Information processing systems, information processing methods, and programs

Abstract

This invention provides an information processing system, information processing method, and program capable of presenting analysis results regarding the supply capacity of order processing centers in online supermarkets. [Solution] In a specific step, the information processing device identifies the store that processes orders placed by customers at an online supermarket, as specified by the user. In a first acquisition step, it acquires order processing performance information that shows the processing performance of each order processed by the store during the target period, for orders where the specified store was the order processing base. In an output step, it uses the order processing performance information to output a supply index, which is an index that shows the processing performance of the store for orders during the target period.

Description

Technical Field

[0001] The present disclosure relates to an information processing system, an information processing method, and a program.

Background Art

[0002] As a system for stores, a system for implementing marketing based on customer attribute information is known. For example, Patent Document 1 discloses a settlement information processing device that generates a report analyzed by customer attribute information based on settlement information acquired from a store settlement terminal or a customer terminal.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, unlike general e-commerce sites, online supermarkets have characteristics such as a large number of products and a requirement for short-time delivery. In particular, when picking products from an order processing base such as a physical store or a distribution center, the supply capacity of the order processing base greatly affects the service quality. Therefore, it has been difficult for the settlement information processing device described in Patent Document 1 above to quantitatively analyze and evaluate the characteristics unique to online supermarkets.

[0005] An object of the present disclosure is to provide an information processing system, an information processing method, and a program that can present an analysis result regarding the supply capacity of an order processing base in an online supermarket in view of the above problems.

Means for Solving the Problems

[0006] An information processing system according to one aspect of the present disclosure comprises one or more processors and memory. The one or more processors are capable of performing the following steps: in a specific step, they identify a store that processes orders placed by customers in an online supermarket, as specified by the user; in a first acquisition step, they acquire order processing performance information showing the processing performance for each order processed by the specified store during a target period, where the store was the order processing center; and in an output step, they use the order processing performance information to output a supply index, which is an index showing the processing performance of the store for orders during the target period.

[0007] An information processing method according to one aspect of this disclosure is a method by which an information processing system performs each of the steps described above.

[0008] A program according to one aspect of this disclosure is a program that causes a computer having one or more processors and memory to perform each of the steps described above. [Effects of the Invention]

[0009] This disclosure provides an information processing system, information processing method, and program capable of presenting analysis results regarding the supply capacity of order processing centers in online supermarkets. [Brief explanation of the drawing]

[0010] [Figure 1] This is a block diagram showing the overall structure of the information processing system. [Figure 2] This is a block diagram showing the hardware configuration of an information processing device. [Figure 3] Block diagram showing the hardware configuration of headquarters terminals and customer terminals. [Figure 4] This is a block diagram showing the functional configuration of the control unit of an information processing device. [Figure 5] This is a sequence diagram showing the flow of the data registration process. [Figure 6] This figure shows an example of the data structure for store processing plan information. [Figure 7] It is a conceptual diagram showing the relationship between order element information and order processing result information. [Figure 8] It is a sequence diagram showing the flow of index output processing. [Figure 9] It is a diagram showing an example of the data structure of the calculation formula master. [Figure 10] It is a diagram showing an example of the display screen of the store-wide index. [Figure 11] It is a diagram showing an example of the display screen of the demand index for each store. [Figure 12] It is a diagram showing an example of the display screen of the supply index for each store. [Figure 13] It is a diagram showing an example of the display screen of the supply index for each store group.

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In each drawing, the same or corresponding elements are denoted by the same reference numerals, and redundant descriptions are omitted as necessary for clarity of explanation.

[0012] 1. Hardware Configuration In this section, the hardware configuration of the information processing system 1 of the present embodiment will be described. FIG. 1 is a block diagram showing the overall configuration of the information processing system 1. In the following description, the processor is synonymous with a circuit (Circuitry) composed of a central processing unit or the like.

[0013] 1.1 Information Processing System 1 The information processing system 1 is a computer system that analyzes order processing in an online supermarket. The information processing system 1 includes an information processing device 2, a head office terminal 3, a store terminal 4, and a customer terminal 5. The information processing device 2, the head office terminal 3, the store terminal 4, and the customer terminal 5 are communicably connected to each other via a network NW such as the Internet or a LAN (Local Area Network).

[0014] 1.2 Information Processing Device 2 The information processing device 2 is a computer such as a server that provides a platform for network super applications and an analysis function for network super order processing. The information processing device 2 receives orders from the customer terminal 5, collects the processing results at the store terminal 4, and outputs various indicators in response to requests from the head office terminal 3 or the store terminal 4.

[0015] Figure 2 is a block diagram showing the hardware configuration of the information processing device 2. The information processing device 2 includes a control unit 21, a storage unit 22, and a communication unit 23, and these components are electrically connected via a communication bus 26 inside the information processing device 2.

[0016] The control unit 21 performs processing and control of the overall operations related to the information processing device 2. The control unit 21 is a processor such as a central processing unit (CPU = Central Processing Unit), for example. The control unit 21 realizes various functions related to the information processing device 2 by reading a predetermined program stored in the storage unit 22. That is, the information processing instructions stored in the storage unit 22 are specifically realized by the control unit 21, which is an example of hardware, and can be executed as each functional unit included in the control unit 21. The functional configuration will be described in more detail in the next section. Note that the control unit 21 is not limited to being single, and may be implemented to have a plurality of control units 21 for each function, or a combination thereof.

[0017] The storage unit 22 is a storage device including a non-temporary computer-readable medium or a tangible storage medium, and stores various information. The storage unit 22 can be implemented as a storage device such as a solid state drive (SSD) or a memory such as a random access memory (RAM), for example.

[0018] The communication unit 23 is a communication interface for connecting to the network NW.

[0019] 1.3 Head Office Terminal 3 Headquarters Terminal 3 is a computer terminal operated by a user who is a staff member at the headquarters of the online supermarket business. Headquarters Terminal 3 can be a smartphone, tablet, personal computer, or other input / output communication terminal. Headquarters Terminal 3 is used to access the analysis functions provided by Information Processing Device 2 and to view and analyze various indicators.

