JP2021162975A - Human resources analysis system, method, and program - Google Patents

Abstract

To provide a technique capable of concretely and objectively analyzing the current or past tasks of personnel who carry out the task.SOLUTION: The human resources analysis system includes: a data acquisition unit that acquires task history information as a history of operations of an application in a terminal device that is used by the task operator in the task; and a task tendency analysis unit that analyzes the task history information and generates a piece of involved task information that is the information about the task that the task operator has been involved in in the past or is currently involved in.SELECTED DRAWING: Figure 2

Description

The present invention relates to a technique for analyzing human resources.

In recent years, against the background of work style reforms, companies are required to improve labor productivity (also simply referred to as "productivity"), which is the result of employees' working hours. In order to improve productivity, it is desirable to have an appropriate education plan for employees to acquire skills that enable them to carry out their duties smoothly, and to allocate employees appropriately for various tasks. Regarding the education plan, it is desirable to formulate and execute an education plan according to the current or future work contents of each employee. Regarding staffing, the work aptitude of each employee, that is, what kind of work the employee is expected to achieve and how much result is estimated, should be taken into consideration when deciding the staffing for the work. Is desirable.

Patent Document 1 discloses a technique for analyzing the characteristics of employees. Patent Document 1 discloses a human resources information analysis system that analyzes human resources information and office log information of employees and outputs behavioral characteristics. Human resources information includes employee's date of birth, age, gender, family information, years of service, place of work, job type information, career, job title, personnel evaluation information, qualification information, skill information, work style, overtime hours, paid leave, etc. Is included. Office log information is information on the time spent on actions of each item such as e-mail correspondence, document creation, customer visit, management work, meetings, information gathering, and breaks.

JP-A-2019-95820

As described above, the analysis targets of the human resources information analysis system of Patent Document 1 are human resources information and office log information. The human resources information may include information on specific tasks such as what kind of work experience each employee has and what kind of work is currently being performed. However, this human resource information is information input by the employee himself / herself or its manager, and may lack objectivity. On the other hand, the office log information is information on the time spent by the employee on each action item, and does not include information on specific work. Therefore, the system of Patent Document 1 is not suitable for human resources management in consideration of the specific work that each employee is currently performing or the specific work that each employee has performed in the past.

One object of the present disclosure is to provide a technique for concretely and objectively analyzing the current or past work of the personnel who carry out the work.

The human resources analysis system according to one aspect of the present disclosure analyzes the business history information with the data acquisition unit that acquires the business history information which is the history of operations on the application in the terminal device used by the business operator, and the above-mentioned It has a business trend analysis department that generates information on the business involved, which is information on the business that the business operator has been involved in in the past or is currently involved in.

According to one aspect of the present disclosure, the past or present work of the work performer can be analyzed concretely and objectively.

It is a block diagram of a human resources analysis system. It is a block diagram of a data processing apparatus. It is a block diagram which shows the hardware configuration of a data processing apparatus. It is a flowchart of business tendency analysis processing. It is a table showing an example of employee information. It is a table which shows an example of business history information. This is a table showing an example of business trend information. It is a flowchart of the recommended condition analysis process. This is a table showing an example of course information. It is a figure which shows an example of a questionnaire. It is a table showing an example of the degree of relevance information showing the degree of relevance between the educational course and the students. It is a table which shows an example of recommended condition information. It is a flowchart of the recommended course estimation process. It is a figure for demonstrating the calculation method of the application tendency agreement degree. This is a table showing an example of course recommendation level information. It is a flowchart of the similar business history extraction process. It is a table which shows an example of business tendency similarity information.

An embodiment of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram of a human resources analysis system according to the present embodiment. The human resources analysis system 10 has an employee use terminal 11 and a data processing device 12. The employee use terminal 11 and the data processing device 12 are connected to each other so as to be able to communicate with each other via the communication network 19. The employee use terminal 11 is a terminal device such as a personal computer used by an employee (business performer) who carries out business in an organization such as a company. The data processing device 12 is an information processing device such as a server that collects, stores, analyzes, and uses employee data in an organization.

