JP2009146257A - Risk analysis device, risk analysis system and risk analysis program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a risk analysis device, capable of easily performing accurate risk analysis on personnel management and business management with high objectivity and high stability. <P>SOLUTION: In the risk analysis device, based on the number of working days and working hours of attendance data in a predetermined period, scores are assigned to data having a predetermined threshold or more of daily data and continuous analysis data satisfying a predetermined condition, and the total of the scores assigned to the daily unit data and the total of the scores assigned to the continuous analysis data are displayed in association with each other. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to a risk analysis apparatus, a risk analysis system, and a risk analysis program for analyzing risks in labor management and business management, and more particularly, to performing the risk analysis based on employee attendance data.

  In recent years, there has been a growing need for risk analysis based on appropriate labor management in order to prevent problems such as a decline in employee retention, frequent deaths from overwork, and whistleblowing accompanying the enforcement of the Whistleblower Protection Act. Yes. Proper labor management also contributes to risk analysis in business management because it leads to optimization of labor costs, improvement of labor productivity, and reduction of labor share.

  Conventionally, as a technology for performing such risk analysis, work shift data management means for each employee, work result data management means for summing up and managing each employee's attendance time, and satisfying predetermined labor standards There has been proposed an attendance management system having warning means for issuing a warning when there are employees who are not present (see, for example, Patent Document 1).

As another conventional technology, as a technology for risk analysis from the viewpoint of employee health management, a health record database that stores employee health check results and an organization for identifying each employee's affiliation or supervisor Organization information acquisition means for acquiring information, work status acquisition means for acquiring the work status of employees such as working hours records, and communications connecting to each employee, employee's boss, and employee health manager Has been proposed (for example, see Patent Document 2).
JP-A-2003-150756 (claim 1) JP 2003-256578 A (Claim 1)

  By the way, the various labor management problems, that is, risks, can be seen by referring to specific cases such as labor court cases, in addition to the fact that the total working days and total working hours in a given period are important. How often the load was continuous is often an important issue.

  For example, even if there are several days of statutory midnight work in a month, the outcome of the trial varies depending on whether it occurs continuously or intermittently.

  Therefore, in addition to quantitative data such as the total number of working days and total working hours within a given period, the above risk analysis uses factors such as how the work load is continuously generated for the employee. In addition, it is necessary to analyze from various perspectives.

  However, the above prior art has a problem that the accuracy of risk analysis is rough because it is based only on quantitative data such as the total working days and the total working hours.

  Multifaceted risk analysis is possible by consulting with specialists such as social insurance laborers and lawyers, but it is not only costly to request such analysis regularly and continuously, Because it depends on the know-how, ability, and constant information gathering ability of these specialists, objective and stable analysis has not always been obtained. In particular, if the above experts request submission of various related materials in addition to attendance data, it takes time and effort to analyze the analysis, so that the expert who is requesting the analysis as well as the above specialist has a more specialized analysis. There was also a problem that the workload in the previous stage leading to was increased.

  Therefore, in view of the above problems, the present invention provides a risk analysis apparatus, a risk analysis system, and a risk analysis program that easily perform labor analysis and business management risk analysis with high accuracy, objectivity, and stability. This is the issue.

In order to solve the above problems, a risk analysis apparatus according to the present invention is a risk analysis apparatus that analyzes risks in labor management and business management from employee time data, and at least a number that identifies each employee. Alternatively, a plurality of predetermined conditions are set on a daily basis with respect to time data input means comprising the name and the attendance date and time of each employee in a predetermined period, and the working time or number of working days of the attendance data. A threshold is set for each of the first extraction condition, the second extraction condition for setting a predetermined number of continuous times or continuous days for each first extraction condition, and each of the first extraction condition and the second extraction condition. Extraction condition storage means for storing a predetermined score set for each extraction condition in correspondence with a value having a value equal to or greater than a threshold value, and the time data input by the input means and the Based on the first extraction condition read from the output condition storage means, daily unit data generation means for generating daily unit data, and read from the extraction condition storage means based on the daily unit data Continuity analysis data generation means for generating data that matches the second extraction condition, aggregation processing means for aggregating the number of days or time of the daily unit data and continuity analysis data, The predetermined score is assigned to data that is equal to or greater than each threshold set in the first and second extraction conditions, and the total of the points given to the data that belongs to the first extraction condition and the data that belongs to the second extraction condition It is characterized by having a scoring processing means for calculating each of the given points, and a display data generating means for displaying the two calculated total scores in correlation with each employee.

