Activity analysis system

Abstract

To provide a system that produces output that will help analyze current working patterns.SOLUTION: An activity analysis system has storage means, control means, and display means, where the storage means records management items including at least matters identifying an individual, activities performed by the individual, and a time spent on the activities, the control means performs cluster analysis based on each data of the matters identifying the individual, the activities, and the time, and the display means outputs clusters created by the control means in a graphical format. The activity analysis system performs cluster analysis of the matters identifying the individual and displays the results.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a man-hour system developed to examine the working style and activity status of individuals in corporations engaged in business activities and other organizations and groups engaged in various social activities, in order to maximize the benefits of each individual and the organizations to which they belong, and in particular to an activity analysis system that analyzes work content and behavior content. [Background technology]

[0002] In recent years, many countries around the world have experienced declining birth rates and aging populations, making securing a labor force a major social issue. Japan, in particular, is the country with the most advanced aging population and declining birthrates, where long working hours have become the norm and women are said to be lagging behind in the workplace. Under these circumstances, improving the working environment is an urgent task, and individual companies are also making efforts to promote work style reform. For example, many patent applications have been filed for systems that improve the efficiency of employee labor and related work, and the technology described in JP 2004-310530 A (Patent Document 1) is one such example.

[0003] Alternatively, patent applications have been filed for systems that analyze individual work styles and find more efficient and productive work styles, such as the technology described in Japanese Patent Laid-Open Publication No. 2004-038234 (Patent Document 2). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-310530 [Patent Document 2] Japanese Patent Application Laid-Open No. 2004-038234 Summary of the Invention [Problem to be solved by the invention]

[0005] In the trend of recent work style reforms like this, there has been a demand for the realization of a system that is more suitable for the interests of both organizations such as companies and the individuals working there. The applicant of the present application has created a system that is more user-friendly and more purposeful in line with the demands of society in recent years. Although it is a part of such a system, in order to analyze the work style of individuals and better reform the work styles of both individuals and organizations, it provides a system that generates outputs to assist in analyzing the current work style.

Means for Solving the Problem

[0006] One aspect of the present disclosure is an activity analysis system having a storage means for recording management items including at least items for identifying an individual, activities performed by the individual, and time spent on the activities, a control means for performing cluster analysis based on each data of the items for identifying the individual, the activities, and the time, and a display means for outputting the clusters created by the control means in a chart format, and which performs cluster analysis on the items for identifying the individual and displays the result.

[0007] Since one aspect of the present disclosure is an activity analysis system having a storage means, a control means, and a display means, it can record necessary management items, perform necessary calculations, and output the results. And because it is provided with the storage means for recording management items including at least items for identifying an individual, activities performed by the individual, and time spent on the activities, by recording an individual belonging to an organization or the like, their activities, and the time spent on those activities, these can be retained and used as data for analyzing the work style of the individual.

[0008] And also, since it has the control means for performing cluster analysis based on each data of the matters identifying the individual, the activity, and the time, matters or activities identifying the individual can be classified into several clusters. Furthermore, since it has the display means for outputting the clusters created by the control means in a chart format, the classification result can be easily recognized visually. In addition, in order to perform cluster analysis of the matters identifying the individual and display the result, a plurality of individuals can be classified into several clusters from the activity and the time spent on the activity, and the characteristics of the working styles of the individuals included in each of the classified clusters can be found, which can help to find the direction of individual working style reform.

[0009] One aspect of the present disclosure can be an activity analysis system that outputs the result of the cluster analysis as an activity table. Since one aspect of the present disclosure is an activity analysis system that outputs the result of the cluster analysis as an activity table, those with similar working styles (individuals) are shown in one activity table, which helps to find the common working style among the individuals included therein.

[0010] One aspect of the present disclosure can be an activity analysis system in which the cluster analysis uses the Ward method and the Euclidean distance. Since one aspect of the present disclosure is an activity analysis system in which the cluster analysis uses the Ward method and the Euclidean distance, the cluster analysis can obtain highly accurate results by using the Ward method, and the Euclidean distance can obtain the value that most conforms to the straight-line distance for analyzing a single unit of working hours.

[0011] One aspect of the present disclosure can be an activity analysis system that further performs cluster analysis of the activity. In one aspect of the present disclosure, since an activity analysis system that further performs cluster analysis of the activities is used, it is possible to preliminarily exclude specific activities and lead to a result that more strongly reflects the relationship between the remaining activities.

