JP7829162B2 - Store management system, store management device, and store management method - Google Patents

Description

Applicable to Article 30, Paragraph 2 of the Patent Act. Published on February 24, 2022, in Panasonic Corporation's online press release and product/service introduction.

This disclosure relates to a store management system, a store management device, and a store management method.

Patent Document 1 describes a method for outputting a business day comparison report using an information processing system to extract and compare sales data for two business days from customer order data collected and recorded chronologically at a store. This output method displays the target month and the comparison month on the same screen in a calendar format, allowing the user to arbitrarily select the target date within the target month and the comparison date within the comparison month. Furthermore, the target month and the comparison month can be changed to other months. When the target date and comparison date are selected and accepted, predetermined data is extracted and edited from the sales data for each of the two selected business days. After performing a predetermined comparison calculation using the edited data from both dates, the calculation result is output.

Patent No. 5046520

Furthermore, in chain stores with multiple locations, if various performance data related to economic activity can be displayed in a comparable manner, store staff can analyze various issues inherent in the store based on the displayed information and make improvements. This can contribute to increased efficiency and productivity in store operations.

The output method described in Patent Document 1 only allows for the extraction and comparison of sales data for two business days; it does not enable comparative evaluation using multiple types of performance data. Furthermore, the lack of graphs and time-series data makes it impossible to conduct detailed analysis and improvement of store issues.

This disclosure provides a store management system, store management device, and store management method that enable detailed analysis and improvement of store issues by displaying various performance data in a comparable manner.

One aspect of this disclosure is a store management system comprising at least one computer device and at least one display device, wherein the processor of the computer device acquires work performance information and sales performance information, and based on the work performance information and sales performance information, simultaneously displays on the display device a work performance graph showing work performance along a time axis and a sales performance graph showing sales performance along the time axis, wherein the sales performance graph includes one or more peaks, and the work performance graph includes one or more peaks corresponding to the peaks in the sales performance graph.

One aspect of this disclosure is a store management device comprising a display device and a processor, wherein the processor acquires work performance information and sales performance information, and based on the work performance information and sales performance information, simultaneously displays on the display device a work performance graph showing work performance along a time axis and a sales performance graph showing sales performance along the time axis, wherein the sales performance graph includes one or more peaks, and the work performance graph includes one or more peaks corresponding to the peaks in the sales performance graph.

One aspect of this disclosure is a store management method using a processor in a store management system comprising at least one computer device and at least one display device, comprising the steps of: acquiring work performance information and sales performance information; and simultaneously displaying on the display device a work performance graph showing the work performance along a time axis and a sales performance graph showing the sales performance along the time axis, based on the work performance information and sales performance information, wherein the sales performance graph includes one or more peaks, and the work performance graph includes one or more peaks corresponding to the peaks in the sales performance graph.

One aspect of this disclosure is a store management system comprising at least one computer device and at least one display device, wherein a processor in the computer device acquires work performance information and work plan information, calculates the number of overtime hours for each predetermined aggregation unit based on the work performance information and the work plan information, and displays the number of overtime hours on the display device.

One aspect of this disclosure is a store management device comprising a display device and a processor, wherein the processor acquires work performance information and work plan information, calculates the number of overtime hours for each predetermined aggregation unit based on the work performance information and the work plan information, and displays the number of overtime hours on the display device.

One aspect of this disclosure is a store management method using a processor in a store management system comprising at least one computer device and at least one display device, the method comprising: acquiring work performance information and work plan information; calculating the number of overtime hours for each predetermined aggregation unit based on the work performance information and the work plan information; and displaying the number of overtime hours on the display device.

According to this disclosure, by displaying various performance data in a comparable manner, it is possible to conduct detailed analysis and improvement of store challenges.

Block diagram showing an example configuration of a store management system corresponding to the embodiments of this disclosure. A conceptual diagram showing the operational flow of labor time input evaluation corresponding to the embodiments of this disclosure. Conceptual diagram showing an example of a display screen for labor hour input evaluation corresponding to the embodiments of this disclosure. Conceptual diagram showing an example of a display screen for labor hour input evaluation corresponding to the embodiments of this disclosure. Conceptual diagram showing an example of a display screen for personnel analysis corresponding to the embodiments of this disclosure. Conceptual diagram illustrating a comparison store selection screen corresponding to the embodiments of this disclosure. A conceptual diagram illustrating a store comparison screen corresponding to the embodiments of this disclosure. A conceptual diagram showing an example of a display screen for overtime analysis corresponding to the embodiments of this disclosure. A conceptual diagram showing a second display screen example for overtime analysis, corresponding to the embodiments of this disclosure. Conceptual diagram showing an example of a display screen for personnel analysis corresponding to the embodiments of this disclosure. Conceptual diagram showing a second display screen example for personnel analysis corresponding to the embodiments of this disclosure. A conceptual diagram illustrating the available personnel screen corresponding to the embodiments of this disclosure.

The embodiments will be described in detail below, with reference to the drawings as appropriate. However, unnecessarily detailed explanations may be omitted. For example, detailed explanations of already well-known matters or redundant explanations of substantially identical configurations may be omitted. This is to avoid unnecessarily verbose explanations and to facilitate understanding for those skilled in the art. The accompanying drawings and the following explanation are provided to enable those skilled in the art to fully understand this disclosure and are not intended to limit the subject matter described in the claims.

For example, the terms "part" or "device" in the embodiments are not limited to physical configurations mechanically implemented by hardware, but also include configurations whose functions are implemented by software such as programs. Furthermore, the functions of one configuration may be implemented by two or more physical configurations, or the functions of two or more configurations may be implemented by, for example, one physical configuration.

(This embodiment)
Figure 1 is a block diagram showing an example configuration of a store management system corresponding to an embodiment of the present disclosure.

The store management system 10 comprises a server device 100, a store system 200, one or more store terminals 300, and one or more worker terminals 400.

The server device 100, the store system 200, one or more store terminals 300, and one or more worker terminals 400 are connected to each other via a communication network 30, such as the Internet, enabling them to communicate with one another.

The server device 100 is an example of a computer device. The server device 100 comprises at least a processor 110, a storage device 120, and a transceiver unit 130. The processor 110 may include an MPU (Micro Processing Unit), a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or a GPU (Graphics Processing Unit). The processor 110 may be composed of various integrated circuits (e.g., LSI (Large-Scale Integration), FPGA (Field Programmable Gate Array)). The processor 110 implements various functions by executing programs stored in the storage device 120. The processor 110 comprehensively controls each part of the server device 100 and performs various processes.

The processor 110 references and executes the store management program stored in the storage device 120, thereby functionally realizing the work schedule/task plan creation unit 111, the required man-hour calculation unit 112, the analysis unit 113, and the improvement proposal/plan generation unit 114.

