JP7830410B2 - Personnel reception system and reception program - Google Patents

Description

This disclosure relates to a human resources computer system and computer programs.

Patent Document 1 discloses a system that collects data such as the percentage of female managers and outputs information based on that data.

Japanese Patent Publication No. 2021-9696

In recent years, the disclosure of human capital information has been required to realize effective human capital management. Examples of human capital information that should be disclosed include several indicators, such as the percentage of female managers. The percentage of female managers is defined, for example, as the proportion of female managers among the total number of managers in a given company.

To disclose human capital information, it is desirable to derive human capital indicators from the HR data held by companies. However, HR data is not always structured in a format suitable for deriving human capital indicators. For example, HR data may include employee gender, job titles, and qualifications within the company, but it can be difficult to automatically derive human capital indicators such as the percentage of female managers from this data.

For example, if a system attempts to automatically calculate the percentage of female managers, it needs to be able to identify, at a minimum, those in management positions among the individuals included in the personnel data. However, personnel data does not always contain data that directly indicates whether someone is in a management position. For instance, personnel data may contain data indicating each person's job title or professional qualification, but since job titles and professional qualifications vary from company to company, it is difficult to identify whether someone is in a management position based solely on their job title or qualification. In particular, a job title with the same name may be a management position in one company but not in another. In this case, it is extremely difficult for a system to identify whether someone is in a management position based on their job title or professional qualification.

Furthermore, when a system attempts to automatically calculate the percentage of female managers, it needs to identify women from the personnel data. While personnel data may generally include gender information, in some cases, identifying "women" when calculating the percentage of female managers can be difficult. That is, in recent years, multiple genders are sometimes used, considering not only legal gender but also gender identity. Therefore, the gender (types and number) in personnel data can vary from company to company. Consequently, it can be difficult for a system to uniquely identify "women" when calculating the percentage of female managers based solely on the gender in the personnel data.

Furthermore, the fact that data values for personnel information such as job title, qualifications, and gender differ from company to company, and that the same data values can have different meanings, makes it difficult to calculate human capital indicators that span multiple companies. Examples of human capital indicators that span multiple companies include the human capital indicators for an entire group of companies. Another example of human capital indicators that span multiple companies is the statistical value (e.g., the average) of human capital indicators for multiple companies.

Therefore, resolving any of the above difficulties is desirable.

One aspect of this disclosure is a human resources computer system. The system is configured to display a settings screen for setting mapping data that corresponds data values included in a company's human resources data to data categories for calculating the company's human capital indicators; to accept an operation to set the mapping data; to save the mapping data to a storage device; to retrieve indicator calculation data corresponding to the data categories for calculating the human capital indicators from the human resources data based on the mapping data stored in the storage device; to calculate the company's human capital indicators from the indicator calculation data; and to display the company's human capital indicators.

Another aspect of this disclosure is a computer program. The program displays a settings screen for setting mapping data that corresponds data values included in a company's personnel data to data categories for calculating the company's human capital indicators; accepts an operation to set the mapping data; saves the mapping data to a storage device; retrieves indicator calculation data corresponding to the data categories for calculating the human capital indicators from the personnel data based on the mapping data stored in the storage device; calculates the company's human capital indicators from the indicator calculation data; and displays the company's human capital indicators.

Further details will be described in the embodiments below.

Figure 1 is a diagram showing the configuration of the personnel computer system. Figure 2 shows an example of a display screen for aggregated human capital indicators. Figure 3 is an explanatory diagram of the drill-down display. Figure 4 shows an example of a company-wide view. Figure 5 is a block diagram showing the calculation method for the index. Figure 6 shows an example of personnel data. Figure 7 shows an example of a mapping screen. Figure 8 shows an example of a mapping screen. Figure 9 shows an example of a mapping screen.

<1. Overview of the Human Resources Computer System and Computer Programs>

(1) The personnel computer system according to the embodiment may perform the following processes: display a setting screen for setting mapping data that corresponds data values included in a company's personnel data to data categories for calculating the company's human capital indicators; accept an operation to set the mapping data; save the mapping data to a storage device; obtain indicator calculation data corresponding to the data categories for calculating the human capital indicators from the personnel data based on the mapping data stored in the storage device; calculate the company's human capital indicators from the indicator calculation data; and display the company's human capital indicators. By using the mapping data, the system can calculate human capital indicators even if the personnel data is not configured in a format suitable for calculating human capital indicators.

(2) Obtaining the data for calculating the indicator may include obtaining the data for calculating the indicator for each of the multiple companies from the personnel data of each of the multiple companies, based on the mapping data of each of the multiple companies set up as a group of companies. The process may further include calculating an aggregated human capital indicator for the entire group of companies from the data for calculating the indicator for each of the multiple companies, and displaying the aggregated human capital indicator. In this case, the aggregated human capital indicator can be calculated from the personnel data of multiple companies, each of which may have different data values.