  According to this configuration, just by entering normal attendance data, quantitative data such as total working days and total working hours, and how the work load is continuously generated for the employee, From this data, it is possible to provide display data that visualizes risk analysis in terms of labor management and business management for individual employees.

  In the risk analysis, the first or second extraction conditions have different degrees of importance in view of the Labor Standards Act, notifications, decisions based on examination requests, precedents, labor trials, response cases, and the like. Therefore, the predetermined score may be set by weighting each of the first and second extraction conditions based on at least the Labor Standards Act, notification, decision by examination request, precedent, labor trial, and corresponding case. .

  The risk analysis must analyze the current situation when a predetermined period expires. Therefore, the second type extraction condition may include a predetermined condition that is continuous for two days or more at the end of the predetermined period.

  The display data generating means takes a total number of points assigned to data belonging to the first extraction condition on the vertical axis, and a coordinate plane taking the total number of points assigned to data belonging to the second extraction condition on the horizontal axis. Is divided into four equal quadrants and divided into first to fourth quadrants, and the degree of risk is grouped in each quadrant, and the score of each employee calculated by the scoring means is on the coordinate plane. It is also possible to generate display data plotted in the above. By generating such display data, it is possible to visualize the identification of employees who are under work load.

Conditions and thresholds that need to be warned in terms of labor management or business management from the working hours or the number of working days based on the above extraction conditions based on the Labor Standards Act, notification, decision by examination request, precedent, labor trial, and response cases Comment storage means for adding a plurality of third extraction conditions set to the above, and associating at least a warning data composed of indications of problems and countermeasure comments with a single or a plurality of combinations of the third extraction conditions The display data generation unit may read the corresponding warning data to generate warning display data.

The warning data may include information related to employee health management and information related to improvement in motivation against a decrease in employee morals.

When the employees who are attending time management are divided into a plurality of groups (for example, in the case of multi-store management, etc.), the input means together with the attendance data of the employees belonging to each group, the age data of each employee, The position data including part, part-time job and data specifying this group are input, and the display data generating means calculates the total working time data and the average working time data for each group together with the risk analysis regarding each employee. To generate labor distribution data by job title and age.

The display data generation means generates data for displaying a transition of overtime hours within a predetermined period of employees belonging to the group and data for newly displaying a list of persons to whom social insurance is applied from working hours. It may be a thing.

In the risk analysis system according to the present invention, the risk analysis device functions as a risk analysis server that can be connected to a communication network such as the Internet, and the risk analysis server is connected from a client terminal via the communication network. The time data, age data, job title data, data specifying a group are received, and the display data generating means transmits / receives the generated display data; the received time data, age data, job title data; And a format conversion means for converting data for identifying the group into a format that can be analyzed by the risk analysis server.

According to this configuration, the user who desires risk analysis can receive the display data indicating the risk analysis result only by transmitting the attendance data of the form used by the user.

A risk analysis program according to the present invention causes a computer to function as the risk analysis device or the risk analysis server.

  As is clear from the above description, the risk analysis apparatus, risk analysis system, and risk analysis program according to the present invention are highly accurate, objective, and highly stable in labor management and business management from minimum attendance data. The risk analysis can be easily performed.

  In other words, the extraction conditions based on the legal background and specific cases are quantitative data such as total working days and total working hours, and how the work load is continuously generated for the employee. It is possible to visualize and display the results of multi-dimensional analysis from continuous data. For example, there is a possibility of inviting employees with reluctance, accidents, overwork, and moral down to work without any sharpness. This has the effect of being able to accurately identify employees who have a certain working style.

  In addition, from the viewpoint of labor management in multi-store management, it is possible to provide data indicating indicators related to management analysis such as appropriate labor costs.

  Further, for social insurance laborers and lawyers, if the analysis is performed on the premise of the display data, it is possible to efficiently perform analysis with higher expertise.

