Labor situation analysis system, labor situation analysis method, and program

Abstract

A labor situation analysis system (20) comprises: a position information acquisition unit (24) that acquires position information for a target person, among a plurality of workers; a work information acquisition unit (25) that acquires work information indicating the work state of the target person; an acquisition unit (26) that acquires first information which includes relationship information and / or area information; an analysis unit (27) that calculates a feature amount for a prescribed period on the basis of the position information, the work information, and the first information, and analyzes the labor situation of the target person using a prescribed estimation formula and a statistical processing value obtained by statistically processing the calculated feature amount for the prescribed period; and an output unit (28) that outputs analysis result information for displaying the result of the analysis.

Description

Labor situation analysis system, labor situation analysis method, and program

[0001] The present invention relates to a work situation analysis system, a work situation analysis method, and a program.

[0002] There is a known indicator of engagement (also called work engagement or employee engagement) related to workers' work. According to Non-Patent Document 1, engagement is defined by the following two points:

[0003] (1) Commitment to the organization, specifically, affective commitment (emotional attachment to the organization) and continuance commitment (desire to stay with the organization).

[0004] (2) extra-role behaviors (discretionary behaviors that enable the organization to function effectively);

[0005] Increasing engagement can lead to improvements in productivity, sales, customer satisfaction, and worker retention within the organization, for example. Patent Literature 1 discloses an organizational development support system (engagement system) that enables on-site and human resources personnel to continuously strengthen and develop the organization in accordance with the attributes of the organization.

[0006] JP 2018-185680 A

[0007] Arnold B. Bakker and Michael P. Reiter (eds.), Work Engagement: A Handbook for Basic Theory and Research, Seiwa Shoten, 2014, p. 23

[0008] The organizational development support system of Patent Document 1 estimates engagement based on responses to a questionnaire. However, responses to a questionnaire are not necessarily objective data. Therefore, in order to increase the reliability of engagement estimation, it is desirable to develop a more objective method for estimating engagement.

[0009] The present invention provides a work situation analysis system and the like that can provide more objective analysis results of work situations (engagement, etc.).

[0010] A work situation analysis system according to one aspect of the present invention includes a location information acquisition unit that acquires location information at the workplace of a subject among a plurality of workers who perform work at the workplace; a work information acquisition unit that acquires work information indicating the work status of the subject; an acquisition unit that acquires first information including relationship information that indicates the work relationships between the plurality of workers at the workplace and at least one of area information that indicates the location and use of each of a plurality of areas included in the workplace; an analysis unit that calculates feature amounts for a predetermined period based on the location information, the work information, and the first information, and analyzes the work situation of the subject using statistically processed values ​​obtained by statistically processing the calculated feature amounts for the predetermined period and a predetermined estimation formula; and an output unit that outputs analysis result information to display the results of the analysis.

[0011] A work situation analysis method according to one aspect of the present invention is a work situation analysis method executed by a computer, and includes the steps of acquiring location information at a workplace of a subject among a plurality of workers performing work at the workplace; acquiring work information indicating the work status of the subject from an information terminal used by the subject for work; acquiring first information including relationship information indicating the work relationships at the workplace between the plurality of workers and at least one of area information indicating the location and use of each of a plurality of areas included in the workplace; calculating feature amounts for a predetermined period based on the location information, the work information, and the first information, and analyzing the work situation of the subject using statistically processed values ​​obtained by statistically processing the calculated feature amounts for the predetermined period and a predetermined estimation formula; and outputting analysis result information for displaying the results of the analysis.

[0012] A program according to one aspect of the present invention is a program for causing the computer to execute the work situation analysis method.

[0013] The work situation analysis system etc. of the present invention can provide more objective analysis results of the work situation.

[0014] FIG. 1 is a block diagram showing the functional configuration of a work situation analysis system according to an embodiment. FIG. 2 is a diagram showing an example of a flowchart of an engagement estimation operation. FIG. 3 is a diagram showing the relationship between a predetermined period, a unit period, and a predetermined time interval. FIG. 4 is a diagram showing an example of a display screen for engagement estimation results. FIG. 5 is a diagram showing an example of a flowchart showing a method for determining statistical processing when there is a shortage of data. FIG. 6 is a flowchart of example 1 of an operation for determining a deterioration in work situation. FIG. 7 is a diagram for explaining the criteria for determining a deterioration in a subject's work situation. FIG. 8 is a flowchart of example 2 of an operation for determining a deterioration in work situation. FIG. 9 is a diagram for explaining the criteria for determining a deterioration in a subject's work situation.

[0015] Hereinafter, the embodiments will be described in detail with reference to the drawings. Note that the embodiments described below are all comprehensive or specific examples. The numerical values, shapes, materials, components, component placement and connection forms, steps, and step order shown in the following embodiments are merely examples and are not intended to limit the present invention. Furthermore, among the components in the following embodiments, components not recited in independent claims will be described as optional components.

[0016] It should be noted that the drawings are schematic diagrams and are not necessarily strict illustrations. In addition, in the drawings, substantially the same components are denoted by the same reference numerals, and overlapping descriptions may be omitted or simplified.

[0017] (Embodiment) [Configuration] First, the configuration of a work situation analysis system according to an embodiment will be described. Fig. 1 is a block diagram showing the functional configuration of a work situation analysis system according to an embodiment.

[0018] The work situation analysis system 20 is a system that can analyze the work situation of each of multiple workers who belong to a company, a government office, or other organization and work in the workplace. The work situation analysis system 20 can, for example, estimate the engagement of workers as an indicator of the work situation and visualize the estimated engagement results.

[0019] In this embodiment, a worker refers to anyone who works. Workers include not only those who receive compensation in exchange for their work, but also those who work without compensation. However, the following describes an example of estimating the engagement of a worker who receives compensation in exchange for their work.

[0020] 1 shows a work situation analysis system 20, a positioning system 30, multiple information terminals 40, a data management system 50, multiple biological information measurement terminals 60, and multiple exercise measurement terminals 70. These systems and terminals will be described below.

[0021] The work situation analysis system 20 performs processing to estimate worker engagement. The work situation analysis system 20 is realized, for example, by one or more server devices. The work situation analysis system 20 includes a communication unit 21, an information processing unit 22, and a storage unit 23.

[0022] The communication unit 21 is a communication module (communication circuit) that enables the work situation analysis system 20 to communicate with the positioning system 30, the multiple information terminals 40, the data management system 50, the multiple biological information measurement terminals 60, and the multiple exercise measurement terminals 70 via a wide area communication network such as the Internet. The communication performed by the communication unit 21 is, for example, wired communication, but may also be wireless communication. There are no particular limitations on the communication standard used for the communication.

[0023] The information processing unit 22 performs information processing for estimating worker engagement. The information processing unit 22 is realized, for example, by a microcomputer, but may also be realized by a processor. The information processing unit 22 includes, as functional components, a location information acquisition unit 24, a work information acquisition unit 25, an acquisition unit 26, an analysis unit 27, and an output unit 28. The functions of the location information acquisition unit 24, the work information acquisition unit 25, the acquisition unit 26, the analysis unit 27, and the output unit 28 are realized, for example, by the microcomputer or processor that constitutes the information processing unit 22 executing a computer program stored in the storage unit 23.

[0024] The storage unit 23 is a storage device that stores information necessary for the information processing, computer programs executed by the information processing unit 22, etc. The storage unit 23 is realized by, for example, a hard disk drive (HDD), but may also be realized by a semiconductor memory or the like.

[0025] The positioning system 30 measures the position information of each of a plurality of workers who perform work at the workplace. Specifically, the position information is information that indicates the coordinates of the worker at the workplace. More specifically, the positioning system 30 measures the position information of each of the plurality of workers at predetermined time intervals and stores (manages) time-series data of the position information.

[0026] The positioning system 30 includes, for example, a positioning server, multiple beacon transmitters distributed throughout the workplace, and beacon receiving terminals carried by each of multiple workers. The beacon receiving terminal measures the received signal strength of the beacon signal received from each of the multiple beacon transmitters and transmits information indicating the measured received signal strength to the positioning server. The positioning server calculates the distance between the beacon receiving terminal and each of the multiple beacon transmitters based on the received information. The positioning server can measure the location information of the beacon receiving terminal (the worker carrying the beacon receiving terminal) by three-point positioning based on the distance between the beacon receiving terminal and each of the multiple beacon transmitters and the location information of each of the multiple beacon transmitters.