(3) The process may further include, upon receiving an operation to drill down from the display of the aggregated human capital indicator to the display of the human capital indicator for any of the multiple companies designated as group companies or any department within each company, drilling down to display the human capital indicator for any of the multiple companies designated as group companies or any department within each company. In this case, drill-down display from the aggregated human capital indicator becomes possible.

(4) Obtaining the indicator calculation data may include obtaining the indicator calculation data for each of the multiple companies from the personnel data of each of the multiple companies based on the mapping data of each of the multiple companies. The process may further include calculating statistical data of human capital indicators for the multiple companies from the indicator calculation data of each of the multiple companies and displaying the statistical data. In this case, statistical data of human capital indicators can be calculated from the personnel data of multiple companies, each of which may have different data values.
(4A) Obtaining the indicator calculation data may include obtaining the indicator calculation data for each of the multiple first companies from the personnel data of each of the multiple first companies based on the mapping data of each of the multiple first companies set up as group companies, and obtaining the indicator calculation data for each of the multiple second companies from the personnel data of each of the multiple second companies based on the mapping data of each of the multiple first companies, which include at least companies other than the multiple first companies set up as group companies. The process may further include calculating an aggregated human capital index for the entire multiple first companies from the indicator calculation data of each of the multiple first companies, calculating statistical data of the human capital index for each of the multiple second companies from the indicator calculation data of each of the multiple second companies, and displaying the aggregated human capital index and the statistical data side by side.

(5) The data categories for calculating the human capital indicators may include one or more data categories selected from the group consisting of gender categories, regular employee categories, managerial positions categories, categories for first-time parental leave takers, and categories for relationship to the employee (e.g., child).

(6) Obtaining the data for calculating the indicator may include obtaining data for calculating the indicator corresponding to the data category for calculating the human capital indicator, based on the mapping data, from the data included in the personnel data that matches the filtering conditions. Calculating the human capital indicator may include calculating the human capital indicator from the data for calculating the indicator obtained from the data that matches the filtering conditions.

(7) The computer program according to the embodiment displays a setting screen for setting mapping data that corresponds data values included in a company's personnel data to data categories for calculating the company's human capital indicators; accepts an operation to set the mapping data; saves the mapping data to a storage device; obtains indicator calculation data corresponding to the data categories for calculating the human capital indicators from the personnel data based on the mapping data saved in the storage device; calculates the company's human capital indicators from the indicator calculation data; and displays the company's human capital indicators. The computer program may be stored in a non-temporary computer-readable storage medium.

<2. Example of an overview of a personnel computer system and computer program>

The system and computer program according to the embodiment will be described in more detail below, based on the drawings.

Figure 1 shows a system 10 according to an embodiment. System 10 can operate as a human resources computer system. System 10 obtains one or more human capital indicators from human resources data 124 and visualizes the human capital indicators.

The system 10 according to this embodiment may operate in conjunction with a human resources management system or may have the functionality of a human resources management system. The human resources management system may be configured, for example, as a human resources database server system for managing human resources data. The human resources management system may provide human resources management services (e.g., SaaS) to companies that have a usage agreement for its human resources management system. The human resources data may include, as necessary, attendance data, wage data, and other data related to people belonging to the company.

Here, as an example, it is assumed that companies A1 and A2, and companies X, Y, and Z, as shown in Figure 1, have contracts to use a human resources management system that operates in conjunction with system 10. However, company A3 has a contract to use a different human resources management system and does not use a human resources management system that operates in conjunction with system 10.

Furthermore, for the purposes of this discussion, we will assume that three companies, A1, A2, and A3, constitute a single group G. Group G is, for example, a group of companies (group companies) that make up a holding company structure. Here, the holding company is a holding company that manages and guides its subsidiary companies. The group of companies, including the subsidiary companies of the holding company and, if necessary, the holding company itself, may be referred to as the "entire holding company" (HD). Note that the composition of a group of companies is not limited to this; for example, it may be a collection of companies formed by capital relationships or contracts, even if they are not structured as a holding company.

The system 10 according to this embodiment can calculate and visualize human capital indicators for the entire group G from the personnel data 124 of each of the multiple companies constituting a single group. System 10 visualizes the human capital indicators for the entire group G to which the company belongs, for companies that have a usage agreement with the system, and enables comparison with statistical data of human capital indicators. In this example, at least Company A1, the holding company of Group G, has a usage agreement for System 10, and the display screen provided by System 10 can be displayed on the computer 22 at Company A1. Companies X, Y, and Z are, for example, competitors of Group G, and these companies X, Y, and Z also have usage agreements for System 10.