FIG. 1 is a hardware configuration diagram of a risk analysis apparatus or a risk analysis server 1 (hereinafter collectively referred to as “risk analysis server 1”) according to the present invention.

The risk analysis server 1 includes a CPU 11 that controls program execution, data reception, calculation, processing, and output, a memory 12 that temporarily stores data processed by the CPU 11, programs used for processing, and an application. An OS 131 that provides basic functions that are commonly used in programs, the hard disk 13 that stores the risk analysis program 132 according to the present invention and the database 133 that is used in the present invention, input of attendance data that will be described later, and the like And an input unit 15 for displaying the data processed by the risk analysis program 132.

When the risk analysis server 1 is used in a stand-alone manner (that is, when used as a risk analysis device), it can be processed with the above configuration, but the risk analysis server 1 is used as a risk analysis system described later. Includes a transmission / reception unit 14.

FIG. 2 is a functional block diagram of the risk analysis system according to the present invention. For clarity of explanation, a part of the hardware configuration diagram of FIG. 1 is omitted, the same components are denoted by the same reference numerals, and detailed description thereof is omitted.

  The risk analysis system according to the present invention is a client-server type system in which the risk analysis server 1 is directly connected to the client terminals C1, C2,... The client terminal C1, C2,... Cn may be connected to the risk analysis server 1 via the Internet network I.

The attendance data transmitted from the client terminals C1, C2... Cn to the risk analysis server 1 via the Internet I is received by the transmission / reception unit 14 and can be processed by the format conversion unit 1321 on the risk analysis server 1. Convert to
The attendance data transmitted from the client terminals C1, C2,... Cn by the format conversion unit 1321 may be electronic data and need not be in a specific format. Therefore, on the client side, in order to use this system, it is only necessary to have an environment in which the company's attendance data can be transmitted via the Internet network I, and it is not particularly necessary to construct a new system.

  As for the attendance data subjected to the format conversion, necessary data is extracted from the extraction condition table database 1331 of the database 133, and the data generation unit 1322 generates data necessary for risk analysis within a predetermined period. The data is totaled and scored by the calculation unit 1323, and display data for displaying the risk analysis result is generated by the display data generation unit 1324.

  The generated display data is transmitted from the transmission / reception unit 14 to the client terminals C1, C2,... Cn via the Internet network I.

  The data generation unit 1322 includes a daily unit data generation unit 1322a, a continuity analysis data generation unit 1322b, and a current state analysis data generation unit 1322c.

  The daily unit data generation unit 1322a selects a condition for extracting quantitative data such as working days and working hours from the format-converted attendance data in the extraction condition table database 1331, as will be described later. Data is generated according to this condition.

  The continuity analysis data generation unit 1322b selects a condition for extracting data having a predetermined number of continuous times or continuous days based on the generated daily unit data in the extraction condition table database 1331 as described later. The data is generated according to this condition.

  The current state analysis data generation unit 1322c selects, from the extraction condition table database 1331, a condition for extracting data that is continuous two or more times at the end of the predetermined period from the generated continuity analysis data, Data is generated according to this condition.

  The calculation unit 1323 includes, from the data generated by the data generation unit 1322, a totaling processing unit 1323a that totals each working day and working time, and a predetermined result set for each extraction condition in the extraction condition table database 1331 as a result of the totalization. A score is set for data that exceeds the threshold, and the total score given to the daily unit data and the total score given to the continuity analysis data and current status analysis data are calculated. And a processing unit 1323b.

  From the scored data, the risk map generation unit 1324a of the display data generation unit 1324 generates display data that visualizes the risk analysis result for the employee, and the display data is transmitted to the client via the Internet network I by the transmission / reception unit 14. Transmit to terminals C1, C2... Cn.

  In addition, in the data generation unit 1322, in addition to the extraction condition for the daily unit data (first extraction condition) and the extraction condition for the continuity analysis data (second extraction condition) including the extraction condition for the current analysis data, A data extraction condition (third extraction condition) for displaying a warning (risk alarm) foreseeing risk occurrence is also generated from the attendance data (not shown).