The storage device 120 stores store management programs and various types of information. The storage device 120 may include memory. The storage device 120 includes a time-based work plan database (DB), an improvement suggestion pattern database, a related information database, a business/workload forecast data database, an employee/employee skills database, a time-based work performance database, and a time-based sales performance database. The storage device 120 may further include other databases.

The hourly work plan database stores hourly work plan information (work schedule information) for each store managed by the store management system 10. The improvement suggestion pattern database stores improvement suggestion pattern information for calculating improvement suggestions.

The business and workload forecast data database stores data on the business operations of each store managed by the store management system 10, as well as forecast data on workload for a specified period. This specified period may be, for example, one week, one month, six months, or one year.

The employee and employee skills database stores data about employees belonging to each store managed by the store management system 10. For example, information such as the employee's assigned store, available working days and times, years of experience, and skills may be included in the employee and employee skills database.

The hourly work performance database stores hourly work performance data for each store managed by the store management system 10. This work performance data includes information such as which employee at a particular store worked from what time to what time.

The hourly sales performance database stores hourly sales performance data for each store managed by the store management system 10.

The related information database stores other related information.

The transmitting/receiving unit 130 includes a communication interface. The transmitting/receiving unit 130 transmits and receives data between the server device 100 and an external device.

The store system 200 is a system managed and operated by the store manager or other personnel. The store system 200 includes one or more computer devices. Each computer device comprises at least a processor and memory. The processor may include an MPU, CPU, DSP, or GPU. The processor may also be composed of various integrated circuits (e.g., LSI, FPGA). The processor implements various functions by executing programs stored in memory. The processor comprehensively controls each part of the computer device and performs various processes.

The store system 200 has a storage device, which stores various types of information related to the store. For example, product information for items sold in the store, delivery schedule information, shipping schedule information, shipping performance information, and other related information are stored in the storage device. Since the server device 100, store terminal 300, and worker terminal 400 are connected to the store system 200 in a communication-enabled manner, they can obtain the necessary information stored in the store system 200's storage device via the communication network 30.

The store system 200 may be a conventional, general-purpose system for managing stores. Necessary information is transmitted from the store system 200 to the server device 100 via sequential processing or batch processing (such as at night). The server device 100 distributes and stores the data received from the store system 200 in the respective databases (DBs) of the storage device 120.

The store terminal 300 is a computer device installed in each store managed by the store management system 10, or in the headquarters of the store chain. The store terminal 300 comprises at least a processor and memory. The processor may include an MPU, CPU, DSP, or GPU. The processor may be composed of various integrated circuits (e.g., LSI, FPGA).

The store terminal 300 comprises at least a control unit 301, a display unit 302, an input receiving unit 303, and a transmission/reception unit 304. The control unit 301 is primarily composed of the aforementioned processor. The control unit 301 implements various functions by executing programs stored in memory. The control unit 301 comprehensively controls each part of the store terminal 300 and performs various processes. The control unit 301 communicates data with external devices such as the server device 100 via the transmission/reception unit 304, acquires necessary information, and displays it on the display unit 302. In the various display screens shown in Figure 3 and later, the control unit 301, in response to user input entered into the input receiving unit 303, performs information acquisition, calculation, and delegates analysis processing to the server device 100, and displays the necessary information on the display unit 302.

Furthermore, when we say that the server device 100 or the processor 110 of the server device 100 displays some information on the display device, it may mean that the server device 100 transmits the information for display to an external device. The store terminal 300 may be the display device itself, such as a large monitor.

The display unit 302 is a display device, such as a monitor or display device. Based on control by the control unit 301 or the processor 110 of the server device 100, the display unit 302 displays various information to the store's personnel.

The input receiving unit 303 is, for example, an input device such as a keyboard, mouse, or touch panel, and receives user input.

The transmitting/receiving unit 304 includes a communication interface. The transmitting/receiving unit 304 transmits and receives data between the store terminal 300 and an external device.

The worker terminal 400 is a terminal operated by workers at each store managed by the store management system 10. An example of a worker terminal 400 is a smartphone, but it is not limited to this. For example, the worker terminal 400 may be a tablet, laptop computer, or desktop computer. The worker terminal 400 includes at least a processor and memory. The processor may include an MPU, CPU, DSP, or GPU. The processor may be composed of various integrated circuits (e.g., LSI, FPGA). The processor implements various functions by executing programs held in memory. The processor comprehensively controls each part of the worker terminal 400 and performs various processes. The worker terminal 400 is used, for example, to input shift preference information indicating desired dates and times for working at the store, and to display the determined shift on a display device.

In Figure 1, the server device 100, the computer device of the store system 200, the store terminal 300, and the worker terminal 400 are each examples of computer devices included in the store management system of this disclosure. The display device may be provided as a display unit 302 in the store terminal 300. The display device may also be provided in a computer device other than the store terminal 300. The display device may be externally connected to the computer device or built into the computer device.

Furthermore, as long as no contradiction arises, a process performed by one processing unit may be performed by another processing unit. For example, a process described as being performed by server unit 100 may be performed by store terminal 300.

Figure 2 is a conceptual diagram showing the operational flow of the labor-hour input evaluation corresponding to the embodiment of this disclosure.

First, in the shift scheduling flow for month N, the required man-hour calculation unit 112 calculates the required man-hours for month N. A man-hour is a unit representing workload; one man-hour is defined as the amount of work one person does for one hour. If 10 people each work for two hours, the calculation would be 10 x 2 = 20 man-hours. The required man-hour calculation unit 112 may calculate the required man-hours for month N based, for example, on data stored in the business/workload forecast data database.

The work plan/task planning unit 111 creates a work plan for month N based on the calculated required man-hours. The work plan/task planning unit 111 may also create the work plan for month N based on information stored in the business/workload forecasting data DB and the employee/employee skills DB. The created work plan for month N is then modified as appropriate according to the personnel situation at each store, and the work plan for month N is finalized.

Next, employees (workers) at each store perform their tasks according to the created work schedule for month N. Information showing the completed work is stored in the worker terminals 400 and the store system 200, and then in the storage device 120 of the server device 100. After the work is completed, a review of the month N shift schedule is conducted.

The analysis unit 113 performs a personnel analysis based on the required man-hours information calculated as described above, and information indicating the work patterns of each worker and the skills of each worker stored in the employee/employee skills database. The analysis results from the analysis unit 113 are displayed on the display unit 302 of the store terminal 300.

Furthermore, the analysis unit 113 performs overtime analysis by comparing the finalized work plan for month N with the work performance information for month N stored in the hourly work performance database. The analysis results from the analysis unit 113 are displayed on the display unit 302 of the store terminal 300.