The system 10 according to this embodiment is composed of one or more computers. The system 10 may, for example, be composed of one or more server computers. The system 10 may be configured, for example, as a client/server system and can be used by users from their client computers 22, 23, 24, 25, 26, 27 via a network 15 such as the Internet. Users may be, for example, human resources personnel, system administrators, or other employees of a company using the system 10.

In the following, client computers will be referred to as "terminals." Terminals 22, 23, 24, 25, 26, and 27 are, for example, personal computers, smartphones, and tablets. Terminals 22, 23, 24, 25, 26, and 27 are equipped with display devices (computer screens) and can display data provided by system 10 on their display devices. Furthermore, terminals 22, 23, 24, 25, 26, and 27 can accept user operations using input devices such as keyboards, mice, and touch panels, and can transmit signals based on those user operations to system 10.

As shown in Figure 1, the computer constituting System 10 may include a processor 110 and a storage device 120. The processor 110 is connected to the storage device 120. The storage device 120 includes, for example, a primary storage device and a secondary storage device. The primary storage device is, for example, RAM. The secondary storage device is, for example, a hard disk drive (HDD) or a solid-state drive (SSD). The storage device 120 contains a computer program 121 executed by the processor 110. The processor 110 reads and executes the computer program 121 stored in the storage device 120. The computer program 121 has program code containing instructions to cause the computer to perform various processes in order to operate the computer as System 10 according to this embodiment. Furthermore, the computer constituting System 10 includes a communication unit 150 for communicating with external devices such as terminals. System 10 transmits data to and receives data from external sources via the communication unit 150.

The processing realized by the processor 110 executing the computer program 121 may include, for example, the first to sixth processing steps 111, 112, 113, 114, 115, and 116 shown in Figure 1.

The first process 111 is the process by which system 10 imports personnel data. The imported personnel data may be from a personnel management system that system 10 is linked to, or from another personnel management system. The import of personnel data is performed, for example, by uploading a personnel data file to system 10 from a personnel management system linked to system 10 or from a user's terminal. The personnel data file is, for example, in CSV format.

The second process 112 is the process of setting the mapping data 125. The third process 113 is the process of calculating the human capital indicators for individual companies. The fourth process 114 is the process of calculating the aggregated human capital indicators for the entire group of companies. The fifth process 115 is the process of calculating statistical data. The sixth process 116 is the process of displaying various data on a display device. The display device is, for example, a display device provided by a terminal. Details of the second to sixth processes 112-116 will be described later.

As shown in Figure 1, the storage device 120 includes a database 122 for storing data used in the system 10.

Database 122 contains group company configuration data 123. Group company configuration data 123 is data that sets up multiple companies (group companies) that constitute a single group, group by group. For example, in group company configuration data 123, three companies, A1, A2, and A3, are set up as a single group G. This can be done, for example, by a user in charge of A1, a holding company (HD), accessing system 10 from terminal 22 and performing an operation to set up A1, A2, and A3 as a single group G in group company configuration data 123. Note that group company configuration data 123 may include the industry of the entire group G, or the industry of each company that constitutes group G.

Database 122 contains personnel data 124. Personnel data 124 is, for example, personnel data imported from a personnel management system linked to system 10 or another personnel management system. The imported personnel data is stored in database 122 as personnel data 124. If system 10 also functions as a personnel management system, it is not necessary to import personnel data already held by system 10. Furthermore, personnel data 124 is, for example, annual.

As an example, a user in charge of Holdings Company A1 can configure group company settings 123 for companies A1, A2, and A3, and then import personnel data into System 10. For personnel data of companies A1 and A2, which use personnel management systems linked to System 10, System 10 imports the data from those systems. For personnel data of company A3, which uses a different personnel management system, the data is uploaded to System 10 from terminal 22.

System 10 can calculate and visualize the human capital indicators for the entire Group G from the personnel data 124 of each of the multiple companies set in the Group Company Setting Data 123. Furthermore, System 10 can also calculate and visualize the human capital indicators for individual companies from the personnel data 124 of each company, or it can calculate and visualize the human capital indicators for each department within a company.

Database 122 contains mapping data 125. Mapping data 125 is data set by the second process 112 (mapping process 112). The user sets the mapping data 125 corresponding to each personnel data 124 imported into system 10. Mapping data 125 is data that maps the data values contained in the personnel data to data categories for calculating human capital indicators.

System 10 refers to the mapping data 125 to associate the data values contained in the personnel data 124 with data categories for calculating human capital indicators, and calculates the human capital indicators from the corresponding data values (data for indicator calculation) in the personnel data 124.

Database 122 contains statistical data 126. The statistical data 126 are values obtained by the fifth processing step 115, which calculates the statistical data. The statistical data, as an example, includes statistical values of human capital indicators. These statistical values are, for example, the average values of human capital indicators for each industry and/or the average values of human capital for all industries.