  Similar to the first and second extraction conditions, the third extraction condition is a component of the extraction condition database 1331, and a predetermined threshold value and a score when the threshold value is exceeded are set. With respect to the third extraction condition, the total processing unit 1323a totals the number of working days in the predetermined period, and the scoring processing unit 1323b assigns a score to data having a numerical value equal to or higher than the threshold value, and the total score is calculated. The database 133 includes a comment table database 1332 in which the comment of the risk alarm corresponds to the contents of the third extraction condition having a calculated total score and a numerical value equal to or greater than a threshold, and has a numerical value equal to or greater than the total score and the threshold. The corresponding comment is read from the comment table database 1332 based on the three extraction conditions, the risk alarm data is generated by the risk alarm generation unit 1324b of the display data generation unit 1324, and the client terminal C1 is transmitted from the transmission / reception unit 14 via the Internet I. , Send to C2 ... Cn.

  FIG. 2 shows a functional block diagram when analyzing data of individual employees. However, when employees who manage attendance are divided into multiple groups, such as when managing multiple stores, group ( (Store) unit analysis is required. FIG. 3 shows a functional block diagram of this multi-store type risk analysis server. For the sake of clarification, a part of the functional block diagram of FIG. 2 is omitted, the same components are denoted by the same reference numerals, and detailed description thereof is omitted.

  The client side shows only the client terminal C1, and store terminals S1, S2,... Sn are further connected to the client terminal C1 so that they can communicate with each other. From each store terminal S1, S2,... Sn, attendance data for each store is transmitted to the client terminal C1 together with data that allows the store to specify. The attendance data for each store is collected by the client terminal C1 and transmitted to the risk analysis server 1 via the Internet network I. As in FIG. 2, it may be transmitted via an ASP server. Also, attendance data may be transmitted directly from the shop terminals S1, S2,... Sn to the risk analysis server 1.

The risk analysis server 1 receives attendance data and the risk analysis of each employee is the same as in FIG.

In the data analysis of individual employees described with reference to FIG. 2, the total result calculated by the calculation unit 1323 is transferred to the store data collection unit 1325 in units of stores. The collected store data is generated by the store display data generation unit 1326 to display store display data for displaying the risk analysis result for each store, and is transmitted from the transmission / reception unit 14 to the client terminal C1 via the Internet I.

FIG. 4 is a diagram showing a processing flow (risk map generation processing flow) of the risk analysis system according to the present invention. Hereinafter, description will be made with reference to FIGS. 2 and 5 to 11 as appropriate.

The risk analysis server 1 receives attendance data created in the format of each client from the client terminals C1, C2,... Cn (S1). The format of each client may be any format as long as it is electronic data. For example, an attendance data list may be attached to an e-mail and transmitted.

It should be noted that the minimum necessary items in the attendance data to be processed by the analysis server 1 are “employee number or name” for identifying the employee, and attendance and departure as shown by the original attendance data L in FIG. “Time stamping date” and “Time stamping time” indicating the time stamped at work and the time stamped at work for each time stamped. In the present embodiment, both the employee number and the name are shown as items for identifying the employee, but either may be used as described above.

The risk analysis server 1 that has received the attendance data is automatically converted into a format that can be processed by the risk analysis program 132 described with reference to FIG. 1 by the format conversion unit 1321 (S2).

The time data after the format conversion has a format as shown by the processing time data 1321 in FIG. 6, for example. That is, it includes an employee number N, a name U, a date D, an attendance stamp I, and an attendance stamp O, and a list of attendance and attendance for a specific employee for a predetermined period is generated.

In the present embodiment, the employee number is “999991” and the name is “Test 1”, and the predetermined period is from July 28, 2007 to August 26, 2007. For example, on July 28, 2007, the attendance time stamp is 10:28 and the retirement time stamp is 22:35.

In order to perform risk analysis processing by the data generation unit 1322 of the risk analysis server 1, various conditions are selected and read from the extraction condition table database 1331 from the processing time data 1321 (S 3).