[0027] The information terminal 40 is an information terminal used by workers when performing their work in the workplace, and is, for example, a personal computer, but it may also be a tablet terminal or the like. The information terminal 40 can provide work information to the working situation analysis system 20. The work information includes usage history information for the information terminal 40 (including operation history information, etc.), online conference information indicating the history or schedule of online conferences using the information terminal 40, and time information indicating the time the information terminal 40 was used. The information terminal 40 can also provide reported information based on the worker's self-reporting to the working situation analysis system 20.

[0028] The data management system 50 is realized by one or more server devices that store (manage) information necessary for estimating engagement. Specifically, the data management system 50 stores terminal information, relationship information, and area information.

[0029] The terminal information is information linking the ID of a worker with the IDs of the beacon receiving terminal, information terminal 40, biological information measuring terminal 60, and motion measuring terminal 70 possessed by the worker. For example, the location information provided by the positioning system 30 includes the ID of the beacon receiving terminal, and by matching the terminal information with the ID of the beacon receiving terminal, it is possible to identify which worker the location information provided by the positioning system 30 belongs to. Similarly, the terminal information makes it possible to identify which worker the work information provided by the information terminal 40 belongs to, which worker the biological information provided by the biological information measuring terminal 60 belongs to, and which worker's motion indexes belong to.

[0030] Relationship information is information that indicates the work relationships between multiple workers in the workplace. More specifically, relationship information includes information regarding the hierarchical relationships between multiple workers. Information regarding the hierarchical relationships between multiple workers is, for example, information regarding the job positions of each of the multiple workers. Job positions refer to work positions. Job positions are positions or ranks, etc. Furthermore, relationship information includes, for example, organizational information regarding the organizations (departments or divisions, etc.) to which each of the multiple workers belongs. Departments or divisions are distinguished by names such as XX Department, XX Section, or XX Center. Furthermore, relationship information includes, for example, business information (for example, information regarding the names of the business operations) in which each of the multiple workers is involved (projects, etc.).

[0031] Area information is information that indicates the location and purpose of each of multiple areas included in a workplace. For example, area information indicates the location (coordinate range) of an area where work is performed and its purpose as work. In other words, area information is map information of the workplace.

[0032] The biological information measuring terminal 60 measures the biological information of the worker. The biological information includes, for example, at least one of heart rate, blood pressure, skin temperature, sweat rate, and voice information. A single biological information measuring terminal 60 may measure multiple types of biological information (for example, heart rate and blood pressure). Alternatively, a single worker may carry multiple biological information measuring terminals 60, and each of the multiple biological information measuring terminals 60 may measure a different type of biological information of the single worker.

[0033] The biological information measurement terminal 60 is, for example, a wearable terminal worn by a worker. The wearable terminal includes, for example, an optical heart rate sensor that measures the worker's heart rate and blood pressure. The wearable terminal also includes, for example, a temperature sensor that measures the worker's skin temperature. The wearable terminal also includes, for example, a sweat sensor that measures the worker's sweat rate.

[0034] The exercise measuring terminal 70 measures the exercise index of the worker. The exercise index represents at least one of the quality and quantity of exercise. The exercise index includes, for example, at least one of the amount of activity and the amount of movement. The amount of activity is expressed, for example, in METs (Metabolic equivalents). The amount of movement is, for example, the number of steps. The exercise measuring terminal 70 is, for example, a wearable terminal worn by the worker. The worker carries the wearable terminal. The wearable terminal is equipped with, for example, a pedometer and measures the number of steps taken by the worker. The wearable terminal also measures, for example, the worker's biometric information (heart rate, blood pressure, skin temperature, sweat rate, etc.) as described above. The wearable terminal may measure the worker's activity amount based on the biometric information.

[0035] [Predetermined Estimation Formula] A predetermined estimation formula for estimating worker engagement is stored in advance in the data management system 50. A method for generating the predetermined estimation formula will be described below.

[0036] The designer or the like of the work situation analysis system 20 collects in advance an estimated value of engagement and a plurality of parameters for each of an unspecified number of workers. The unspecified number of workers may be workers working in the same workplace or workers working in different workplaces.

[0037] The engagement estimate is collected by surveying workers and analyzing their responses to the survey. For example, known methods such as those disclosed in U.S. Patent Application Publication No. 2009 / 0129994 can be used to estimate a worker's engagement based on their response choices from a set of options.

[0038] The parameters are, for example, the conversation time between the worker and a specific person, the amount of activity of the worker, the overtime hours of the worker, etc. The feature amount may be a parameter extracted from declared information that can be obtained from the information terminal 40, a parameter extracted from biological information that can be measured by the biological information measuring terminal 60, or a parameter extracted from exercise indices that can be measured by the exercise measuring terminal 70.

[0039] The parameters are collected without using the work situation analysis system 20 before the work situation analysis system 20 starts providing services, but they may also be collected by test running the work situation analysis system 20, for example.

[0040] The designer or the like determines, from among the multiple parameters, a parameter that has a strong correlation with the estimated value of engagement as a feature. The designer or the like calculates the strength of the correlation, for example, by multiple regression analysis. That is, the designer or the like determines a multiple regression equation using the estimated value of engagement as the objective variable and multiple parameters for a predetermined period as multiple explanatory variables, and further determines the coefficient of determination of the multiple regression equation. The coefficient of determination is a value between 0 and 1. The larger the coefficient of determination, the stronger the correlation. The designer or the like determines, for example, multiple explanatory variables when the coefficient of determination is greater than a threshold value as multiple feature quantities.

[0041] Then, the designer or the like removes terms including parameters that are not adopted as feature quantities from the multiple regression equation, defines the equation as a predetermined estimation equation, and stores the equation in the data management system 50 .

[0042] Note that the designer may obtain a simple regression equation instead of the multiple regression equation and obtain the strength of correlation (coefficient of determination) from the simple regression equation. In other words, the designer may obtain the correlation between at least one feature and engagement by regression analysis or the like.

[0043] [Engagement Estimation Operation] The operation of estimating engagement using such a predetermined estimation formula will now be described. Figure 2 is a diagram showing an example of a flowchart of the engagement estimation operation. Note that, although a method for estimating the engagement of one subject will be described below, it is also possible to estimate the engagement of each of multiple workers working in the same workplace using a similar method.

[0044] First, the acquisition unit 26 of the work situation analysis system 20 acquires the above-mentioned predetermined estimation formula, terminal information, relationship information, and area information by communicating with the data management system 50 using the communication unit 21 (S11). The relationship information is information indicating the work-related relationships in the workplace of multiple workers, including the subject, and the area information is information indicating the location and use of each of multiple areas included in the workplace.

[0045] Note that if the relationship information and / or the area information are not necessary for calculating the feature amount, it is not necessary to acquire the first information including the relationship information and / or the area information. In other words, the acquisition unit 26 may acquire the first information including the relationship information and / or the area information.

[0046] Next, the location information acquisition unit 24 communicates with the positioning system 30 using the communication unit 21 to acquire location information of each of the multiple workers, including the target person, from the positioning system 30 (S12). More specifically, the location information here is time-series data of location information for a predetermined period of time, in other words, the movement trajectories of each of the multiple workers in the workplace. The predetermined period is not particularly limited, but in the following description, it is assumed to be the 28 days immediately preceding the day on which engagement estimation is performed.

[0047] In step S12, it is sufficient to acquire at least the location information of the subject, and location information of workers other than the subject does not need to be acquired if it is not necessary to calculate the feature amount.

[0048] Next, the work information acquisition unit 25 acquires the subject's work information for the predetermined period from the information terminal 40 by communicating with the information terminal 40 using the communication unit 21 (S13). Work information is information that indicates the subject's work status, and includes usage history information of the information terminal 40, online conference information that indicates the history or schedule of online conferences that used the information terminal 40, and time information that indicates the time the information terminal 40 was used. Note that in step S13, it is sufficient to acquire work information necessary for calculating feature amounts, and it is not essential to acquire all of the usage history information, online conference information, and time information.

[0049] Next, the acquisition unit 26 communicates with the information terminal 40, the biometric information measurement terminal 60, and the exercise measurement terminal 70 using the communication unit 21 to acquire the subject's biometric information, the subject's exercise index, and the subject's declared information for the above-mentioned specified period (S14).