The statistical data 126 here refers to statistical values calculated from the personnel data 124 and mapping data 125 of multiple companies imported into the system 10. For example, statistical data 126 refers to data in a state where it is not possible to identify which company the data belongs to (a collection of two or more companies). The statistical data 126 for each industry or for all industries may be calculated, for example, when there is personnel data 124 and its mapping data 125 for three or more companies in each industry or for all industries, and not calculated when there is only data 124 and 125 for one or two companies in each industry or for all industries.

System 10 allows users to compare the human capital indicators (aggregated human capital indicators) of the entire HD (Group G) or the human capital indicators of individual companies with the human capital indicators shown in the statistical data 126.

Figure 2 shows an example of a screen 200 (dashboard) that displays human capital indicators for the holding company (HD), which consists of companies A1, A2, and A3, along with statistical data 126. The data displayed on this screen 200 is generated by system 10 and displayed on terminal 22 for screen display, for example, on terminal 22 logged into system 10. Terminal 22 is, for example, the terminal of a user in charge of company A1, which is a holding company. On terminal 22, screen 200 is displayed, for example, using browser software.

Screen 200 displays, as an example, three human capital indicators: the gender wage gap, the rate of paternity leave taken by men, and the ratio of women in management positions. To display these indicators, screen 200 includes a first display section 210 for the gender wage gap, a second display section 220 for the rate of paternity leave taken by men, and a third display section 230 for the ratio of women in management positions. The first display section 210 for the gender wage gap includes, as an example, the display of three indicators: "Gender Wage Gap (All Workers)," "Gender Wage Gap (Regular Employees)," and "Gender Wage Gap (Non-Regular Employees)."

In each display unit 210, 220, and 230, the value in the "Company" column indicates either the human capital index value for the entire HD or the human capital index value for any of the companies comprising the HD. The "Company" is selected in the company selection unit 201.

In the company selection unit 201, one company is selected from either the entire HD or the multiple companies that comprise the HD. In each display unit 210, 220, and 230, the "Company" portion displays the name of the selected HD or company.

In the company selection section 201, if the entire HD is selected, screen 200 will display the aggregated human capital indicators for the entire HD, along with the statistical data for those human capital indicators. If any of the companies comprising the HD are selected, screen 200 will display the human capital indicators for the selected company, along with the statistical data for those human capital indicators.

In each display unit 210, 220, and 230, the "Average for the Compared Industry" column shows the average value of the human capital indicator for the industry as statistical data. The "Industry" in "Average for the Compared Industry" is selected by the industry selection unit 202. The industry selection unit 202 selects the industry to be compared from among multiple industries.

In each display unit 210, 220, and 230, "Average for All Industries" shows the average of human resource indicators across all industries as statistical data.

The human capital indicators displayed in each display unit 210, 220, and 230 are the values for the year selected in the year selection unit 203.

By referring to screen 200, users can compare the human capital indicators for the entire HD (Group G) or for each company with the human capital indicators (benchmark) shown in statistical data 126. While the human capital indicators are displayed in a table format on screen 200, they may also be displayed in a graph or other format. Furthermore, the human capital indicators for the entire HD and/or for each of the multiple companies comprising the HD may be displayed simultaneously.

Screen 200 is also called the Holdings View (HD View). HD View 200 is also shown in Figure 3. HD View 200 can be used in formulating human resource strategies. For example, HD View 200 can be used to set key performance indicators (KPIs) for communicating human resource strategies externally. By referring to HD View 200, users can check the situation at the HD (Group G) or company level, including comparisons with other companies. For example, an HD representative can check the overall HD indicators in HD View 200, set overall HD KPIs, and verify their achievement.

System 10, when receiving a drill-down operation (a state in which the entire HD is selected) in the company selection unit 201, allows the user to select one of the multiple companies (corporations A1, A2, A3) that make up the HD, and then drill down to display the human capital indicators for the selected company. Therefore, the user can view not only the aggregated human capital indicators for the entire HD, but also its breakdown (the human capital indicators for each company). Furthermore, the user can compare the human capital indicators of each company with statistical data.

System 10, when displaying any company (for example, Company A2) on screen 200, can accept an operation (drill-down operation) to display detailed data about that company (for example, human capital indicators for each business unit of the company). This operation can be performed, for example, by the user selecting the text "Company A2" displayed as a user interface on screen 200.

Figure 4 shows an example of screen 400 (drill-down display) displayed after performing a drill-down operation on Company A2. Screen 400 is also called the Company-Wide View 400, as shown in Figure 3. Figure 4 displays human capital indicators for business units B1 and B2 of Company A2. The Company-Wide View 400, as an example, includes a first display section 410 for the gender wage gap, a second display section 420 for the rate of men taking childcare leave, and a third display section 430 for the ratio of female managers.