As illustrated in FIG. 1331a, extraction condition 1331b, score 1331c, amount 1331d, continuity 1331e, and warning 1331f. The extraction conditions are set based on the Labor Standards Act, notification, decision by request for examination, precedent, labor trial, response case, etc., cause of employee retirement, accident, overwork, moral down, etc. , Set working days. These extraction conditions can be added and modified sequentially, reflecting legal revisions, new cases, etc. In addition, the extraction condition can be appropriately selected according to the priority point for risk analysis on the client side.

  In the present embodiment, the condition No. As for 1331a, 6, 7, 8, 17, 19, 30, 37, 39, 55, 59, 68 are selected.

The extraction condition 1331b is, for example, the condition No. 6 “Working between 22:00 and 29:00 is 5 times or more”, condition no. 7 “Working days are 22 days or more”, condition no. 37, “the maximum number of consecutive working days is 6 days or more”, and a condition and a threshold value for this condition.

As will be described later, the score 1331c is a score assigned to data exceeding the threshold value of the extraction condition 1331b. The score is determined according to the Labor Standards Act, notification, request for examination, precedent, labor referee, and corresponding cases. Based on this, each extraction condition is set by weighting.

As will be described later, the amount 1331d is an extraction condition used for aggregation of data on a daily basis, and the extraction condition indicated as “Yes” in this column (in this embodiment, condition No. 7, 8, 17, 30, 68) (hereinafter, this condition is referred to as “first extraction condition”).

  As will be described later, the continuity 1331e is an extraction condition used for the aggregation of continuous data corresponding to a predetermined condition. In this embodiment, the extraction condition displayed as “Yes” (in this embodiment, Condition No. 37, 39, 55, 59, 68) is applicable (hereinafter, this condition is referred to as “second extraction condition”).

  The warning 1331f is an extraction condition that is used to generate risk alarm data, which will be described later, when a predetermined condition is met, and an extraction condition (in this embodiment, “Yes” in this column). , Condition Nos. 6, 19, and 55) (hereinafter, this condition is referred to as “third extraction condition”).

  Returning to FIG. 4, among the selected extraction conditions, first, daily unit data is generated by the daily unit data generation unit 1322a.

  Regarding the daily unit data, as described above, in this embodiment, the condition No. 7, 8, 17, 30, and 68 are selected, and the working days, working hours, and the like are calculated from each data of the processing time data 1321 according to these conditions.

  FIG. 7 shows an example of generated daily unit data. In addition to the employee number N, name U, attendance stamp I, and attendance stamp O (date D is listed in attendance stamp I and attendance stamp O) in the processing time data 1321, the selected conditions A table R is provided. The conditions used for daily unit data generation are the range of R1 surrounded by the thick line in the condition table R, that is, the condition 7, the condition 8, the condition 17, the condition 19, and the condition 30.

Hereinafter, a data generation example will be described for condition 7 “the working days are 22 days or more” and condition 8 “the total working hours is 205 hours or more” on July 28, 2007.

  Since work is on July 28, 2007, condition 7 is counted as “1 working day” and recorded as “1”. Condition 8 is that the attendance time is 10:23 and the leaving time is 22:35, and one hour of lunch break is deducted. Therefore, the working hours of this day are counted as “11.2 hours”. Therefore, “11.2” is recorded. Thereafter, recording is performed by the same processing method, and the same processing is performed for other conditions according to each condition.

In FIG. 4, when the daily unit data is generated, the tabulation processing unit 1323a calculates the tabulated value of the corresponding extraction condition within the period during which risk analysis is performed, that is, the predetermined period (S5). As shown in FIG. 10, the total data includes the employee number N, the user name U, the total start date Ds, the total end date De, the condition number. R and the total value T correspond to each condition No. The total value corresponding to is calculated. The period from the aggregation start date Ds to the aggregation end date De corresponds to the risk analysis period (the predetermined period). For example, when the aggregation start date Ds is July 27, 2007 and the aggregation end date De is August 26, 2007, the total value of the working days of condition 7 is 26 (excluding Saturdays and Sundays) Therefore, 26 is recorded in the total value T column, and the total working time of the condition 8 is 291.81 hours, so that 291.81 is recorded in the total value T column. Thereafter, the aggregation processing of other daily unit data is performed in the same manner, and the data is recorded in the aggregation value T column.