FIG. 2 is a block diagram of the data processing device according to the present embodiment. The data processing device 12 has a data acquisition unit 21, a processing unit 22, and a storage unit 23. The processing unit 22 has a business tendency analysis unit 221, a recommended condition analysis unit 222, a recommended course estimation unit 223, and a human resources search unit 224. The storage unit 23 has employee information 231, work history information 232, work tendency information 233, course information 234, questionnaire result information 235, recommended condition information 236, and recommended course information 237.

The data acquisition unit 21 cooperates with the employee use terminal 11 of the employee registered in the employee information 231 to acquire the business history information 232 which is the history of the operation of the application on the employee use terminal 11. Employee information 231 is information about each of the employees managed by the human resources analysis system 10. The business history information 232 is information that reflects the business history acquired from the operation history of the employee use terminal 11. The processing unit 22 performs various processes using the business history information 232. The storage unit 23 stores various information used by the processing unit 22 for processing and various information of the processing result by the processing unit 22.

The business tendency analysis unit 221 analyzes the employee business history information 232 collected by the data acquisition unit 21, and the business tendency information (involvement) which is information on the business in which the employee has been involved in the past or the business in which the employee is currently involved. Business information) 233 is generated. The business tendency information 233 is information about the business in which the employee is involved or the business in which the employee is involved, which is generated from the business history information 232 of the employee. This business trend information 233 is information that can be widely used for human resource utilization and human resource development in an organization.

The recommended condition analysis department 222 is based on the questionnaire result information 235 obtained from each employee (student) who took the educational course registered in the course information 234, and the employee whose educational course was useful for the work. Employees who are the target of recommending educational courses based on the extracted employee business tendency information 232 and the employee business tendency information 233, and based on the student business tendency information 233. Generates recommended condition information (recommended involved work information) 236, which is related work information for conditioning the target person or target employee). Course information 234 is information on various educational courses that employees are required to take as appropriate. Questionnaire result information 235 is information on the answers to the questionnaire obtained from the employees who took the education course. The recommended condition information 236 is information for conditioning which employee is recommended to take the educational course for each educational course.

The recommended course estimation unit 223 determines whether or not to recommend the educational course to the employee based on the work tendency information 233 of the employee and the recommended condition information 236 of the educational course, and determines whether or not to recommend the educational course to the employee. Generates recommended course information 237, which is information on educational courses recommended for attendance. Recommended course information 237 is information that records which educational course is recommended for which employee.

The human resources search unit 224 is based on the work tendency information 233 of the designated employee and the work tendency information 233 of the employees other than the designated employee, and the employee whose work is similar to that of the designated employee. Is extracted.

FIG. 3 is a block diagram showing a hardware configuration of the data processing device according to the present embodiment. The data processing device 12 is a computer having a processor 31, a main memory 32, a storage device 33, a communication device 34, an input device 35, and a display device 36 as hardware, and these are connected to the bus 37.

The storage device 33 stores data so that it can be written and read, and the storage device 33 realizes the storage unit 23 shown in FIG. The processor 31 reads the data stored in the storage device 33 into the main memory 32, and executes the processing of the software program using the main memory 32. When the processor 31 executes the software program, the data acquisition unit 21, the business tendency analysis unit 221, the recommended condition analysis unit 222, the recommended course estimation unit 223, and the human resource search unit 224 shown in FIG. 2 are realized. The communication device 34 transmits the information processed by the processor 31 via the communication network 19 including wired, wireless, or both, and transmits the information received via the communication network 19 to the processor 31. The received information is used by the processor 31 for software processing. The input device 35 is a device that receives information input by an operator such as a keyboard or a mouse, and the input information is used for software processing by the processor 31. For example, the employee information 231 is input to the storage device 33 via the communication device 34 and the input device 35. The display device 36 is a device that displays image or text information on a display screen as a result of software processing by the processor 31.

Although an example in which the data processing device 12 is realized by one computer is shown here, the embodiment is not limited to this. As another example, the data processing device 12 may be realized by a plurality of computers. For example, the business tendency analysis unit 221 and the human resources search unit 224 and the recommended condition analysis unit 222 and the recommended course estimation unit 223 shown in FIG. 2 may be realized by separate server devices.

