JP7084861B2 - Evaluation processing system and evaluation processing method - Google Patents

Description

The present invention relates to an evaluation processing system and an evaluation processing method. Specifically, the present invention clarifies the influence of maintaining and improving the physical and mental health of employees on corporate performance, and specifically presents it as an actual management measure. Regarding the technology to do.

It is said that the quality of work styles such as employee shifts and work contents in a company will affect the productivity of the company, and there is a movement to take measures such as business improvement by looking at the correlation between the two.

As such a technique, for example, a plurality of data indicating the operating state of a store based on a function given in advance by inputting information indicating an employee's behavioral state that changes with the passage of time in a predetermined real space inside the store. A store support function calculation unit that calculates a plurality of types of store support functions that are indicators, a pattern determination unit that determines which of the output of the store support function matches the type of situation pattern, and the plurality of types of stores. A situation pattern storage unit that records each calculated output value of the support function and the situation pattern as time-series data, a pass / fail correlation information storage unit that records a plurality of preset pass / fail correlation determination patterns, and the employee. A shift pattern storage unit that records time-series data of each shift pattern and its work status, and a productivity improvement information generation unit are provided, and the plurality of types of store support functions are the work status of the employee. The plurality of types of store support functions calculated by the store support function calculation unit, which are composed of data representing the work contents, location allocation, time allocation, motivation / vitality, and sales status of the store. The situation pattern determination unit determines which combination matches the type of the situation pattern, and the productivity improvement information generation unit converts the time-series data of the situation pattern into the pass / fail correlation determination pattern. It is characterized in that a corresponding typical pattern is extracted, the presence or absence of a time-series correlation between the typical pattern and the work status of each employee is determined, and information on the operation improvement of the store is generated using the time-series correlation. A store management information system (see Patent Document 1) and the like have been proposed.

WO2014 / 083656

As shown by the prior art, there was a concept of proposing operational improvement for the company by analyzing the correlation between the contents and conditions of the actual operation of the employees and the sales of the company. In such a conventional concept, the direction of improvement is proposed regarding the operation contents such as employee shifts and work contents that are directly related to the store sales.

On the other hand, in recent years, there is a trend of so-called work style reform, and there is also a movement of "health management" in which companies actively work on maintaining and improving the physical and mental health of employees. However, there was also an aspect in which health management was promoted without clarifying the effect of the physical and mental health of employees on the business performance of the company.

Therefore, an object of the present invention is to clarify the influence of maintaining and improving the physical and mental health of employees on corporate performance, and to provide a technique concretely presented as an actual management measure.

The evaluation processing system of the present invention that solves the above problems includes a storage device that stores health information indicating the health condition of each member in each organization, financial information of each organization, and institutional information for the member. Based on the health information, the system information, and the financial information, the objective variable is the quality of the predetermined financial index in the organization group consisting of the predetermined organizations of each organization, and the implementation items of the predetermined system in the organization group. And the process of generating a regression equation using a predetermined health item as an explanatory variable in the member, and the value of the predetermined item of the health information and the system information in the predetermined organization is set for the regression equation and the said in the organization. It is characterized by including a calculation device for specifying the quality of the financial index, outputting the quality of the financial index and the value of the predetermined item, and executing the process.

Further, the evaluation processing method of the present invention includes information processing including a storage device that stores health information indicating the health condition of each member in each organization, financial information of each organization, and institutional information for the member. By regression analysis based on the health information, the system information, and the financial information, the system sets the quality of the predetermined financial index in the organization group consisting of the predetermined organizations of each organization as the objective variable, and sets the quality of the predetermined system in the organization group as the objective variable. A process of generating a regression equation using a predetermined health item in an action item and a member as an explanatory variable, and setting a value of a predetermined item of the health information and the institutional information in the predetermined organization for the regression equation to the organization. It is characterized in that the quality of the financial index in the above is specified, the quality of the financial index and the process of outputting the value of the predetermined item are executed.

According to the present invention, the influence of maintaining and improving the physical and mental health of employees on corporate performance can be clarified and can be concretely presented as an actual management measure.

It is a network configuration diagram including the evaluation processing system of this embodiment. It is a figure which shows the hardware configuration example of the evaluation processing system of this embodiment. It is a figure which shows the hardware configuration example of the employee terminal of this embodiment. It is a figure which shows the data structure example of the enterprise information table of this embodiment. It is a figure which shows the data structure example of the health information table of this embodiment. It is a figure which shows the data structure example of the activity information table of this embodiment. It is a figure which shows the data structure example of the financial information table of this embodiment. It is a figure which shows the flow example 1 of the evaluation processing method in this embodiment. It is a figure which shows the data structure example of the primary result table in this embodiment. It is a figure which shows the data structure example of the primary aggregation table in this embodiment. It is a figure which shows the data structure example of the primary expectation degree table in this embodiment. It is a figure which shows the data structure example of the secondary result table in this embodiment. It is a figure which shows the data structure example of the secondary aggregation table in this embodiment. It is a figure which shows the data structure example of the secondary expectation degree table in this embodiment. It is a figure which shows the output example 1 in this embodiment. It is a figure which shows the flow example 2 of the evaluation processing method in this embodiment. It is a figure which shows the correction log example of the multiple regression type in this embodiment. It is a figure which shows the output example 2 in this embodiment.

－－－ Network configuration －－－

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. FIG. 1 is a network configuration diagram including the evaluation processing system 100 of the present embodiment. The evaluation processing system 100 shown in FIG. 1 is a computer system that clarifies the influence of maintaining and improving the physical and mental health of employees on corporate performance, and specifically presents it as a management measure based on actual financial indicators. In other words, it is a system that proposes financial improvement advice based on "health management" to the company concerned.