[0050] Note that the biometric information, the exercise index, and the declared information do not need to be acquired if they are not required for calculating the feature amount. In other words, the acquiring unit 26 only needs to acquire the second information including at least one of the biometric information, the exercise index, and the declared information as needed.

[0051] Next, the analysis unit 27 calculates feature quantities based on the location information for the predetermined period acquired in step S12, the work information for the predetermined period acquired in step S13, the first information acquired in step S11, and the second information acquired in step S14 (S15). One feature quantity is calculated for 28 days, with one day (24 hours) being the unit period, for example. If it is necessary to substitute n feature quantities (n is a natural number) into a predetermined estimation formula, then in step S15, each of the n feature quantities is calculated for 28 days.

[0052] A specific example of a method for calculating a feature quantity will be described. For example, if the feature quantity is the conversation time between the subject and other workers, the analysis unit 27 can calculate the conversation time from the location information and terminal information of multiple workers. For example, the analysis unit 27 can calculate the conversation time by considering the time when the subject and other workers are within a predetermined distance (e.g., one meter) as the conversation time between the subject and other workers. More accurately, the analysis unit 27 can determine the conversation time between the subject and other workers as the time when the subject and other workers are within the predetermined distance and audio information is being output from microphones located around the conversation site. In this case, the microphone may be carried by the worker, or may be installed near the worker's workplace, for example.

[0053] Furthermore, the analysis unit 27 can calculate the conversation time between the subject and other workers in online conferences based on the online conference information included in the work information. Furthermore, if the feature is the conversation time between the subject and a worker who has a specific relationship with the subject (such as a superior, subordinate, or colleague involved in the same work), the analysis unit 27 can calculate the conversation time between the subject and the worker who has a specific relationship with the subject by using the relationship information in addition to the location information and terminal information.

[0054] Furthermore, if the feature quantities are the subject's overtime hours, the number of times the subject has worked overtime, the subject's night shift hours, and the subject's holiday work hours, the analysis unit 27 can calculate the subject's overtime hours, the number of times the subject has worked overtime, the subject's night shift hours, and the subject's holiday work hours based on the work information. In this case, the analysis unit 27 can calculate the subject's overtime hours, the number of times the subject has worked overtime, the subject's night shift hours, and the subject's holiday work hours by considering the time from when the information terminal 40 indicated in the work information is turned on to when the information terminal 40 is turned off as working time. The analysis unit 27 may also calculate the subject's overtime hours, the number of times the subject has worked overtime, the subject's night shift hours, and the subject's holiday work hours based on attendance information output from an attendance management system (not shown). Other feature quantities and their calculation (acquisition) methods will be described separately below.

[0055] After step S15, the analysis unit 27 statistically processes the n feature quantities for a predetermined period to obtain statistically processed values ​​(S16). When determining the predetermined estimation formula, the designer of the work situation analysis system 20 determines in advance what statistical processing to perform on the feature quantities included in the predetermined estimation formula. In step S16, the analysis unit 27 performs the statistical processing determined for each of the n feature quantities. Specifically, the statistical processing includes calculating a cumulative value, calculating an average value, calculating a maximum value, calculating a minimum value, calculating a standard deviation, calculating a variance, calculating a mode value, calculating the number of values ​​above a threshold, and calculating the number of values ​​below a threshold. In other words, in step S16, the analysis unit 27 obtains the cumulative value, average value, maximum value, minimum value, standard deviation, variance, mode value, number of values ​​above a threshold, or number of values ​​below a threshold for the feature quantities for the predetermined period as statistically processed values.

[0056] Next, the analysis unit 27 estimates the engagement of the subject by substituting the n statistically processed values ​​corresponding to the n feature quantities into the predetermined estimation formula acquired in step S11 (S17). That is, the analysis unit 27 analyzes the work situation of the subject. The analysis unit 27 also stores the estimated engagement (work situation) of the subject in the storage unit 23.

[0057] The processes of steps S11 to S17 are performed, for example, at predetermined time intervals. Fig. 3 is a diagram showing the relationship between a predetermined period, a unit period, and a predetermined time interval.

[0058] As described above, the predetermined period is, for example, 28 days, and the unit period shorter than the predetermined period is, for example, 1 day (24 hours). As shown in FIG. 3 , if the predetermined time interval is 2 days (unit period x 2), the analysis unit 27 can estimate the engagement of the subject every two days from the data for the immediately preceding 28 days and store the estimated engagement in the storage unit 23. In this way, if engagement is estimated at a predetermined time interval shorter than the predetermined period rather than every predetermined period (28 days), the subject or the subject's manager, etc. (hereinafter also referred to as the subject, etc.) can refer to the estimated engagement results more frequently. Note that, if it is desired to estimate engagement most frequently, the predetermined time interval may be set to the same length as the unit period (1 day).

[0059] Thereafter, the output unit 28 outputs analysis result information for displaying the engagement estimation result (the result of the analysis of the working situation) in response to a request from the subject or when predetermined conditions are met (S18). The output unit 28 outputs (transmits) the analysis result information to the information terminal 40 by communicating with the information terminal 40 using the communication unit 21. As a result, the engagement estimation result is displayed on the display unit of the information terminal 40. Figure 4 is a diagram showing an example of a display screen for the engagement estimation result.

[0060] The analysis result information may be information for displaying only the most recent engagement (corresponding to the engagement score in Figure 4), or may be information for displaying time series data of engagement over the most recent period (e.g., one week) (corresponding to the score trend in Figure 4).

[0061] When analysis result information is output at the request of a subject or the like, the analysis result information may be information for displaying engagement over a specified period (one day or multiple days) specified by the subject or the like.

[0062] In addition, the display screen may display detailed information about the statistically processed values ​​of the features used to estimate engagement, and in this case, the analysis result information includes information indicating the statistically processed values ​​of the features used to estimate engagement.

[0063] The analysis result information may also be information indicating an estimated result of the engagement of multiple workers, including the subject. The multiple workers may be, for example, workers who belong to the same organization as the subject. In this case, the display unit of the information terminal 40 may display the distribution of the engagement of the multiple workers and the position of the subject within the distribution.

[0064] Furthermore, a predetermined condition that serves as a trigger for outputting (transmitting) the analysis result information may be set in advance, and the output unit 28 may output the analysis result information when the predetermined condition is satisfied. The predetermined condition may be, for example, that the absolute value of engagement has deteriorated (or improved) by more than a threshold value, or that the latest engagement has deteriorated (or improved) by more than a predetermined value compared to the most recent engagement. The predetermined condition may also be that a predetermined time has arrived, such as a certain time on a certain day of every month.

[0065] As described above, the work situation analysis system 20 can estimate the engagement of a subject and visualize the estimated engagement results. For example, the first information, which includes the subject's location information obtained from the positioning system 30, the subject's work information (usage history information) obtained from the information terminal 40, and at least one of relationship information and area information, is information that the subject can obtain without taking any special action. In other words, when engagement is estimated from this information, the subject does not need to take any special action to estimate engagement. Therefore, in such cases, the work situation analysis system 20 can estimate engagement while reducing the burden on the subject.

[0066] While FIG. 2 illustrates a method for estimating the engagement of a single subject, a similar method can be used to estimate the engagement of multiple workers working in the same workplace. Therefore, the analysis unit 27 may estimate the engagement of multiple workers and determine a representative value, such as the average or median, of the estimated engagement of the multiple workers as the engagement of the organization to which the subject belongs. In other words, the analysis unit 27 may acquire statistically processed values ​​for multiple workers, including the subject, and apply the acquired statistically processed values ​​to a predetermined estimation formula to convert the estimated engagement of the multiple workers into a representative value, such as the average or median, thereby analyzing the working conditions of the organization to which the subject belongs. In this case, the output unit outputs analysis result information for displaying the results of the analysis of the organization.

[0067] Here, the term "organization" refers to a group such as a team, department, division, office, or company to which the subject belongs, and there is no particular limitation on the size of the group.