[0020] Figure 3(A) is a block diagram showing the hardware configuration of the headquarters terminal 3. The headquarters terminal 3 comprises a control unit 31, a storage unit 32, a communication unit 33, an input unit 34, and a display unit 35, and these components are electrically connected within the headquarters terminal 3 via a communication bus 36. The hardware configuration of the control unit 31, storage unit 32, and communication unit 33 is substantially the same as that of the control unit 21, storage unit 22, and communication unit 23 of the information processing device 2, so a detailed explanation is omitted. The input unit 34 is a keyboard, mouse, or touch panel, etc., that accepts operation input from headquarters staff. The display unit 35 is a liquid crystal display, etc., which displays input screens and display screens for analysis functions, etc.

[0021] 1.4 Store Terminal 4 Store terminal 4 is a computer terminal operated by a user who is a staff member (hereinafter referred to as "store staff") at a physical store that serves as an order processing center for online supermarket orders. Store terminal 4 can be a smartphone, tablet, personal computer, or other communication terminal capable of input / output. Store terminal 4 is used to process picking, packing, and delivery of goods based on orders from customer terminal 5. Since the hardware configuration of store terminal 4 is substantially the same as that of headquarters terminal 3, a detailed explanation is omitted.

[0022] 1.5 Customer Terminal 5 Customer terminal 5 is a computer terminal operated by consumers or end-users (hereinafter referred to as "customers") who use the online supermarket. Customer terminal 5 can be a smartphone, tablet, personal computer, or other communication terminal capable of input / output. Customer terminal 5 is used to run the online supermarket application and order products.

[0023] Figure 3(B) is a block diagram showing the hardware configuration of the customer terminal 5. The customer terminal 5 comprises a control unit 51, a storage unit 52, a communication unit 53, an input unit 54, and a display unit 55, and these components are electrically connected within the customer terminal 5 via a communication bus 56. The hardware configurations of the control unit 51, storage unit 52, and communication unit 53 are substantially the same as those of the control unit 21, storage unit 22, and communication unit 23 of the information processing device 2, so their explanation is omitted. The input unit 54 is a keyboard, mouse, or touch panel, etc., that accepts operation input from the customer. The display unit 55 is a liquid crystal display, etc., which displays the online supermarket order screen, etc.

[0024] 2. Functional Configuration This section describes the functional configuration of this embodiment, particularly the functional configuration of the information processing device 2. The information processing method described later is executed by the information processing device 2. Figure 4 is a block diagram showing the functional configuration of the control unit 21 of the information processing device 2. The control unit 21 executes a program to realize the functions of the registration unit 210, the identification unit 211, the first acquisition unit 212, the second acquisition unit 213, the calculation unit 214, the analysis unit 215, and the output control unit 216.

[0025] The registration unit 210 registers store processing plan information, order information from customer terminal 5, and processing results from store terminal 4 in the storage unit 22 as a data registration step. The registration unit 210 also stores calculation formulas for calculating various indicators, which will be described later.

[0026] The identification unit 211, as a identification step, identifies the store that will process the customer order placed by the online supermarket, as specified by the user. In the following, the user is, for example, a headquarters staff member operating the headquarters terminal 3. However, the user is not limited to this, and may also be a store staff member operating the store terminal 4.

[0027] The first acquisition unit 212, as the first acquisition step, acquires order processing performance information that shows the processing performance for each order processed by the store designated by the identification unit 211 during the target period, where the store was the order processing base. For example, the order processing performance information includes at least one of the following: information regarding product availability and information regarding the time required for delivery work.

[0028] The second acquisition unit 213, as the second acquisition step, acquires store processing plan information, which is pre-planned as the amount of processing capacity that the store can handle during the target period. The store processing plan information is information for calculating the ratio of actual results to the planned capacity of the store, and may include, for example, at least one of the number of order slots and the number of delivery slots.

[0029] The calculation unit 214 calculates various indicators, such as supply indicators or demand indicators, using at least one of the order processing performance information and the store processing plan information as a calculation step. Here, the supply indicator is an indicator that shows the store's processing performance for orders during the target period. The demand indicator is an indicator that shows the store's demand during the target period. For example, the calculation unit 214 may calculate parameter values ​​by performing statistical processing on order processing performance information, and then calculate various indicators (e.g., the supply indicator) by applying these parameter values ​​to calculation formulas stored in the registration unit 210.

[0030] The analysis unit 215 performs an analysis of the indicators calculated by the calculation unit 214 as an analysis step. The analysis may be rule-based analysis or analysis using an artificial intelligence model.

[0031] The output control unit 216 implements the functions of the display control unit 217 and the data output control unit 218 as an output step. Specifically, the output control unit 216 outputs the supply indicator, demand indicator calculated by the calculation unit 214, or the analysis results generated by the analysis unit 215 to a display terminal (e.g., headquarters terminal 3).

[0032] As one aspect of the output step, the display control unit 217 displays on the display terminal an input area for information necessary for information processing by the control unit 21 or the results of information processing. For example, the display control unit 217 generates a display screen including various indicators or analysis results and displays it on the headquarters terminal 3.

[0033] Furthermore, the display control unit 217 causing information to be displayed on the display terminal may mean that the display control unit 217 transmits screen data showing that information to the display terminal, or it may mean that the display control unit 217 transmits data necessary to generate a screen showing that information to the display terminal.

[0034] As one aspect of the output step, the data output control unit 218 outputs the results of information processing by the control unit 21 to a display terminal. For example, the data output control unit 218 outputs various indicators or analysis results in a downloadable format such as a spreadsheet or CSV.

[0035] 3. Operation of Information Processing Device 2 Section 3 will explain the flow of information processing performed by the information processing device 2, with reference to the diagram. The information processing includes data registration processing and indicator output processing.

