Work support system, work support method, and program

Abstract

To provide a business support system, a business support method, and a program capable of reducing a business burden on a creator in creating a sales plan.SOLUTION: A business support system comprising: a prediction condition information acquisition unit configured to acquire prediction condition information indicating a prediction condition of a sales plan; and a sales plan prediction unit configured to predict a sales plan of a retail store in the prediction condition indicated by the acquired prediction condition information based on a relationship between a plurality of pieces of information affecting the sales plan.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a business support system, a business support method, and a program. [Background technology]

[0002] Traditionally, in the retail industry, sales plans are created by buyers. If actual sales deviate from the sales plan, it will affect sales. For this reason, buyers are required to create more accurate sales plans. Creating more accurate sales plans requires taking into account various factors that affect sales, which places a heavy burden on buyers.

[0003] Various technologies have been proposed to enable highly accurate operations in the retail industry. For example, Patent Document 1 below discloses a technology that enables highly accurate product demand forecasting using a prediction model based on product sales performance data. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 7107222 Summary of the Invention [Problem to be solved by the invention]

[0005] However, while the technology described in Patent Document 1 can forecast demand, which is one element of a sales plan, based on sales performance, it cannot predict the sales plan itself. As a result, buyers themselves had to create sales plans that took into account factors other than sales performance.

[0006] In view of the above-mentioned problems, an object of the present invention is to provide a business support system, a business support method, and a program that can reduce the workload imposed on a creator when creating a sales plan. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems, one embodiment of the present invention provides a business support system that includes a forecast condition information acquisition unit that acquires forecast condition information indicating forecast conditions for a sales plan, and a sales plan prediction unit that predicts the sales plan of a retail store under the forecast conditions indicated by the acquired forecast condition information based on the relationship between multiple pieces of information that affect the sales plan.

[0008] A business support method according to one embodiment of the present invention is a business support method executed by a computer, which includes a forecast condition information acquisition process for acquiring forecast condition information indicating forecast conditions for a sales plan, and a sales plan prediction process for predicting a retail store's sales plan under the forecast conditions indicated by the acquired forecast condition information based on the relationship between multiple pieces of information that affect the sales plan.

[0009] A program according to one aspect of the present invention is a program for causing a computer to function as a forecast condition information acquisition means for acquiring forecast condition information indicating forecast conditions for a sales plan, and a sales plan prediction means for predicting a retail store's sales plan under the forecast conditions indicated by the acquired forecast condition information based on the relationship between multiple pieces of information that affect the sales plan. [Effects of the Invention]

[0010] According to the present invention, the workload imposed on the creator of a sales plan can be reduced. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagram illustrating an example of a configuration of a business support system according to an embodiment of the present invention. [Figure 2] 1 is a block diagram showing an example of a functional configuration of a sales plan creation device according to an embodiment of the present invention; [Figure 3] FIG. 10 is a diagram showing an example of given day of the week rule information included in given day of the week generation information according to the present embodiment. [Figure 4]FIG. 10 is a diagram showing an example of event information included in the day-of-week given condition generation information according to the present embodiment. [Figure 5] FIG. 10 is a diagram illustrating an example of day-of-week condition information according to the present embodiment. [Figure 6] FIG. 10 is a diagram illustrating an example of a sales plan prediction screen according to the present embodiment. [Figure 7] FIG. 10 is a diagram illustrating an example of an output of a sales plan forecast result according to the present embodiment. [Figure 8] FIG. 10 is a diagram illustrating an example of an output of a sales plan forecast result according to the present embodiment. [Figure 9] FIG. 10 is a diagram illustrating an example of an output of a sales plan forecast result according to the present embodiment. [Figure 10] FIG. 10 is a sequence diagram illustrating an example of a process flow for generating a given day of the week according to the present embodiment. [Figure 11] FIG. 10 is a sequence diagram illustrating an example of a processing flow related to generation of a sales plan forecast model according to the present embodiment. [Figure 12] FIG. 10 is a sequence diagram illustrating an example of a processing flow related to a sales plan prediction according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[0013] <1. Business support system configuration> The configuration of a business support system according to this embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of a business support system according to this embodiment.

[0014] The business support system 1 shown in FIG. 1 is a system for supporting the creation of sales plans in retail stores. The business support system 1 predicts and outputs a sales plan under input prediction conditions based on the relationships between multiple pieces of information that affect the sales plan, thereby supporting the creation of a sales plan by a user. The user is, for example, a person in charge of creating a sales plan at a retail store (hereinafter also referred to as a "creator"). The business support system 1 predicts a sales plan based on the results of learning (machine learning) about the relationships between multiple pieces of information that affect the sales plan, using, for example, AI (Artificial Intelligence). The plurality of pieces of information that affect the sales plan are information that indicates past performance of the retail store that is the target of the sales plan prediction. The plurality of pieces of information that affect the sales plan are, for example, sales performance information, sales influence information, and day of the week given information.