Furthermore, the analysis unit 113 performs a labor-hour input evaluation based on the results of the overtime analysis, information showing the work performance for month N stored in the hourly work performance DB, and information showing the sales performance for month N stored in the hourly sales performance DB. The labor-hour input evaluation will be described later with reference to Figures 3 and 4. The results of the labor-hour input evaluation by the analysis unit 113 are displayed on the display unit 302 of the store terminal 300.

Users of the store terminal 300 refer to the analysis results of the personnel analysis, the overtime analysis, and the labor-hour input evaluation displayed on the display unit 302 as appropriate, and adjust personnel and revise labor-hour input plans accordingly. Personnel adjustments may include, for example, changing the terms of contracts with workers. Personnel adjustments may also include providing training to workers or hiring new workers.

Figure 3 is a conceptual diagram showing an example of a display screen for labor hour input evaluation corresponding to an embodiment of this disclosure.

The analysis unit 113 retrieves work performance information from the hourly work performance database and sales performance information from the hourly sales performance database. Based on the work performance information and sales performance information, the analysis unit 113 displays a work performance graph showing work performance along a time axis and a sales performance graph showing sales performance along a time axis on the display device. In this example, the display device is the display unit 302 of the store terminal 300.

The display screen shown in Figure 3 shows two line graphs representing two types of actual values along the time axis. The first actual value is the actual value for the number of people involved, and is shown by the dashed line L1. This dashed line L1 corresponds to the work performance graph. The second actual value is the actual sales value, and is shown by the solid line L2. This solid line L2 corresponds to the sales performance graph.

The sales performance graph (solid line L2) includes one or more peaks P21 and P22. On the other hand, the work performance graph (dashed line L1) includes one or more peaks P11 and P12, corresponding to peaks P21 and P22 in the sales performance graph (solid line L2).

The work performance graph is generated by the analysis unit 113 by aggregating the man-hours worked for each day of the week and categorized as either a normal day or an unusual day. The sales performance graph is generated by aggregating sales performance for each day of the week and categorized as either a normal day or an unusual day. Here, sales refer to sales per man-hour. Sales per man-hour is a value that represents the sales per hour per employee.

"By day of the week" means aggregating the values for the same day of the week within the aggregation period. For example, if there are four Mondays between January 1st and January 31st, "by day of the week" means summing the actual values for those four Mondays.

A "special day" refers to a day that differs from normal, such as a day when a store holds a special event like a sale. For example, even on a regular weekday like Monday, store sales and customer numbers will differ between a normal day and a special day. Therefore, it is meaningful to distinguish between normal days and special days in accounting.

In the example shown in Figure 3, the analysis unit 113 aggregates data by day of the week and by whether it is a normal day or an unusual day, and displays sales performance graphs and work performance graphs. However, the aggregation units are not limited to these. Those skilled in the art may appropriately change the aggregation units depending on the type of business, location, and size of the store.

The left side of the display screen in Figure 3 provides an area for selecting the display target. In this example, the left-hand area of the display screen shows a selection UI for narrowing down the region, store, and department. In Figure 3, "Tokai" is selected for the region, "Store A" for the store, and "Food Department" for the department.

On the left side of the display screen in Figure 3, there is a selection area for selecting the analysis results to be displayed. The user interface of this selection area is conventional technology and can be designed appropriately by those skilled in the art; therefore, a detailed explanation is omitted. In the example in Figure 3, selection areas are provided for selecting overtime analysis, labor-hour input evaluation, departmental personnel analysis, and departmental personnel list. Furthermore, labor-hour input evaluation is already selected. Therefore, the display screen shows a graph illustrating the analysis results of labor-hour input evaluation.

Furthermore, by having the user enter data in the input area at the top of the display screen and clicking the "Apply" button in the upper right corner of the screen, the user can refine the aggregated results by aggregation period, departmental groups, and group teams.

<Determining the peak time difference>
As shown in Figure 3, by simultaneously displaying sales performance graphs and work performance graphs, each with its own peak, on the display device, users such as store managers operating the store terminal 300 can perform detailed analysis and improvements regarding the store's issues.

Furthermore, based on factors such as the time difference between peak sales figures and work performance figures, the computer system can determine the appropriateness of the man-hours allocated.

The analysis unit 113 calculates the time difference between the peak included in the sales performance graph and the peak included in the work performance graph. The analysis unit 113 determines whether the man-hours allocated are appropriate by comparing the calculated time difference with a predetermined threshold.

The predetermined thresholds mentioned above may be stored, for example, in the memory of the server device 100. The analysis unit 113 generates work performance graphs and sales performance graphs for each predetermined group within the store. The threshold values are determined according to the group. The predetermined group may be a single store or a group consisting of multiple stores. Furthermore, the predetermined group may be a departmental group within a single store, such as a "food group" or a "home appliance group," or it may be a team belonging to a departmental group, such as "Team A" or "Team B." The predetermined group may also be a task group, such as "Task A" or "Task B," when a team is responsible for multiple tasks.

For example, in the case of a store's cashier team, it's best to have no time difference between the peak sales period and the peak labor hours. This is because having more employees working during busy cashier hours allows them to serve more customers. Similarly, for a bento box preparation team, it's ideal for the peak labor hours to occur a few hours before the peak sales period. This is because the actual preparation and stocking of bento boxes takes time, and these tasks need to be completed before the sales peak. The above are merely examples; the appropriate time difference between the peak sales period and the peak labor hours will vary depending on the store group. Therefore, as mentioned above, the predetermined threshold is determined to be a different value for each group. This allows the computer system to appropriately determine whether the labor hours are appropriate according to the group's operations.

The analysis unit 113 outputs information indicating whether the input time is appropriate or not. This information may be displayed, for example, on the display unit 302 of the store terminal 300. The output format of the information indicating the judgment result is not particularly limited, but it may be output in the form of text information, image information, etc.

Furthermore, if the analysis unit 113 determines that the input man-hour is not appropriate, the analysis unit 113 may output information indicating a suggested correction to the input man-hour. The content and format of the information indicating the suggested correction are not particularly limited, but for example, it may output text information such as "Please move the peak of the input man-hour forward by N hours" or "Please move the peak of the input man-hour backward by N hours." The value of N may be calculated by the analysis unit 113 based on the calculated time difference and a predetermined threshold.

Furthermore, the analysis unit 113 may search for time periods with low sales per labor hour. For example, a baseline sales per labor hour can be set for each time period, and this baseline time can be stored in the memory of the server device 100. The analysis unit 113 then displays information on the display unit 302 indicating that training should be conducted if the sales per labor hour is lower than the baseline value for that time period. The format of this information is not particularly limited, but it could be text information such as, "Since sales per labor hour at time N are low, we recommend that employees working at time N receive training." Additionally, information such as file paths or URLs of materials related to the training program may be displayed on the display unit 302.