[0068] [Response when data is insufficient] As shown in Figure 3 above, the amount of data for feature quantities is insufficient during the predetermined period (28 days) from the start of data measurement. In this way, when the amount of data for calculated feature quantities is insufficient for the predetermined period, the analysis unit 27 may not estimate engagement, or may estimate engagement by performing statistical processing using different methods for each type of feature quantity as follows. Figure 5 is a diagram showing an example of a flowchart illustrating a method for determining statistical processing when data is insufficient.

[0069] As described above, the statistical processing to be performed on each feature is predetermined for each feature, so the analysis unit 27 of the work situation analysis system 20 determines whether the feature is to be subjected to the first statistical processing or the second statistical processing (S21).

[0070] The first statistical processing is a process for calculating the average value, maximum value, minimum value, standard deviation, variance, or mode, and it is considered that even if there is a lack of data, the first statistical processing will have little effect on the statistical processing value obtained as a result of the first statistical processing.

[0071] Therefore, when the analysis unit 27 determines that the feature is one to be subjected to the first statistical processing (first statistical processing in S21), it does not supplement the missing feature, but instead performs the first statistical processing on the feature with a data amount less than that of the specified period to obtain the statistical processing value (S22).

[0072] On the other hand, the second statistical processing is a process for calculating the cumulative value, the number of times the threshold value is exceeded, or the number of times the threshold value is exceeded, and if the amount of data of the feature quantity is insufficient, it is considered that the statistical processing value obtained as a result of the second statistical processing will be significantly affected. Specifically, there is a concern that the statistical processing value obtained will be smaller than usual.

[0073] Therefore, when the analysis unit 27 determines that the feature is to be subjected to the second statistical processing (second statistical processing in S21), it complements the missing feature for the data amount less than the predetermined period, and performs the second statistical processing on the feature for the predetermined period obtained by the complementation to obtain a statistical processing value (S23). For example, when only four days' worth of feature is stored, the analysis unit 27 can complement the missing feature by regarding the four days' worth of feature as seven sets.

[0074] In this way, even if the amount of data for the calculated features is less than that for a specified period, the work situation analysis system 20 can optimize the estimated value of engagement by supplementing the missing features in accordance with the statistical processing performed on the features.

[0075] [Example 1 of Determining Operation of Deterioration (or Improvement) of Working Conditions] The working condition analysis system 20 can also determine whether a subject's working condition has deteriorated (or improved). For example, the working condition analysis system 20 notifies the subject when it determines that the subject's working condition has deteriorated, thereby encouraging the subject to improve their working condition before it significantly deteriorates. FIG. 6 is a flowchart of Example 1 of Determining Operation of Deterioration of Working Conditions. In the following description of Example 1 of the determination operation, the feature amount before statistical processing is referred to as the pre-processing feature amount, and the statistical processing value (the feature amount after statistical processing) is simply referred to as the feature amount.

[0076] The analysis unit 27 calculates (acquires) feature quantities (statistical processing values) of the subject (S31). The method for calculating the feature quantities is the same as the processing in steps S11 to S16 above, and therefore a detailed description thereof will be omitted. The feature quantities acquired here are, for example, feature quantities with the largest coefficient of determination in a predetermined estimation formula (such as a multiple regression formula) and with a high correlation with engagement, but the type of feature quantities to acquire may be empirically or experimentally determined by the designer of the work situation analysis system 20, etc.

[0077] Next, the analysis unit 27 determines whether the subject's working conditions have worsened based on the calculated feature values ​​of the subject (S32). If it is determined in step S32 that the subject's working conditions have worsened (Yes in S32), the output unit 28 communicates with the information terminal 40 of the subject, etc., using the communication unit 21, and outputs (transmits) notification information to the information terminal 40 (S33). As a result, a notification screen indicating that the subject's working conditions have worsened is displayed on the display unit of the information terminal 40. As with the display screen of FIG. 4 , the notification screen may display the subject's feature values ​​and recent trends in the subject's feature values. Note that if it is not determined in step S32 that the subject's working conditions have worsened (No in S32), the output unit 28 does not output the notification information.

[0078] The criteria for the determination in step S32 will be described in more detail below. Fig. 7 is a diagram for explaining the criteria for determining whether the working conditions of a subject have deteriorated.

[0079] As described above with reference to Fig. 3, the feature amounts of the subject are calculated at predetermined time intervals (two days in the example of Fig. 3), and the feature amounts calculated in the past are stored in the storage unit 23. Therefore, as shown in Fig. 7(a), the analysis unit 27 can make the determination in step S32 by comparing the feature amount calculated in step S31 with the subject's own past feature amounts.

[0080] For example, if a larger value of the feature F indicates a worsening working situation, the analysis unit 27 determines that the working situation of the subject has worsened if the feature F(k) of the subject acquired in step S31 is greater than the feature F(k-1) of the subject's past record immediately preceding the feature F(k) + a predetermined value (≧0). k is an integer indicating the order of the predetermined period. As described above with reference to FIG. 3 , the feature F(k) is acquired based on the pre-processing feature for the predetermined period T(k), and the feature F(k-1) is acquired based on the pre-processing feature for the predetermined period T(k-1) immediately preceding the predetermined period T(k). In the example of FIG. 3 , the start and end points of the predetermined period T(k) and the immediately preceding predetermined period T(k-1) are offset by a predetermined time interval (e.g., two days).

[0081] Furthermore, the analysis unit 27 may determine that the working conditions of the subject have deteriorated when the feature F(k) of the subject is greater than the average value of a predetermined number of feature values ​​immediately preceding the feature F(k) of the subject plus a predetermined value (≧0). Specifically, when the predetermined number is 5, the analysis unit 27 determines that the working conditions of the subject have deteriorated when F(k) is greater than the average value of F(k−1) to F(k−5) plus the predetermined value.

[0082] Furthermore, the analysis unit 27 may determine that the working conditions of the subject have worsened when the feature quantity F(k) of the subject is greater than the feature quantity of the subject for the same period of the previous year plus a predetermined value (≧0). The analysis unit 27 may determine that the working conditions of the subject have worsened when the feature quantity F(k) of the subject is greater than the average value of the feature quantities of the subject for the same period of the past few years plus a predetermined value (≧0).

[0083] 7B, the analysis unit 27 may make the determination in step S32 by comparing the feature F(k) acquired in step S31 with the feature F1 of the organization to which the subject belongs (hereinafter also referred to as the target organization). The feature F1 of the target organization is, for example, a representative value such as the average or median of the feature values ​​of multiple workers working in the target organization. Note that the feature F and the feature F1 are the same type of feature; for example, if the feature F indicates overtime hours, the feature F1 also indicates overtime hours.

[0084] For example, the analysis unit 27 makes the determination in step S32 by comparing the feature F(k) of the subject acquired in step S31 with the feature F1(k) of the target organization for the same period. If larger values ​​of the feature F and the feature F1 indicate a worsening working situation, the analysis unit 27 determines that the working situation of the subject has worsened if the feature F(k) of the subject acquired in step S31 is larger than the feature F1(k) of the target organization for the same period plus a predetermined value (≧0).

[0085] Furthermore, the analysis unit 27 may determine that the feature quantity F(k) of the subject has deteriorated if the feature quantity F(k) of the subject is greater than the average value of a predetermined number of the most recent feature quantities of the subject organization plus a predetermined value (≧0). Here, the predetermined number of most recent feature quantities includes the most recent feature quantity and the feature quantity immediately before it. Specifically, if the predetermined number is 5, the analysis unit 27 determines that the subject's working conditions have deteriorated if F(k) is greater than the average value of F1(k) to F1(k-4) plus the predetermined value.

[0086] Furthermore, the analysis unit 27 may determine that the feature quantity F(k) of the subject has deteriorated when the feature quantity F(k) of the subject is greater than the feature quantity of the target organization for the same period of the previous year plus a predetermined value (≧0). The analysis unit 27 may determine that the working conditions of the subject have deteriorated when the feature quantity F(k) of the subject is greater than the average value of the feature quantities of the target organization for the same period of the past few years plus a predetermined value (≧0).

[0087] 7C, the analysis unit 27 may make the determination in step S32 by comparing the feature F(k) acquired in step S31 with the feature F2 of an organization to which the subject does not belong (hereinafter also referred to as the other organization). The other organization may be another organization within the company to which the subject organization belongs, or may be an organization belonging to another company. The feature F2 of the other organization is, for example, a representative value such as the average or median of the feature values ​​of multiple workers working in the other organization. Note that the feature F and the feature F2 are the same type of feature; for example, if the feature F indicates overtime hours, the feature F2 also indicates overtime hours.