  Returning to FIG. 4, when each aggregate value is calculated, it is determined whether or not each aggregate value is equal to or greater than the threshold value indicated in the condition extracted in S3 (S6). The threshold value of the extraction condition is, for example, that in condition 7, the total number of working days is “22 days or more”, and in condition 8, the total working time is “205 hours or more”.

  When the total value is less than the threshold value, the daily unit data is excluded from the items to be considered for risk analysis, and the process is terminated. On the other hand, if the total value is equal to or greater than the threshold value, the scoring processing unit 1323b assigns a score (see FIG. 5) associated in advance in the extraction condition table (S7). In the present embodiment, for example, when the condition 7 is equal to or greater than the threshold value, a score of 5 is recorded in the score P column of FIG. If condition 8 is equal to or greater than the threshold value, a score of 5 is recorded in the score P column of FIG.

  The scoring processing unit 1323b calculates the sum of the points given to the daily unit data extraction condition that is equal to or higher than the threshold (S8).

When the second extraction condition is selected in S3, continuity analysis data is generated based on the daily unit data generated in S4 (S9). The continuity analysis data is extracted by the continuity analysis data generation unit 1322b from the continuous data within the predetermined period, and by the current state analysis data generation unit 1322c, the expiration date of the predetermined period, that is, the most recent state. Data indicating continuity is also extracted.

  In the present embodiment, first, FIG. 8 shows that continuity analysis data R2 (condition 37, condition 68) is selected. FIG. 9 shows that the current state analysis data R3 (condition 39, condition 55, condition 59) is selected. For example, in condition 37 of FIG. 8, there is “continuous working days”, so the number of days is counted sequentially from the first day of the predetermined period, and the count becomes “6” on August 2, but the next working day is Since it will be August 4, the count will be restarted from 1. Since condition 39 in FIG. 9 is “the most recent number of consecutive working days”, when the number of consecutive working days is counted on the expiration date of the predetermined period, that is, August 26, 2007, August 14 From August to August 26, the worker has worked for 13 consecutive days, so “13” is recorded in the August 26 column of the expiration date of condition 39.

  When the continuity analysis data is generated in S9, the tabulation processing unit 1323a calculates the tabulated value of the corresponding extraction condition within the period during which risk analysis is performed, that is, the predetermined period (S10). In the present embodiment, for example, the condition 37 is “the maximum number of consecutive working days”, and therefore, the maximum number of consecutive 13 days from August 14 to August 26. , “13” is recorded. Also, in condition 39, since “the most recent number of consecutive working days”, it is 13 days as described above, and “13” is recorded in the total value T column. For other conditions, the aggregate value is calculated by the same process.

  When each aggregate value is calculated, it is determined whether or not each aggregate value is equal to or greater than the threshold value indicated in the condition extracted in S3 (S11). Here, the threshold is, for example, that in condition 37, the maximum number of consecutive working days is “6 days or more”, and in condition 39, the latest number of consecutive working days is “7 or more”. It is.

When the total value is less than the threshold value, the continuity data and the current state analysis data are excluded from the items to be considered in the risk analysis, and the process ends. On the other hand, when the total value is equal to or greater than the threshold value, the scoring processing unit 1323b assigns a score (see FIG. 5) previously associated with the extraction condition table (S12). In the present embodiment, for example, when the condition 37 is equal to or greater than the threshold value, a score of 5 is recorded in the score P column of FIG. Further, when the condition 39 is equal to or greater than the threshold value, the score 1 is recorded in the score P column of FIG.

  In condition 37, since there is a period of working for 13 consecutive days, it is determined that the threshold value is exceeded. Further, even in the condition 39, since there are the number of working days that have been continued for the last 13 days, it is determined to be equal to or greater than the threshold value.

  The scoring processing unit 1323b calculates the sum of the points given to the continuity analysis data and the current condition analysis data that are equal to or greater than the threshold (S13).

  A risk map is generated by the display data generation unit 1324b from the total score of the daily unit data totaled in S8, the continuity analysis data totaled in S13, and the total score of the current status analysis data (S14).