The evaluation processing system 100 in the present embodiment can be assumed to be a server device operated by an organization that may propose management improvement measures to a company, such as a financial institution, a vendor, or a management consultant company.

However, the operation form of the evaluation processing system 100 is not limited, and various forms such as the operation form of the company itself having the intention of improving the management can be adopted.

The evaluation processing system 100 is connected to the corporate system 300 of the above-mentioned company and the financial institution system 400 such as a bank having transactions with the company via an appropriate network 10 such as the Internet so as to be capable of data communication. ..

It is assumed that a company that receives a management improvement measure proposal from such an evaluation processing system 100 acquires various information about its own employees in the corporate system 300 and manages them appropriately.

For example, the result of the health examination that the employee receives every year and the life log obtained from the employee terminal 200 carried by the employee (eg, the number of walks, the walking distance, the calories burned, and the heart rate sensed by the wearable unit). , Blood pressure, activity, sleep, happiness, etc.).

In the present invention, the information related to health and the information related to the life log are collectively defined as health information, but in the present embodiment, the health information 326 and the activity information 327 are shown separately for the sake of simplicity of explanation.

The results of the above-mentioned health examination may include so-called medical big data held by the affiliated health insurance company of the company concerned, and values such as lifestyle-related diseases and hospitalization risk determined based on the data.

In addition, the corporate system 300 of the company also possesses various systems that can be used by employees and information 325 regarding the implementation status thereof. These various systems are so-called welfare programs, and their implementation status may include information such as the frequency and rate of use of the system by employees as well as whether or not it has been introduced.

In addition, the above-mentioned company naturally manages information 328 regarding its financial status. As the information 328 regarding the financial status, for example, sales by year, cost of sales, gross profit, SG & A expenses, and operating profit can be assumed. Information 328 regarding the financial status is also managed as financial information 425 in the financial institution system 400 of the financial institution that has a business with the company.

It is assumed that the evaluation processing system 100 of the present embodiment acquires each information 325 to 328 of such a company from the company system 300 of the company at predetermined intervals, and stores and manages the information in its own storage device 101.
--- Hardware configuration ---
Further, the hardware configuration of the evaluation processing system 100 in this embodiment is as shown in FIG.

That is, the evaluation processing system 100 includes a storage device 101, a memory 103, and an arithmetic unit 10.
4. The input device 105, the output device 106, and the communication device 107 are provided.
Of these, the storage device 101 is composed of an appropriate non-volatile storage element such as an SSD (Solid State Drive) or a hard disk drive.
Further, the memory 103 is composed of a volatile storage element such as a RAM.

Further, the arithmetic unit 104 is a CPU that executes the program 102 held in the storage device 101 by reading it into the memory 103, etc., to perform integrated control of the apparatus itself, and to perform various determinations, arithmetic operations, and control processes.
Further, the input device 105 is a device such as a keyboard, a mouse, and a microphone that accepts key input and voice input from the user.
Further, the output device 106 is a device such as a display or a speaker that displays the processing data in the arithmetic unit 104.

Further, the communication device 107 can be assumed to be a network interface card that is connected to an appropriate network 10 such as the Internet and is responsible for communication processing with other devices such as an employee terminal 200, a corporate system 300, and a bank system 400.
The storage device 101 includes an analysis engine 110 in the program 102 for implementing the functions required for the evaluation processing system of the present embodiment.
The analysis engine 110 includes a correlation analysis engine 1101 and a multiple regression analysis engine 1102.

Of these, the correlation analysis engine 1101 is an engine that statistically analyzes the correlation (when one of the variables changes, the other changes accordingly), and the existing one is appropriately adopted. do it.

Further, the multiple regression analysis engine 1102 is an engine that performs multiple regression analysis, and in the case of the present embodiment, when the quality of the financial index of the company is set as the objective variable, the explanatory variables thereof are used as the various systems and employees of the company. A prediction formula (regression formula) will be obtained as the situation regarding the health of the members. Of course, the existing method of multiple regression analysis and the engine itself may be appropriately adopted.

Further, the storage device 101 includes a company information table 125, a health information table 126, an activity information table 127, a financial information table 128, a primary result table 130, a primary summary table 131, a primary expectation table 132, and a secondary result table 140. At least the secondary aggregation table 141, the secondary expectation table 142, and the regression equation correction log 150 are stored. However, the specific configuration of these various tables will be described later.

Further, FIG. 3 shows an example of the hardware configuration of the employee terminal 200 according to the present embodiment. That is, the employee terminal 200 includes a storage device 201, a memory 203, an arithmetic unit 204, an input device 205, an output device 206, a communication device 207, and a sensor unit 210.
Of these, the storage device 201 is composed of an appropriate non-volatile storage element such as an SSD (Solid State Drive) or a hard disk drive.
Further, the memory 203 is composed of a volatile storage element such as a RAM.

Further, the arithmetic unit 204 is a CPU that executes the program 202 held in the storage device 201 by reading it into the memory 203, etc., to perform integrated control of the apparatus itself, and to perform various determinations, calculations, and control processes.
Further, the input device 205 is a device such as a keyboard, a mouse, and a microphone that accepts key input and voice input from the user.
Further, the output device 206 is a device such as a display or a speaker that displays the processing data in the arithmetic unit 204.

Further, the communication device 207 can be assumed to be a network interface card that is connected to an appropriate network 10 such as the Internet and is responsible for communication processing with other devices such as the corporate system 300. Alternatively, it is possible to assume a case where direct communication with the evaluation processing system 100 is possible.