[0012] One aspect of the present disclosure can be a method for creating an activity table that uses any of the activity analysis systems described above, performs cluster analysis of the activities, and then performs cluster analysis of items for identifying the individual to create an activity table. In one aspect of the present disclosure, since a method for creating an activity table that uses any of the activity analysis systems described above, performs cluster analysis of the activities, and then performs cluster analysis of items for identifying the individual to create an activity table is used, it is possible to obtain an activity table in which specific activities are excluded in advance and the relationship between the remaining activities is more strongly reflected.

Advantages of the Invention

[0013] According to the present disclosure, in order to practice the reform of the individual's working style, it is possible to provide assistance for analyzing the characteristics of the individual's working style and serve as a basis for improving the work performed by individuals and groups.

Brief Description of the Drawings

[0014]

Figure 1

Figure 2

Figure 3

Figure 4

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Figure 6

Figure 7

Mode for Carrying Out the Invention

[0015] Generally, a man-hour system is a system introduced to analyze the working and moving ways of each individual constituting a group such as a corporation, to realize appropriate labor without overburdening the individual, and to realize efficient distribution of labor force for the group. Among such systems, the system taken up here is an activity analysis system (hereinafter also simply referred to as the "system") that analyzes the working ways of individuals and produces an output that helps analyze the working ways of individuals in order to find more efficient and productive working ways.

[0016] <System Configuration> FIG. 1 is a system configuration diagram of the activity analysis system 6. This system 6 has a management server 1, personal terminals 2 (2a, 2b, 2c,...) used by individuals such as employees who carry out daily work, and administrator terminals 3 (3a, 3b, 3c,...) used by individuals (hereinafter also referred to as "administrators") who manage the working ways of managers and the personnel department, etc. These are respectively connected via a network 5. Note that a system administrator (not shown) who manages the system is also connected to the system via the network 5.

[0017] The management server 1 receives instructions from the personal terminals 2 and the administrator terminals 3 via the network 5 and performs processing according to the instructions. The configuration of this management server 1 includes a central processing unit (CPU) that functions as an arithmetic device and a control device, a main storage device such as a RAM, an external storage device such as a hard disk and an SSD, a communication device such as a modem, and a computer program. These components constitute functional blocks described later.

[0018] This management server 1 may be a computer management server other than various terminals 2 and 3 connected to the network, but it can also be a management server that doubles as the computer of the administrator terminal 3. Furthermore, it may be a cloud management server used for cloud computing.

[0019] The personal terminal 2 is a computer used by an individual belonging to a group such as a company or an individual who has received a certain kind of permission, and can be one or more computers 2a, 2b, ···. This personal terminal 2 is configured with a communication device capable of connecting to and communicating with a network such as an in-house LAN or the Internet. When a program is started and connected to a network such as the Internet, it can acquire and display the data stored in the management server 1, transmit the data input through the input device to the management server 1, or receive the data from the management server 1 and print and output it through the output device. The computer serving as this personal terminal 2 may be a so-called personal computer, or a mobile phone terminal, a tablet terminal, etc.

[0020] The administrator terminal 3 is a computer used by an administrator and can be one or more computers 3a, 3b, ···. This administrator terminal 3 is configured with a communication device capable of connecting to and communicating with a network. When a program is started and connected to a network such as the Internet, it can acquire and display the data stored in the management server 1, transmit the data input through the input device to the management server 1, or receive the data from the management server 1 and output it in the form of an email, etc. through the output device. The computer serving as this administrator terminal 3 may be a so-called personal computer, or a mobile phone terminal, a tablet terminal, etc.

[0021] Fig. 2 shows the functional configuration of the management server 1 as a block diagram. As shown in Fig. 2, the management server 1 has a control means 11, an ID recognition means 12, a storage means 13, a display means 14, and other means 15 such as a communication means.

[0022] The control means 11 controls various means described below and operates to perform their functions. For example, it selects and retrieves necessary data from the data recorded as various management items in the storage means 13, and performs calculations according to the purpose.

[0023] The ID recognition means 12 has a function of identifying predetermined ID information for identifying a person who can access the system 6. More specifically, for access requests from various terminals 2 and 3 to the system 6, it determines whether the person has access rights, and if so, the degree or what the access rights are for, etc. An example of the mode of determining the presence or absence of access rights based on a password is given.