[0036] 3.1 Data Registration Process First, the data registration process by Information Processing System 1 will be explained using Figures 5 to 7. Figure 5 is a sequence diagram showing the flow of the data registration process.

[0037] [Registration of store processing plan information (S101~S102)] The headquarters terminal 3 or store terminal 4 inputs the processing plan for each store based on user input and transmits it to the information processing device 2 (S101). For example, the number of order slots or delivery slots for a specific date and time are entered. The registration unit 210 of the information processing device 2 registers this information as store processing plan information (T1) in the storage unit 22 (S102).

[0038] Figure 6 shows an example of the data structure of store processing plan information T1. Store processing plan information T1 has records for the number of pre-planned order slots (T13) and delivery slots (T14) for each store ID (T10), day (T11), and time slot (T12). The number of order slots (T13) and the number of delivery slots (T14) are examples of planned values ​​that indicate the processing capacity that the store, which is the order processing center, can handle during each time period. The Order Slot (T13) is a value that indicates the upper limit of the total number of orders that a store is planned to be able to process on a particular day (T11) and time period (T12). This Order Slot may be set, for example, based on the number of personnel available for picking and packing operations at the store. The Order Slot (T13) corresponds to the total number of orders that can be accepted during that time period, including both orders that are designated for delivery to the customer and orders that are designated for in-store pickup by the customer. The delivery slot count (T14) is a value that indicates the maximum number of orders planned to be delivered from the store to customers on a particular day (T11) and time period (T12). This delivery slot count may be set based on delivery resources such as the store's delivery vehicles and drivers. Typically, the delivery slot count (T14) is set to a value less than or equal to the order slot count (T13).

[0039] As shown in the example above, store processing plan information for multiple stores may be stored in a single table, or it may be stored in separate tables for each store.

[0040] [Order processing and registration of order processing results (S103~S111)] When a customer orders goods from the customer terminal 5 using the online supermarket application (S103), the registration unit 210 of the information processing device 2 issues an order ID (S104) and registers information related to the order as order element information (S105). The order element information includes, for example, the customer ID, store ID, the unit price of the goods, the quantity, the number of items ordered, the pick-up time, and whether or not a coupon is used.

[0041] The information processing device 2 then identifies the order processing location (store) corresponding to the order ID and sends the order processing request to the store terminal 4 of the identified store (S106). In customer information, each customer is associated with an order processing location (store) identified based on the customer's address or postal code, and the information processing device 2 may identify the order processing location for each order by reading the customer information. However, the information processing device 2 is not limited to this and may determine the order processing location each time based on the delivery address or postal code provided by the customer.

[0042] Upon receiving this order processing request, the store, which is the order processing center, has its staff perform order processing tasks such as picking, packing, and delivery. For each process, the store terminal 4 transmits the processing results (order ID, processing type, start or completion time, and number of items processed, etc.) to the information processing device 2 (S107, S109). The registration unit 210 of the information processing device 2 updates the order element information as needed based on the received processing results (S108, S110).

[0043] Figure 7 is a conceptual diagram showing the relationship between order element information and order processing performance information. As shown on the left side of Figure 7, the registration unit 210 stores order element information linked to the order ID at each stage of order processing.

[0044] For example, when an order is placed, the registration unit 210 stores information such as store ID, customer ID, number of items ordered, unit price, total payment amount, pickup time, and whether or not a coupon is used as order element information. Also, when picking, the registration unit 210 stores information such as pick start time, pick completion time, and number of items processed as order element information. When packing, it stores information such as pack start time, pack completion time, and number of items processed as order element information. When delivery, it stores information such as delivery start time and delivery completion time as order element information. The registration unit 210 also stores cancellation information such as whether or not an order was canceled or the number of canceled items, out-of-stock information such as whether or not an item is out of stock, whether or not there are missing items or the number of missing items, or other information as order element information.

[0045] Once the series of processes is complete, the registration unit 210 aggregates the accumulated order element information for each order ID and generates order processing performance information by performing appropriate calculations for each order ID (S111). As shown on the right side of Figure 7, the registration unit 210 generates order processing performance information such as the number of items ordered, picking time, packing time, number of items picked, number of items packed, delivery time, out-of-stock information, and cancellation information. In addition to the information at the time of ordering, the order processing performance information may also include calculated information, such as picking time, packing time, pick-pack processing rate per hour (pick-pack UPH), pick-pack processing rate per hour (pick-pack UPH), whether there are packing delays, and whether there are delivery delays. The registration unit 210 registers this order processing performance information in the storage unit 22.

[0046] The above process of generating order processing performance information from order element information may also be performed in the first acquisition step by the first acquisition unit 212, which will be described later. That is, in response to receiving an indicator output request, the first acquisition unit 212 may acquire order element information of the processing performance associated with each order ID corresponding to the store and period specified by the user, and acquire order processing performance information corresponding to the order ID based on the order element information.

[0047] 3.2 Indicator Output Processing Next, the indicator output processing by the information processing system 1 will be explained using Figures 8 to 13. 3.2.1 Overview of Indicator Output Processing First, let's explain the overview of the indicator output process. Figure 8 is a sequence diagram showing the flow of the indicator output process.

[0048] First, a request for indicator output is sent from the headquarters terminal 3 to the information processing device 2 (S121). This request specifies the store (or store group) to be analyzed and the period.

[0049] Next, the identification unit 211 of the information processing device 2 identifies the order ID corresponding to the specified store and period (identification step: S122). Next, the first acquisition unit 212 acquires the order processing performance information corresponding to the identified order ID from the storage unit 22 (first acquisition step: S123). Next, the second acquisition unit 213 acquires the store processing plan information corresponding to the specified store and period from the storage unit 22 (second acquisition step: S124).

[0050] The calculation unit 214 calculates supply indicators and demand indicators based on the acquired order processing performance information and store processing plan information (calculation step: S125). Then, the analysis unit 215 analyzes the calculated indicators as necessary (analysis step: S126).

[0051] Finally, the output control unit 216 outputs (for example, displays) the calculated indicators and analysis information to the headquarters terminal 3 (output step: S127).