Further, the sensor unit 210 assumes, for example, a wearable sensor, and the number of walks, walking distance, calories burned, blood glucose level, and activity (eg, conversation, desk work, and number of movements) by the wearer of the wearable sensor, that is, an employee. ), Sleep (eg, wake-up time, bedtime, sleep quality), etc. It is a sensor that observes events. As specific examples of the sensor, for example, an acceleration sensor, a heartbeat sensor, a blood pressure level sensor, a blood pressure sensor, a brain wave sensor, a blood flow sensor, and the like can be assumed in various ways.

Further, the employee terminal 200 is provided with a GPS unit in conjunction with the sensor unit 210 described above, and even if information such as the travel distance, speed, and position of the employee is recorded and held as a life log 225 described later. good.
The storage device 201 stores a life log 225 in addition to the program 202 for implementing the functions required as the employee terminal of the present embodiment.

The life log 225 is an observation value related to various events detected by the above-mentioned sensor unit 210 and the like, and is a source of the activity information table 127 held by the evaluation processing system 100. Therefore, it is assumed that the employee terminal 200 uploads the value of the life log 225 to the evaluation processing system 100 via, for example, the corporate system 300 (or directly) at predetermined intervals.
--- Data structure example ---

Subsequently, the tables used by the evaluation processing system 100 of the present embodiment will be described. However, among the various tables, the company information table 125, the health information table 126, the activity information table 127, and the financial information table 128 shall be shown, and the other tables, that is, the primary result table 130, the primary summary table 131, and the primary expectation degree. The table 132, the secondary result table 140, the secondary summary table 141, the secondary expectation table 142, and the regression equation correction log 150 will be described later.

FIG. 4 shows an example of the company information table 125 in this embodiment. The company information table 125 is a table that stores information mainly related to various systems introduced by the company among various information of the company that receives proposals for improvement measures.

The data structure is a collection of records associated with data such as the type of business, company size, system, welfare, and owned facilities of the company, using the company name and company code as keys.

Of these, system information includes information on the existence and usage of various training systems, childcare systems and in-house incentive systems. In addition, the welfare information includes information on the existence and usage status of systems such as stockholding associations, property accumulation savings, and recreational facilities. In addition, the owned facility information includes information on the existence and usage status of facilities such as cafeterias and sports gyms.

Further, FIG. 5 shows an example of data structure of the health information table 126 of the present embodiment. The health information table 126 is a table that stores information on the health of employees.

The data structure is a record that associates values such as information acquisition date, attributes / inspection values, lifestyle, medication / medical history, and results with values such as employee name, employee number, and company code as keys. Is a collection of.

Of these, the attributes / test values include values such as gender, age, BMI value, glucose metabolism, liver function, and triglyceride. These values are the results of the health examination conducted by the employee at the affiliated health insurance of the company to which the employee belongs, and are obtained from the health information 326 in the company system 300 of the company.

Lifestyles also include values such as smoking cessation, drinking, and exercising. These values are also the results of interviews conducted by the employee in the health examination conducted by the affiliated health insurance company of the company to which the employee belongs, and are obtained from the health information 326 in the company system 300 of the company.

In addition, the medication / medical history is the history of suffering from each of the eight major lifestyle-related diseases and receiving medical examinations and treatments. These values are also the results of interviews conducted by the employee in the health examination conducted by the affiliated health insurance company of the company to which the employee belongs, and are obtained from the health information 326 in the company system 300 of the company.

In addition, the results include values such as the risk of hospitalization by disease, the expected number of days of hospitalization due to the eight major lifestyle-related diseases, and the risk comparison with the health condition. Each value of these results is obtained by performing data analysis on medical big data such as various findings associated with insurance claims of life insurance companies and health insurance-owned health examination results based on artificial intelligence. Of course, for such processing, existing ones may be appropriately adopted, and the processing values may be acquired and utilized as the above-mentioned "result". The above-mentioned artificial intelligence is a combination of various factors such as various test values in health examinations, questions regarding lifestyle-related and medication, and notification items regarding past pre-existing diseases required when enrolling in general life insurance. In addition to predicting the possibility of hospitalization due to the onset of the eight major lifestyle-related diseases and the number of days, the risk is compared with the health condition arbitrarily specified as a standard value.

Further, FIG. 6 shows an example of data configuration of the activity information table 127 of the present embodiment. The activity information table 127 is a table in which information on various activities performed or occurred by employees during a predetermined period is accumulated.

The data structure is a set of records that associate data such as information acquisition date, exercise, activity (during work), sleep, and happiness with values such as employee name, employee number, and company code as keys. The body. These values are measured by the sensor unit 210 in the employee terminal 200 carried by the employee, and are provided to the evaluation processing system 100 by the corporate system 300 that collects the values from the employee terminal 200.

Of the above, the exercise includes the values of items such as the number of walks, the walking distance, and the calories burned as the contents of the exercise performed by the employee. These values are the average value or the median value of a predetermined period such as the latest one month.

In addition, the activity level (during work) includes the number of times of conversation, desk work, and movement that the employee has with a colleague or the like during work. These values are also measured by the sensor unit 210 in the employee terminal 200 carried by the employee, and are provided to the evaluation processing system 100 by the corporate system 300 that collects the values from the employee terminal 200.

Sleep also includes wake-up time, bedtime, and sleep quality values for the employee. The quality of sleep is determined based on a predetermined rule by measuring the sleep cycle (light sleep, deep sleep, REM sleep) with the heart rate monitor and accelerometer of the sensor unit 210 (existing technology). These values are also the sensor unit 21 in the employee terminal 200 carried by the employee.
It is measured at 0 and is provided to the evaluation processing system 100 by the corporate system 300 that collects the values from the employee terminal 200.