[0024] The storage means 13 records items necessary for managing personal information such as an individual's name, employee number, management number, assignment, etc., various items indicating the content of work, customer name, activities performed by an individual, time spent on those activities, and other man-hours as management items, and has a function of providing a database. Taking an individual A of a certain company as an example, for example, the individual's name, assignment, attendance days of individual A, activities (work content), time spent on each activity (work hours), etc. all correspond to management items.

[0025] The display means 14 has a function of displaying the management items recorded by the storage means 13 and the items obtained by processing by the control means 11 on various terminals 2 and 3, outputting them as a report, or displaying the clusters obtained by classifying individuals in a chart format. It also displays the input screens on various terminals.

[0026] The management server 1 can also be provided with various functions such as alert generation means for observing abnormal values and issuing alerts, and communication means for transmitting various outputs such as alert information and reports to output target terminals such as the personal terminal 2 and the administrator terminal 3 (other means 15).

[0027] <Functions of the system> To analyze the work content or activity content (collectively referred to as "activity") of each employee, officer, member, etc. (collectively referred to as "individuals") in an enterprise, group, project, or other organization (collectively referred to as "organization"), it is necessary to accurately grasp the activity and the time spent on that activity (referred to as "working hours"). In the system, in order to incorporate an individual's activity into the system, various activities performed by individuals, which are determined in advance according to the organization to which the individual belongs, can be specified by more detailed options classified into large categories, medium categories, and small categories.

[0028] For example, taking a man-hour system applicable to a construction company and its employees as an example, the large categories include management items such as sales, planning, accounting, human resources, order receiving, design, construction, etc., which are prepared as options. The medium categories include management items such as planning and formulation, system implementation, personnel evaluation, participation in training, etc., and the small categories include management items such as meetings, document creation, movement, phone calls and emails, copying, etc., which are all prepared as options. Individuals such as employees can accurately register their activities by selecting appropriate options from each classification in the order of large category, medium category, and small category.

[0029] In the system, the activities performed by each individual are basically carried out by each individual using the personal terminal 2 to input and register them into the system. Through the individual's input operation, items identifying the individual such as the individual's name, the activities performed by the individual, and management items such as working hours are recorded in the storage means 13.

[0030] While registering the activity and working hours as actual achievements as described above, it is also possible to write the plan for future work. The input of the plan is also carried out in the same way as when registering the actual achievements. That is, in the individual's input method, there is no difference between the actual achievements and the plan. If the input date and time are in the past, it is the input of the actual achievements of the work done, and if the date and time are in the future, it is the input of the plan for future work, and the storage means 13 records this.

[0031] Regarding the scheduled input, individual B, who is the supervisor of individual A, can also input the schedule of individual A. For example, when individual A is involved in the work of a certain facility construction project this month, and individual B, who is the administrator, is considering assigning individual A to another facility construction project next month, or when individual B summons individual A to a meeting scheduled on a certain date, etc. However, persons other than individual A can adopt a mode that makes it impossible to input achievements, that is, past activities. Also, even for individual A, re - input can be made impossible after registration once and obtaining the approval of individual B.

[0032] <System functions> The system 6 can create, display, or utilize the activity table described below.

[0033] (1) Activity table (Figure 3) An individual can average the time spent on each activity during a day's work over a certain period such as monthly, and create a list called an activity table. In other words, the activity table is a table showing items identifying an individual, the activities the individual performs, and the time spent on those activities. An example of such an activity table is shown in Figure 3. In Figure 3, for all 61 employees of Company A, for each individual, the name, department, and the time spent on each of the activities from Activity A to Activity K in a day are shown in hours.

[0034] In the activity table 20 shown in Table 3, Tetsuya Yamada with the serial number 1 belongs to the planning department. When averaging the working hours of a certain month, it can be seen that he spends 10.6 hours on Business A per day, and for Business B to Business H, although omitted in the figure, he spends 0.4 hours on Business I, 0 hours on Business J, and 0 hours on Business K. The types (number) and content of activities can be determined by each company. For example, Business A can be the core business of planning and formulation, Business I can be the core business of system implementation, Business J can be non-core business such as phone calls and emails, and Business K can be non-core business such as clerical work like copying.