[0052] [effect] In this way, the information processing device 2 outputs a supply index for each order processed at the designated order processing location using order processing performance information for each order in the online supermarket. This allows the information processing device 2 to specifically analyze the supply capacity of each order processing location, which is a challenge unique to online supermarkets.

[0053] Furthermore, the information processing device 2 may output supply indicators for a designated order processing location using store processing plan information in addition to order processing performance information. This allows the information processing device 2 to evaluate indicators that show performance against the plan, such as the occupancy rate. As a result, the user can objectively grasp the operational status or processing capacity of each location.

[0054] 3.2.2 Details of indicator output processing Next, we will explain the details of the indicator output processing performed by Information Processing System 1.

[0055] [Calculation of supply indicators (S125)] The supply indicator is an indicator that shows the store's processing performance for orders during a specified period, i.e., its supply capacity. The supply indicator can also be described as the store's order processing capacity for orders during a specified period. For example, if the order processing performance information includes information on product availability, the supply indicator may include indicators related to product procurement performance. Also, if the order processing performance information includes information on the time required for delivery, the supply indicator may include indicators related to product delivery performance. One example of procurement performance is the stockout rate. Another example of delivery performance is the full-service rate, pick-up-up-hours (UPH), pack-up-up-hours (UPH), or pick-pack-up-up-hours (UPH). This allows the information processing device 2 to specifically evaluate the store's supply capacity from the perspectives of product availability and operational efficiency.

[0056] Figure 9 shows an example of the data structure of the calculation formula master T2. The calculation unit 214 calculates various indicators by referring to a calculation formula master (T2) as shown in Figure 9. This master holds the indicator name (T21), items of order processing performance information necessary for calculation (T22), items of store processing plan information (T23), and calculation formula (T24).

[0057] <Explanation of supply indicators> (Full rate) The "fullness rate" is an example of information indicating how well delivery slots are filled, and is calculated as "number of orders / number of order slots" (i.e., the ratio of the number of orders to the number of order slots). This is an indicator of how much of the order slots available to the store have been filled. The calculation unit 214 calculates the fullness rate using the number of orders obtained from the order processing performance information for the specified store and specified period. Specifically, the calculation unit 214 first obtains the number of order slots (y) from the store processing plan information for the specified store and period, and the order ID (x1) from the order processing performance information for the specified store and period. The calculation unit 214 obtains the number of orders (COUNT(x1)) by counting the types of order IDs. Then, the calculation unit 214 calculates the occupancy rate by dividing the number of orders (COUNT(x1)) by the number of order slots (y). If, in addition to delivery, in-store pickup is also available as a method of receiving goods, the service utilization rate may be calculated as the number of deliveries / the number of delivery slots (i.e., the ratio of deliveries to the number of delivery slots). In this case, the calculation unit 214 calculates the service utilization rate using the number of deliveries obtained from the order processing performance information for the designated store and the designated period.

[0058] (UPH (Units Per Hour)) "UPH" is calculated as "Number of items processed / Working time required for processing." This is an indicator of staff work efficiency. The calculation unit 214 uses order processing performance information for a specified store and period to calculate the number of items picked per hour, the number of items packed per hour, or the number of items picked and packed per hour. The order processing performance information includes, for each order, at least one of the number of items picked and the number of items packed, and at least one of the picking time and the packing time.

[0059] Specifically, for "Pick UPH," the calculation unit 214 obtains the number of items to be picked (x1) and the picking work time (x2) from the order processing performance information for the specified store and period, and calculates Pick UPH by dividing the total number of items to be picked (x1) by the total picking work time (x2). Similarly, for "Pack UPH," the calculation unit 214 obtains the number of items to be packed (x1) and the packing work time (x2) from the order processing performance information for the specified store and period, and calculates Pack UPH by dividing the total number of items to be packed by the total packing work time. The calculation unit 214 may also calculate "Pick Pack UPH." Specifically, the calculation unit 214 first calculates the sum of the total number of items to be picked and the total number of items to be packed (total pick pack items), and the sum of the total picking work time and the total packing work time (total pick pack work time). The calculation unit 214 then calculates the pick-pack UPH by dividing the total number of pick-pack processing points by the total pick-pack work time.

[0060] (Out of stock rate) The "stockout rate" is calculated as "number of stockouts / number of orders". This is an indicator of the ability to procure goods. The calculation unit 214 uses order processing performance information, including the number of stockouts and the number of orders, for each order at a designated store and for a designated period, to calculate the stockout rate as a supply indicator, which shows the ratio of stockouts to the number of orders. Specifically, the calculation unit 214 obtains the number of out-of-stock items (x1) and the number of ordered items (x2) from the order processing performance information for the specified store and period, and calculates the total number of out-of-stock items by summing the number of out-of-stock items (x1) and the total number of ordered items by summing the number of ordered items (x2) through statistical processing. Then, the calculation unit 214 calculates the out-of-stock rate by dividing the total number of out-of-stock items by the total number of ordered items.

[0061] (On-time shipping rate) The on-time shipping rate represents the ratio of orders for which packing was completed within the scheduled delivery start time to the total number of orders, and is calculated as "(Number of orders - Number of delayed packings) / Number of orders". For each delivery slot, an on-time shipping is counted if the packing completion time does not exceed the scheduled delivery start time. Specifically, the calculation unit 214 obtains the number of delayed packings (COUNT(x1)) by counting whether or not there was a delay in packing, and obtains the number of orders (COUNT(x2)) by counting the types of order IDs. The calculation unit 214 then calculates the on-time shipping rate by subtracting the value obtained by dividing the number of delayed packings (COUNT(x1)) by the number of orders (COUNT(x2)) from 1.