Note that "time slot" and "each time slot" refer to periods with a predetermined length of time. For example, if each "time slot" is set to one hour, then 24 time slots are provided per day. Time slots are not limited to one hour; they may be two hours or longer, and may include morning, afternoon, early morning, late night, etc. Furthermore, multiple time slots may have the same or different lengths. While this disclosure describes an embodiment where each time slot is one hour, it is not limited to this.

Figure 4 is a conceptual diagram showing an example of a display screen for labor hour input evaluation corresponding to an embodiment of this disclosure. The display format in Figure 4 is basically the same as the display format exemplified in Figure 3; therefore, only the differences will be explained. In the display screen shown in Figure 3, two line graphs were displayed for each day, but in the display screen shown in Figure 4, three line graphs are displayed for each day. Specifically, an additional line graph showing reference labor hours for a standard store, etc., is added. In Figure 4, the solid line L3 is the line graph showing the reference labor hours.

In Figure 4, the dashed line L1 represents the work performance graph for the first group at store A (for example, the group responsible for delicatessen operations). The solid line L2 represents the sales performance graph for the first group at store A. The solid line L3 represents the work performance graph for a second group performing the same tasks at a different store.

The second group may be a standardized group based on data from multiple stores selected according to predetermined criteria. The predetermined criteria may be, for example, "the top three stores in terms of sales in the area including the stores being evaluated," representing high-performing stores. When this criterion is used, the work performance graph obtained from the average values of the top three stores will be displayed as a solid line (L3). The predetermined criteria may also be other criteria than those described above.

The second group may be a group of the same business or department as the first group at another store of similar size at store A. For example, if the first group corresponds to the delicatessen operations at store A and the second group corresponds to the delicatessen operations at store B, then the sales performance or number of employees of the delicatessen operations at store A and store B are of similar size. Therefore, a second group is selected such that the difference between the numerical value indicating the size of the first group and the numerical value indicating the size of the second group is less than or equal to a predetermined value. The numerical value indicating the size of the group refers to a numerical value that is linked to the size of the group, such as sales or the number of employees over a predetermined period.

Furthermore, in the display example shown in Figure 4, the display unit 302 may also display an additional line graph corresponding to the actual sales figures for reference.

Furthermore, the processor of the server device 100 may display the skill information of the personnel belonging to the first group on the display unit 302. Skill information refers to information indicating the skills possessed by each personnel. Skill information may be text information, such as "cash register level 1." Alternatively, skill information may be image information, such as the star ratings 1 through 3 shown in Figure 11.

Figure 5 is a conceptual diagram showing an example of a display screen for personnel analysis corresponding to an embodiment of this disclosure. The personnel analysis screen is typically displayed on the display unit 302 of the store terminal 300.

Figure 5 does not depict the selection area on the left side of the screen shown in Figure 3. However, from the perspective of standardizing the user interface, the same selection area on the left side as in Figure 3 may be displayed in the personnel analysis screen.

The personnel analysis displays two types of values along a time axis: a line graph and a bar graph. The first value is the man-hour staffing ratio, shown as a bar graph. The second value is the average skill level, shown as a dashed line graph. The bar graph showing the man-hour staffing ratio and the line graph showing the average skill level are displayed for each day of the week.

Note that in Figure 5, a single day of the week is not divided into normal days and unusual days. However, similar to the man-hour input evaluation screen shown in Figure 3, it may be possible to further divide the days into normal days and unusual days.

The man-hour sufficiency rate is the ratio obtained by dividing available man-hours by required man-hours. Available man-hours refer to the number of personnel with a certain level of skill during that time period. Whether or not a personnel possesses a certain level of skill is determined from information about the personnel's skills and the terms of their contract. This information about personnel's skills and contract terms can be stored, for example, in the employee/employee skills database shown in Figure 1.

The average skill level refers to the average skill level of the personnel being aggregated. The skill level of each personnel is calculated appropriately based on information about their skills and their contractual terms. Since the formula for determining each personnel's skill level can be designed by those skilled in the art, a detailed explanation is omitted. The personnel's skill levels may be fixedly stored in the employee/employee skill database shown in Figure 1, or the analysis unit 113 of the server device 100 may dynamically calculate the skill level values from the information stored in the employee/employee skill database. The analysis unit 113 may then calculate the average skill level for the group of personnel being aggregated.

Bar graphs showing labor-hour sufficiency rates may be displayed using different colors. For example, time periods where the labor-hour sufficiency rate is insufficient, i.e., below 100%, may be displayed in red. When the labor-hour sufficiency rate is within an appropriate range, for example between 100% and 140%, the bar graph may be displayed in blue. When the labor-hour sufficiency rate is excessive, for example exceeding 140%, the bar graph may be displayed in yellow. Other methods besides color coding, such as shading, may also be used to distinguish between different time periods.

Furthermore, a line indicating the baseline average skill level may be displayed. In the example in Figure 5, the baseline average skill level is 2.0, and a baseline line is drawn at the height of skill level 2.0. By comparing this baseline line with the dashed line graph showing the average skill level, users can easily confirm whether the average skill level of personnel deployed in each time period is below, appropriate, or above the baseline.

Figure 6 is a conceptual diagram illustrating a comparison store selection screen corresponding to an embodiment of this disclosure. Figure 7 is a conceptual diagram illustrating a store comparison screen corresponding to an embodiment of this disclosure.

The user of the store terminal 300 specifies the aggregation period, region, line (department), group, range of employees, range of group sales, etc., in the search criteria specification area at the top of the display screen, and then presses the search button. Then, information about stores matching the user's specified search criteria is extracted from the storage device 120 of the server device 100 and displayed on the display unit 302 as a comparison store selection screen.

The store selection screen may also display various information corresponding to the extracted stores. For example, store sales, sales per labor hour, and the number of employees may be displayed. Sales, sales per labor hour, and the number of employees for each group may also be displayed.

The filtering and display order of the information shown can be adjusted by the user of the store terminal 300 by operating checkboxes to indicate the departments to be displayed and dropdown lists to indicate the display order. For example, in Figure 6, of the four departments—food, clothing, health and beauty care, and home and leisure—only the food department is checked, and only stores with data for the food department are displayed. Furthermore, the display order is selected from the dropdown list to show stores in descending order of sales.

The extracted and displayed stores A through D also have checkboxes, and the user of the store terminal 300 checks the checkboxes of the stores they wish to compare. In Figure 6, stores B and C are checked. When the user of the store terminal 300 presses the "Compare Selected Stores" button in this state, the display screen transitions to the store comparison screen shown in Figure 7.

In the store comparison screen shown in Figure 7, information about the selected stores for comparison is displayed vertically. For each store, basic information, labor-hour input evaluation, and skill status are displayed.