[0015] Sales performance information is information that indicates past sales performance at a retail store. Examples of sales performance information include sales amount, number of retailers, etc. Sales amount is the sales amount by day. Daily sales amount may be shown by product category. Product categories may be categorized into departments such as meat, and each department may be further categorized into product groups such as beef, pork, and chicken.

[0016] Sales impact information is at least one piece of information that indicates factors that affect sales performance. Sales impact information is, for example, weather information or sales promotion information. Weather information is information that indicates past weather data in the area where the retail store is located. Weather information is, for example, temperature (average temperature, maximum temperature, minimum temperature), precipitation, general weather conditions, etc. Sales promotion information is information about product sales promotions (such as sales, etc.). Sales promotion information is, for example, the promotion period (start date and end date and time), etc.

[0017] The given day of the week information is information that associates each date in the year for which the sales plan is to be predicted (the target prediction year) with a date in the previous year that has similar sales characteristics. An example of a sales characteristic is the presence or absence of an event. Examples of events include public holidays such as New Year's Day, seasonal events such as New Year's Day, Setsubun, and cherry blossom viewing, and special sales held in stores.

[0018] A user can obtain sales plan prediction results from the business support system 1 by inputting sales plan prediction conditions into the business support system 1. The user can use the prediction results obtained from the business support system 1 as a sales plan as is, or can create a sales plan based on the prediction results. As a result, by using the business support system 1, the user does not need to create a sales plan from scratch, thereby reducing the workload involved in creating a sales plan.

[0019] As shown in FIG. 1, the business support system 1 includes a developer terminal 10, a user terminal 20, a sales plan creation device 30, a sales performance information management server 40, a weather information management server 50, and a sales promotion information management server 60. The network NW may be configured to transmit and receive information using, for example, a LAN (Local Area Network), a WAN (Wide Area Network), a telephone network (such as a mobile phone network or a fixed telephone network), a regional IP (Internet Protocol) network, or the Internet.

[0020] (1) Developer Terminal 10 The developer terminal 10 is a terminal used by a developer. The developer in this embodiment is a person involved in the development of the business support system 1, and is, for example, a creator of an AI that predicts a sales plan. The developer terminal 10 is, for example, a tablet terminal or a PC (Personal Computer). The developer terminal 10 is communicably connected to the sales plan creation device 30 via the network NW.

[0021] (2) User terminal 20 The user terminal 20 is a terminal used by a user. In this embodiment, the user is a person associated with a retail store, such as a buyer. The user terminal 20 is, for example, a mobile terminal such as a smartphone or a tablet terminal, or a PC (Personal Computer). The user terminal 20 is communicably connected to the sales plan creation device 30 via the network NW.

[0022] Note that various UIs (User Interfaces) are displayed on the user terminal 20 by an application (hereinafter also referred to as a "business support app") that enables the user to use the business support system 1. The user can use the business support system 1 by operating the UI displayed on each terminal by the business support app. The functions of the business support app may be provided by installing the business support app on the user terminal 20 (i.e., a native app), or may be provided by a web system (i.e., a web app). In the case of a web app, the business support app is managed by a server, and its functions are provided via a web browser.

[0023] (3) Sales plan creation device 30 The sales plan creation device 30 is a device that supports the creation of a sales plan by a user. To provide this support, the sales plan creation device 30 performs, for example, generating given days of the week, learning about sales plan predictions, and predicting sales plans. The sales plan creation device 30 is, for example, one or more servers (for example, cloud servers), PCs, or other devices. The sales plan creation device 30 is communicably connected to a developer terminal 10, a user terminal 20, a sales performance information management server 40, a weather information management server 50, and a sales promotion information management server 60 via a network NW.

[0024] (4) Sales performance information management server 40 The sales performance information management server 40 is a server that manages sales performance information. The sales performance information management server 40 is connected to the sales plan creation device 30 via the network NW so as to be able to communicate with each other.

[0025] (5) Weather information management server 50 The weather information management server 50 is a server that manages weather information. The weather information management server 50 is communicably connected to the sales plan creation device 30 via a network NW.

[0026] (6) Sales promotion information management server 60 The sales promotion information management server 60 is a server that manages sales promotion information. The sales promotion information management server 60 is connected to the sales plan creation device 30 via the network NW so as to be able to communicate with the sales plan creation device 30.