Hereinafter, more specific processing of each part will be described.

FIG. 4 is a flowchart of the business tendency analysis process. The business tendency analysis process is a process of acquiring business history information 232 and generating business tendency information 233.

In step S101, the data acquisition unit 21 acquires the business history information 232 of each month of each employee registered in the employee information 231.

FIG. 5 is a table showing an example of employee information. In the employee information 231, the employee identification information (ID) of each employee and the name are recorded in association with each other. For example, it is recorded that the name of the employee whose employee ID is "1000" is "User A".

FIG. 6 is a table showing an example of business history information. The business history information 232 records information about which employee is using which application, and what is the window title of the application. The application of the active window is regarded as the application used in the employee use terminal 11. The application and window title of the active window may be recorded in the business history information 232. For example, an employee whose employee ID is "1000" is using the application of "mail software" at the time of "2019/10/1 10:00", and the window title of the mail software is "working style". It is recorded that it was "about analysis PJ".

Returning to FIG. 4, in step S102, the business tendency analysis unit 221 calculates the ratio of the usage time of each application for each employee based on the business history information 232, and the business tendency information 233 is used as the application tendency information. Record in. Here, the ratio of the usage time of an application is the ratio of the usage time of the application to the total value of the usage time of all the applications. Further, in step S103, the business tendency analysis unit 221 extracts a predetermined number of words having the highest number of appearances in the history of the window title of each month for each employee based on the business history information 232, and uses it as word tendency information. , Record in business trend information 233. For example, the words up to the predetermined number may be extracted from the history of the window title in descending order of the number of appearances.

FIG. 7 is a table showing an example of business trend information. The business tendency information 233 includes application tendency information indicated by the ratio of the usage time of each application in a certain period of time by a certain employee, and word tendency information indicated by a predetermined number of words having the highest number of appearances in the window title. Is recorded. For example, for an employee whose employee ID is "1000", the ratio of the usage time of the application 1 is "20" in the period from the aggregation start date "2019/8/1" to the aggregation end date "2019/8/31". % ”, The usage time ratio of App 2 is“ 35% ”, the word with the highest number of occurrences extracted from the window title is“ work style ”, and the second word is“ analysis ”. Yes, it is recorded that the third word is "patent".

FIG. 8 is a flowchart of the recommended condition analysis process. The recommended condition analysis process is a process for generating recommended condition information 236 based on the work tendency information 233 of the employee who has taken the education course.

In step S201, the recommended condition analysis unit 222 is related to the educational course as a job type from the questionnaire result information 235 obtained from the students after taking the educational course for each educational course registered in the course information 234. Extract students with a high degree. Here, the degree of relevance as a job type is called the degree of job type relevance, and the students with a high degree of job type relevance are referred to as job type related students.

FIG. 9 is a table showing an example of course information. In the course information 234, the course identification information (ID) of each course and the course name are recorded in association with each other. For example, it is recorded that the course name of the educational course whose course ID is "AAA" is "Course 1".

In addition, the content of the questionnaire asked to the students is such that the students can judge whether or not the educational course has a high degree of occupational relevance.

FIG. 10 is a diagram showing an example of a questionnaire. Questionnaire 41 describes the content of the question to be asked to the students and five options for answers other than the question. The content of the question in Question Q1 is "Is this training related to your most recent work?" This question is a question for judging the degree of occupational relevance of the relevant educational course. The options for answering the question are "5. Directly related", "4. Indirectly related", "3, neither can be said", "2, not very related", "1, not related at all". There is. The option number is the job type relevance, and the higher the option number, the higher the job type relevance. For example, a student whose job type relevance degree is equal to or higher than a predetermined threshold value (for example, “4”) is defined as a job type related student.

FIG. 11 is a table showing an example of the degree of relevance information indicating the degree of relevance between the educational course and the students. The relevance information 42 includes course identification information (ID) that identifies the educational course, the date of attendance of the educational course, and the employee ID that identifies the employee who attended the educational course on the date of attendance. The degree of job type relevance between the relevant educational course and the relevant employee at the time of attendance and the degree of field relevance described later are recorded in association with each other.