[0062] (Delayed delivery rate) The late delivery rate represents the percentage of orders where the actual delivery completion time was later than the scheduled delivery date and time, relative to the total number of deliveries per day. It is calculated as "Number of late delivery orders on the order receipt date / Number of deliveries on the order receipt date". Specifically, the calculation unit 214 obtains the number of late delivery orders (COUNT(x1)) by counting whether or not an order was late, and the number of deliveries (COUNT(x2)) by counting whether or not an order was delivered. The calculation unit 214 then calculates the late delivery rate by dividing the number of late delivery orders (COUNT(x1)) by the number of deliveries (COUNT(x2)).

[0063] (absence rate) The missing order rate represents the percentage of orders in which one or more ordered items are missing, relative to the total number of orders, and is calculated as "number of missing orders / total number of orders". Specifically, the calculation unit 214 obtains the number of missing orders (COUNT(x1)) by counting whether or not items are out of stock, and obtains the total number of orders (COUNT(x2)) by counting the types of order IDs. The calculation unit 214 then calculates the missing order rate by dividing the number of missing orders (COUNT(x1)) by the total number of orders (COUNT(x2)).

[0064] <Setting up custom metrics> The calculation formula master may also contain other operational indicators or indicators related to stockouts that are unique to the business operator or store. In this case, the registration unit 210 of the information processing device 2 may, in the storage step, store the received calculation formula in the supply indicator calculation formula master in response to receiving a specification of a unique calculation formula including parameters from the user (head office staff or store staff). Then, when an indicator output request is received, the calculation unit 214 may extract the specified parameters from the order processing performance information based on the calculation formula master in Figure 9, apply them to the stored calculation formula, and calculate the user-defined custom indicator as the supply indicator. In this way, the information processing device 2 allows businesses or stores to flexibly set and present operational indicators that they wish to manage independently.

[0065] [Calculation of demand indicators (S125)] The output control unit 216 may output demand indicators in addition to supply indicators, which are indicators that show store demand or customer purchasing trends. Demand indicators are calculated based on parameters obtainable from at least a portion of order processing performance information for a specified store and period, such as sales, number of orders, or customer ID. Examples of demand indicators include sales, number of orders, number of ordering users, number of accessing users, number of newly registered users, average order value (AOV), average number of items per order (UPO), average unit price (AUP), number of cancellations, cancellation rate, or coupon usage rate for each store.

[0066] <Explanation of demand indicators> (Number of ordering users) The number of ordering users indicates the number of customers who placed orders through the online supermarket application at the specified store and during the specified period.

[0067] (Number of users accessing the site) The number of accessing users indicates the number of customers who accessed the online supermarket application at the specified store and during the specified period.

[0068] (Average Over-the-Counter Price (AOV)) The unit price per basket indicates the price per order and is calculated as "sales / number of orders".

[0069] (Average Order Quantity (UPO)) The average order count represents the average number of items per order and is calculated as "order count / number of orders".

[0070] (Average Unit Price (AUP)) The average unit price is the average unit price of the product and is calculated as "sales / number of items ordered".

[0071] (Number of cancellations) The number of cancellations indicates the number of orders that were cancelled.

[0072] (Cancellation rate) The cancellation rate represents the ratio of canceled orders to the total number of orders placed at a specified store and during a specified period, and is calculated as "number of cancellations / number of orders".

[0073] (Coupon usage rate) The coupon redemption rate represents the percentage of orders to which a coupon was applied relative to the total number of orders placed at a designated store and during a designated period. It is calculated as "Number of coupons applied / Total number of orders".

[0074] [Display indicators (S127)] Figures 10, 11, and 12 show examples of display screens shown on the headquarters terminal 3.

[0075] <Display of indicators for all stores> Figure 10 shows an example of the display screen 80 for all-store indicators. When the user selects the "All Stores" tab 801 and specifies the period 802, the output control unit 216 displays the actual values ​​of the demand indicator 803 and supply indicator 804, aggregated for all stores, along with the month-on-month change, on the headquarters terminal 3. In this figure, the demand indicator 803 is sales, number of orders, and price per basket. In this figure, the supply indicator 804 is the occupancy rate, UPH, and stockout rate.

[0076] <Display of demand indicators by store> Figure 11 shows an example of the display screen 81 for store-specific demand indicators. When the user selects the "Store-Specific (Demand)" tab 811, the screen transitions to the display screen 81. On the display screen 81, the user can individually specify a period 812 and one or more stores. The user can also specify a store group 813 that includes multiple stores. For example, if the identification unit 211 receives a specification of a store group 813 from the user, it identifies the multiple stores included in the store group as the specified stores. In this case, the output control unit 216 displays a list of demand indicators 814 for each store belonging to the specified store group. In this figure, the sales, number of orders, and unit price per basket for the Nakameguro store, Hachioji store, and Urawa store, which are located in the Kanto region, are displayed in a list. The output control unit 216 may also display the coupon usage rate for each store belonging to a specified store group. This allows users to see at a glance whether there are differences in coupon usage rates among stores belonging to the same store group, and to consider specific improvement actions such as the content or distribution method of coupons in accordance with the customer characteristics of each store.

[0077] <Display of supply indicators by store (output of indicators for multiple stores)> Figure 12 shows an example of the display screen 82 for store-specific supply indicators. When the user selects the "Store-Specific (Supply)" tab 821, the screen transitions to the display screen 82. On the display screen 82, as with the display screen 81, the user can individually specify a period 812 and one or more stores. The user can also specify a store group 813 that includes multiple stores. For example, when the identification unit 211 receives a store group specification from the user, it identifies the multiple stores included in the store group as the specified stores. In this case, the output control unit 216 outputs the supply indicators for the multiple identified stores. For example, the output control unit 216 displays a list of supply indicators 824 for each store belonging to the specified store group. In this figure, the full-capacity rate, UPH, and on-time shipment rate for the Nakameguro store, Hachioji store, and Urawa store, which are included in the Kanto region, are displayed in a list. This allows the user to compare and analyze the supply capacity of each store. In particular, by comparing supply indicators specific to online supermarkets, such as the full-capacity rate, UPH, or stockout rate, the supply-side challenges specific to online supermarkets at each store can be individually and objectively grasped. This makes it possible to implement concrete improvement actions, such as adjusting resources like staffing or order limits at each store, or sharing the know-how of successful stores with other stores.