The degree of happiness is a value determined by the technique developed by the applicant (Patent No. 5588563). This technique obtains the degree of happiness from the acceleration data obtained by the sensor unit 210 of the employee terminal 200 based on the knowledge that the active state of the tissue appears in the statistical distribution of the unconscious shaking of the human body. It will be calculated.
Further, FIG. 7 shows an example of data configuration of the financial information table 128 of the present embodiment. The financial information table 128 is a table in which financial data of each company is accumulated.

The data structure is a collection of records associated with data such as the target year, sales, cost of sales, gross profit, administrative expenses, and operating profit, using values such as company name and company code as keys.

These values are financial information 328 to financial information 425 managed by the company system 300 of the company or the bank system 400 of the financial institution having a transaction with the company, and the company system 300 or the bank system 400 is the evaluation processing system. It will be provided to 100.
－－－ Flow example 1 －－－

Hereinafter, the actual procedure of the evaluation processing method in the present embodiment will be described with reference to the drawings. Various operations corresponding to the evaluation processing methods described below are realized by a program read by the evaluation processing system 100 into a memory or the like and executed. Then, this program is composed of the code for performing various operations described below.

FIG. 8 is a diagram showing a flow example 1 of the evaluation processing method in the present embodiment. In this case, first, the evaluation processing system 100 refers to the company information table 125, classifies each company based on the values in each column of the industry and the company size, and identifies the company group for each company having the same industry and the company size. (S10). For example, each company whose industry is "manufacturing" and whose company size is "medium" is specified, and a group of companies is specified.

Subsequently, the evaluation processing system 100 extracts the corresponding record from the health information table 126 and the financial information table 128 for each constituent company of a certain company group specified in s10 above, and the value indicated by the record is used as a correlation analysis engine. Input to 1101 to perform correlation analysis (s11).

As a result, it is determined whether or not there is a correlation between each item of the health information table 126 and each item of the financial information table 128 for a certain group of companies having a common industry and company size.

As a result of the above-mentioned s11, the evaluation processing system 100 acquires a correlation between a predetermined financial index in the company group and a predetermined health item in the employees of the company group (s12).

FIG. 9 shows a configuration example of the primary result table 130 in the present embodiment as the correlation information obtained in s12. As shown in the primary result table 130 of FIG. 9, the correlation information indicates whether or not there is a correlation with the upward / downward tendency (good or bad) of financial indicators such as sales increase / decrease and profit increase / decrease. It is a table defined in association with the tendency of the value of a specific item (the existence of a correlation is specified) of the health information table 126 such as a person with a small BMI value / a large number of people and a person with a small number of walks / a large number of walks.

Subsequently, the evaluation processing system 100 refers to the health information table 126 of each company belonging to the above-mentioned company group with respect to the specific item of the health information table 126 in which the existence of the correlation is specified in the above-mentioned primary result table 130. The health trends of employees in each company are tabulated for the above-mentioned specific items (s13).

The evaluation processing system 100 obtains the primary aggregation table 131 illustrated in FIG. 10 by this aggregation. As illustrated in FIG. 10, this primary aggregation table 131 uses the company name and company code of each company belonging to the above-mentioned company group as a key, and the above-mentioned specific item as a "condition", and the employee corresponding to the specific item. It is a collection of records in which the ratio of employees is associated with the ratio of all employees.

Subsequently, the evaluation processing system 100 uses the expected degree of increase / decrease of the financial index as the objective function for the specific item for which the existence of the correlation with the increase / decrease of the financial index is specified, which has been obtained up to s13 described above. Multiple regression analysis with a specific item as an explanatory variable is executed by the multiple regression analysis engine 1102, and a regression equation is generated (s14). The existing technique may be appropriately adopted for this multiple regression analysis method itself.

Further, the evaluation processing system 100 sets the value of a specific item in the current health information table 126 of the company to be processed with respect to the regression equation obtained in s14 described above, and determines the degree of increase / decrease of the current financial index. That is, the degree of expectation is specified (s15).

It should be noted that the following method can also be adopted without performing the multiple regression analysis as described above. For example, the evaluation processing system 100 sets each company in the above-mentioned group of companies according to the tendency of the financial index to rise / fall (eg, sales rise / fall, profit rises / falls, etc.). The conditions in the relevant companies grouped by the classification, that is, the average value or the median value of the values of the specific items in the above-mentioned primary summary table 131 are specified.

Further, the evaluation processing system 100 collates the value of the specific item for each tendency of the financial index obtained in this way to rise / fall with the value of the specific item in the company to be processed, and according to the closeness (achievement degree). Calculate the degree of expectation regarding the rise of the relevant financial index / the trend in the following paragraph.

For example, the value of a specific item of a company that tends to "increase sales" is "ratio of people with low BMI value: 30%, ratio of people with high BMI value: 50%, ratio of people with low number of walks: 50%, walking. When the ratio of people with a large number: 20%, the ratio of people with a small desk work: 50%, the ratio of people with a large number of desk work: 40%, etc., the value of the relevant specific item in a certain processing target company is the above-mentioned "sales". If the value of a specific item of a company that tends to "increase" is 70%, it can be calculated that the expectation of "increasing sales" of the company is 70%.

The result of the expectation degree of each company obtained by s15 is shown in the primary expectation degree table 132 of FIG. In this example, for example, in the current situation of the company "A", the expectation of "increasing sales" is calculated as "70%", and the expectation of "increasing profit" is calculated as "65%". I understand.

Subsequently, the evaluation processing system 100 extracts the corresponding record from the company information table 125 and the financial information table 128 for each constituent company of a certain company group specified in s10 above, and the value indicated by the record is used as a correlation analysis engine. Input to 1101 to perform correlation analysis (s16).

As a result, it is determined whether or not there is a correlation between each item of the company information table 125 and each item of the financial information table 128 for a certain group of companies having a common industry and company size.