Returning to FIG. 8, in step S202, the recommended condition analysis unit 222 extracts the application tendency information near the attendance date of the occupation-related student of the education course. The vicinity of the attendance date may be a period near the attendance date to the extent that the application tendency that reflects the work of the student at the time of the attendance can be obtained. For example, 3 months immediately before the attendance date. May be good.

Further, in step S203, the recommended condition analysis unit 222 calculates the average value of the usage time ratio of each application from the work history information 232 or the work tendency information 233 near the attendance date of the occupation-related student, and the education concerned. Register in the recommended condition information 236 as the application tendency information of the course.

FIG. 12 is a table showing an example of recommended condition information. In the recommended condition information 236, the application tendency information of the educational course and the word tendency information described later are recorded in association with the course ID that identifies the educational course. For example, as the application tendency information obtained from the operation history of the occupation-related students of the education course whose course ID is "AAA", the ratio of the usage time of the application 1 is "20%", and the usage time of the application 2 is It is recorded that the ratio is "35%".

Returning to FIG. 8, in step S204, the recommended condition analysis unit 222 receives the education from the questionnaire result information 235 obtained from the students after taking the education course for each education course registered in the course information 234. Extract students who are highly relevant to the course as a field of work. Here, the degree of relevance as a field of business is referred to as the degree of field relevance, and the students with a high degree of field relevance are referred to as field-related students.

With reference to FIG. 10, the content of the question in question Q2 is "Is this training useful for the work you are actually in charge of?" This question is a question for judging the degree of field relevance of the educational course. The options for answering the question are "5. Useful immediately", "4. Useful in the future", "3, I can't say either", "2, Not very useful", and "1. Not useful at all". The option number is the field relevance, and the higher the option number, the higher the field relevance. For example, a field-related student is defined as a student whose field-related degree is equal to or higher than a predetermined threshold value (for example, “4”).

Returning to FIG. 8, in step S205, the recommended condition analysis unit 222 selects the top predetermined words that frequently appear in the window title from the work history information 232 or the work tendency information 233 near the course date of the field-related students. Extract. Further, in step S206, the recommended condition analysis unit 222 refers to the word group extracted for each of the field-related students, extracts the top predetermined words common to many field-related students, and provides the education. Register in the recommended condition information 236 as the word tendency information of the course. For example, a word having a large number of field-related students registered in the business tendency information 233 may be extracted as a word having a large number of appearances in the window title. In the recommended condition information 236 of FIG. 12, the word that appears most frequently is "working style" as the word tendency information obtained from the operation history of the field-related students of the educational course whose course ID is "AAA". Second, it is recorded that the second word is "analysis".

FIG. 13 is a flowchart of the recommended course estimation process. The recommended course estimation process is a process for determining which educational course is recommended for employees.

In step S301, the recommended course estimation unit 223 extracts the latest work trend information 233 of the target employee (target employee) who recommends the educational course. As shown in FIG. 7, the business tendency information 233 includes application tendency information and word tendency information.

Subsequently, in step S302, the recommended course estimation unit 223 determines the degree of matching (app tendency matching degree) between the application tendency information of the target employee and the application tendency information of each educational course that the target employee has not attended. Calculate and store in course recommendation level information (described later). The app tendency matching degree is an index showing a larger value as the distance between arrays having the ratio of the usage time of each of a plurality of applications as an element is shorter.

FIG. 14 is a diagram for explaining a method of calculating the app tendency matching degree.

FIG. 14 shows a radar chart 51 showing the application tendency information of the target employee and a radar chart 52 showing the application tendency information of the educational course “Lecture 1”. In the example of FIG. 14, there are eight applications, App 1 to App 8, and the usage time ratio of each application is assigned to each axis of the radar charts 51 and 52.

Looking at the radar chart, the target employees have the usage time ratio of the application "App 1" being "A1", the usage time ratio of the application "App 2" being "A2", and the application "App 3". The usage time ratio of the application "A3" is "A3", the usage time ratio of the application "App 4" is "A4", the usage time ratio of the application "App 5" is "A5", and the usage time ratio of the application "App 6" is "A5". The usage time ratio of the application "App 7" is "A6", the usage time ratio of the application "App 7" is "A7", and the usage time ratio of the application "App 8" is "A8".