[0027] <2. Functional configuration of the sales plan creation device> The configuration of the business support system 1 according to this embodiment has been described above. Next, the functional configuration of the sales plan creation device 30 according to this embodiment will be described with reference to Fig. 2 to Fig. 9. Fig. 2 is a block diagram showing an example of the functional configuration of the sales plan creation device 30 according to this embodiment. As shown in FIG. 2, the sales plan creation device 30 includes a communication unit 310, a storage unit 320, and a control unit 330.

[0028] (1) Communications unit 310 The communication unit 310 has the function of transmitting and receiving various information. The communication unit 310 is communicably connected to the developer terminal 10, the user terminal 20, the sales performance information management server 40, the weather information management server 50, and the sales promotion information management server 60 via the network NW, and transmits and receives various information.

[0029] In communication with the developer terminal 10, the communication unit 310 receives and transmits day of the week given condition generation information. The day of the week given condition generation information is information used to generate day of the week given conditions. The day of the week given condition generation information includes, for example, day of the week given condition rule information and event information. The given day of the week rule information is a rule for generating given days of the week (hereinafter also referred to as "given day of the week rule"). For example, the given day of the week rule information indicates given day of the week rules for associating each date of the target year for prediction with each date of the previous year. The event information indicates the relationship between dates and whether or not an event occurs. For example, the event information indicates whether or not an event occurs on each date in the target year of prediction and on each date in the previous year.

[0030] In communication with the user terminal 20, the communication unit 310 receives prediction condition information and transmits sales plan information. The prediction condition information is information indicating the prediction conditions of a sales plan. The prediction condition information is information indicating, for example, the prediction period (which can be specified in daily units), whether or not to output total sales, and the product field (department, product group, etc.) for which sales will be output. The prediction condition information is input into the user terminal 20 by the user. The sales plan information is information indicating the prediction results of a sales plan. For example, the sales plan information indicates, for each date specified as the prediction period, the predicted amount for each specified product field, the corresponding date of the previous year, sales for the previous year, and a forecast of sales compared to the previous year.

[0031] In communication with the sales performance information management server 40, the communication unit 310 receives sales performance information. In communication with the weather information management server 50, the communication unit 310 receives weather information. In communication with the sales promotion information management server 60, the communication unit 310 receives sales promotion information.

[0032] (2) Storage section 320 The storage unit 320 has a function of storing various types of information. The storage unit 320 is configured by a storage medium provided as hardware in the sales plan creation device 30, such as a hard disk drive (HDD), a solid state drive (SSD), a flash memory, an electrically erasable programmable read-only memory (EEPROM), a random access read / write memory (RAM), a read-only memory (ROM), or any combination of these storage media.

[0033] The storage unit 320 stores, for example, day-of-week given condition generation information received by the communication unit 310 from the developer terminal 10, prediction condition information received from the user terminal 20, sales performance information received from the sales performance information management server 40, weather information received from the weather information management server 50, sales promotion information received from the sales promotion information management server 60, day-of-week given condition information generated by the day-of-week given condition information generation unit 333 described later, a sales plan forecast model generated by the sales plan learning unit 335 described later, and sales plan forecast results (sales plan information) by the sales plan forecasting unit 337 described later. The sales plan forecast model is a trained model that has learned about the relationships between multiple pieces of information that affect the sales plan based on training data. The training data includes sales performance information, weather information, sales promotion information, and day-of-week given condition information.

[0034] (3) Control unit 330 The control unit 330 has a function of controlling the overall operation of the sales plan creation device 30. The control unit 330 is realized, for example, by causing a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) provided as hardware in the sales plan creation device 30 to execute a program. As shown in Figure 2, the control unit 330 includes a day of the week given condition generation information acquisition unit 331, a day of the week given condition rule setting unit 332, a day of the week given condition information generation unit 333, a learning data acquisition unit 334, a sales plan learning unit 335, a prediction condition information acquisition unit 336, a sales plan prediction unit 337, and an output processing unit 338.

[0035] (3-1) Day of the week condition generation information acquisition unit 331 The day-of-week given condition generation information acquisition unit 331 has a function of acquiring the day-of-week given condition generation information. The day-of-week given condition generation information acquisition unit 331 acquires the day-of-week given condition generation information that the communication unit 310 receives from the developer terminal 10.

[0036] (3-2) Day of the week given condition rule setting unit 332 The given day of the week rule setting unit 332 has a function of setting given day of the week rules. The given day of the week rule setting unit 332 sets given day of the week rules and whether or not an event occurs, based on the given day of the week generation information acquired by the given day of the week generation information acquisition unit 331. The given day of the week rule setting unit 332 generates a program capable of generating given day of the week information in accordance with the given day of the week rules and whether or not an event occurs, based on, for example, given day of the week rule information and event information included in the given day of the week generation information.