[0078] In Figures 11-12, the output control unit 216 displays the demand and supply indicators on separate tabs, but both indicators may be displayed on a single screen. This allows for a comprehensive understanding of the store's situation.

[0079] <Permission Management> The output control unit 216 may restrict the display of indicators according to the attributes or permissions of the user requesting the indicator output. For example, the output control unit 216 may restrict the stores to which supply indicators are displayed depending on whether the user is a headquarters staff member or a store staff member. As an example, the output control unit 216 may display supply indicators for all stores to a user with headquarters staff privileges operating the headquarters terminal 3. On the other hand, the output control unit 216 may display supply indicators for stores related to the store staff member operating the store terminal 4, and restrict the display of supply indicators for stores other than those related to the store staff member. Stores related to the store staff member may be, for example, the store to which the store staff member belongs or stores belonging to the store group of that store. This allows for the provision of necessary information while protecting confidential information between stores. In addition, demand indicators may also be restricted in display according to the user's attributes or permissions, similar to supply indicators.

[0080] <Displaying metrics by store group> Figure 13 shows an example of a display screen 83 for supply indicators 835 and analysis summary 836 by store group. The identification unit 211 may accept the user's specification of multiple store groups. In this case, the identification unit 211 identifies the multiple stores included in each store group as the specified stores. In this figure, the Meguro area is specified as the own group 833, and the Shonan area is specified as the comparison group 834. The output control unit 216 then outputs a supply indicator that has been statistically processed for multiple stores, for example, the average value of the supply indicator. As shown in Figures 11-12, the output control unit 216 may not only display the indicator for each store within a group, but may also output the supply indicators 835 between groups in a comparable manner, as shown in Figure 13. As an example, the supply indicators 835 are the full capacity rate, UPH, and on-time shipment rate. This allows the user to compare and analyze supply capacity by region (e.g., Kanto area and Kansai area) or by characteristic (e.g., station area group and suburban group, large store group and small store group). By comparing supply indicators specific to online supermarkets, it becomes possible to objectively understand the supply-side challenges unique to online supermarkets from a macro perspective. This makes it possible to take concrete improvement actions, such as reallocating resources like personnel or order slots, or sharing the know-how of successful groups with other groups.

[0081] The output control unit 216 may also output demand indicators for each of the specified store groups, such as the coupon redemption rate. This allows users to compare and analyze demand indicators by region or by characteristic. This enables them to grasp the demand characteristics or the effectiveness of measures for each group from a macro perspective, which can be used to help with strategic resource allocation or marketing planning.

[0082] <Display methods for various indicators> In Figures 10 to 13 above, the output control unit 216 displays the numerical values ​​of various indicators as a list, but the various indicators may also be visualized as graphs or represented in a table format of a different form. Furthermore, although the output control unit 216 outputs predetermined indicators, it may also output the specified indicators in response to indicator specifications received from the user. The output control unit 216 may also accept indicator specifications in a selection format or as free text. When accepting free text, the information processing device 2 may identify the indicator to be calculated from the output results obtained by inputting a prompt containing free text into an artificial intelligence model such as a large-scale language model, and output the calculation results of those indicators.

[0083] <Output of metrics for multiple departments> The identification unit 211 may also identify multiple departments of a specified store in response to receiving multiple department specifications from the user. For example, the departments may be vegetables, processed foods, or dairy products. The output control unit 216 may then output supply indicators calculated for each of the specified departments. Examples of supply indicators include departmental pick-up rate or departmental stockout rate. This allows for a more detailed analysis of the store's overall supply capacity, as well as departmental analysis.

[0084] [Analysis of various indicators (S126)] The analysis unit 215 may, in the analysis step, acquire analysis information output in response to inputting input information, including multiple supply indicators or demand indicators, into the artificial intelligence model. For example, the artificial intelligence model may be a generative AI such as a large-scale language model (LLM). Note that the artificial intelligence model is not limited to LLMs and may be other machine learning models. The output control unit 216 may output this analysis information along with various indicators in the output step.

[0085] In the example in Figure 13, the analysis summary 836 displays correlations or insights that would be difficult for a human to discover, in text format, such as: "The Shonan area is overwhelmed, with almost all order slots filled on average. This means that serious opportunity costs are occurring. On the other hand, the Meguro area is at a high level of 90.0%, but still has 10% room to attract customers, indicating that the supply capacity is healthy." The analysis summary 836 may be generated per store or per month.

[0086] <Anomaly detection> The analysis unit 215 may, in the analysis step, determine whether or not it has detected an anomaly in an indicator based on an indicator corresponding to multiple target periods, i.e., time-series data, or an indicator corresponding to multiple stores, i.e., inter-store comparison data. The supply to be analyzed is mainly supply indicators, but may also be demand indicators. For example, the analysis unit 215 may output an alert indicating the possibility of fraudulent use in response to detecting a cancellation rate that deviates significantly from the average in a particular store or period. Alternatively, the analysis unit 215 may output an alert indicating the possibility of improper inventory management or operation in response to detecting a stockout rate that deviates significantly from the average in a particular store or period. This allows for the early detection of problems. Anomaly detection methods include rule-based methods that detect anomalies when time-series data or inter-store comparison data meets predetermined conditions, and AI-based methods that detect anomalies by inputting time-series data or inter-store comparison data into an artificial intelligence model. For example, the analysis unit 215 obtains a demand indicator or supply indicator for a period and a specified store specified by the user, and inputs a prompt to the artificial intelligence model that includes the indicator, a pre-set condition to be considered an anomaly (for example, the degree of deviation from the average of all stores), and a command to determine whether the indicator satisfies the condition and output it as an anomaly if it does not, thereby obtaining whether an anomaly has been detected. Alternatively, the analysis unit 215 obtains a demand indicator or supply indicator for a first period and a second period for the same store specified by the user, and inputs a prompt to the artificial intelligence model that includes the indicator and a command to determine whether the difference between the first period and the second period is within a predetermined acceptable range and output it as an anomaly if it is not, thereby obtaining whether an anomaly has been detected. Furthermore, the analysis unit 215 obtains the demand indicator or supply indicator for the first period of the first store specified by the user, and the demand indicator or supply indicator for the first period of the second store not specified by the user, and inputs a prompt to the artificial intelligence model that includes the indicator and a command to determine whether the difference obtained by comparing the indicators at the stores is within a predetermined acceptable range, and if it is not within the acceptable range, outputs it as an anomaly, thereby obtaining whether or not an anomaly has been detected.