The basic information displayed includes the store's sales, sales per labor hour, and the number of employees. For labor hour investment evaluation, two line graphs showing two types of performance values along a time axis are displayed, as shown in Figure 3. The first performance value is the actual labor hours invested, displayed as a dashed line. The second performance value is the actual sales value, displayed as a solid line. Regarding skill status, the number of employees assigned to each task and their skill levels are displayed as bar graphs.

By selecting and displaying comparison data for other stores in this manner, users of the store terminal 300 can verify whether their store's man-hour allocation is appropriate by comparing it with the status of other stores.

The user interfaces in Figures 6 and 7 are merely illustrative examples; those skilled in the art may use a different user interface than those shown in the figures to display store comparison information on the display unit 302.

Figure 8 is a conceptual diagram showing an example of a display screen for overtime analysis corresponding to an embodiment of this disclosure. Figure 9 is a conceptual diagram showing a second example of a display screen for overtime analysis corresponding to an embodiment of this disclosure. The display content of the selection area on the left side of the screen in Figures 8 and 9 is the same as in Figure 3, so a detailed explanation is omitted. Note that "overtime" refers to hours worked outside of regular working hours.

The overtime analysis display screen includes a summary display area that shows a summary of the overtime situation for each analysis target. The summary display area shows the analysis target name, overtime situation, and overtime evaluation. The analysis target name may include the group name, the team name within the group, or the name of the work performed by the team. The overtime situation refers to the ratio between working hours based on actual work performance information and planned working hours based on work plan information. For example, if the confirmed work plan for month N shows 100 hours of work, but the actual work hours for month N were 150 hours, then 50 hours of overtime were worked from the plan, and the overtime situation would be 150/100 = 150%. The analysis unit 113 calculates the overtime situation for each predetermined aggregation unit (described later) and displays it on the display unit 302.

Overtime hours are evaluated appropriately if, for example, the overtime rate is around 100%, and if it significantly exceeds 100%, it is evaluated as excessive or very excessive. For example, a threshold of 130% or more could be used to evaluate overtime as excessive, and 150% or more as very excessive; however, these thresholds can be set appropriately by those skilled in the art.

Users of the store terminal 300 can select each area of the analysis target name displayed in the summary display area. Figure 8 shows the state where "Task A" is selected from among the multiple analysis target names displayed in the summary area. Figure 9 shows the state where "Task B" is selected from among the multiple analysis target names displayed in the summary area. Depending on this selection, the analysis results showing the overtime status of the analysis target are displayed as a graph in the center of the screen.

The analysis unit 113 calculates the overtime status for the relevant month for each predetermined aggregation unit. In Figure 8, the predetermined aggregation unit includes at least a group, day of the week, and time slot. The overtime status is aggregated for the period specified in the aggregation period input unit located in the upper right corner of the screen. Note that the aggregation unit only needs to include at least one of the following: group, day of the week, and time slot.

The analysis unit 113 acquires work performance information and work plan information. The analysis unit 113 obtains work performance information from the hourly work performance database. The analysis unit 113 also obtains work plan information from the hourly work plan database. Based on the work performance information and work plan information, the analysis unit 113 calculates the number of overtime hours for each predetermined aggregation unit and displays the number of overtime hours on the display unit 302.

For example, in Figures 8 and 9, the number of overtime hours worked by each day of the week and by time of day for multiple personnel responsible for Task A during the relevant month are displayed as bar graphs. The number of overtime hours by day refers to the total number of overtime hours for each day of the week (Monday through Sunday) and for public holidays. The bar graph at the top of the display screen in Figure 8 shows that Tuesday had the highest number of overtime hours.

The number of overtime hours by time of day is displayed by further dividing the total number of overtime hours for each day of the week (Monday to Sunday) and for holidays into time slots. In the example in Figure 8, the number of overtime hours for each time slot on Monday is displayed as a bar graph, and it can be seen from the bar graph at the bottom of the screen that the number of overtime hours is highest in the 10:00 AM hour. In this embodiment, for the 10:00 AM hour, if a person who was scheduled to finish work before 11:00 AM continues working beyond 11:00 AM, it is counted as one instance of overtime. Those skilled in the art may implement a different method for counting overtime hours. Also, in Figures 8 and 9, the total number of overtime hours for Monday in the bar graph at the top of the screen is the sum of the hourly overtime hours for Monday in the bar graph at the bottom of the screen for 24 hours.

In Figure 8, the breakdown of overtime hours by day and time slot is displayed on the right side of the screen. For example, if the user selects Monday, 10:00 AM for the time slot breakdown of overtime hours, the breakdown of overtime hours for Monday, 10:00 AM will be displayed. Alternatively, as shown in Figure 9, options for selecting what to display may be shown. Examples of content to display as a graph include the number of days with overtime, the number of days with a work hour shortage, the number of days with a required man-hour shortage, and the number of days with a required man-hour surplus.

Furthermore, the analysis unit 113 may calculate the number of overtime hours for each task belonging to a group, in addition to the aggregation unit. The analysis unit 113 may then display at least one of the tasks and the number of overtime hours for each task on the display unit 302, in descending order of the number of overtime hours. For example, suppose the group "Team B" has three tasks: Task A, Task B, and Task C. If the analysis unit 113 calculates that Task A in Team B has 50 overtime hours, Task B in Team B has 10 overtime hours, and Task C in Team B has 20 overtime hours, then the number of overtime hours for each task or task will be displayed on the display unit 302 in the order of Task A, Task C, and Task B.

Furthermore, the number of overtime hours may be aggregated, for example, on a monthly basis. The analysis unit 113 may calculate the monthly number of overtime hours for each task belonging to the group based on the work performance information and work plan information, and display the monthly number of overtime hours for each task on the display unit 302.

In addition, the analysis unit 113 may search for time periods with low sales per man-hour. For example, a baseline value for sales per man-hour may be set for each time period, and this baseline value may be stored in the memory of the server device 100. The analysis unit 113 then retrieves sales performance information from the hourly sales performance DB and calculates sales per man-hour for each predetermined aggregation unit based on the retrieved sales performance information. The predetermined aggregation unit shall include at least a time period. If the sales per man-hour is lower than the baseline value for each time period, the analysis unit 113 displays information on the display unit 302 indicating that training should be conducted. The format of the information indicating that training should be conducted is not particularly limited, but it may be text information such as, for example, "Since sales per man-hour at time N are low, we recommend that employees working at time N receive training." In addition, information such as file paths or URLs of materials related to the training program may be displayed on the display unit 302. Furthermore, the analysis unit 113 may search whether there is a shortage of personnel for a predetermined number of consecutive months. For example, if it is determined that there is a staff shortage for several consecutive months, it may be determined that there is a chronic staff shortage and a suggestion to hire new personnel may be made. On the other hand, if it is determined that there is no staff shortage for several consecutive months, it may be determined that there is a temporary staff shortage and a suggestion to provide training to the personnel or change working hours through contract modifications may be made. Furthermore, based on the aforementioned labor-hour input evaluation (linking sales performance and labor-hour input), it may be determined whether the overtime work incurred is appropriate and different suggestions may be displayed depending on the result of the evaluation.