[0037] Here, with reference to Fig. 3, the day-of-week given condition rule information included in the day-of-week given condition generation information according to this embodiment will be described. Fig. 3 is a diagram showing an example of the day-of-week given condition rule information included in the day-of-week given condition generation information according to this embodiment. Fig. 3 shows five rules as an example of the day-of-week given condition rules indicated by the day-of-week given condition rule information. Note that the content and number of the day-of-week given condition rules are not limited to the example shown in Fig. 3.

[0038] Rule 1 states that "colored parts in event information shall be the same as the previous year, regardless of the day of the week." In the event information according to this embodiment, for example, dates for each year are displayed in a table format, and dates on which events occur are displayed in color. According to rule 1, dates on which events occur in the prediction year are aligned with dates on which events occur in the previous year. For example, January 1, 2023 (Sunday), which is New Year's Day in the prediction year, is associated with January 1, 2022 (Saturday), which is also New Year's Day in the previous year. In this case, the dates in the prediction year and the dates in the previous year will be the same, but the days of the week may be different.

[0039] Rule 2 states that "the day is adjusted to the day of the week, just as in the previous year." Dates that were not adjusted according to Rule 1 are adjusted according to Rule 2. According to Rule 2, dates on which there are no events in the prediction year are adjusted to dates on which there are no events in the previous year. For example, 2023 / 1 / 5 (Thursday), a date on which there are no events in the prediction year, is associated with 2022 / 1 / 6 (Thursday), a date on which there are also no events in the previous year. In this case, the day of the week in the prediction year and the day of the week in the previous year will be the same, but the dates may be different.

[0040] Rule 3 states that "if rule 2 cannot be applied due to the influence of rule 1, enter a date of the same day of the week within one week." For example, suppose "Setsubun" is set as an event on 2 / 3 of each year. In this case, rule 1 first associates 2 / 3 / 2023 (Friday) of the target year with 2 / 3 / 2022 (Thursday) of the previous year. Next, rule 2 adjusts the date for 2 / 2 / 2023 (Thursday) of the target year. In the previous year, the Thursday closest to 2 / 2 is 2 / 3. However, because 2 / 3 of the previous year has already been adjusted according to rule 1, it cannot be used for adjusting the date according to rule 2. Therefore, rule 1 prevents the application of rule 2 when adjusting the date for 2 / 2 / 2023 (Thursday) of the target year. In this case, rule 3 associates 2 / 2 / 2023 (Thursday) of the target year with 1 / 27 / 2022 (Thursday).

[0041] Rule 4 states that "December 26th and 27th may be treated differently to accommodate year-end events starting on December 24th, 25th, or 28th." For example, December 26th, 2023 (Tuesday) of the target year of prediction is associated with December 26th, 2022 (Monday) of the previous year, and December 27th, 2023 (Wednesday) is associated with December 27th, 2022 (Tuesday) of the previous year. If no events are scheduled for December 26th and 27th of the target year of prediction, the dates will not be adjusted according to Rule 1, but will be adjusted according to Rule 2. However, Rule 4 may ignore Rule 2 and associate the same date instead of the same day of the week.

[0042] Rule 5 states that "In the case of a leap year, the occurrence of 2 / 29 results in one more day than the previous year, so rule 3 is used to compensate."

[0043] Here, the event information included in the given day of the week generation information according to this embodiment will be described with reference to Fig. 4. Fig. 4 is a diagram showing an example of event information included in the given day of the week generation information according to this embodiment. In the example shown in Fig. 4, 2023 is the target year for prediction, and 2022 is the previous year. For ease of explanation, Fig. 4 also shows an example for 2021.

[0044] As shown in Figure 4, dates on which events occur each year are colored. For example, New Year's Day, New Year's Day, and consecutive holidays are set as events on 1 / 1. For example, New Year's Day and consecutive holidays are set as events on 1 / 2-4. For example, consecutive holidays are set as events on the Monday of the second week of January and the Saturday and Sunday before that (1 / 7-9 in 2023, 1 / 8-10 in 2022, 1 / 9-11 in 2021). For example, Christmas is set as an event on 12 / 24-25. For example, the end of the year and consecutive holidays are set as events on 12 / 28-30. For example, New Year's Eve, the end of the year and consecutive holidays are set as events on 12 / 31.

[0045] (3-3) Day of the week given information generation unit 333 The given day of the week information generating unit 333 has a function of generating given day of the week information. The given day of the week information generating unit 333 generates given day of the week information based on given day of the week rules set by the given day of the week rule setting unit 332. For example, the given day of the week information generating unit 333 uses a program generated by the given day of the week rule setting unit 332 to obtain, as given day of the week information, information indicating given day of the week conditions automatically generated by the program.