On the other hand, looking at the radar chart 52, in the course 1, the ratio of the usage time of the application "App 1" is "B1", the ratio of the usage time of the application "App 2" is "B2", and the ratio of the usage time of the application "App 2" is "B2". The usage time ratio of "3" is "B3", the usage time ratio of the application "App 4" is "B4", the usage time ratio of the application "App 5" is "B5", and the usage time ratio of the application "App 5" is "B5". The usage time ratio of the application "App 6" is "B6", the usage time ratio of the application "App 7" is "B7", and the usage time ratio of the application "App 8" is "B8".

The formula (1) is a formula for calculating the degree of matching of application tendencies between the target employee and the course 1.

If the distance between the array of the application tendency information of the target employee and the array of the application tendency information of the course 1 is short, the shapes of the radar chart 51 and the radar chart 52 are close to each other, and the degree of agreement between the application tendencies is high.

The application tendency information can be expressed as an array having the ratio of the usage time of each application as an element.

FIG. 15 is a table showing an example of course recommendation degree information. In the course recommendation degree information 43, for a certain employee (for example, a target employee), the app tendency matching degree and the frequently-appearing word matching number described later are recorded in association with the course name of each educational course. For example, as the course recommendation degree information 43 of "course 1" for the target employee, it is described that the application tendency matching degree is "50%" and the frequent word matching degree is "2".

Returning to FIG. 13, in step S303, the recommended course estimation unit 223 calculates the degree of agreement between the word tendency information of the target employee and the word tendency information of each educational course that the target employee has not attended, and the course. Store in recommendation level information (described later). Here, as an example, the degree of coincidence of word tendencies is, here, as an example, the number of frequently occurring word matches. The number of frequent word matches is the number of words common to the word tendency information of the target employee and the word tendency information of the educational course. As described above, in the example of FIG. 15, it is described that the number of frequently occurring word matches is “2” as the course recommendation degree information 43 of “course 1” for the target employee.

Subsequently, in step S304, the recommended course estimation unit 223 extracts an educational course in which both the app tendency matching degree and the number of frequently occurring word matching are equal to or higher than a predetermined threshold value as the recommended course for the target employee, and the recommended course information 237. Register with. In FIG. 15, for example, if the threshold value for the app tendency matching degree is 70% and the threshold value for the frequent word matching number is 1, the application tendency matching degree is "85%" and the frequent word matching number is "2". "Lecture 2" is the recommended course.

FIG. 16 is a flowchart of a similar business history extraction process. The similar work history extraction process is a process for extracting other employees whose work related to the designated employee (designated employee) is similar.

In step S401, the human resources search unit 224 extracts the current (for example, the latest past one month) business trend information 233 for the employee (designated employee) designated by the operator of the data processing device 12. Next, in step S402, the human resources search unit 224 calculates, for employees other than the designated employee (other employees), the degree of app tendency matching with the designated employee in the present and the past and the number of frequently occurring word matches. Record as business tendency similarity information.

FIG. 17 is a table showing an example of business tendency similarity information. In the business tendency similarity information 44, the employee ID of another employee with respect to the designated employee, the aggregation disclosure date, the aggregation end date, the application tendency matching degree, and the number of frequently occurring word matches are recorded. For example, an employee whose employee ID is "1001" has an application tendency matching degree of "20" with a designated employee from the aggregation start date "2019/8/1" to the aggregation end date "2019/8/31". % ”, And it is recorded that the number of frequently occurring word matches is“ 0 ”.

In step S403, the human resources search unit 224 extracts other employees whose app tendency matching degree and the number of frequently occurring word matching satisfy predetermined conditions and their periods. For example, other employees whose app tendency matching degree and one or both of the frequent word matching number are equal to or more than a predetermined threshold value and the period thereof may be extracted. In the example of FIG. 17, assuming that the threshold value for the app tendency matching degree is 70% and the threshold value for the frequent word matching number is 1, the aggregation start date “2019/9 /” of the employee whose employee ID is “1002” The period from "1" to the aggregation end date "2019/9/30" and from the aggregation start date "2019/10/1" of the employee whose employee ID is "1002" to the aggregation end date "2019/10/30" The period up to "" is extracted. It is highly probable that during the extracted period, the extracted other employees were involved in work similar to the work in which the designated employee is currently involved.