[0088] For example, the analysis unit 27 makes the determination in step S32 by comparing the feature amount F(k) acquired in step S31 with the feature amount F2(k) of another organization for the same period. If the feature amounts F and F2 indicate that the working conditions are worsening as the values ​​thereof increase, the analysis unit 27 determines that the working conditions of the subject have worsened if the feature amount F(k) of the subject acquired in step S31 is greater than the feature amount F2(k) of the other organization for the same period plus a predetermined value (≧0).

[0089] Furthermore, the analysis unit 27 may determine that the feature quantity F(k) of the subject has deteriorated if the feature quantity F(k) of the subject is greater than the average value of a predetermined number of the most recent feature quantities of other organizations plus a predetermined value (≧0). Here, the predetermined number of most recent feature quantities includes the most recent feature quantity and the feature quantity immediately before it. Specifically, if the predetermined number is 5, the analysis unit 27 determines that the subject's working conditions have deteriorated if F(k) is greater than the average value of F2(k) to F2(k-4) plus the predetermined value.

[0090] Furthermore, the analysis unit 27 may determine that the feature quantity F(k) of the subject has deteriorated when the feature quantity F(k) of the subject is greater than the feature quantities of other organizations for the same period of the previous year plus a predetermined value (≧0). The analysis unit 27 may determine that the working conditions of the subject have deteriorated when the feature quantity F(k) of the subject is greater than the average value of the feature quantities of other organizations for the same period of the past few years plus a predetermined value (≧0).

[0091] 7(d), the analysis unit 27 may determine that the working conditions of the subject have deteriorated if the feature F(k) of the subject acquired in step S31 is greater than a predetermined target value. The predetermined target value may be, for example, statutory working hours, and may be set by the government or a health organization, but may also be set by the subject or the company to which the subject belongs (e.g., the subject's manager).

[0092] As described above, the analysis unit 27 can determine the working situation of the subject by comparing the feature calculated in step S31 with a predetermined determination standard (hereinafter also referred to as a feature standard value). The feature standard value is any one of the subject's past feature, the feature in the subject organization, the feature in another organization different from the subject organization, and a predetermined target value.

[0093] The work situation analysis system 20 notifies the subject when it determines that the subject's work situation has worsened, thereby preventing a significant deterioration in the subject's work situation and encouraging improvement of the work situation.

[0094] In step S31, the analysis unit 27 can estimate engagement by performing the same processing as in steps S11 to S17 above, and can make the determination in step S32 using the engagement instead of the feature amount. In the description of example 1 of the determination operation, the feature amount may be read as engagement. That is, the analysis unit 27 can determine the subject's working situation by comparing the engagement (evaluation value indicating the subject's working situation) obtained from the feature amount and a predetermined estimation formula with a predetermined determination criterion (hereinafter also referred to as the evaluation criterion value). The evaluation criterion value is any one of the subject's past engagement, engagement at the subject organization, engagement at another organization different from the subject organization, and a predetermined target value.

[0095] Furthermore, in step S32 of the first example of the determination operation, improvement may be determined instead of or in addition to deterioration. The determination of improvement can be realized in the same manner as the determination of deterioration. The output of notification information in step S33 may be performed when it is determined that the feature or engagement has improved.

[0096] [Example 2 of Determining Operation of Deteriorating (or Improving) Working Conditions] The working condition analysis system 20 can also determine whether working conditions in a target organization are deteriorating (or improving). For example, if the working condition analysis system 20 determines that working conditions in the target organization have deteriorated, it can notify the manager of the target organization, thereby encouraging improvement of the working conditions in the target organization before the working conditions in the target organization deteriorate significantly. FIG. 8 is a flowchart of Example 2 of Determining Operation of Deteriorating Working Conditions. In the following description of Example 2 of the determination operation, the feature values ​​before statistical processing are referred to as pre-processing feature values, and the statistical processing values ​​(feature values ​​after statistical processing) are simply referred to as feature values.

[0097] The analysis unit 27 calculates (acquires) feature quantities (statistical processing values) for the target organization (S41). Specifically, the analysis unit 27 calculates feature quantities for each of multiple workers belonging to the target organization and sets a representative value, such as the average or median, of the feature quantities for the multiple workers as the feature quantities for the target organization. The method for calculating the feature quantities for each of the multiple workers is similar to the processing in steps S11 to S16 above, and therefore a detailed description thereof will be omitted. The feature quantities acquired here are, for example, feature quantities with the largest coefficient of determination in a predetermined estimation formula (such as a multiple regression formula) and with a high correlation with engagement, but the type of feature quantities to acquire may be empirically or experimentally determined by the designer of the work situation analysis system 20, etc.

[0098] Next, the analysis unit 27 determines whether the labor situation in the target organization has deteriorated based on the calculated feature quantities in the target organization (S42). If it is determined in step S42 that the labor situation in the target organization has deteriorated (Yes in S42), the output unit 28 communicates with the information terminal 40 of the manager of the target organization using the communication unit 21, thereby outputting (transmitting) notification information to the information terminal 40 (S43). As a result, a notification screen indicating that the labor situation in the target organization has deteriorated is displayed on the display unit of the information terminal 40. As with the display screen of FIG. 4, the notification screen may display the feature quantities in the target organization and the most recent trends in the feature quantities in the target organization. Note that if it is not determined in step S42 that the labor situation in the target organization has deteriorated (No in S42), the output unit 28 does not output the notification information.

[0099] The criteria for the determination in step S42 will be described in more detail below. Fig. 9 is a diagram for explaining the criteria for determining whether the working conditions of the target organization have deteriorated.

[0100] The feature amounts of the target tissue are calculated at predetermined time intervals (for example, every two days), and the feature amounts calculated in the past are stored in the storage unit 23. Therefore, as shown in Fig. 9(a), the analysis unit 27 can make the determination in step S42 by comparing the feature amount calculated in step S41 with the past feature amounts of the target tissue itself.

[0101] For example, if the feature F1 indicates that the working conditions are worsening as the value of the feature F1 increases, the analysis unit 27 determines that the feature F1(k) in the target organization has deteriorated if the feature F1(k) in the target organization acquired in step S41 is greater than the feature F1(k-1) in the target organization immediately preceding the feature F1(k) in the target organization plus a predetermined value (≧0). k is an integer indicating the order of the predetermined period. As described above with reference to FIG. 3 , the feature F1(k) is acquired based on the pre-processing feature for the predetermined period T(k), and the feature F1(k-1) is acquired based on the pre-processing feature for the predetermined period T(k-1) immediately preceding the predetermined period T(k). In the example of FIG. 3 , the start and end points of the predetermined period T(k) and the immediately preceding predetermined period T(k-1) are offset by a predetermined time interval (e.g., two days).

[0102] Furthermore, the analysis unit 27 may determine that the working conditions in the target organization have deteriorated when the feature F1(k) in the target organization is greater than the average value of a predetermined number of feature values ​​immediately preceding the feature F1(k) in the target organization plus a predetermined value (≧0). Specifically, when the predetermined number is 5, the analysis unit 27 determines that the working conditions in the target organization have deteriorated when F1(k) is greater than the average value of F1(k−1) to F1(k−5) plus the predetermined value.

[0103] Furthermore, the analysis unit 27 may determine that the working conditions in the target organization have deteriorated when the feature quantity F1(k) in the target organization is greater than the feature quantity in the target organization for the same period of the previous year plus a predetermined value (≧0). The analysis unit 27 may determine that the working conditions in the target organization have deteriorated when the feature quantity F1(k) in the target organization is greater than the average value of the feature quantities in the target organization for the past few years for the same period of time plus a predetermined value (≧0).

[0104] 9B, the analysis unit 27 may make the determination in step S42 by comparing the feature F1(k) for the target organization acquired in step S41 with the feature F2 for another organization to which the subject does not belong. The other organization may be another organization within the company to which the target organization belongs, or may be an organization within another company. The feature F2 for the other organization is, for example, a representative value such as the average or median of the feature values ​​of multiple workers working in the other organization. Note that the feature F1 and the feature F2 are the same type of feature; for example, if the feature F1 indicates overtime hours, the feature F2 also indicates overtime hours.