The Enterprise-Wide View400 can be used to verify management indicators for a company. It can be used for optimizing personnel allocation, verifying workforce planning processes, and setting and monitoring KPIs for management/business units. By referring to the Enterprise-Wide View400, users can conduct workforce analysis, check the status of each business unit within the company, and set and verify the achievement of company-wide KPIs.

System 10, upon receiving a drill-down operation to view human capital indicators for any department (e.g., division/section) within the enterprise-wide View 400, can drill down to the human capital indicator display 500 for that department. This display 500 is also called the business unit/department/section View 500. The business unit/department/section View 500 can be used for checking the status at the department/section level. The business unit/department/section View 500 can be used for aggregating and displaying human capital indicators at the department/section level, checking for staffing surpluses and shortages, and creating organizational description summaries.

System 10, upon receiving a drill-down operation to a display of personal data belonging to a department/section within the business unit/department/section View 500, can drill down to the display 600 (personal view 600) of that personal data. The personal view 600 can be used for verification of personal personnel data by superiors, including the human resources department, or by the individual themselves or others.

Furthermore, drilling down to the company-wide View 400, department/section View 500, and individual View 600 may be restricted to companies that have a usage agreement for the human resources management system linked to System 10. For example, within Group G, only companies A1 and A2 have usage agreements for the human resources management system, while company A3 does not. Therefore, companies A1 and A2 may be able to drill down to the company-wide View 400, department/section View 500, and individual View 600, while company A3 may be unable to do so.

System 10 can calculate each human capital indicator (including statistical data) displayed in HD View 200, company-wide View 400, and business unit/department/section View 500 from personnel data 124 stored in storage device 120. Figure 5 illustrates how System 10 calculates human capital indicators from personnel data 124.

System 10 utilizes mapping data 125 to calculate human capital indicators from each company's personnel data 124. Mapping data 125 is set for each company. For example, mapping data 125A is set for Company A1. Mapping data 125A is used to obtain indicator calculation data for Company A1 from Company A1's personnel data 124A. The indicator calculation data for Company A1 is used to calculate (process 113) human capital indicators for Company A1 as a whole or its internal departments. Similarly, mapping data 125B, 125C, 125D, 125E, and 125F are set for Companies A2, A3, and Companies X, Y, and Z, respectively, and are used to obtain indicator calculation data for each company from their respective personnel data 124B, 124C, 124D, 124E, and 124F.

System 10, in order to calculate the aggregated human capital indicator for the entire HD, refers to the group company setting data 123 and identifies companies A1, A2, and A3, which are set as group companies constituting the HD (Group G). Then, based on the mapping data 125A, 125B, and 125C of the identified companies A1, A2, and A3, System 10 obtains the indicator calculation data for each of these companies from their personnel data 124A, 124B, and 124C. System 10 then calculates the aggregated human capital indicator for the entire HD from the indicator calculation data for each of companies A1, A2, and A3 (process 114).

System 10 calculates statistical data for human capital indicators. Based on the mapping data 125A, 125B, 125C, 125D, 125E, and 125F from the personnel data 124A, 124B, 124C, 124D, 124E, and 124F of each company that has a contract to use System 10, it obtains indicator calculation data for each company A1, A2, A3, X, Y, and Z. From this indicator calculation data, it calculates statistical values (e.g., average values) of human capital indicators (process 115).

Examples of human capital indicators calculated by System 10 include the aforementioned gender wage gap (all workers, regular employees, and non-regular employees), the rate of men taking parental leave, and the percentage of women in management positions.

The wage gap between men and women (for all workers, regular employees, and non-regular employees) can be calculated, for example, based on the method for calculating the wage gap between men and women published by the Ministry of Health, Labour and Welfare. To calculate the wage gap between men and women (for all workers, regular employees, and non-regular employees), all workers are divided into four categories: "female regular employees," "female non-regular employees," "male regular employees," and "male non-regular employees." Then, the total wages for each category are divided by the number of employees in each category to obtain the average annual wage for each.

The gender wage gap for all workers is calculated as: average annual wage for women (regular and non-regular) / average annual wage for men (regular and non-regular). The gender wage gap for regular employees is calculated as: average annual wage for female regular employees / average annual wage for male regular employees. The gender wage gap for non-regular employees is calculated as: average annual wage for female non-regular employees / average annual wage for male non-regular employees.

The rate of men taking childcare leave can be calculated based, for example, on the calculation method for the percentage of childcare leave taken or the percentage of childcare leave taken combined with childcare-related leave, as published by the Ministry of Health, Labour and Welfare. The percentage of childcare leave taken is calculated as follows: "Number of male employees who took childcare leave during the published fiscal year" / "Number of male employees employed by the employer whose spouses gave birth during the published fiscal year."

The percentage of female managers is calculated, for example, by dividing the number of female managers by the total number of managers.