[0046] An example of the given day of the week information according to this embodiment will now be described with reference to Fig. 5. Fig. 5 is a diagram showing an example of the given day of the week information according to this embodiment. The given day of the week information shown in Fig. 5 is generated based on the given day of the week rule information shown in Fig. 3 and the event information shown in Fig. 4.

[0047] As shown in FIG. 5, dates that were colored in the event information shown in FIG. 4 are associated with the same day of the previous year, regardless of the day of the week, according to rule 1. Dates that were not colored in the event information shown in FIG. 4 are associated with days of the week according to rule 2. For example, January 5 (Thursday) and January 6 (Friday) of 2023 are associated with January 6 (Thursday) and January 7 (Friday) of 2022, respectively. Dates to which rule 2 cannot be applied are associated with dates on the same day of the week within a week or so according to rule 3. For example, when adjusting the date for December 23 (Saturday) of 2023, December 24 (Saturday) of 2022 is associated with December 24 (Sunday) of 2023 according to rule 1, so rule 2 cannot be applied to December 24 (Saturday) of 2022. Therefore, 12 / 23 (Sat) of 2023 corresponds to 12 / 17 (Sat) of 2022, which is one week before 12 / 24 (Sat) of 2022. 12 / 26 (Tue) and 12 / 27 (Wed) of 2023 correspond to 12 / 26 (Mon) and 12 / 27 (Tue) of 2022, respectively, according to rule 4.

[0048] (3-4) Learning data acquisition unit 334 The learning data acquisition unit 334 has a function of acquiring learning data. For example, the learning data acquisition unit 334 acquires, as learning data, sales performance information received by the communication unit 310 from the sales performance information management server 40, weather information received from the weather information management server 50, sales promotion information received from the sales promotion information management server 60, and day of the week given condition information generated by the day of the week given condition information generation unit 333.

[0049] (3-5) Sales Planning Learning Department 335 The sales plan learning unit 335 has a function of learning sales plan predictions. For example, the sales plan learning unit 335 generates a sales plan prediction model (trained model) that has learned about the relationships between multiple pieces of information that affect the sales plan, based on the learning data acquired by the learning data acquisition unit 334.

[0050] (3-6) Prediction condition information acquisition unit 336 The prediction condition information acquisition unit 336 has a function of acquiring prediction condition information. For example, the prediction condition information acquisition unit 336 acquires the prediction condition information that the communication unit 310 receives from the user terminal 20.

[0051] (3-7) Sales Planning and Forecasting Department 337 The sales plan prediction unit 337 has a function of predicting a sales plan. For example, the sales plan prediction unit 337 predicts the sales plan of the retail store under the prediction conditions indicated by the prediction condition information acquired by the prediction condition information acquisition unit 336, based on the relationship between multiple pieces of information that affect the sales plan.

[0052] In this embodiment, the sales plan prediction unit 337 predicts the sales plan using a sales plan prediction model generated by the sales plan learning unit 335 learning about the relationships between multiple pieces of information that affect the sales plan. The sales plan prediction unit 337 inputs the prediction condition information acquired by the prediction condition information acquisition unit 336 into the sales plan prediction model. Based on this input, the sales plan prediction model predicts the sales plan. The sales plan prediction unit 337 acquires information output from the sales plan prediction model as the prediction result.

[0053] (3-8) Output processing unit 338 The output processing unit 338 has a function of controlling the output of various information. The output processing unit 338 transmits the day of the week given condition information generated by the day of the week given condition information generation unit 333 from the communication unit 310 to the developer terminal 10. In addition, the output processing unit 338 transmits the sales plan information generated by the sales plan prediction unit 337 from the communication unit 310 to the user terminal 20. In addition, the output processing unit 338 displays a sales plan prediction screen on the user terminal 20. The sales plan prediction screen is a screen on which the user inputs prediction condition information and executes sales plan prediction.

[0054] Here, the sales plan prediction screen according to this embodiment will be described with reference to Fig. 6. Fig. 6 is a diagram showing an example of the sales plan prediction screen according to this embodiment.

[0055] As shown in FIG. 6, the sales plan prediction screen G1 has input fields A1 to A4 for inputting prediction conditions, and a sales plan output button B1 for executing sales plan prediction. Input field A1 is an area for inputting the prediction period. Input field A2 is an area for selecting whether or not to output total sales. Input field A3 is an area for inputting the department for which department sales are to be output. Input field A4 is an area for selecting the product group for which product group sales are to be output. After inputting the necessary forecasting conditions in the input areas A1 to A4, the user presses the sales plan output button B1, which causes the sales plan creation device 30 to forecast the sales plan, and the forecast results are displayed on the user terminal 20.