[0035] Through the input form previously created by the display means 14, for the activity table 20, when an individual inputs from the personal terminal 2 the labor hours spent on each activity listed in the activity table 20, that is, how much time is spent on each activity, the storage means 13 records the input items as management items and accumulates them in the record database. Then, in accordance with the creation instruction of the activity table 20 from the administrator terminal 3 by the administrator, the control means 11 calls the time spent on each activity recorded in the storage means 13, performs necessary calculations such as aggregation, and the display means 14 outputs the activity table 20 in a form as shown in, for example, Figure 3.

[0036] (2) Cluster analysis (Figures 4 to 7) The above activity table 20 shows, for each individual, how much time is spent on each activity. However, even if there are company-wide characteristics such as the tendency of the working styles of individuals across the entire company, it is difficult to identify them. Therefore, in the system 6, a cluster analysis is performed on the activity table 20 including all individuals, dividing it into clusters that group individuals with similar working styles. In other words, in the system 6, using the time spent by each individual on each activity as data, individuals are classified into several clusters based on the similarity between these data. And once such clusters are obtained, based on them, the administrator and each individual can find out the relationships between individuals and the tendencies of working styles, etc., and can utilize them for work style reform.

[0037] The activity analysis system 6 can perform cluster analysis, which is one of the methods of machine learning (AI). And among the methods of cluster analysis, the hierarchical agglomerative method can be used. The hierarchical method is a method of calculating the similarity between all data and grouping from the combinations with high similarity. On the other hand, the non - hierarchical method has the demerit that it is necessary to determine the number of clusters to be classified and the initial values in advance, and it is difficult to make an objective judgment because it depends on the knowledge and experience of the analyst, so it is difficult to adopt. Also, although the non - hierarchical method has the merit that it is possible to classify big data because the amount of calculation is small, since the number of personal activities is limited and the amount of data will not be large, there is no need to utilize such a merit.

[0038] Also, among the hierarchical methods, there are hard clustering in which each individual belongs to one group and soft clustering in which each individual is allowed to belong to multiple groups, but hard clustering can be performed. This is because it is easier to clearly recognize the characteristics of an individual by making the individual belong to one cluster rather than being classified into multiple clusters. However, it is also possible to perform soft clustering if necessary.

[0039] To form clusters, there are several methods for gathering similar things. For example, the single - linkage method, the complete - linkage method, the group - average method, Ward's method, the centroid method, the weighted - average method, the median method, etc. can be mentioned. And when the similarity is regarded as the distance between data, there are also several types of ways to define that distance. For example, the Euclidean distance, the Mahalanobis distance, the Manhattan distance, the Chebyshev distance, etc. can be mentioned.

[0040] As an example, the distance between each data can use the Euclidean distance, and a method of calculating the similarity by the Ward method can be adopted. This is because although the Ward method has a certain amount of calculation, its accuracy is high. The Euclidean distance represents the straight-line distance between two points, which is easy to understand, and only the unit of data such as the time spent on all activities needs to be considered.

[0041] The specific distance between individuals using the Euclidean distance is calculated by finding the difference in labor time between the two for each activity, squaring the difference, summing up these squared values obtained for each activity for all activities, and determining it as the square root of the value. This is calculated for all individuals between every pair of other individuals. Then, the two individuals with the shortest distance are merged, and the merged entity is treated as one unit, and those with a close distance between the merged unit and other individuals or other units are merged, and the merged ones are grouped together. This operation is repeated until finally merged into one. In this way, a dendrogram is formed simultaneously. Finally, according to the desired number of clusters, a plurality of clusters, for example, 3 to 8 types of clusters, are output.

[0042] An example of clustering analysis of all 61 individuals shown in Figure 3 and classifying them into the top four types of clusters is shown in Figures 4 to 7. If the four clusters are named cluster a to cluster d respectively, Figure 4 shows cluster a, Figure 5 shows cluster b, Figure 6 shows cluster c, and Figure 7 shows cluster d.

[0043] The activity tables 21, 22, 23, and 24 shown in FIGS. 4 to 7 are such that when the administrator gives an instruction from the administrator terminal 3 to perform cluster analysis, inputs the period during which the activity to be analyzed was performed, and the number of clusters to be obtained, the control means 11 calls up the items identifying individuals, the activities performed by the individuals, and the time spent on the activities recorded in the storage means 13, and performs calculations for cluster analysis. Then, the display means 14 creates and outputs, for example, four graphs as shown in FIGS. 4 to 7, the number of which is the number of clusters to be obtained from the generated clusters.

