questionnaire-based method and at least one of the face method, a skeletal method, and a genome method, determines one level indicating personality for each person to be diagnosed based on two or more levels indicating personality estimated by those methods, and then identifies the frequency distribution, the information processing apparatus according to claim 1.

4. The information processing apparatus according to claim 1, wherein 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.

5. A program for causing a computer to function as an information processing device according to any one of claims 1 to 4.

6. The computer comprises: an information acquisition step in which it acquires personal information that allows for the estimation of the personality of each person being diagnosed, with at least one of the persons belonging to an organization and / or persons wishing to work for the organization being the person being diagnosed; a plurality of personality estimation steps in which the computer uses the personal information acquired in the information acquisition step to estimate the level of personality of each person being diagnosed using mutually different estimation methods; a distribution identification step in which the computer uses the level of personality estimated for each person being diagnosed in the plurality of personality estimation steps to identify the frequency distribution of the level of personality of a plurality of persons being diagnosed belonging to each division unit assumed to be part of the organization; and a position calculation step in which the computer calculates the relative position in the frequency distribution of the level of personality of a person being diagnosed who is of interest among the persons being diagnosed, based on the frequency distribution identified for each division unit in the distribution identification step, wherein in each of the personality estimation steps, the computer estimates the level of personality of the person being diagnosed for one or more items predetermined for each personality estimation step. An information processing method in which, in the distribution identification step, the computer determines one level of personality for each person to be diagnosed based on the two or more levels of personality estimated by the two or more personality estimation steps for items in which the level of personality of the person to be diagnosed has been estimated, and then identifies the frequency distribution, and in the position calculation step, the computer calculates the relative position of the level of personality of the person to be diagnosed in the frequency distribution for each item.

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