[0056] The output processing unit 338 also displays the sales plan information on the user terminal 20. The output processing unit 338 generates the sales plan information based on the prediction results by the sales plan prediction unit 337. The sales plan information is, for example, information indicating the predicted amount of sales at the retail store under the prediction conditions indicated by the prediction condition information. The output processing unit 338 transmits the generated sales plan information from the communication unit 310 to the user terminal 20 and displays it.

[0057] Here, the sales plan forecast result according to this embodiment will be described with reference to Fig. 7 to Fig. 9. Fig. 7 to Fig. 9 are diagrams showing an example of the output of the sales plan forecast result according to this embodiment.

[0058] Figure 7 shows the sales plan forecast results when the forecasting conditions are input to "output" the retail store's total sales from "2023 / 10 / 01 to 2023 / 10 / 02" on the sales plan forecast screen G1 shown in Figure 6. As shown in Figure 7, for each of "2023 / 10 / 01 (Sun)" and "2023 / 10 / 02 (Mon)," the forecast amount of the retail store's total sales, the corresponding date in the previous year, the sales in the previous year, and the sales forecast compared to the previous year are output.

[0059] Figure 8 shows the sales plan forecast results when forecast conditions are entered to output department sales for the "meat" department from "2023 / 10 / 01 to 2023 / 10 / 02" on the sales plan forecast screen G1 shown in Figure 6. As shown in Figure 8, the sales forecast amount for the meat department, the corresponding date in the previous year, sales in the previous year, and sales forecast compared to the previous year are output for each of "2023 / 10 / 01 (Sunday)" and "2023 / 10 / 02 (Monday)."

[0060] Figure 9 shows the sales plan forecast results when forecast conditions are entered on the sales plan forecast screen G1 shown in Figure 6 so that department sales for the "meat" department from "2023 / 10 / 01 to 2023 / 10 / 02" are output for each product group sales of "beef" and "pork." As shown in Figure 9, for each of "2023 / 10 / 01 (Sunday)" and "2023 / 10 / 02 (Monday)," the forecast sales amounts for beef and pork, the corresponding dates in the previous year, sales in the previous year, and sales forecasts compared to the previous year are output.

[0061] <3. Processing flow> The functional configuration of the sales plan creation device 30 according to this embodiment has been described above. Next, the flow of processing according to this embodiment will be described with reference to Figs.

[0062] (1) Process flow for generating day of the week conditions The flow of processing related to generation of given days of the week conditions according to this embodiment will be described with reference to Fig. 10. Fig. 10 is a sequence diagram showing an example of the flow of processing related to generation of given days of the week conditions according to this embodiment.

[0063] As shown in FIG. 10, first, the developer inputs the given day of the week generation information to the developer terminal 10 (step S101). The developer terminal 10 transmits the day-of-week given condition generation information input by the developer to the sales plan creation device 30 (step S102). The day-of-week given condition generation information acquisition unit 331 of the sales plan creation device 30 acquires the day-of-week given condition generation information received by the communication unit 310 from the developer terminal 10 (step S103). The day-of-week given condition generation information acquisition unit 331 stores the acquired day-of-week given condition generation information in the storage unit 320. The day-of-week given condition rule setting unit 332 of the sales plan creation device 30 sets a day-of-week given condition rule based on the day-of-week given condition generation information acquired by the day-of-week given condition generation information acquisition unit 331 (step S104).

[0064] The day-of-week given condition information generating unit 333 of the sales plan creation device 30 generates day-of-week given condition information based on the day-of-week given condition rules set by the day-of-week given condition rule setting unit 332 (step S105). The day-of-week given condition information generating unit 333 stores the generated day-of-week given condition information in the storage unit 320. The output processing unit 338 of the sales plan creation device 30 transmits the given day of the week information generated by the given day of the week information generating unit 333 to the developer terminal 10 via the communication unit 310 (step S106).

[0065] (2) Process flow for generating a sales plan forecast model The flow of processing related to the generation of a sales plan forecast model according to this embodiment will be described with reference to Fig. 11. Fig. 11 is a sequence diagram showing an example of the flow of processing related to the generation of a sales plan forecast model according to this embodiment.

[0066] 11, first, the sales performance information management server 40 links (transmits) sales performance information to the sales plan creation device 30 (step S201). The sales performance information is information that can be acquired from, for example, a POS (Point of Sale) system used by a retail store. Next, the weather information management server 50 cooperates with (transmits) the weather information to the sales plan creation device 30 (step S202). The weather information is information that can be acquired from, for example, the website of the Japan Meteorological Agency. Next, the sales promotion information management server 60 links (transmits) the sales promotion information to the sales plan creation device 30 (step S203). The sales promotion information is, for example, information managed by a retail store as past sales promotion results. The processing order from step S201 to step S203 is not limited to the order shown in FIG. 13, and may be any order.