As a result of the above-mentioned s16, the evaluation processing system 100 acquires a correlation between a predetermined financial index in the company group and each item related to the system, welfare program, and owned facility in the company group (s17).

FIG. 12 shows a configuration example of the secondary result table 140 in the present embodiment as the correlation information obtained in s17. As shown in the secondary result table 140 of FIG. 12, the correlation information indicates whether or not there is a correlation with the upward / downward tendency (good or bad) of financial indicators such as sales increase / decrease and profit increase / decrease. , There is a sports gym in the owned facility, there is a recreation center in the welfare program, and so on.

Subsequently, the evaluation processing system 100 refers to the company information table 125 of each company belonging to the above-mentioned company group with respect to the specific item of the company information table 125 in which the existence of the correlation is specified in the above-mentioned secondary result table 140. , The system, welfare, and owned facilities of each company are totaled for the above-mentioned specific items (s18).

The evaluation processing system 100 obtains the secondary aggregation table 141 illustrated in FIG. 13 by this aggregation. As illustrated in FIG. 13, this secondary aggregation table 141 corresponds to the specific item with the above-mentioned specific item as a "condition" using the company name and company code of each company belonging to the above-mentioned company group as a key. It is a collection of records that associate the system, welfare, and the existence of owned facilities (which may be the utilization rate). However, this secondary summary table 141 also merges the values of the primary summary table 131, and the corresponding item of the health information table 126 is also included as a specific item.

Subsequently, the evaluation processing system 100 is based on the secondary result table 140 and the secondary summary table 141 obtained in the above-mentioned s17 and s18, and the current state of the current situation regarding the upward / downward tendency of each financial index in each of the above-mentioned companies. Estimate the degree of expectation (s19). The method for estimating the degree of expectation is the same as that described in s14 to s15.

In addition, the regression equation generated here determines the degree of expectation of the rise and fall of the financial index for at least one of the action item and the health item for which the existence of the correlation with the tendency of the rise and fall of the financial index is specified. It is a regression equation with a specific item as an explanatory variable as an objective function.

Subsequently, the evaluation processing system 100 calculates the value of the above-mentioned specific item for improving the tendency of the rise and fall of the financial index based on the regression equation generated by the estimation of the expectation degree in the above-mentioned s19 (s20). ), This is set in the secondary expectation table 142 (FIG. 14).

For example, the above-mentioned regression equation is a function such as the expected degree of sales increase K = ax + by-cz + dw ... (a, b, c, d, ... Are constants. X, y, z, w, ... (Variable to substitute the value of a specific item) If the current expectation of "sales increase" in company "A" is 70%, the corresponding regression equation is used to improve this expectation to 90%. By substituting 90% for the left side K of the above and moving up or down the assigned value of any of the variables corresponding to each specific item on the right side in predetermined steps, the calculation is performed so that the regression equation holds.

Further, when it is assumed that the evaluation processing system 100 improves the above-mentioned tendency of rising / falling financial indicators, the values of specific items in the health information table 126 and the company information table 125, and the above-mentioned degree of expectation. The expected degree and the value of the specific item are output to the output device 106 (s21), and the process is terminated. FIG. 15 shows an example of the screen 1500 to be output here.

The person in charge of the company will browse this screen 1500 and consider and promote the introduction of measures such as setting up a sports gym for employees in order to improve the financial index.
－－－ Flow example 2 －－－
Subsequently, the subsequent processing after the output in the above-mentioned s21 will be described. FIG. 16 is a diagram showing a flow example 2 of the evaluation processing method in the present embodiment.

In this case, the evaluation processing system 100 outputs the value of a specific item for improving the degree of expectation regarding the financial index in the processing in s21, and then the predetermined period in which the improvement measure is considered to have been introduced has elapsed. The values of the specific items of the health information table 126 and the company information table 125 in the company are set in the regression equation obtained in the above-mentioned s19, and the degree of expectation of the financial index is calculated (s25).

Subsequently, in the evaluation processing system 100, the expected degree of the financial index calculated in the above-mentioned s25 is lower than the expected degree (example: 90%) when it is assumed that the improvement is made in the above-mentioned flow example 1. Is determined (s26). It should be noted that, since the judgment is made on the premise that the degree of expectation increases, the judgment content is as follows. However, if the premise is that the degree of expectation decreases, the degree of expectation has increased in this judgment. It may be determined.
As a result of the above determination, when the degree of expectation of the financial index has not decreased (s27: N), the evaluation processing system 100 ends the processing.

On the other hand, when the expectation of the financial index is lowered as a result of the above determination (s27: Y), the evaluation processing system 100 aims at the expectation of the financial index calculated in s25 as a regression equation for the organization. A new regression equation is generated for the company by using the value of the specific item (value of the specific item in the company information table 125 and the health information table 126) of the company at the above-mentioned predetermined time as an explanatory variable as a variable (s28). ).
Further, the evaluation processing system 100 stores the regression equation obtained in the above-mentioned s28 in the storage device (s29).

Subsequently, the evaluation processing system 100 has constants, variables, codes, etc. between the regression equation for the above-mentioned enterprise group (obtained in s19) and the regression equation for the above-mentioned enterprise (obtained in s28). It is determined whether there are different elements with respect to (s30).
As a result of the above determination, when different elements do not exist (s30: N), the evaluation processing system 100 ends the processing.

On the other hand, when a different element exists as a result of the above determination (s30: Y), the evaluation processing system 100 stores the information of the element as the regression equation correction log 150 (s31). FIG. 17 shows a modified log example 150 of the multiple regression equation in this embodiment.

Further, the evaluation processing system 100 determines whether the ratio of the companies that use the regression equation in which the different elements specified in s30 are adopted exceeds the predetermined standard among the companies constituting the above-mentioned company group (s32). ).
As a result of the above determination, when the corresponding ratio is below the predetermined standard (s32: N), the evaluation processing system 100 ends the processing.