[0105] For example, the analysis unit 27 makes the determination in step S42 by comparing the feature amount F1(k) for the target organization acquired in step S41 with the feature amount F2(k) for another organization for the same period. If the feature amounts F1 and F2 indicate that the working conditions are worsening as the values ​​thereof increase, the analysis unit 27 determines that the working conditions in the target organization have worsened if the feature amount F1(k) for the target organization acquired in step S41 is greater than the feature amount F2(k) for the other organization for the same period plus a predetermined value (≧0).

[0106] Furthermore, the analysis unit 27 may determine that the working conditions in the target organization have deteriorated if the feature F1(k) in the target organization is greater than the average value of a predetermined number of the most recent feature values ​​of the other organizations plus a predetermined value (≧0). Here, the predetermined number of most recent feature values ​​includes the most recent feature value and the feature value immediately preceding it. Specifically, if the predetermined number is 5, the analysis unit 27 determines that the working conditions in the target organization have deteriorated if F1(k) is greater than the average value of F2(k) to F2(k-4) plus the predetermined value.

[0107] Furthermore, the analysis unit 27 may determine that the working conditions of the target organization have deteriorated when the feature quantity F1(k) of the target organization is greater than the feature quantities of other organizations for the same period of the previous year plus a predetermined value (≧0). The analysis unit 27 may determine that the working conditions of the target organization have deteriorated when the feature quantity F1(k) of the target organization is greater than the average value of the feature quantities of other organizations for the same period of the past few years plus a predetermined value (≧0).

[0108] 9(c), the analysis unit 27 may determine that the working conditions of the target organization have deteriorated if the feature F1(k) for the target organization acquired in step S41 is greater than a predetermined target value. The predetermined target value may be, for example, statutory working hours, and may be set by a government or health organization, but may also be set by the company to which the target organization belongs (e.g., a manager of the target organization).

[0109] As described above, the analysis unit 27 can determine the working conditions of the target organization by comparing the feature amounts calculated in step S41 with predetermined determination criteria (hereinafter also referred to as feature amount reference values). The feature amount reference values ​​are any of past feature amounts in the target organization, feature amounts in other organizations different from the target organization, and predetermined target values.

[0110] The labor situation analysis system 20 can prevent a significant deterioration in the labor situation of the target organization and encourage improvement of the labor situation by notifying the manager of the target organization, etc., when it determines that the labor situation of the target organization has deteriorated.

[0111] In step S41, the analysis unit 27 may estimate the engagement of each of multiple workers belonging to the target organization, use a representative value, such as the average or median of the engagement of the multiple workers, as the engagement in the target organization, and perform the determination in step S42 using the engagement instead of the feature value. The method for estimating the engagement of each of multiple workers is the same as the processing in steps S11 to S17 above. In the description of example 2 of the determination operation, the feature value may be replaced with engagement. That is, the analysis unit 27 can determine the working conditions of the target organization by comparing the engagement (evaluation value indicating the working conditions of the target organization) obtained from the feature values ​​of multiple workers belonging to the target organization and a predetermined estimation formula with a predetermined determination criterion (hereinafter also referred to as the evaluation criterion value). The evaluation criterion value is either past engagement in the target organization, engagement in another organization different from the target organization, or a predetermined target value.

[0112] Furthermore, in step S42 of the second example of the determination operation, improvement may be determined instead of or in addition to deterioration. The determination of improvement can be realized in the same manner as the determination of deterioration. The output of notification information in step S43 may be performed when it is determined that the feature or engagement has improved.

[0113] [Notification Based on Multiple Determinations] In the above-described examples 1 and 2 of the determination operation, the result of a single determination of the deterioration or improvement of the working conditions of the subject or the subject organization was used as the final determination result. Here, the analysis unit 27 may make a final determination based on the results of multiple determinations of the deterioration or improvement of the working conditions of the subject or the subject organization. The final determination means determining whether or not to output notification information.

[0114] Specifically, the analysis unit 27 performs a plurality of determinations based on a plurality of feature amounts corresponding to a plurality of different predetermined periods and a predetermined determination criterion (see, for example, FIG. 7 or FIG. 9 ). The output unit 28 outputs notification information based on the results of the plurality of determinations.

[0115] For example, the output unit 28 outputs notification information when the same determination result is obtained a predetermined number of times in a plurality of determinations. For example, the output unit 28 outputs notification information when an improvement determination or a deterioration determination is obtained a predetermined number of times in a row, and does not output notification information unless an improvement determination or a deterioration determination is obtained a predetermined number of times in a row. The predetermined number of times may be determined empirically or experimentally as appropriate and is not particularly limited.

[0116] Furthermore, the output unit 28 may output the notification information on the condition that the same determination result accounts for a predetermined percentage or more in multiple determinations. For example, the output unit 28 outputs the notification information when six or more of the most recent ten determination results have been determined to be improved or worsened, and does not output the notification information when five or fewer of the most recent ten determination results have been determined to be improved or worsened. The predetermined percentage may be determined empirically or experimentally as appropriate and is not particularly limited.

[0117] In this way, by configuring the system to make a final judgment based on the results of multiple judgments, the work situation analysis system 20 can prevent notification information from being output due to the occurrence of a single irregular judgment result.

[0118] [Specific Example of Feature 1: Feature Related to "Job Resources"] Feature values ​​(parameters that may be used as feature values) used in a predetermined estimation formula are, for example, feature values ​​(parameters) related to "job resources," "personal resources," or "job demands" defined in the "job demands-resources model," i.e., the "JD-R model." The feature value may also be a feature value related to a worker's empathy or understanding of at least one of the vision, mission, and philosophy of the group (company, etc.) to which the worker belongs for work. Alternatively, the feature value may be a feature value related to two or more of the above.

[0119] Specifically, the feature quantities related to "job resources" are feature quantities related to at least one of "support from those around you," "relationships with those around you," "discretion in your work," "coaching from colleagues," "feedback from colleagues," "diversity of relationships," and "opportunities for career development."

[0120] The feature quantities related to "support from those around" and "relationships with those around" include the amount of time the subject spent talking with other workers and the number of conversations the subject had with other workers, etc. The feature quantities related to "work discretion" include the worker's overtime hours, the number of overtime hours, the number of night shifts, and the number of hours worked on holidays, etc.

[0121] The feature quantities related to "coaching from colleagues" and "feedback from colleagues" include mood information indicating the subject's mood at the end of work. The mood information can be acquired based on, for example, the declaration information input to the information terminal 40.

[0122] The feature quantity related to "interpersonal relationship diversity" includes the number of communications within the department to which the subject belongs and the number of people with whom the subject communicates within the department. The number of communications within the department and the number of people with whom the subject communicates within the department can be obtained, for example, from the location information of each of multiple workers, or from location information and voice information, or from reported information entered into the information terminal 40. Furthermore, the number of online communications and the number of people with whom the subject communicates using the information terminal 40 can be obtained, for example, from online conference information or reported information entered into the information terminal 40.

[0123] The features related to "career development opportunities" include the number of spaces used by the subject and the number of times the subject used specialized tools. The number of spaces used and the number of times the subject used specialized tools can be obtained, for example, from location information and area information, or from usage history information of the information terminal 40 or declaration information entered into the information terminal 40.

[0124] [Specific Example of Feature 2: Feature Related to "Personal Resources"] Specifically, the feature related to "personal resources" is a feature related to at least one of "optimism," "resilience," and "recovery status."

[0125] The feature amount related to "optimism" includes mood information indicating changes in the subject's mood between morning and evening. The mood information indicating changes in the subject's mood between morning and evening can be acquired from, for example, the declared information input to the information terminal 40.

[0126] The feature quantities related to "resilience" include rest time, time when no data was entered into the PC, and the number of times when no data was entered into the PC (the number of times when no data was entered into the PC for a predetermined period of time or more), etc. The rest time, time when no data was entered into the PC, and the number of times when no data was entered into the PC can be obtained from, for example, the usage history information of the information terminal 40 or the declaration information entered into the information terminal 40.

[0127] The feature quantity related to "resilience" also includes the subject's movement amount at work. The subject's movement amount at work can be obtained, for example, from the subject's location information or from the subject's exercise measurement terminal 70.