[0067] The learning data acquisition unit 334 of the sales plan creation device 30 acquires learning data (step S204). The learning data acquisition unit 334 acquires, as learning data, the sales performance information, weather information, and sales promotion information linked in steps S201 to S203, and the day-of-week given information generated in step S105 of FIG. 10. The learning data acquisition unit 334 stores the acquired learning data in the storage unit 320. Next, the sales plan learning unit 335 of the sales plan creation device 30 learns about the sales plan prediction based on the learning data acquired by the learning data acquisition unit 334 (step S205). Next, the sales plan learning unit 335 generates a sales plan forecast model based on the learning results (step S206). Next, the sales plan learning unit 335 stores the generated sales plan forecast model in the storage unit 320 (step S207).

[0068] (3) Sales plan forecast processing flow The flow of processing related to sales plan prediction according to this embodiment will be described with reference to Fig. 12. Fig. 12 is a sequence diagram showing an example of the flow of processing related to sales plan prediction according to this embodiment.

[0069] As shown in FIG. 12, first, the user inputs the forecasting conditions from the sales plan forecast screen into the user terminal 20 (step S301). The user terminal 20 transmits the prediction condition information indicating the prediction conditions input by the user to the sales plan creation device 30 (step S302).

[0070] The forecast condition information acquisition unit 336 of the sales plan creation device 30 acquires the forecast condition information received by the communication unit 310 from the user terminal 20 (step S303). The sales plan prediction unit 337 of the sales plan creation device 30 predicts the sales plan using the sales plan prediction model stored in the storage unit 320 based on the prediction condition information acquired by the prediction condition information acquisition unit 336 (step S304). The output processing unit 338 of the sales plan creation device 30 generates sales plan information based on the prediction result output by the sales plan prediction unit 337 (step S305). The output processing unit 338 stores the generated sales plan information in the storage unit 320. The output processing unit 338 of the sales plan creation device 30 transmits the generated sales plan information to the user terminal 20 via the communication unit 310 (step S306).

[0071] The user terminal 20 displays the forecast result based on the sales plan information received from the sales plan creation device 30 (step S307). The user checks the forecast results (sales plan) displayed on the user terminal 20 (step S308).

[0072] The processing flow according to this embodiment has been described above. As described above, the business support system 1 according to this embodiment includes a prediction condition information acquisition unit 336 that acquires prediction condition information indicating the prediction conditions of the sales plan, and a sales plan prediction unit 337 that predicts the sales plan of a retail store under the prediction conditions indicated by the acquired prediction condition information based on the relationship between multiple pieces of information that affect the sales plan.

[0073] With this configuration, a user can obtain sales plan prediction results from the business support system 1 by inputting sales plan prediction conditions into the business support system 1. The user can use the prediction results obtained from the business support system 1 as a sales plan as is, or can create a sales plan based on the prediction results. As a result, by using the business support system 1, the user does not need to create a sales plan from scratch, thereby reducing the workload involved in creating a sales plan. Therefore, the business support system 1 according to this embodiment can reduce the workload imposed on the creator when creating a sales plan.

[0074] <4. Modifications> The above describes the embodiments. Next, modifications of the above-described embodiments will be described. Note that each modification described below may be applied to the embodiments alone or in combination with each other. Furthermore, each modification may be applied in place of the configuration described in the embodiments, or may be applied in addition to the configuration described in the embodiments.

[0075] In the above-described embodiment, an example has been described in which the business support system 1 is a single device (e.g., a server) having all of the day-of-week given-condition generation function, model generation function, and prediction function, but the present invention is not limited to such an example. For example, the business support system 1 may be realized by multiple devices each having a day-of-week given-condition generation device having a function for generating day-of-week given conditions (day-of-week given-condition generation function), a sales plan learning device having a function for generating a sales plan prediction model (prediction model generation function), and a sales plan prediction device having a function for predicting a sales plan (prediction function). Furthermore, the business support system 1 may be realized by multiple devices combining some of the devices or a device that integrates some of the functions with the remaining devices or a device that has the remaining functions.

[0076] In the above-described embodiment, an example has been described in which sales performance information, weather information, and sales promotion information, which are part of the learning data, are automatically linked from a server (system) that manages each piece of information to the sales plan creation device 30, but the present invention is not limited to such an example. For example, the sales performance information, weather information, and sales promotion information may be linked to the sales plan creation device 30 by the developer from the developer terminal 10.

[0077] In the above-described embodiment, the sales promotion information management server 60 and other devices are connected via a network NW, but the present invention is not limited to this example. For example, the sales promotion information management server 60 and other devices do not necessarily have to be connected via a network NW.

[0078] Furthermore, in the above-described embodiment, an example has been described in which the sales plan information generated by the output processing unit 338 is transmitted from the communication unit 310 to the user terminal 20 and displayed thereon, but the present invention is not limited to such an example.