On the other hand, as a result of the above determination, when the corresponding ratio exceeds a predetermined standard (s32: Y), the evaluation processing system 100 executes an update process for reflecting the element in the regression equation for the company group (s33). , End the process. At this time, it is preferable to deliver the notification screen 1800 as shown in FIG. 18 to the corporate system 300 of each company constituting the company group to notify the regression type update event.

Although the best mode for carrying out the present invention has been specifically described above, the present invention is not limited to this, and various modifications can be made without departing from the gist thereof.
According to this embodiment, the influence of maintaining and improving the physical and mental health of employees on corporate performance can be clarified and concretely presented as an actual management measure.

The description herein reveals at least the following: That is, in the evaluation processing system of the present embodiment, the arithmetic unit sets the values of the current health information and the predetermined items of the system information in the predetermined organization to the regression equation in the output processing. The quality of the financial index in the above-mentioned is specified, and the value of the predetermined item for improving the quality of the specified financial index to a predetermined value is calculated based on the regression equation. It may be possible to output the value of the predetermined item, the quality of the financial index when the improvement is assumed, and the value of the predetermined item.

According to this, the values of the above-mentioned predetermined items are specifically presented as improvement indicators for health management in the organization, and by extension, the influence of maintaining and improving the physical and mental health of employees on corporate performance becomes clearer. It will be possible to present it concretely as an actual management measure.

Further, in the evaluation processing system of the present embodiment, the arithmetic unit performs a predetermined financial in the organization group by a correlation analysis based on the health information, the system information, and the financial information in the process of generating the regression equation. The correlation between the quality of the index and the implementation item of the predetermined system in the organization group and the predetermined health item in the members was specified, and the existence of the correlation with the quality of the financial index was identified by the correlation analysis. For at least one of the action item and the health item, a regression equation may be generated using the quality of the financial index as an objective function and the item as an explanatory variable.

According to this, prior to the regression analysis, it is possible to identify those having a correlation in the correlation analysis and use them as the target of the regression analysis, and the analysis accuracy can be improved. As a result, the impact of maintaining and improving the physical and mental health of employees on corporate performance will be clarified, and it will be possible to concretely present it as an actual management measure.

Further, in the evaluation processing system of the present embodiment, in the correlation analysis, the arithmetic unit uses the health information and the first correlation analysis based on the financial information to determine the quality of a predetermined financial index in the organization group and the organization. A process for identifying the correlation with a predetermined health item in the members of the group, and a second correlation analysis based on the financial information and the institutional information are performed, and the quality of the predetermined financial index in the organization group and the relevant In the process of specifying the correlation with the action items of the predetermined system in the organization group, and in the process of generating the regression equation, the correlation with the quality of the financial index is performed by the first and second correlation analyzes. For at least one of the action item and the health item for which the existence of the relationship has been identified, a regression equation may be generated with the quality of the financial index as the objective function and the item as the explanatory variable. ..

According to this, after undergoing correlation analysis based on health information and financial information for which specific numerical values can be easily obtained, there is a possibility that specific numerical values cannot be obtained and only the existence or nonexistence of the system can be determined. It is possible to efficiently identify the correlation in consideration of the information acquisition status by performing a two-step analysis such as performing a correlation analysis in consideration of information. As a result, the impact of maintaining and improving the physical and mental health of employees on corporate performance will be clarified, and it will be possible to concretely present it as an actual management measure.

Further, in the evaluation processing system of the present embodiment, the storage device further holds the attribute information of each organization, and the arithmetic device is at least one of the industry and scale indicated by the attribute information in the correlation analysis. Each tissue may be classified based on the above-mentioned tissue group to specify the tissue group.

According to this, it is possible to appropriately deal with the environment in which the behavioral characteristics of employees and the system implementation status are likely to differ depending on the organizational attributes such as the type and scale of the organization, and to make the above-mentioned regression analysis appropriate. As a result, the impact of maintaining and improving the physical and mental health of employees on corporate performance will be clarified, and it will be possible to concretely present it as an actual management measure.

Further, in the evaluation processing system of the present embodiment, the arithmetic unit outputs the value of the predetermined item for improving the quality of the financial index to a predetermined value, and then the health information and the system in the organization at a predetermined time. The value of a predetermined item of information is set in the regression equation to calculate the quality of the financial index, and the quality of the calculated financial index is different from the quality of the financial index when it is assumed that the improvement is made. In this case, as a regression equation for the relevant organization, a regression equation is generated with the quality of the calculated financial index as the objective variable and the implementation items of the predetermined system in the relevant organization at the predetermined time and the predetermined health items of the members as explanatory variables. However, the regression equation may be stored in the storage device.

According to this, the regression equation generated for the organization group is modified to the regression equation peculiar to the organization, and it can be operated for the organization. As a result, the impact of maintaining and improving the physical and mental health of employees on corporate performance will be clarified, and it will be possible to concretely present it as an actual management measure.

Further, in the evaluation processing system of the present embodiment, when a different element exists between the regression equation for the tissue group and the regression equation for the organization, the arithmetic unit uses the information of the element as the regression equation correction log. A process of memorizing and a process of reflecting the element in the regression equation for the tissue group when the ratio of the organizations using the regression equation in which the element is adopted exceeds a predetermined standard in the tissues constituting the tissue group. , May be further executed.

According to this, even if it is a regression analysis result for a tissue group, that is, a regression equation, after a certain period of time, the regression equation elements different from those for the tissue group are the main elements among the organizations constituting the tissue group. It will be possible to respond appropriately to situations such as occupying a position and continue to improve the regression equation for organizational groups. As a result, the impact of maintaining and improving the physical and mental health of employees on corporate performance will be clarified, and it will be possible to concretely present it as an actual management measure.