[0087] <Goal management> The analysis unit 215 may also perform a goal management step in the analysis step, which involves comparing targets with actual results. As part of the goal management step, the registration unit 210 may first receive and store the target values ​​of the indicators to be analyzed from the user. Examples of indicators to be analyzed include sales, occupancy rate, or UPH, and their target values ​​include sales budget, target occupancy rate, or UPH target value. As part of the goal management step, the analysis unit 215 may calculate a difference indicator based on the difference between the stored target values ​​and the actual values ​​of the supply indicator or demand indicator. The difference indicator is also called the achievement rate or budget-actual difference. The difference indicator is, for example, the achievement rate based on the difference between the target sales and the actual sales for a specified period and a specified store. The output control unit 216 then outputs the difference indicator.

[0088] <Calculation of opportunity cost> Furthermore, in the analysis step, the analysis unit 215 may collect the behavioral history of multiple customers on the online supermarket application and calculate an indicator of lost sales opportunities for the store during the target period based on the behavioral history. For example, the behavioral history may include at least one of the following: page view history, page abandonment history, history of items added to the electronic cart, and order history. For example, the analysis unit 215 may collect, for multiple customers, the viewing history of pages showing order slots, the abandonment history when any of the displayed order slots were full, the history of items stored in the electronic cart, and the subsequent order history. Based on this behavioral history, the analysis unit 215 may calculate an opportunity loss index for the store during the target period (e.g., opportunity loss amount). For example, the analysis unit 215 can calculate the opportunity loss amount using a formula such as "number of visiting users in a congested state × expected CVR (Conversion Rate) × expected average purchase price". Here, a congested state may be a full state, or both a full state and a near-full state. A full state refers to a state where the order slots or delivery slots set for the target period are all booked and orders cannot be processed. The analysis unit 215 may determine a state to be full if all order slots or all delivery slots for the target period are booked. A near-full state refers to a state where there are available slots for the entire target period, but there are restrictions on making reservations. For example, if a specific time slot (such as morning flights), a specific day of the week (such as Saturdays and Sundays), or the most recent date is fully booked, or if the overall remaining slots are very limited, it will be considered a near-full-service state. The analysis unit 215 may determine that it is a near-full-service state if there are remaining slots in the order slots or delivery slots for the target period, but there are a certain number of reservations. Having a certain number of reservations means that the remaining slots are less than a predetermined number, or the remaining slot ratio (remaining slots / order slots or remaining slots / delivery slots) is less than a predetermined value. In particular, the analysis unit 215 may determine that it is a near-full-service state if there are a certain number of reservations in a predetermined time slot, a predetermined day of the week, within the most recent predetermined number of days in the target period, or a combination of these. The formula for measuring opportunity loss can be arbitrarily set; for example, it could be a formula such as "number of hours of congestion × estimated sales per hour." The output control unit 216 may output this opportunity loss index in the output step. This allows the user to quantitatively understand the sales lost due to stockouts or full delivery slots.

[0089] <Interactive Query> The analysis unit 215 may also perform processing using an interactive query method. For example, if the analysis unit 215 receives free text input from the user regarding a question, it may search for information by inputting a prompt containing the free text into the artificial intelligence model. The analysis unit 215 may then obtain analysis results by inputting a prompt containing the retrieved information into the artificial intelligence model and provide an answer to the question.

[0090] <Proposed improvement measures> Furthermore, the analysis unit 215 may propose actions to improve store operations based on the analysis results of the indicators. For example, if the analysis unit 215 calculates the sales progress rate against this month's sales budget, it may input a prompt including that indicator into the artificial intelligence model. The analysis unit 215 may then obtain actions to achieve sales targets (e.g., distributing flyers) from the artificial intelligence model and propose them to the user. For example, if the analysis unit 215 calculates the stockout rate for each store, it may input a prompt including these indicators into the artificial intelligence model. The analysis unit 215 may then obtain actions to improve the stockout rate (e.g., reviewing the product master for the Nakameguro store) from the artificial intelligence model and propose them to the user. In addition, the analysis unit 215 may obtain demand indicators and supply indicators for a specified period and a specified store, and obtain improvement proposals obtained by inputting a prompt including commands to output those indicators and improvement proposals based on those indicators into the artificial intelligence model, and output these as analysis results to the user.

[0091] 4. Variations While the present disclosure has been described above with reference to embodiments, it is not limited thereto. Various modifications to the structure and details of the present disclosure are possible, which can be understood by those skilled in the art within the scope of the invention.

[0092] In the embodiment described above, store processing plan information T1 and order processing performance information are stored in the storage unit 22, but they may also be stored in an external device accessible by the information processing device 2.

[0093] In the embodiments described above, the information processing device 2 is described as a single device, but some or all of the components of the information processing device 2 may be realized by multiple information processing devices or circuits. In this case, the multiple information processing devices or circuits may be centrally located or distributed. For example, the information processing devices or circuits may be realized in a form in which each is connected via a communication network, such as a client-server system or a cloud computing system. Furthermore, the functions of the information processing device 2 may be provided in SaaS (Software as a Service) format.