  FIG. 11 illustrates the risk map M. In the present embodiment, the total number of daily unit data is plotted on the vertical axis, and the coordinate plane with the total number of points assigned to the continuity analysis data and the current status analysis data is plotted on the horizontal axis. The quadrant is divided into the fourth quadrant, and the degree of risk is grouped in each quadrant, and the total score of each employee is plotted on the coordinate plane. However, the risk map is not limited to this form as long as the two total scores are displayed in correlation with each other.

  The vertical axis “amount of overwork” gradually increases from the M0 and M2 regions to the M1 and M3 regions. The horizontal axis “continuity of overwork” gradually increases from the M1 and M0 regions to the M3 and M2 regions.

For example, the area where the score of the analyzed employee is plotted may be determined as follows. In the present embodiment, the area where the employee “Test No. 1” is plotted is the M3 area.
If you belong to the M0 area: “I am overworked, but it doesn't show any signs of danger right now. If I start moving to the M2 area, it's quite dangerous.”
When belonging to the M1 area: “Dangerous overworked condition where the daily working hours are extremely long and the body blows like a body blow.”
When belonging to the M2 area: “Overworking without sharpness. Dangerous overwork that is likely to cause sudden injury or illness due to the occurrence of excessively busy conditions or lack of rest.”
When belonging to the M3 area: “The most dangerous overworked state with long working hours and chronic condition. If an accident or death from overwork occurs during this time, the company's responsibility is inevitable.”

  FIG. 12 shows a display example of the risk alarm A. In the extraction condition table in FIG. 5, the condition No. 1 in which the warning 1331 f is “Yes”. As with the first extraction condition and the second extraction condition, 6, 19, 55 may be scored according to the set threshold value. These conditions are not data directly reflected in the risk map, but the conditions for displaying the risk alarm A corresponding to each of the employee's working days and working hours (hereinafter referred to as “third extraction condition”). ).

  The risk alarm A includes, for example, department name a1, name a2, total period a3, title a4, alarm transition scroll bar a5, problem type column a6, problem a7 currently in progress, and work style a8 that is the current problem. It consists of descriptions of actions a9 that should be taken by superiors in labor management.

  As described with reference to FIG. 2, the risk alarm is scored for the third extraction condition, and the corresponding comment is read from the comment table database 1332 according to the score and the extraction condition, and is generated by the risk alarm generation unit 1324b. The

  13 and FIG. 14, in the case of multi-store management, enter the employee's attendance data belonging to each store, job data including each employee's age data, part, part-time job, and data specifying this store, This is store unit data generated by the store data collection unit 1325 and store display data generation unit 1326 described with reference to FIG.

  FIG. 13 is a diagram showing a labor distribution table K in the store. The in-store labor distribution table K includes basic information k1 such as sales, productivity, average age, total working hours, average working hours, working days, working hours at midnight, and working time distribution k2 for each day (each day of the week). And a working time distribution k3 during the centralization period.

  According to the labor distribution table K, for example, it becomes possible to grasp the working hours for each job position, such as the degree of dependence on new employees, the time zone and number of human resources input, employees and part-time workers, and therefore appropriate labor management is possible. As a result, it is possible to provide an indicator of cost reduction for personnel costs.

  FIG. 14 is a diagram showing a compliance monitoring table W in the store. Whether the compliance monitoring table W in the store becomes a social insurance application from the store name w1, the total period w2, the comparison graph w3 of the reference overtime hours and the actual overtime hours of each employee, and the working hours And a monitoring table w4.

  According to the compliance monitoring table W in the store, it is possible to monitor at any time whether it meets various statutory requirements in terms of labor.

  13 According to the labor distribution table K in the store and FIG. 14 compliance monitoring table W in the store, it becomes possible to manage costs related to personnel costs and provide data that contributes to business management from the labor management viewpoint. .