As shown in Figure 9, the overtime analysis display screen may also display additional hints for improvement. This hint information is generated by the improvement suggestion/plan generation unit 114 shown in Figure 1, based on the analysis results displayed in Figure 8. For example, if the overtime hours calculated by the analysis unit 113 are disproportionately high on specific days and times, the improvement suggestion/plan generation unit 114 may generate hint information suggesting calling in additional personnel for those days and times. Alternatively, based on information stored in the employee/employee skills database, the improvement suggestion/plan generation unit 114 may generate hint information encouraging the conversion of some part-time/temporary employees to full-time or contract employees. Contract changes can improve the types of work and working hours that these personnel can handle, contributing to a reduction in overtime hours. Furthermore, the improvement suggestion/plan generation unit 114 may generate hint information suggesting training for existing employees or hiring new personnel.

The improvement proposal/plan generation unit 114 searches the improvement proposal pattern database to see if any possible improvement proposal patterns are registered, while referring to employee information obtained from the employee/employee skills database and the expected work content and workload obtained from the work/workload forecast data database.

An improvement suggestion pattern is information that includes both the applicable conditions and the content of the improvement suggestion if those conditions are met. For example, if the workload during a given time period is high compared to the average skill level of existing personnel, the suggestion might propose support, training, contract changes, or new hiring. Another example is a suggestion pattern that might be registered in the improvement suggestion pattern database if the skill level of personnel with high overtime hours is significantly below the average or standard skill level of the organization, proposing training for those personnel. Various other improvement suggestion patterns not exemplified above may also be registered in the improvement suggestion pattern database.

The improvement suggestion/plan generation unit 114 then searches the improvement suggestion pattern database for any possible improvement suggestion patterns, referencing employee information obtained from the employee/employee skills database and anticipated work content and workload obtained from the work/workload forecast data database. If a suitable improvement suggestion pattern is found, the improvement suggestion/plan generation unit 114 generates hint information based on that pattern. The store terminal 300 acquires the generated hint information and displays it on the display unit 302 as part of the overtime analysis screen.

Figure 10 is a conceptual diagram showing an example of a display screen for personnel analysis corresponding to an embodiment of this disclosure. Figure 11 is a conceptual diagram showing a second example of a display screen for personnel analysis corresponding to an embodiment of this disclosure. The selection area on the left side of the screen in Figures 10 and 11 is the same as in Figure 3, so a detailed explanation is omitted.

The overtime analysis display screen includes a summary area that shows a summary of the staffing situation for each analysis target. The summary area displays the analysis target name, the man-hour sufficiency rate, and the man-hour surplus/shortage evaluation. The analysis target name refers to the group name, the team name within the group, the name of the tasks performed by the team, etc. The man-hour sufficiency rate is the ratio obtained by calculating available man-hours ÷ required man-hours, as described above based on Figure 5.

The assessment of labor hour surplus or shortage is as follows: for example, if the labor hour sufficiency rate is around 100%, it is considered appropriate. If the labor hour sufficiency rate significantly exceeds 100%, it is considered a labor hour surplus. Conversely, if the labor hour sufficiency rate significantly falls below 100%, it is considered a labor hour shortage. The threshold values used to determine whether a labor hour shortage, appropriate level, or surplus are considered appropriate can be appropriately set by those skilled in the art.

The user of the store terminal 300 can select each area of the analysis target name displayed in the summary display area. Figures 10 and 11 show the state where Team B is selected from among the multiple analysis target names displayed. Based on this selection, the analysis results showing the personnel status of the analysis target are displayed as a graph in the center of the display screen. Alternatively, a period input section may be placed in the upper right corner of the display screen, and the personnel status for the period specified in the period input section may be aggregated.

The analysis results are displayed in graphs showing the labor hour sufficiency rate and labor hour surplus/shortage by day of the week and time of day. The labor hour sufficiency rate is shown as a solid line graph, and the labor hour surplus/shortage is shown as a bar graph. A baseline is drawn in the center of the graph in the time direction; this baseline represents 100% for the labor hour sufficiency rate and 0 labor hour for the labor hour surplus/shortage.

A surplus or deficit of man-hours refers to the difference between the required man-hours and the available man-hours. For example, if 10 man-hours are required for a given time period, and 8 man-hours are available, the surplus or deficit would be 8 - 10 = -2 man-hours. -2 man-hours means there is a shortage of man-hours.

On the right side of the display screen, the man-hour sufficiency rate for each task corresponding to the name of the analysis target is shown. In the example in Figure 10, the man-hour sufficiency rates for Monday at 10:00 AM are displayed, showing that tasks A, B, and C performed by Team B have man-hour sufficiency rates of 50%, 100%, and 100%, respectively.

As shown in Figures 10 and 11, the personnel analysis display screen may also display additional hint information for improvement. This hint information is generated by the improvement suggestion/plan generation unit 114 shown in Figure 1, based on the analysis results displayed in Figures 10 and 11. For example, the improvement suggestion/plan generation unit 114 may generate hint information suggesting improvements to the personnel sufficiency rate at a predetermined date and time, based on the calculated trends in personnel sufficiency rate and personnel surplus/shortage. In the example in Figure 10, the improvement suggestion/plan generation unit 114 generates hint information suggesting improvements to the personnel sufficiency rate at 12:00 PM on Monday. The store terminal 300 acquires the generated hint information and displays it on the display unit 302 as part of the personnel analysis screen.

When a user of the store terminal 300 selects the bar graph representing Monday 12:00 PM on the display screen, based on the displayed hint information, detailed personnel information for Monday 12:00 PM is displayed in the area on the right side of the display screen, as shown in Figure 11. For example, a pie chart showing the number of personnel according to their skill proficiency level is displayed. The pie chart in Figure 11 shows that there are 5 personnel with a skill proficiency level of 1 star, 15 personnel with a skill proficiency level of 2 stars, and 10 personnel with a skill proficiency level of 3 stars.

Furthermore, as detailed personnel information, the personnel composition of those available to work on the selected date and time is displayed in a table format. The table showing the personnel composition includes data items such as employee name, available working hours, and skill level. The control unit 301 of the store terminal 300 retrieves information for each person from the employee/employee skill database and displays it on the display unit 302 as part of the personnel analysis screen. The server device 100 or the store terminal 300 also calculates the number of personnel available to work in the organization being analyzed (Team B in this example) and their average skill level on that date and time. The control unit 301 of the store terminal 300 displays information based on these values on the display unit 302 as part of the personnel analysis screen. Note that in Figure 11, the number of available personnel is shown as 999 and the average skill level as 3.0; however, these are examples of maximum values according to the specifications, and in reality, the values calculated each time by the server device 100 or the store terminal 300 are displayed as described above.