[0128] The feature quantities related to the "recovery status" include the PC operation time and the number of times the PC was operated before the start of work, after the end of work, during late night hours, and on holidays. The PC operation time and the number of times the PC was operated before the start of work, after the end of work, during late night hours, and on holidays can be obtained from, for example, the usage history information of the information terminal 40, attendance information output from an attendance management system (not shown), or the declaration information input to the information terminal 40.

[0129] The feature quantity related to the "recovery status" also includes the interval between work hours (the length of time from the end of work on a certain day to the start of work on the following day). The interval between work hours can be obtained, for example, from the usage history information of the information terminal 40, attendance information output from an attendance management system (not shown), or declaration information input to the information terminal 40.

[0130] The feature quantity related to the “recovery status” also includes the volume of the worker’s voice. The volume of the worker’s voice is measured, for example, by a microphone provided in the biological information measurement terminal 60.

[0131] [Specific Example 3 of Feature Amount: Feature Amount Related to "Work Demands"] More specifically, the feature amount related to "work demands" is a feature amount related to at least one of "quantitative work burden," "qualitative work burden," and "physical burden at work."

[0132] The feature quantity related to the "quantitative workload" includes the subject's working hours (the length of time from the time of entering the workplace to the time of leaving the workplace). The working hours can be obtained, for example, from the subject's location information, the usage history information of the information terminal 40, or the attendance information output from an attendance management system (not shown).

[0133] The feature amount related to the "quantitative workload" also includes the subject's PC usage time after work hours. The PC usage time after work hours can be acquired from the usage history information of the information terminal 40, for example.

[0134] Furthermore, the feature quantity related to the "quantitative workload" also includes the time spent at the rest area by the subject and the number of times the subject has used the rest area. The time spent at the rest area by the subject and the number of times the subject has used the rest area can be obtained, for example, by combining the subject's location information with area information related to the rest area, etc.

[0135] The feature quantity related to the "quantitative workload" also includes the time and number of times when there is no PC input between the start time and the end time of work (the number of times when no input continues for a predetermined period of time or more). The time and number of times when there is no PC input between the start time and the end time of work can be obtained from the usage history information of the information terminal 40, for example.

[0136] The feature amount related to the "quantitative workload" also includes the amount of conversation at work. The amount of conversation at work can be acquired from the output (audio information) of a microphone provided in the biological information measurement terminal 60, for example.

[0137] Furthermore, the feature quantity related to the "quantitative workload" includes the number of keyboard operations per unit time and the amount of mouse cursor movement per unit time. The number of keyboard operations per unit time and the amount of mouse cursor movement per unit time can be acquired from, for example, the usage history information of the information terminal 40.

[0138] The feature quantity related to the "qualitative work burden" includes the PC operation time. The PC operation time can be acquired from the use history information of the information terminal 40, for example.

[0139] Furthermore, the feature quantity related to the "qualitative work burden" includes task hours with a high qualitative burden. Task hours with a high qualitative burden can be acquired, for example, from biological information measured by the biological information measurement terminal 60. The analysis unit 27 can assume, for example, that a state in which the heart rate as biological information is higher than a threshold value is a state of high qualitative burden, and acquire (calculate) the accumulated time in the state of high qualitative burden as task hours with a high qualitative burden.

[0140] The feature quantity related to "physical strain at work" includes the subject's activity level. The subject's activity level is expressed, for example, by METs. The subject's activity level can be obtained, for example, from biological information (heart rate, blood pressure, skin temperature, sweat rate, etc.) measured by the biological information measuring terminal 60.

[0141] The feature quantity related to "physical strain at work" also includes the subject's number of steps. The subject's number of steps can be acquired, for example, from the subject's location information. Alternatively, the worker's number of steps can be measured, for example, by a pedometer (exercise measurement terminal 70) carried by the subject.

[0142] Furthermore, the feature amount relating to "physical strain at work" includes the subject's maximum heart rate, which can be obtained from, for example, measurement data of the heart rate as biological information.

[0143] [Specific Example 4 of Feature Quantity: Feature Quantity Related to "Ideal Empathy"] A feature quantity related to ideal empathy (a sense of empathy or understanding for at least one of the vision, mission, and ideals of the group to which a worker belongs for work) is extracted, for example, from the declared information input to the information terminal 40. A feature quantity related to ideal empathy is, for example, an index that indicates the degree to which a worker understands the meaning of their work.

[0144] [Modifications] The system configuration (FIG. 1) described in the above embodiment is an example. In the above embodiment, a process described as being executed by a certain device may be executed by another device. For example, in the above embodiment, some or all of the information described as being stored in the data management system 50 may be stored in the storage unit 23 of the work situation analysis system 20.

[0145] Furthermore, in the above embodiment, the work situation analysis system 20 analyzed the work situation of the subject by estimating engagement, but it may also analyze the work situation of the subject by estimating or calculating indicators other than engagement.

[0146] Furthermore, in the above embodiment, a predetermined estimation formula (such as a multiple regression model) was used to estimate engagement, but engagement may also be estimated by a method other than using a predetermined estimation formula. For example, the analysis unit 27 may estimate engagement using a machine learning model. This machine learning model is a trained model that has learned the correspondence between the estimated values ​​of engagement and multiple parameters for each of an unspecified number of workers (i.e., the data used to generate the predetermined estimation formula), and can output an estimated value of engagement when statistically processed values ​​of feature quantities are input.

[0147] Furthermore, in the above-described embodiment, the specific aspect of the positioning system 30 is not particularly limited. For example, the positioning system 30 may include a positioning server, a plurality of beacon receivers distributed in a workplace, and a beacon transmitting terminal carried by each of a plurality of workers. In other words, the positioning system 30 may have a configuration in which the relationship between the transmission and reception of beacon signals is reversed from that described in the above-described embodiment.

[0148] The positioning system 30 may also measure the position information using other positioning calculation methods. Examples of other positioning calculation methods include methods that use the angle of arrival of a wireless communication signal to a receiver, such as AoA (Angle of Arrival) or AoD (Angle of Departure), and ToA (Time of Arrival). Alternatively, examples of other positioning calculation methods include methods that use the time difference between the arrival times of wireless communication signals to a receiver, such as TDoA (Time Difference of Arrival). In this way, the position information may be actually measured based on communication between communication devices distributed throughout the workplace and communication terminals carried by workers, and the specific positioning calculation method for obtaining the position information is not particularly limited.

[0149] [Effects, etc.] Hereinafter, examples of inventions obtained from the disclosure of this specification will be described, and effects, etc. obtained from the exemplified inventions will be explained.

[0150] Invention 1 is a work situation analysis system 20 comprising: a location information acquisition unit 24 that acquires location information at the workplace of a subject of a plurality of workers performing work at the workplace; a work information acquisition unit 25 that acquires work information indicating the work status of the subject from an information terminal 40 that the subject uses for work; an acquisition unit 26 that acquires first information including relationship information that indicates the work relationships at the workplace between the plurality of workers and at least one of area information that indicates the location and use of each of a plurality of areas included in the workplace; an analysis unit 27 that calculates feature amounts for a predetermined period based on the location information, the work information, and the first information, and analyzes the work situation of the subject using statistically processed values ​​obtained by statistically processing the calculated feature amounts for the predetermined period and a predetermined estimation formula; and an output unit 28 that outputs analysis result information to display the results of the analysis.

[0151] Such a work situation analysis system 20 can provide more objective analysis results of the work situation by analyzing the work situation of the subject based on location information, work information, and first information.

[0152] Invention 2 is the work situation analysis system 20 of Invention 1, in which the analysis unit 27 calculates the feature values ​​for each unit period shorter than the predetermined period for the predetermined period, and obtains at least one of the cumulative value, average value, maximum value, minimum value, standard deviation, variance, mode, number of times above the threshold, and number of times below the threshold for the feature values ​​for the predetermined period as statistical processed values.

[0153] Such a work situation analysis system 20 can improve the accuracy of the analysis by acquiring feature values ​​such as cumulative value, average value, maximum value, minimum value, standard deviation, variance, mode, number above the threshold, and number below the threshold, and analyzing the work situation of the subject.

[0154] Invention 3 is the work situation analysis system 20 of Invention 1 or 2, wherein the analysis unit 27 analyzes the work situation of the subject at a predetermined time interval that is shorter than the predetermined period.

[0155] Such a work situation analysis system 20 can provide analysis results of the work situation more frequently than a predetermined period.