System 10 calculates the above-mentioned indicators from personnel data. Figure 6 shows examples of personnel data 124A and 124B for companies A1 and A2, respectively. Personnel data 124A and 124B may contain employee data and employee family data. In personnel data 124A of company A1, the "gender" data item can take one of two values: male or female. On the other hand, in personnel data 124B of company A1, the "gender" data item can take multiple gender data values, considering not only legal gender but also gender identity. Thus, the gender data values differ between companies A1 and A2.

Neither the personnel data 124A nor 124B for companies A1 and A2 directly distinguishes between regular and non-regular employees, nor does it directly distinguish between managerial and non-managerial positions.

However, the "Employee Classification" data item in personnel data 124A and 124B for companies A1 and A2 may be related to the distinction between regular and non-regular employees. The "Employee Classification" data value in personnel data 124A for company A1 is determined internally by company A1 and is "Part-time/Temporary/Contract/Executive/Full-time Employee." On the other hand, the "Employee Classification" data value in personnel data 124B for company A2 differs slightly in expression from company A1, being "Regular Employee/Dispatch/Contract Employee/Part-timer/Executive."

Furthermore, the "Job Title" and "Job Qualification Title" data items in personnel data 124A and 124B for companies A1 and A2 may be related to the distinction between management and non-management positions. The data values for "Job Title" and "Job Qualification Title" in personnel data 124A for company A1 are determined internally by company A1 and are "Team Leader/Member/Business Unit Manager/Executive/Section Chief/Department Manager" and "L1/L2/L3/L4/L5/M1/M2/M3/Executive," respectively. On the other hand, the data values for "Job Title" and "Job Qualification Title" in personnel data 124B for company A2 are "General Employee/Supervisor/Section Chief/Section Chief/Department Manager/General Manager/Director/Representative Director" and "J1/J2/J3/S4/S5/S6/M7/M8/Executive."

Thus, the data values for "Job Title" and "Job Qualification Title" differ between companies A1 and A2. Furthermore, each data item in personnel data 124A and 124B of companies A1 and A2 can have unique data values.

System 10 calculates a unified human capital index from personnel data, which may contain differing data values. To achieve this, it maps the data values included in the personnel data to data categories for calculating the human capital index. Figure 7 shows a mapping screen 700 for setting this mapping as mapping data 125. When a user performs a mapping operation on this screen 700, the mapping is completed, and upon performing a "Save" operation, the mapping data 125 is saved to the storage device 120.

The mapping screen 700 includes a first setting unit 710 (see Figure 7(A)) for setting data categories related to "employees" in the personnel data, and a second setting unit 720 (see Figure 7(B)) for setting data categories related to "family members."

The first setting unit 710 shown in Figure 7(A) includes a data classification setting unit comprising a gender setting unit 711, a regular employee classification setting unit 712, a manager classification setting unit 713, and a first-time parental leave classification setting unit 714. The second setting unit 720 shown in Figure 7(B) includes a relationship setting unit 721 as a data classification setting unit.

Figures 8 and 9 show examples of settings in the first setting unit 710 and the second setting unit 720. Here, the mapping of data values for personnel data 124A of company A1 is explained as an example, but similar mapping is performed for companies A2 and A3, and companies X, Y, and Z.

Figure 8(A) shows the details of the gender setting unit 711 for setting gender data categories. Here, the system 10 can uniquely identify "female" or "male" from the personnel data 124A when calculating human capital indicators related to "women" or "men," such as the ratio of female managers or the rate of men taking paternity leave. In other words, the gender setting unit 711 sets the data values of the "gender" data items in the personnel data 124A to correspond to "female" or "male" for calculating the indicators. Here, the data values of "male" and "female" in the personnel data 124A are corresponding to the indicator calculation data categories "male" and "female," respectively.

System 10 reads the data value of the "gender" data item in the personnel data associated with "gender" for indicator calculation from the storage device 120, and displays all the read data values (in this case, "female [gender]" and "male [gender]") on the gender setting unit 711 as candidates for data values that can be associated with the indicator calculation data category "male". The user selects a data value that can be associated with the indicator calculation data category "male" or "male" from the candidates, thereby setting the gender mapping data 125.

Figure 8(B) shows the details of the regular employee classification setting unit 712 for setting data classifications for regular employees. Here, the system 10 can uniquely identify regular employees and non-regular employees from the personnel data 124A when calculating human capital indicators related to regular employees/non-regular employees, such as the gender wage gap (regular employees) or the gender wage gap (non-regular employees). Specifically, the regular employee classification setting unit 712 maps the data values of the "employee classification" data items in the personnel data 124A to "regular employees/non-regular employees/others" for calculating indicators. Here, the data value of "employee" in the personnel data 124A is mapped to the indicator calculation data classification "regular employees," the data value of "part-time/contract/temporary employees" is mapped to the indicator calculation data classification "non-regular employees," and the data value of "executives" is mapped to the indicator calculation data classification "others."