To increase the number of available staff, the user of the store terminal 300 presses the button located in the lower right corner of the display screen to search for available staff candidates. This transitions the display to the available staff screen shown in Figure 12. Note that the available staff screen may be displayed as a pop-up instead of a screen transition.

Figure 12 is a conceptual diagram illustrating a screen showing the number of available personnel, corresponding to an embodiment of this disclosure.

The display screen shown in Figure 12 shows a list of personnel who meet the search criteria. The control unit 301 of the store terminal 300 sets the personnel search criteria when transitioning from the personnel analysis screen shown in Figure 11 to the available personnel screen shown in Figure 12. The search criteria are determined based on the information displayed on the previous personnel analysis screen and the user's input history. For example, on the personnel analysis screen displaying the personnel status for Team B, if the user selects Task A, which has a man-hour sufficiency rate of 50% (see Figure 10), and also selects Monday at 12:00 based on the displayed hint information (see Figure 11), and then presses the button to search for available personnel candidates, the four parameters Monday, 12:00, Team B, and Task A become the search criteria.

In the available personnel screen shown in Figure 12, available personnel may be categorized and displayed in multiple groups. These groups may include, for example, three groups: a group of available personnel who can work without requiring any additional measures; a group of personnel who are not yet ready to work due to insufficient skills, etc., but who can work after training; and a group of personnel who can work after a contract change is recommended. The displayed items for each personnel may differ depending on which group they belong to. For example, employee name, employment category, and available working hours may be displayed in common across all three groups. Skill proficiency, represented by one to three stars, is displayed for the available personnel group and the personnel recommended for contract change group. The presence and number of skills similar to those required to perform Task A are displayed for the personnel recommended for training group.

As described above, by displaying the personnel analysis screen, users of the store terminal 300 can check the man-hour sufficiency rate and man-hour surplus/shortage for a given organization or task, along a timeline. Furthermore, by displaying hint information, users can be informed of dates and times when man-hour improvements can be made. Additionally, for dates and times when man-hours are insufficient, users can refer to detailed personnel information to review staffing arrangements.

Furthermore, by displaying the available personnel screen via a screen transition from the personnel analysis screen or as a pop-up, users of the store terminal 300 can assign appropriate personnel to the date and time when they recognize a shortage of man-hours. In addition, when selecting personnel to assign, they can easily determine whether appropriate training or contract changes are necessary.

As described above, the store management system 10 includes at least one computer device (e.g., server device 100) and at least one display device (e.g., display unit 302). The processor 110 of the computer device acquires work performance information and sales performance information. Based on the work performance information and sales performance information, the processor 110 simultaneously displays a work performance graph showing work performance along a time axis and a sales performance graph showing sales performance along a time axis on the display device (e.g., display unit 302). The sales performance graph includes one or more peaks. The work performance graph includes one or more peaks corresponding to the peaks in the sales performance graph. This allows the user to perform detailed analysis and improvement of store issues by displaying work performance information and sales performance information in a comparable manner on the display device (e.g., display unit 302).

The work performance graph is generated by aggregating man-hours for each day of the week and categorized as either a normal or unusual day. Similarly, the sales performance graph is generated by aggregating sales performance for each day of the week and categorized as either a normal or unusual day. Since customer traffic can vary by day of the week and type of day, the above methods allow for the comparative display of performance information across different days and types of days.

The processor 110 calculates the time difference between the peak in the sales performance graph and the peak in the work performance graph. The processor 110 compares the time difference with a predetermined threshold to determine whether the labor hours allocated are appropriate. The processor 110 also outputs information indicating the result of this determination. This allows the store management system to determine the appropriateness of the labor hours allocated and notify the user.

If the processor 110 determines that the input time is incorrect, it outputs information indicating a suggested correction to the input time. This allows the user to receive the suggested correction from the store management system.

The processor 110 generates work performance graphs and sales performance graphs for each predetermined group within the store. The threshold values are determined according to the group. This allows the store management system to make judgments that are adapted to the potential differences in peak time between groups.

Sales figures represent sales per labor hour. This allows the store management system to appropriately display performance information for stores where multiple personnel work on a shift basis, such as retail stores.

The processor 110 displays information on a display device (e.g., display unit 302) indicating that training should be conducted when the sales per labor hour fall below a standard value for each time period. This allows users to become aware of time periods with low sales per labor hour and to plan training accordingly.

The processor 110 simultaneously displays on a display device (e.g., display unit 302) the work performance graph and sales performance graph for the first group at the first store, and the work performance graph for the second group at a second store different from the first store, which is responsible for the same tasks or department as the first group. The second group may be a group from one or more stores selected as a standard reference based on predetermined criteria. The difference between the numerical value indicating the sales performance or number of personnel of the first group and the numerical value indicating the size of the second group may be less than or equal to a predetermined value. This allows the user to understand the challenges of their own group's man-hour allocation while referring to the work performance of other comparable groups, such as a group composed of other exemplary stores with sales rankings within the top three, or a group of other stores of a similar size to their own.

The processor 110 displays the skill information of the personnel belonging to the first group on a display device (e.g., display unit 302). This allows the user to understand the store's challenges based on performance data, while also considering the personnel's skills.

The store management device (e.g., store terminal 300) comprises a display device (e.g., display unit 302) and a processor (e.g., control unit 301). The processor (e.g., control unit 301) acquires work performance information and sales performance information. Based on the work performance information and sales performance information, the processor (e.g., control unit 301) simultaneously displays a work performance graph showing work performance along a time axis and a sales performance graph showing sales performance along a time axis on the display device. The sales performance graph includes one or more peaks. The work performance graph includes one or more peaks corresponding to the peaks in the sales performance graph. This allows the store management device (e.g., store terminal 300) to display work performance information and sales performance information on the display device (e.g., display unit 302) in a comparable manner, enabling the user to perform detailed analysis and improvement of store issues.

In a store management system 10 including at least one computer device (e.g., server device 100) and at least one display device (e.g., display unit 302), the processor 110 of the computer device (e.g., server device 100) executes a store management method. The processor 110 acquires work performance information and sales performance information. Based on the work performance information and sales performance information, the processor 110 simultaneously displays a work performance graph showing work performance along a time axis and a sales performance graph showing sales performance along a time axis on the display device (e.g., display unit 302). The sales performance graph includes one or more peaks. The work performance graph includes one or more peaks corresponding to the peaks in the sales performance graph. This allows the processor 110 to display the work performance information and sales performance information on the display device (e.g., display unit 302) in a comparable manner, enabling the user to perform detailed analysis and improvement of store issues.