[0044] In addition, items necessary for these analyses, such as the activity to be analyzed, the selection of a method for gathering similar items used in cluster analysis, and the selection of a method for calculating the distance between two items, can be selected in more detail by the administrator or the like so that the person making the input can determine them. The control means 11 performs processing based on such selections.

[0045] The system 6 creates FIGS. 4 to 7, but does not interpret the classification into four clusters, so it is necessary for the administrator or the like to find the characteristics of the working methods for each cluster from these tables. When the administrator refers to FIG. 4, it can be seen that cluster a is a group of employees mainly performing operations I and J. That is, it can be seen that the employees belonging to cluster a perform the core operation of system execution and also perform non-core operations such as telephone calls and emails as main operations in the same way as the core operation.

[0046] Similarly, when the administrator refers to FIG. 5, it can be seen that cluster b is a group of employees mainly performing operation A. That is, it can be seen that the employees belonging to cluster b mainly perform the core operation of planning and formulation. Also, referring to FIG. 6, it can be seen that cluster c is a group of employees mainly performing operation J. That is, it can be seen that the employees belonging to cluster c mainly perform non-core operations such as telephone calls and emails. Then, referring to FIG. 7, it can be seen that in cluster d, it is a group of employees mainly engaged in Business I. That is, it can be seen that the employees belonging to cluster d mainly perform the core business of system execution.

[0047] Based on the above cluster classification, the administrator can find out the working styles of each individual and the characteristics of the working styles in the group, etc., and can link them to the support and suggestions for the working styles of each individual, and the reform of the working styles of individuals in the group, etc. For example, from the fact that clusters a and d are obtained, it can be seen that there are many individuals who mainly perform the core business of system execution regardless of the department they belong to, and there are also many individuals who mainly perform non-core businesses such as phone calls and emails together with the core business of system execution. On the other hand, while there are many individuals mainly engaged in the core business of planning and proposal in cluster b, no group that mainly performs non-core business together with the core business of planning and proposal has been found. Although it may be due to the characteristics of each core business of system execution and planning and proposal, it is suggested that there may be room for consideration in the direction of reducing non-core businesses such as phone calls and emails for individuals whose core business is system execution.

[0048] The examples shown in the above embodiments are only one embodiment of the present invention, and within the scope not departing from the gist of the present invention, changes to the components in the embodiments, addition of known technologies, and other modifications can be appropriately made. For example, the required number of clusters is not limited to 4, and other numbers may be used. Also, as a method of gathering similar things, a method other than the Ward method can be used, and a distance other than the Euclidean distance can also be adopted as the method of determining the distance between data.

[0049] Also, regarding the activities, although all activities or the activities selected by the administrator or the like are used, cluster analysis can be performed on all activities, activities with low relevance to each other can be found, and such activities can be excluded to perform cluster analysis on individuals.

[0050] Cluster analysis for individuals leads to distances between individuals based on activities and the time spent on them, and classifies them into clusters. For cluster analysis of activities, the distances between activities can be derived based on the time spent by individuals and then classified into clusters.

[0051] By performing cluster analysis of activities before cluster analysis of individuals, specific activities can be excluded in advance, and results that more strongly reflect the relationships between the remaining activities can be obtained.

Explanation of Signs

[0052] 1 Management server 2, 2a, 2b, 2c Personal terminals 3, 3a, 3b, 3c Administrator terminals 5 Network 6 Activity analysis system 11 Control means 12 ID recognition means 13 Memory means 14 Display means 15 Other means 20 Activity table 21 Activity table showing cluster a 22 Activity table showing cluster b 23 Activity table showing cluster c 24 Activity table showing cluster d

Claims

【Claim 1】 Storage means for recording management items including at least items identifying each individual, activities performed by each individual, and time spent on the activities, for a plurality of individuals constituting a group; Control means for performing cluster analysis; Display means for outputting the clusters created by the control means in a chart format, and having: An activity analysis system that uses the time spent by each individual on each activity as data, performs cluster analysis to divide the individuals with similar working styles into clusters based on the similarity between the data, and displays the results.

Images