System 10 reads the data value of the "Employee Classification" data item associated with the "Regular Employee Classification" for indicator calculation from the storage device 120, and displays the read data value as a candidate for the associated data value in the Regular Employee Classification Setting Unit 712, in order to display the screen shown in Figure 8(B). Note that in each setting unit 711, 712, 713, 714, and 721, it is also possible to set multiple data values for a single data classification using "and" / "or" conditions.

Figure 8(C) shows the details of the manager classification setting unit 713 for setting data classifications for managerial positions. Here, the system 10 is configured to uniquely identify managers from the personnel data 124A when calculating human capital indicators related to managers, such as the ratio of female managers. Specifically, the manager classification setting unit 713 maps the data values of the "job qualification name" or "position name" data items in the personnel data 124A to "manager/non-manager/other" for calculating indicators. Here, the data values for "business unit manager/section manager/department manager" in the personnel data 124A are mapped to the indicator calculation data classification "manager," the data values for "team leader/member" are mapped to the indicator calculation data classification "non-manager," and the data values for "executive" are mapped to the indicator calculation data classification "other."

System 10 reads the data values of the personnel data items "Job Skill Qualification Name" and "Job Title Name" associated with the "Management Classification" for indicator calculation from the storage device 120, and displays the read data values as candidates for the associated data values in the Management Classification Setting Unit 713, in order to display the screen shown in Figure 8(C).

Figure 9(A) shows the details of the initial parental leave classification setting unit 714 for setting the data classification for the first parental leave. Here, the system 10 is configured to uniquely identify "first parental leave" from the personnel data 124A when calculating human capital indicators related to parental leave, such as the rate of men taking parental leave. Specifically, the initial parental leave classification setting unit 714 associates the data value of the "Leave of Absence Reason Name" data item in the personnel data 124A with "first parental leave" for calculating the indicator. Here, the data value of "◆Childcare (Paid Leave)" in the personnel data 124A is associated with the indicator calculation data classification "first parental leave."

System 10 reads the data value of the "Leave of Absence Reason Name" data item associated with the "Initial Parental Leave Category" for indicator calculation from the storage device 120, and displays the read data value as a candidate for the associated data value in the Initial Parental Leave Category Setting Unit 714, in order to display the screen shown in Figure 9(A).

Figure 9(B) shows the details of the relationship setting unit 721 for setting data categories for relationships. Here, the system 10 is configured to uniquely identify "children" from the personnel data 124A when calculating human capital indicators that require identifying employees with "children," such as the rate of paternity leave taken by men. Specifically, the relationship setting unit 721 associates the data value of the "relationship name" data item in the personnel data 124A with "children" for calculating the indicator. In this case, the data values of "second daughter/second son/eldest daughter/eldest son" in the personnel data 124 are associated with the indicator calculation data category "children."

System 10 reads the data value of the "Relationship Name" data item associated with the "Relationship" for indicator calculation from the storage device 120, and displays the read data value as a candidate for the corresponding data value in the relationship setting unit 721, in order to display the screen shown in Figure 9(B).

Now, when calculating human capital indicators, system 10 may filter the personnel data 124. System 10 can calculate human capital indicators using only the data from the personnel data 124 that matches the filtering criteria. For example, when using a company's personnel data to calculate its human capital indicators, instead of using the data of all employees included in the company's personnel data 124, system 10 can use only the data of those who match the filtering criteria.

In this case, system 10 obtains indicator calculation data corresponding to the data category for calculating human capital indicators, based on mapping data, from the data of individuals that match the filtering conditions within the personnel data. Then, system 10 calculates the human capital indicators from the indicator calculation data obtained from the data that matches the filtering conditions. Such filtering can also be applied when calculating aggregated human capital indicators and statistical data.

The filtering conditions may, for example, be criteria for distinguishing between data used for calculating human capital indicators and data not used for calculating human capital indicators within the personnel data. For example, the filtering condition could be place of residence. In this case, only the personnel data of individuals whose place of residence information is in a specific place of residence, or only the personnel data of individuals whose place of residence is outside of that specific place of residence, will be used for calculating human capital indicators. Filtering conditions such as specific places of residence may be pre-set in system 10 or may be set by the user. Examples of place of residence as a filtering condition include country, region consisting of multiple countries, customs zone, domestic region, prefecture, state, or municipality. As an example, only the personnel data of individuals whose place of residence information is outside of a specific region may be used for calculating human capital indicators. In this case, human capital indicators (including aggregated human capital indicators and statistical data) can be calculated while excluding residents of the specific region.

Filtering criteria may include not only place of residence but also other attributes of each individual. These other attributes may include, for example, gender, age, occupation, or job title. Filtering criteria may also be a combination of two or more attributes.