As described above, the present embodiment can be organized as follows. However, this embodiment is not limited to those shown below.

The human resources analysis system uses a data processing device to analyze the business history information and the data acquisition unit that acquires the business history information, which is the history of operations on the terminal device used by the business operator in the business, and the business operator. Has a business trend analysis department that generates information on the business involved, which is information on the business involved in the past or the business currently involved. As a result, since the history of operations on the terminal device performed by the business operator using the application is analyzed, the past or current business of the business operator can be analyzed concretely and objectively.

In addition, the data acquisition department acquires the usage time information regarding the time used and the window title of the active window for the application, and the business tendency analysis department analyzes the usage time information and the window title, and the involved business information. To generate. In this way, the usage time and window title of the application are acquired and analyzed, so what kind of work the business operator did and how long he / she was involved in, and what kind of work he / she was involved in or was involved in. It is possible to acquire and analyze information that reflects the situation.

In addition, the business tendency analysis unit calculates the ratio of the usage time of each application used in the terminal device based on the usage time information. Since the ratio of the usage time of each application is calculated, it is possible to know what kind of work the business operator has performed and at what ratio, and use it for analysis of the work of human resources.

In addition, the business tendency analysis department extracts a word from the window title and totals the number of occurrences of the word. In this way, from the words extracted from the window title of the application, it is possible to know in detail what kind of work was involved or involved, and to use it for analysis of the work of human resources.

In addition, the data processing device extracts the student's involvement work information based on the work history information of the student who took the education course related to the work, and recommends the education course based on the student's involvement work information. Whether to recommend an education course to the business practitioner based on the recommended condition analysis department that generates the recommended related business information that conditions the target person, and the business practitioner's related business information and recommended related business information. It also has a recommended course estimation unit for determining whether or not it is. This makes it possible to objectively recommend an educational course suitable for the business operator based on the history of operations performed by the application.

In addition, the data acquisition department acquires usage time information regarding the time used for a plurality of applications, and the business tendency analysis department analyzes the usage time information of the business operator to generate information on the business involved in the business operator. By analyzing the usage time information of the students, the recommended work information is generated, and the recommended course estimation department uses each of the multiple applications for the work performer's work information and the recommended work information. Generate an array with the ratio of time as an element, and determine whether to recommend an education course to the business operator based on the distance between the array of the business information involved by the business operator and the array of recommended business information. .. Since it is determined whether or not to recommend an educational course to a business operator based on the inter-array distance of the array whose factor is the ratio of the application usage time, the educational course recommended to the business operator can be quantitatively determined.

In addition, the data acquisition department acquires the window titles of the active windows for a plurality of applications, and the business trend analysis department generates the business information related to the business operator based on the words included in the window titles of the business operator. The recommended involvement work information is generated based on the words contained in the window title of the student, and the recommended course estimation department is based on the degree of matching between the words of the involvement work information of the work performer and the words of the recommended involvement work information. , Judge whether to recommend an educational course to the business operator. Since it is determined whether or not to recommend the educational course to the business operator based on the degree of matching of the words included in the window title, the educational course recommended to the business operator can be quantitatively determined.

Further, the data processing device is based on the information on the business involved in the designated business operator who is the designated business operator and the information on the business involved in the business operator different from the designated business operator, and the data processing device with the designated business operator. It also has a human resources search department that extracts business performers with similar related business. As a result, it is possible to easily extract the business performers involved in the business similar to a certain business performer.

In addition, the human resources search department extracts the business performers whose current or past involved business is similar to the designated business performer, and the time when the business performer was involved in the business. As a result, it is possible to easily extract a business performer who has experience in a business similar to a certain business performer and a period of time involved in the business.

Although the embodiments of the present invention have been described above, the present invention is not limited to these embodiments, and these embodiments may be used in combination within the scope of the technical idea of the present invention. , Some configurations may be changed.