The store management system 10 includes at least one computer device (e.g., server device 100) and at least one display device (e.g., display unit 302). The processor 110 of the computer device (e.g., server device 100) acquires work performance information and work plan information. Based on the work performance information and work plan information, the processor 110 calculates the number of overtime hours for each predetermined aggregation unit. The processor 110 displays the number of overtime hours on the display device (e.g., display unit 302). This allows for the visualization of the number of overtime hours, rather than just the total overtime hours, for each predetermined aggregation unit. Therefore, users can easily identify issues such as man-hours spent.

The predetermined aggregation unit includes groups, days of the week, and time zones. This allows for the visualization of overtime hours in stores with multiple groups, such as retail shops, where customer traffic can vary depending on the day of the week and time of day.

The processor 110 calculates the number of overtime hours for each task belonging to a group, in addition to the aggregation unit, and displays at least one of the tasks and the number of overtime hours for each task on a display device (e.g., display unit 302) in descending order of the number of overtime hours. This allows the user to easily identify tasks with a high number of overtime hours.

The processor 110 calculates the monthly overtime hours for each task belonging to the group, based on work performance information and work plan information. The processor 110 displays the monthly overtime hours for each task on a display device (e.g., display unit 302). This allows the user to check the overtime hours for each predetermined aggregation unit while also referring to the monthly overtime hours.

The processor 110 calculates the overtime status, which represents the ratio between working hours based on actual work performance information and scheduled working hours based on work plan information, for each predetermined aggregation unit. The processor 110 displays the overtime status on a display device (e.g., display unit 302). This allows the user to check the overtime status in an easy-to-understand ratio, such as 150%.

The processor 110 acquires sales performance information. Based on the sales performance information, the processor 110 calculates the sales per labor hour for each predetermined aggregation unit. If the sales per labor hour is lower than the baseline value for each time period, the processor 110 displays information on the display device (e.g., display unit 302) indicating that training should be conducted. Each predetermined aggregation unit includes at least a time period. This allows users to become aware of time periods with low sales per labor hour and to plan training accordingly.

The store management device (e.g., store terminal 300) comprises a display device (e.g., display unit 302) and a processor (e.g., control unit 301). The processor (e.g., control unit 301) acquires work performance information and work plan information. Based on the work performance information and work plan information, the processor (e.g., control unit 301) calculates the number of overtime hours for each predetermined aggregation unit. The processor (e.g., control unit 301) displays the number of overtime hours on the display device (e.g., display unit 302). This allows the store management device (e.g., store terminal 300) to visualize the number of overtime hours, rather than just the total overtime hours, for each predetermined aggregation unit. Therefore, users can easily identify issues such as man-hours being spent.

In a store management system 10 including at least one computer device (e.g., server device 100) and at least one display device (e.g., display unit 302), the processor 110 of the computer device (e.g., server device 100) executes a store management method. The processor 110 acquires work performance information and work plan information. Based on the work performance information and work plan information, the processor 110 calculates the number of overtime hours for each predetermined aggregation unit. The processor 110 displays the number of overtime hours on the display device (e.g., display unit 302). This allows the store management method to visualize the number of overtime hours, rather than the total overtime hours, for each predetermined aggregation unit. Therefore, users can easily identify issues such as man-hours.

While various embodiments have been described above with reference to the drawings, it goes without saying that this disclosure is not limited to these examples. It will be clear to those skilled in the art that various modifications or alterations can be conceived within the scope of the claims, and these will naturally fall within the technical scope of this disclosure. Furthermore, the components of the above embodiments may be combined in any way without departing from the spirit of the disclosure.

The execution order of operations, procedures, steps, and stages in the devices, systems, programs, and methods described in the claims, specifications, and drawings is not explicitly stated as "before" or "prior to," and can be implemented in any order unless the output of a previous process is used in a later process. Even if the operation flow in the claims, specifications, and drawings is described using terms such as "first" and "next" for convenience, this does not mean that it is essential to perform the operations in that order.

This disclosure is useful for store management systems, store management devices, and store management methods that enable detailed analysis and improvement of store challenges.

10 Store Management System 30 Communication Network 100 Server Device 110 Processor 111 Work Schedule/Work Plan Creation Unit 112 Required Person-Hour Calculation Unit 113 Analysis Unit 114 Improvement Proposal/Plan Generation Unit 120 Storage Device 130 Transmit/Receive Unit 200 Store System 300 Store Terminal 301 Control Unit 302 Display Unit 303 Input Reception Unit 304 Transmit/Receive Unit 400 Worker Terminal

Claims (7)

It includes at least one computer device and at least one display device,
The processor included in the aforementioned computer device
We obtain work performance information and work plan information.
Based on the aforementioned work performance information and work plan information, the number of overtime hours for each task belonging to the group is calculated.
The display device will show at least one of the aforementioned tasks and the number of overtime hours for those tasks, in descending order of the number of overtime hours.
Store management system. The aforementioned processor,
Based on the aforementioned work performance information and work plan information, the monthly number of overtime hours for each task belonging to the group is calculated.
The number of monthly overtime hours for each of the aforementioned tasks is displayed on the display device.
The store management system according to claim 1 . The aforementioned processor,
The number of overtime hours for each predetermined aggregation unit, including the group, day of the week, and time slot, is calculated.
The calculated number of overtime hours is displayed on the display device.
The store management system according to claim 1 or claim 2. The aforementioned processor,
The overtime status, which represents the ratio between the working hours based on the work performance information and the scheduled working hours based on the work plan information, is calculated for each predetermined aggregation unit.
The overtime status is displayed on the display device.
The store management system according to claim 3 . The aforementioned processor,
We obtain sales performance information,
Based on the aforementioned sales performance information, the sales per person-hour for each predetermined aggregation unit is calculated.
If the sales per man-hour are lower than the standard value for each time period, the display device will show information indicating that training should be conducted.
The predetermined aggregation unit includes at least a time period,
The store management system according to claim 3 or claim 4 . Equipped with a display device and a processor,
The aforementioned processor,
We obtain work performance information and work plan information.
Based on the aforementioned work performance information and work plan information, the number of overtime hours for each task belonging to the group is calculated.
The display device will show at least one of the aforementioned tasks and the number of overtime hours for those tasks, in descending order of the number of overtime hours.
Store management device. A store management method using a processor provided in a store management system comprising at least one computer device and at least one display device,
Steps to obtain work performance information and work plan information,
Based on the aforementioned work performance information and work plan information, the steps include calculating the number of overtime hours for each task belonging to the group ,
The process includes the step of displaying at least one of the aforementioned tasks and the number of overtime hours for those tasks on the display device, in descending order of the number of overtime hours .
Store management methods.