[0079] In the above-described embodiment, an example has been described in which sales promotion information indicating the past (for example, past sales promotion results) is linked from the sales promotion information management server 60 to the sales plan creation device 30, but the present invention is not limited to such an example. For example, when making a future prediction, the sales promotion information linked from the sales promotion information management server 60 to the sales plan creation device 30 may be sales promotion information indicating the future (for example, future sales promotion prediction).

[0080] The above describes the modified examples of the embodiment of the present invention. In addition, the business support system 1, developer terminal 10, user terminal 20, sales plan creation device 30, sales performance information management server 40, weather information management server 50, and sales promotion information management server 60 in the above-described embodiment may be partly or entirely implemented by a computer. In this case, a program for implementing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be read into a computer system and executed. Note that the term "computer system" here includes hardware such as an OS and peripheral devices. Additionally, "computer-readable recording media" refers to portable media such as flexible disks, optical magnetic disks, ROMs, CD-ROMs, etc., and storage devices such as hard disks built into computer systems. Furthermore, "computer-readable recording media" may also include devices that dynamically store programs for a short period of time, such as communication lines when transmitting programs via networks such as the Internet or communication lines such as telephone lines, and devices that store programs for a certain period of time, such as volatile memory within computer systems that serve as servers or clients in such cases. Furthermore, the above program may be one that realizes part of the above-mentioned functions, or may be one that can realize the above-mentioned functions in combination with a program already recorded in a computer system, or may be one that is realized using a programmable logic device such as an FPGA (Field Programmable Gate Array).

[0081] The embodiments of the present invention have been described in detail above with reference to the drawings, but the specific configuration is not limited to that described above, and various design changes can be made within the scope of the gist of the present invention. [Explanation of symbols]

[0082] 1...Business support system, 10...Developer terminal, 20...User terminal, 30...Sales plan creation device, 40...Sales performance information management server, 50...Weather information management server, 60...Sales promotion information management server, 310...Communication unit, 320...Storage unit, 330...Control unit, 331...Day of week given condition generation information acquisition unit, 332...Day of week given condition rule setting unit, 333...Day of week given condition information generation unit, 334...Learning data acquisition unit, 335...Sales plan learning unit, 336...Prediction condition information acquisition unit, 337...Sales plan prediction unit, 338...Output processing unit, NW...Network

Claims

1. a forecast condition information acquisition unit that acquires forecast condition information indicating forecast conditions of the sales plan; a sales plan forecasting unit that forecasts a sales plan of the retail store under the forecast conditions indicated by the acquired forecast condition information based on the relationship between a plurality of pieces of information that affect the sales plan; A business support system equipped with:

2. The plurality of pieces of information that affect the sales plan are sales performance information that indicates past sales performance of the retail store, at least one or more pieces of sales influence information that indicate factors that affect the sales performance, and day of the week condition information that indicates information that associates each date in the forecast target year with a date in the previous year that has similar sales characteristics. The business support system according to claim 1 .

3. The sales impact information is weather information or sales promotion information; The business support system according to claim 2 .

4. a day of the week given condition generation information acquisition unit that acquires a day of the week given condition rule for associating each date of the target year of prediction with each date of the previous year, and day of the week given condition generation information indicating whether or not an event occurs on each date of the target year of prediction and each date of the previous year; a day of the week given information generation unit that generates the day of the week given information based on the acquired day of the week given information; The business support system according to claim 2 , further comprising:

5. a learning data acquisition unit that acquires the sales performance information, the sales influence information, and the day of the week given information as learning data; a sales plan learning unit that generates a sales plan prediction model that has learned about the relationship between a plurality of pieces of information that affect the sales plan based on the acquired learning data; Furthermore, the sales plan forecasting unit forecasts the sales plan using the generated sales plan forecasting model. The business support system according to claim 2 .

6. an output processing unit that outputs sales plan information indicating, as the sales plan, a predicted amount of sales at the retail store under the prediction conditions indicated by the prediction condition information based on the prediction result by the sales plan prediction unit; The business support system according to claim 1 , further comprising:

7. a forecast condition information acquisition step of acquiring forecast condition information indicating forecast conditions of the sales plan; a sales plan forecasting process for forecasting a sales plan of a retail store under the forecast conditions indicated by the acquired forecast condition information based on the relationship between a plurality of pieces of information that affect the sales plan; A computer-implemented business support method comprising:

8. Computer, a forecast condition information acquisition means for acquiring forecast condition information indicating forecast conditions of the sales plan; a sales plan forecasting means for forecasting a sales plan of a retail store under the forecast conditions indicated by the acquired forecast condition information based on the relationship between a plurality of pieces of information that affect the sales plan; A program to function as a

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