10 ... Human resources analysis system, 11 ... Employee use terminal, 12 ... Data processing device, 19 ... Communication network, 21 ... Data acquisition unit, 22 ... Processing unit, 23 ... Storage unit, 31 ... Processor, 32 ... Main memory, 33 ... Storage device, 34 ... Communication device, 35 ... Input device, 36 ... Display device, 37 ... Bus, 41 ... Questionnaire, 42 ... Relevance information, 43 ... Course recommendation level information, 44 ... Business tendency similarity information, 51 ... Radar chart, 52 ... Radar chart, 221 ... Business trend analysis department, 222 ... Recommended condition analysis department, 223 ... Recommended course estimation department, 224 ... Human resources search department, 231 ... Employee information, 232 ... Business history information, 233 ... Business Trend information, 234 ... Course information, 235 ... Questionnaire result information, 236 ... Recommended condition information, 237 ... Recommended course information

Claims (11)

A data acquisition unit that acquires business history information, which is the history of operations on applications on terminal devices used by business operators in business.
A business tendency analysis department that analyzes the business history information and generates information on the business involved, which is information on the business that the business performer has been involved in in the past or is currently involved in.
Human resources analysis system with. The data acquisition unit acquires usage time information regarding the usage time and the window title of the active window for the application.
The business tendency analysis unit analyzes the usage time information and the window title, and generates the involved business information.
The human resources analysis system according to claim 1. The business tendency analysis unit calculates the ratio of the usage time of each application used in the terminal device based on the usage time information.
The human resources analysis system according to claim 2. The business tendency analysis unit extracts a word from the window title and totals the number of occurrences of the word.
The human resources analysis system according to claim 2. Based on the work history information of the students who have taken the education course related to the work, the information on the work involved of the student is extracted, and the target person who recommends the education course is the condition based on the information on the work involved of the student. The recommended condition analysis department that generates recommended related business information, which is the related business information to be attached,
It further has a recommended course estimation unit that determines whether or not to recommend the educational course to the business practitioner based on the business practitioner's involved business information and the recommended involved business information.
The human resources analysis system according to claim 1. The data acquisition unit acquires usage time information regarding the time used for a plurality of applications, and obtains usage time information.
The business tendency analysis unit generates information on the business involved by the business performer by analyzing the usage time information of the business performer, and analyzes the usage time information of the student to obtain the recommended business information. Generate and
The recommended course estimation unit generates an array having the ratio of the usage time of each of the plurality of applications as an element for the work information involved in the work performer and the recommended work information involved in the work, and the involvement of the work performer. Based on the distance between the arrangement of business information and the arrangement of the recommended involved business information, it is determined whether or not to recommend the educational course to the business performer.
The human resources analysis system according to claim 5. The data acquisition unit acquires the window title of the active window for a plurality of applications.
The work tendency analysis unit generates information on the work involved in the work performer based on the words included in the window title of the work performer, and the recommended work involved work based on the words included in the window title of the student. Generate information,
The recommended course estimation unit determines whether or not to recommend the educational course to the business practitioner based on the degree of agreement between the word of the business information involved by the business operator and the word of the recommended business information. ,
The human resources analysis system according to claim 5. Based on the information on the work involved by the designated work performer who is the designated work performer and the information on the work involved by the work performer different from the designated work performer, the work execution in which the designated work performer and the work involved are similar. It also has a human resources search department that extracts people.
The human resources analysis system according to claim 1. The human resources search unit extracts business performers whose current or past involved business is similar to that of the designated business performer, and the time when the business performer was involved in the business.
The human resources analysis system according to claim 8. Acquires business history information, which is the history of operations on the application in the terminal device used by the business operator in business.
The business history information is analyzed to generate information on the business involved, which is information on the business in which the business performer has been involved in the past or the business in which the business operator is currently involved.
A method of human resources analysis that a computer does. Acquires business history information, which is the history of operations on the application in the terminal device used by the business operator in business.
The business history information is analyzed to generate information on the business involved, which is information on the business in which the business performer has been involved in the past or the business in which the business operator is currently involved.
A human resources analysis program that lets a computer do things.

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