Further, in the evaluation processing method of the present embodiment, when the information processing system outputs the processing, the values of the predetermined items of the current health information and the system information in the predetermined organization are set for the regression equation. The quality of the financial index in the current state is specified, the value of the predetermined item for improving the quality of the specified financial index to a predetermined value is calculated based on the regression equation, and the quality of the financial index in the current state is calculated. The value of the predetermined item, the quality of the financial index when the improvement is assumed, and the value of the predetermined item may be output.

Further, in the evaluation processing method of the present embodiment, when the information processing system generates the regression equation, a predetermined organization group is subjected to a correlation analysis based on the health information, the system information, and the financial information. The correlation between the quality of the financial index and the implementation item of the predetermined system in the organization group and the predetermined health item in the members was identified, and the existence of the correlation with the quality of the financial index was identified by the correlation analysis. For at least one of the action item and the health item, a regression equation may be generated using the quality of the financial index as an objective function and the item as an explanatory variable.

Further, in the evaluation processing method of the present embodiment, when the information processing system performs the correlation analysis, the quality of the predetermined financial index in the organization group is determined by the first correlation analysis based on the health information and the financial information. A process for identifying the correlation with a predetermined health item in the members of the organization group, and a second correlation analysis based on the financial information and the institutional information are performed, and the quality of the predetermined financial index in the organization group and the quality of the predetermined financial index are determined. In the process of specifying the correlation with the action items of the predetermined system in the organization group, and in the process of generating the regression equation, the quality of the financial index is determined by the correlation analysis of the first and the second. For at least one of the action item and the health item for which the existence of the correlation has been identified, a regression equation may be generated with the quality of the financial index as the objective function and the item as the explanatory variable.

Further, in the evaluation processing method of the present embodiment, the information processing system further holds the attribute information of each organization in the storage device, and at least one of the industry and scale indicated by the attribute information in the correlation analysis. Each tissue may be classified based on the above to specify the tissue group.

Further, in the evaluation processing method of the present embodiment, after the information processing system outputs the value of the predetermined item for improving the quality of the financial index to a predetermined value, the health information in the organization at a predetermined time and the said. The value of the predetermined item of the system information is set in the regression equation to calculate the quality of the financial index, and the quality of the calculated financial index is the quality of the financial index when it is assumed that the improvement is made. If they are different, as a regression equation for the organization, a regression equation is used with the quality of the calculated financial index as the objective variable and the implementation items of the predetermined system in the organization at the predetermined time and the predetermined health items of the members as the explanatory variables. It may be generated and the regression equation is stored in the storage device.

Further, in the evaluation processing method of the present embodiment, when the information processing system has a different element between the regression equation for the tissue group and the regression equation for the organization, the information of the element is input to the regression equation correction log. And the process of reflecting the element in the regression equation for the tissue group when the ratio of the organization using the regression equation in which the element is adopted exceeds a predetermined standard in the organization constituting the tissue group. And may be further executed.

10 Network 100 Evaluation processing system 101 Storage device 102 Program 103 Memory 104 Computing device 105 Input device 106 Output device 107 Communication device 110 Analysis engine 1101 Correlation analysis engine 1102 Multiple regression analysis engine 125 Company information table 126 Health information table 127 Activity information table 128 Financial information table 130 Primary result table 131 Primary summary table 132 Primary expectation table 140 Secondary result table 141 Secondary expectation table 142 Secondary expectation table 150 Regressive correction log 200 Employee terminal 201 Storage device 202 Program 203 Memory 204 Calculation Device 205 Input device 206 Output device 207 Communication device 210 Sensor unit 225 Life log 300 Corporate system 325 Corporate information 326 Health information 327 Activity information 328 Financial information 400 Bank system 425 Financial information

Claims (14)