[0156] Invention 4 is the work situation analysis system 20 of Invention 3, wherein the analysis unit 27, when the calculated feature quantities are less than those for a predetermined period, and when the feature quantities are feature quantities to be subjected to a first statistical processing, performs the first statistical processing on the feature quantities with a data amount less than those for the predetermined period to obtain a statistical processing value, and when the feature quantities are feature quantities to be subjected to a second statistical processing, complements the shortfall in the feature quantities and performs the second statistical processing on the feature quantities for the predetermined period obtained by the complementation to obtain a statistical processing value, wherein the first statistical processing is processing to calculate an average value, a maximum value, a minimum value, a standard deviation, a variance, or a mode, and the second statistical processing is processing to calculate a cumulative value, the number of times a threshold value is exceeded, or the number of times a threshold value is exceeded.

[0157] Such a work situation analysis system 20 can provide the results of an analysis of the work situation by complementing the features according to the statistical processing performed on the features, even if it can only calculate features for a data amount less than that for a specified period.

[0158] Invention 5 is the work situation analysis system 20 of any of Inventions 1 to 4, wherein the acquisition unit 26 further acquires second information including at least one of the subject's biometric information, the subject's exercise index, and reported information obtained by the subject's self-report, and the analysis unit 27 calculates feature quantities for a predetermined period based on the location information, work information, the first information, and the second information.

[0159] Such a work situation analysis system 20 can provide more objective analysis results of the work situation by analyzing the work situation of the subject based on location information, work information, first information, and second information.

[0160] Invention 6 is the work situation analysis system 20 of any of Inventions 1 to 5, in which the analysis unit 27 acquires statistically processed values ​​for a plurality of workers including the subject, and analyzes the work situation for the organization to which the subject belongs by applying the acquired statistically processed values ​​to a predetermined estimation formula, and the output unit 28 outputs analysis result information to display the results of the analysis for the organization.

[0161] Such a work situation analysis system 20 can provide more objective analysis results of the work situation by analyzing the work situation of the organization to which the subject belongs based on location information, work information, and first information.

[0162] Invention 7 is a work situation analysis method executed by a computer, the work situation analysis method including: a step S12 of acquiring location information at the workplace of a subject of a plurality of workers performing work at the workplace; a step S13 of acquiring work information indicating the work status of the subject from an information terminal 40 used by the subject for work; a step S11 of acquiring first information including relationship information indicating the work relationships at the workplace between the plurality of workers and at least one of area information indicating the location and use of each of a plurality of areas included in the workplace; steps S15 to S17 of calculating feature amounts for a predetermined period based on the location information, the work information, and the first information, and analyzing the work situation of the subject using statistically processed values ​​obtained by statistically processing the calculated feature amounts for the predetermined period and a predetermined estimation formula; and a step S18 of outputting analysis result information for displaying the results of the analysis.

[0163] Such a work situation analysis method can provide more objective analysis results of the work situation by analyzing the work situation of the subject based on location information, work information, and first information.

[0164] Invention 8 is a program for causing a computer to execute the work situation analysis method of Invention 7.

[0165] According to such a program, the computer can provide a more objective analysis result of the working situation by analyzing the working situation of the subject based on the location information, work information, and first information.

[0166] (Other Embodiments) Although the embodiments have been described above, the present invention is not limited to the above-described embodiments.

[0167] For example, in the above embodiment, the work situation analysis system is described as being realized by one or more server devices. As such, the "system" in this specification may be configured by a single device or by multiple devices. When the system is configured by multiple devices, the components (especially functional components) of the system may be allocated in any way among the multiple devices.

[0168] Furthermore, the method of communication between the devices in the above-described embodiment is not particularly limited. Furthermore, a relay device (such as a broadband router, not shown) may be involved in the communication between the devices.

[0169] In the above-described embodiment, the processing performed by a specific processing unit may be performed by another processing unit. The order of multiple processing operations may be changed, or multiple processing operations may be performed in parallel.

[0170] In the above-described embodiments, each component may be realized by executing a software program suitable for that component, or by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory.

[0171] Furthermore, each component may be realized by hardware. For example, each component may be a circuit (or integrated circuit). These circuits may form a single circuit as a whole, or each may be a separate circuit. Furthermore, each of these circuits may be a general-purpose circuit or a dedicated circuit.

[0172] Furthermore, the general or specific aspects of the present invention may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a computer-readable recording medium such as a CD-ROM, or as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium.

[0173] For example, the present invention may be realized as a work situation analysis method executed by a computer such as the work situation analysis system of the above-described embodiment, or as a program (computer program product) for causing a computer to execute the work situation analysis method. Furthermore, the present invention may be realized as a computer-readable non-transitory recording medium on which such a program is recorded.

[0174] In addition, the present invention also includes forms obtained by applying various modifications to each embodiment that a person skilled in the art would think of, or forms realized by arbitrarily combining the components and functions of each embodiment within the scope of the present invention.

[0175] 20 Work situation analysis system 24 Location information acquisition unit 25 Work information acquisition unit 26 Acquisition unit 27 Analysis unit 28 Output unit 30 Positioning system 40 Information terminal

Claims

1. A work situation analysis system comprising: a location information acquisition unit that acquires location information at a workplace of a target person among a plurality of workers performing work at the workplace; a work information acquisition unit that acquires work information indicating the work status of the target person; an acquisition unit that acquires first information including relationship information that indicates the work-related relationships at the workplace between the plurality of workers and at least one of area information that indicates the location and use of each of a plurality of areas included in the workplace; an analysis unit that calculates feature amounts for a predetermined period based on the location information, the work information, and the first information, and analyzes the work situation of the target person using statistical processing values ​​obtained by statistically processing the calculated feature amounts for the predetermined period and a predetermined estimation formula; and an output unit that outputs analysis result information to display the results of the analysis.

2. The work situation analysis system of claim 1, wherein the analysis unit calculates the feature amount for each unit period shorter than the specified period for the specified period, and obtains at least one of the cumulative value, average value, maximum value, minimum value, standard deviation, variance, mode, number above a threshold, and number below a threshold of the feature amount for the specified period as the statistical processing value.

3. The work situation analysis system according to claim 1 or 2, wherein the analysis unit analyzes the work situation of the subject at a predetermined time interval shorter than the predetermined period.

4. The work situation analysis system of claim 3, wherein the analysis unit: if the calculated data amount of the feature is less than the specified period, and the feature is a feature to be subjected to a first statistical processing, performs the first statistical processing on the feature with the data amount less than the specified period to obtain the statistical processing value; if the feature is a feature to be subjected to a second statistical processing, complements the shortfall in the feature and performs the second statistical processing on the feature for the specified period obtained by the complementation to obtain the statistical processing value; the first statistical processing is a process of calculating an average value, a maximum value, a minimum value, a standard deviation, a variance, or a mode; and the second statistical processing is a process of calculating a cumulative value, the number of times a threshold value is exceeded, or the number of times a threshold value is exceeded.

5. The work situation analysis system of claim 1 or 2, wherein the acquisition unit further acquires second information including at least one of the subject's biometric information, the subject's exercise index, and the subject's self-reported information, and the analysis unit calculates the feature amount for the specified period based on the location information, the work information, the first information, and the second information.

6. The working situation analysis system of claim 1 or 2, wherein the analysis unit acquires the statistical processing values ​​for the plurality of workers including the subject, and performs an analysis of the working situation of the organization to which the subject belongs by applying the acquired statistical processing values ​​to the predetermined estimation formula, and the output unit outputs the analysis result information to display the results of the analysis of the organization.

7. A work situation analysis method executed by a computer, comprising the steps of: acquiring location information at a workplace of a subject among a plurality of workers performing work at the workplace; acquiring work information indicating the work status of the subject from an information terminal used by the subject for work; acquiring first information including relationship information indicating the work-related relationships at the workplace between the plurality of workers and at least one of area information indicating the location and use of each of a plurality of areas included in the workplace; calculating feature amounts for a predetermined period based on the location information, the work information, and the first information, and analyzing the work situation of the subject using statistical processing values ​​obtained by statistically processing the calculated feature amounts for the predetermined period and a predetermined estimation formula; and outputting analysis result information for displaying the results of the analysis.

8. A program for causing the computer to execute the work situation analysis method according to claim 7.

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