The present invention is not limited to the embodiments described above, and various modifications are possible. For example, the human capital indicators calculated by system 10 are not limited to those described above, and may include, for example, the percentage of female workers among all workers, the percentage of female workers among regular employees, the percentage of female workers among newly hired workers, the mid-career hiring ratio of newly hired regular employees, the gender ratio of executives, the rate of women taking childcare leave, etc. Furthermore, the data categories set as mapping data are not limited to those described above, and may include those necessary for the calculated indicators as appropriate.

10: Human Resources Computer System 15: Network 22: Terminal 23: Terminal 24: Terminal 25: Terminal 26: Terminal 27: Terminal 110: Processor 111: First Processing 112: Second Processing 113: Third Processing 114: Fourth Processing 115: Fifth Processing 116: Sixth Processing 120: Storage Device 121: Computer Program 122: Database 123: Group Company Setting Data 124: Human Resources Data 124A: Human Resources Data 124B: Human Resources Data 124C: Human Resources Data 124D: Human Resources Data 124E: Human Resources Data 124F: Human Resources Data 125: Mapping Data 125A: Mapping Data 125B: Mapping Data 125C: Mapping Data 125D: Mapping Data 125E: Mapping Data 125F: Mapping Data 126: Statistical Data 150 : Communication unit 200 : Screen 201 : Company selection unit 202 : Industry selection unit 203 : Year selection unit 210 : First display unit 220 : Second display unit 230 : Third display unit 400 : Screen 410 : First display unit 420 : Second display unit 430 : Third display unit 500 : Display 600 : Display 700 : Mapping screen 710 : First setting unit 711 : Gender setting unit 712 : Regular employee classification setting unit 713 : Manager classification setting unit 714 : First parental leave classification setting unit 720 : Second setting unit 721 : Relationship setting unit

Claims (7)

It is a personnel computer system,
A settings screen is displayed for setting up mapping data that corresponds the data values included in a company's personnel data to data categories used to calculate the company's human capital indicators.
The system accepts an operation to set the mapping data and saves the mapping data to a storage device.
Based on the mapping data stored in the storage device, the data for calculating the human capital indicators corresponding to the data categories for calculating the human capital indicators is obtained from the personnel data.
From the aforementioned data for calculating the indicators, the aforementioned human capital indicators of the company are calculated.
Display the aforementioned human capital indicators of the aforementioned company.
A human resources computer system configured to perform processes that include the following. Obtaining the aforementioned indicator calculation data includes obtaining the aforementioned indicator calculation data for each of the multiple companies from the personnel data of each of the multiple companies, based on the mapping data of each of the multiple companies set up as a group company,
The aforementioned process is,
From the data used to calculate the indicators for each of the aforementioned companies, an aggregated human capital indicator for the entire group of companies is calculated.
The personnel computer system according to claim 1, further comprising displaying the aggregated human capital indicators. The aforementioned process is,
The personnel computer system according to claim 2, further comprising: receiving an operation to drill down from the display of the aggregated human capital indicators to the display of human capital indicators for any of the multiple companies designated as group companies or any department within each company, and then drilling down to display the human capital indicators for any of the multiple companies designated as group companies or any department within each company. Obtaining the aforementioned indicator calculation data includes obtaining the aforementioned indicator calculation data for each of the multiple companies from the personnel data of each of the multiple companies based on the aforementioned mapping data for each of the multiple companies,
The aforementioned process is,
From the data used to calculate the indicators for each of the aforementioned companies, statistical data of the human capital indicators for the aforementioned companies is calculated.
Display the aforementioned statistical data.
A personnel computer system according to any one of claims 1 to 3, further comprising the following: The personnel computer system according to claim 1, wherein the data categories for calculating the human capital indicators include one or more data categories selected from the group consisting of gender categories, regular employee categories, managerial positions categories, categories for first-time parental leave takers, and child relationship categories. Obtaining the aforementioned indicator calculation data includes obtaining indicator calculation data corresponding to the data category for calculating the human capital indicator, based on the mapping data, from the data included in the personnel data that matches the filtering conditions,
The personnel computer system according to claim 1, wherein calculating the human capital indicator includes calculating the human capital indicator from indicator calculation data obtained from data that matches the filtering conditions. A settings screen is displayed for setting up mapping data that corresponds the data values included in a company's personnel data to data categories used to calculate the company's human capital indicators.
The system accepts an operation to set the mapping data and saves the mapping data to a storage device.
Based on the mapping data stored in the storage device, the data for calculating the human capital indicators corresponding to the data categories for calculating the human capital indicators is obtained from the personnel data.
From the aforementioned data for calculating the indicators, the aforementioned human capital indicators of the company are calculated.
Display the aforementioned human capital indicators of the aforementioned company.
A computer program that causes a computer to perform a process that includes the following.