A storage device that stores health information indicating the health status of each member in each organization, financial information of each organization, and institutional information for the member.
By regression analysis based on the health information, the system information, and the financial information, the quality of the predetermined financial index in the organization group consisting of the predetermined organizations of each organization is set as the objective variable, and the action items of the predetermined system in the organization group and the implementation items of the predetermined system in the organization group. The process of generating a regression equation using a predetermined health item as an explanatory variable in the members, and the value of the predetermined item of the health information and the system information in the predetermined organization are set for the regression equation and the finance in the organization. A calculation device that identifies the quality of the index and executes the process of outputting the quality of the financial index and the value of the predetermined item.
An evaluation processing system characterized by including. The arithmetic unit is
In the process of outputting, the value of the current health information and the predetermined item of the system information in the predetermined organization is set for the regression equation to specify the quality of the current financial index, and the specified financial index is specified. When the value of the predetermined item for improving the quality of the predetermined item is calculated based on the regression equation, the quality of the financial index in the current state, the value of the predetermined item, and the improvement are assumed. It outputs the quality of the financial index and the value of the predetermined item.
The evaluation processing system according to claim 1. The arithmetic unit is
In the process of generating the regression equation, the quality of the predetermined financial index in the organization group and the action items and composition of the predetermined system in the organization group are analyzed by the correlation analysis based on the health information, the system information and the financial information. The finance for at least one of the action item and the health item for which the correlation with a predetermined health item in the member is specified and the existence of the correlation with the quality of the financial index is identified by the correlation analysis. A regression equation is generated with the quality of the index as the objective function and the above item as the explanatory variable.
The evaluation processing system according to claim 1. The arithmetic unit is
In the correlation analysis,
The process of identifying the correlation between the quality of a predetermined financial index in the organization group and the predetermined health item in the members of the organization group by the first correlation analysis based on the health information and the financial information, and the above-mentioned. A second correlation analysis based on the financial information and the system information is performed, and a process of identifying the correlation between the quality of the predetermined financial index in the organization group and the action item of the predetermined system in the organization group is executed.
In the process of generating the regression equation,
The objective function is the quality of the financial index for at least one of the action item and the health item for which the existence of a correlation with the quality of the financial index is identified by each of the first and second correlation analyzes. And generate a regression equation with the above items as explanatory variables.
The evaluation processing system according to claim 3, wherein the evaluation processing system is characterized in that. The storage device is
Further retain the attribute information of each organization,
The arithmetic unit is
In the correlation analysis, each organization is classified based on at least one of the type of industry and the scale indicated by the attribute information, and the organization group is specified.
The evaluation processing system according to claim 3 , wherein the evaluation processing system is characterized in that. The arithmetic unit is
After outputting the value of the predetermined item for improving the quality of the financial index to a predetermined value, the value of the predetermined item of the health information and the system information in the organization at a predetermined time is set in the regression equation and described above. If the quality of the financial index is calculated and the quality of the calculated financial index is different from the quality of the financial index when the improvement is assumed, the calculated financial index is used as a regression equation for the organization. A regression equation is generated with pass / fail as the objective variable and the implementation items of the predetermined system in the organization at the predetermined time and the predetermined health items of the members as explanatory variables, and the regression equation is stored in the storage device.
The evaluation processing system according to claim 2, wherein the evaluation processing system is characterized in that. The arithmetic unit is
When there is a different element between the regression equation for the tissue group and the regression equation for the organization, the process of storing the information of the element as the regression equation correction log and the process of storing the information of the element as the regression equation correction log.
When the ratio of tissues using the regression equation in which the element is adopted exceeds a predetermined standard among the tissues constituting the tissue group, the process of reflecting the element in the regression equation for the tissue group is performed.
Is to further execute,
The evaluation processing system according to claim 6, wherein the evaluation processing system is characterized in that. An information processing system including a storage device that stores health information indicating the health status of each member in each organization, financial information of each organization, and institutional information for the member.
By regression analysis based on the health information, the system information, and the financial information, the quality of the predetermined financial index in the organization group consisting of the predetermined organizations of each organization is set as the objective variable, and the action items of the predetermined system in the organization group and the implementation items of the predetermined system in the organization group. Processing to generate a regression equation with a predetermined health item as an explanatory variable in the members,
For the regression equation, the values of the predetermined items of the health information and the system information in the predetermined organization are set, the quality of the financial index in the organization is specified, and the quality of the financial index and the value of the predetermined item are output. And the processing to do
An evaluation processing method characterized by executing. The information processing system
In the process of outputting, the value of the current health information and the predetermined item of the system information in the predetermined organization is set for the regression equation to specify the quality of the current financial index, and the specified financial index is specified. When the value of the predetermined item for improving the quality of the predetermined item is calculated based on the regression equation, the quality of the financial index in the current state, the value of the predetermined item, and the improvement are assumed. Outputs the quality of the financial index and the value of the predetermined item.
The evaluation processing method according to claim 8, wherein the evaluation processing method is characterized by the above. The information processing system
In the process of generating the regression equation, the quality of the predetermined financial index in the organization group and the action items and composition of the predetermined system in the organization group are analyzed by the correlation analysis based on the health information, the system information and the financial information. The finance for at least one of the action item and the health item for which the correlation with a predetermined health item in the member is specified and the existence of the correlation with the quality of the financial index is identified by the correlation analysis. Generate a regression equation with the quality of the index as the objective function and the above item as the explanatory variable.
The evaluation processing method according to claim 8, wherein the evaluation processing method is characterized by the above. The information processing system
In the correlation analysis,
The process of identifying the correlation between the quality of a predetermined financial index in the organization group and the predetermined health item in the members of the organization group by the first correlation analysis based on the health information and the financial information, and the above-mentioned. A second correlation analysis based on the financial information and the system information is performed, and a process of identifying the correlation between the quality of the predetermined financial index in the organization group and the action item of the predetermined system in the organization group is executed.
In the process of generating the regression equation,
The objective function is the quality of the financial index for at least one of the action item and the health item for which the existence of a correlation with the quality of the financial index is identified by each of the first and second correlation analyzes. And generate a regression equation with the above items as explanatory variables.
The evaluation processing method according to claim 10, wherein the evaluation processing method is characterized in that. The information processing system
In the storage device, the attribute information of each of the tissues is further retained, and the attribute information is further retained.
In the correlation analysis, each organization is classified based on at least one of the type of industry and the scale indicated by the attribute information, and the organization group is specified.
The evaluation processing method according to claim 10 , wherein the evaluation processing method is characterized in that. The information processing system
After outputting the value of the predetermined item for improving the quality of the financial index to a predetermined value, the value of the predetermined item of the health information and the system information in the organization at a predetermined time is set in the regression equation and described above. If the quality of the financial index is calculated and the quality of the calculated financial index is different from the quality of the financial index when the improvement is assumed, the calculated financial index is used as a regression equation for the organization. A regression equation is generated with pass / fail as the objective variable and the implementation items of the predetermined system in the organization at the predetermined time and the predetermined health items of the members as explanatory variables, and the regression equation is stored in the storage device.
The evaluation processing method according to claim 9, wherein the evaluation processing method is characterized by the above. The information processing system
When there is a different element between the regression equation for the tissue group and the regression equation for the organization, the process of storing the information of the element as the regression equation correction log and the process of storing the information of the element as the regression equation correction log.
When the ratio of tissues using the regression equation in which the element is adopted exceeds a predetermined standard among the tissues constituting the tissue group, the process of reflecting the element in the regression equation for the tissue group is performed.
To execute further,
13. The evaluation processing method according to claim 13.

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