Hardware configuration of risk analysis server Functional block diagram of risk analysis system Functional block diagram of multi-store risk analysis system Process flow diagram of risk analysis system Figure showing the extraction condition table Diagram showing attendance data for analysis processing Diagram showing daily unit data Diagram showing continuity data Diagram showing current state analysis data Diagram showing aggregate data Diagram showing risk map Figure showing an example of risk alarm display Diagram showing labor distribution in stores Diagram showing the compliance monitoring table in the store

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Risk analysis server 13 Hard disk 13 Transmission / reception part 132 Risk analysis program 133 Database 1321 Format conversion part 1322 Data generation part 1323 Calculation part 1324 Display data generation part

Claims (10)

A risk analysis device for analyzing labor management and business management risks from employee time data,
A means for inputting attendance data comprising at least the number or name identifying each employee and the attendance date and time of each employee in a predetermined period;
A first extraction condition for setting a plurality of predetermined conditions in daily units for the working hours or the number of working days of the attendance data, and a second for setting a predetermined number of continuous times or continuous days for each first extraction condition A threshold value is set for each of the extraction conditions and the first extraction condition and the second extraction condition, and a predetermined score set for each extraction condition is stored in association with a value having a value equal to or greater than the threshold value. Extraction condition storage means
The daily unit data generating unit for generating daily unit data from the time data input by the input unit and the first extraction condition read out from the extraction condition storage unit, and the daily unit data Based on the continuity analysis data generation means for generating data that matches the second extraction condition read from the extraction condition storage means, and a tabulation process for counting the number of days or time of the daily unit data and continuity analysis data The predetermined score is given to the data exceeding the threshold values set in the first and second extraction conditions, and the data belonging to the first extraction condition is given among the data and the aggregated data The scoring processing means for calculating the total of the points and the total of the points assigned to the data belonging to the second extraction condition, and for each employee, the two calculated total points are correlated and displayed. Risk analysis apparatus characterized by having a display data generation unit.   The predetermined score is set by weighting each of the first and second extraction conditions based on at least the Labor Standards Act, notification, decision by examination request, precedent, labor trial, and corresponding case. The risk analysis apparatus according to claim 1, wherein:   The risk analysis apparatus according to claim 1 or 2, wherein the second type of extraction condition includes a predetermined condition that continues for two days or more twice at the end of the predetermined period. The display data generating means takes a total number of points assigned to data belonging to the first extraction condition on the vertical axis, and a coordinate plane taking the total number of points assigned to data belonging to the second extraction condition on the horizontal axis. Is divided into four equal quadrants and divided into first to fourth quadrants, and the degree of risk is grouped in each quadrant, and the score of each employee calculated by the scoring means is on the coordinate plane. The risk analysis apparatus according to any one of claims 1 to 3, wherein the display data plotted in (1) is generated.   Conditions and thresholds that need to be warned in terms of labor management or business management from the working hours or the number of working days based on the above extraction conditions based on the Labor Standards Act, notification, decision by examination request, precedent, labor trial, and response cases Comment storage means for adding a plurality of third extraction conditions set to the above, and associating at least a warning data composed of indications of problems and countermeasure comments with a single or a plurality of combinations of the third extraction conditions 5. The risk analysis apparatus according to claim 1, wherein the display data generation means reads out the corresponding warning data and generates warning display data. .   6. The risk analysis apparatus according to claim 1, wherein the warning data includes information related to employee health management and data related to improvement of motivation against a decrease in employee morale. .   When the employees who are attending time management are divided into a plurality of groups, the input means uses the time data of the employees belonging to each group together with the time data of each employee, post data including part-time job, and this group. The display data generating means calculates and generates total working time data and average working time data for each group together with risk analysis for each employee, and generates labor by job title and age. 7. The risk analysis apparatus according to claim 1, wherein the risk analysis apparatus generates distribution data.   The display data generation means generates data for displaying a transition of overtime hours within a predetermined period of employees belonging to the group and data for newly displaying a list of persons to whom social insurance is applied from working hours. The risk analysis apparatus according to any one of claims 1 to 7, wherein the risk analysis apparatus is one.   The risk analysis device functions as a risk analysis server that can be connected to a communication network such as the Internet, and the risk analysis server is configured to receive the attendance data, age data, job title from a client terminal via the communication network. Risk analysis is performed on the data for identifying the data and the group, and the transmission / reception means for transmitting the generated display data by the display data generation means, and the received time data, age data, position data, and data for identifying the group. A risk analysis system comprising a format conversion means for converting into a format that can be analyzed by a server.   A program causing a computer to function as the risk analysis device or the risk analysis server.