[0094] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) An information processing system comprising one or more processors and memory, The one or more processors mentioned above are capable of performing the following steps: In a specific step, the system identifies the store that will process the customer's order at the online supermarket, as specified by the user. In the first acquisition step, order processing performance information is acquired that shows the processing performance for each order processed by the designated store during the target period, where the store was the order processing center for the specified order. In the output step, the order processing performance information is used to output a supply index, which is an indicator showing the processing performance of the store for orders during the target period. Information processing system. (Note 2) The aforementioned one or more processors are capable of further executing the second acquisition step, In the second acquisition step, store processing plan information, which is pre-planned as the processing capacity of the store during the target period, is acquired. In the output step, the supply indicator is output using the order processing performance information and the store processing plan information. The information processing system described in Appendix 1. (Note 3) Display terminal for displaying the supply indicator The information processing system described in Appendix 1, including the information processing system described in Appendix 1. (Note 4) The aforementioned order processing information includes information regarding product availability or information regarding the time required for delivery. The aforementioned supply indicator is an indicator relating to the procurement or delivery performance of goods ordered by the aforementioned store during the aforementioned period. The information processing system described in Appendix 1. (Note 5) The aforementioned store processing plan information includes the number of order slots, The aforementioned 1 or more processors In the output step, the number of orders obtained from the order processing performance information of the store during the target period is used to output the occupancy rate, which represents the ratio of the number of orders to the number of order slots, as the supply indicator. The information processing system described in Appendix 2. (Note 6) The aforementioned order processing performance information includes, for each order, at least one of the number of items to be picked and the number of items to be packed, and at least one of the picking time and the packing time. The aforementioned 1 or more processors In the output step, the order processing performance information for the store during the target period is used to output the number of items picked per hour, the number of items packed per hour, or the number of pick-pack items processed per hour as the supply indicator. The information processing system described in Appendix 1. (Note 7) The aforementioned order processing information includes the number of out-of-stock items and the number of items ordered for each order. The aforementioned 1 or more processors In the output step, the stockout rate, which represents the ratio of the number of out-of-stock items to the number of ordered items, is output as the supply indicator, using the order processing performance information of the store during the target period. The information processing system described in Appendix 1. (Note 8) The aforementioned 1 or more processors In the first acquisition step described above, For each order ID corresponding to the store and period specified by the user, order element information indicating the processing history associated with that order ID is obtained. Based on the aforementioned order element information, the order processing record information corresponding to the order ID is obtained. The order element information includes at least one of the following: number of items ordered, pick start time and pick completion time, pack start time and pack completion time, number of items to be picked, number of items to be packed, receipt time, delivery start time, delivery completion time, out-of-stock information, and cancellation information. The information processing system described in Appendix 1. (Note 9) The aforementioned store processing plan information includes at least one of the following: the number of order slots and the number of delivery slots. The information processing system described in Appendix 2. (Note 10) The aforementioned 1 or more processors In the aforementioned specific step, upon receiving a designation from the user for a store group including multiple stores, the multiple stores included in the store group are identified as the designated stores. Output the supply indicators for the aforementioned multiple stores. The information processing system described in Appendix 1. (Note 11) The aforementioned 1 or more processors In the output step, the display of the supply indicator for stores other than the store to which the user is related is restricted. The information processing system described in Appendix 1. (Note 12) The aforementioned 1 or more processors In the output step, a demand indicator, which is an indicator showing the demand of the store based on the order processing performance information, is output in addition to the supply indicator. The information processing system described in Appendix 1. (Note 13) The aforementioned one or more processors are further capable of performing a storage step and a calculation step. In the storage step, upon receiving a calculation formula including parameters from the user, the calculation formula is stored as the calculation formula for the supply index. In the calculation step, The parameters are obtained from the order processing performance information, The supply index is calculated by applying the acquired parameters to the calculation formula. The information processing system described in Appendix 1. (Note 14) The aforementioned one or more processors are capable of further executing the goal management step, In the aforementioned goal management step, The user inputs the target value, Output a difference index based on the difference between the target value and the supply index. The information processing system described in Appendix 1. (Note 15) The aforementioned one or more processors are capable of performing further analysis steps. In the analysis step, the analysis information output in response to inputting the input information, which includes multiple supply indicators, into the artificial intelligence model is obtained. In the output step, the analysis information is output. The information processing system described in Appendix 1. (Note 16) The aforementioned one or more processors are capable of performing further analysis steps. In the analysis step described above, it is determined whether or not an anomaly in the supply indicator has been detected based on supply indicators corresponding to multiple target periods or supply indicators corresponding to multiple stores. The information processing system described in Appendix 1. (Note 17) The aforementioned 1 or more processors In the aforementioned specific step, in response to receiving the designation of multiple departments from the user, the multiple departments of the designated store are identified. In the output step, the supply indicator is output for each of the multiple departments. The information processing system described in Appendix 1. (Note 18) The aforementioned one or more processors are capable of performing further analysis steps. In the aforementioned analysis step, We collect the browsing history of multiple customers on the online supermarket application, Based on the aforementioned behavioral history, the opportunity loss index for the store during the target period is calculated. In the output step, the opportunity loss index is output. The information processing system described in Appendix 1. (Note 19) The information processing system performs each of the steps described in any one of the appendices 1 to 18. Information processing methods. (Note 20) A program for causing a computer having one or more processors and memory to perform each of the steps described in any one of the appendices 1 to 18. [Explanation of Symbols]

[0095] 1. Information Processing System 2. Information Processing Device 3. Headquarters terminal 4 Store terminals 5 Customer terminals 21 Control Unit 22 Memory section 23 Communications Department 26 Communications Bus 31 Control Unit 32 Storage section 33 Communications Department 34 Input section 35 Display section 36 Communications Bus 51 Control Unit 52 Storage section 53 Communications Department 54 Input section 55 Display section 56 Communications Bus 80 display screen 81 Display screen 82 Display screen 83 Display screen 210 Registration Department 211 Specific section 212 First acquisition part 213 Second Acquisition Department 214 Calculation Unit 215 Analysis Department 216 Output Control Unit 217 Display Control Unit 218 Data Output Control Unit T1 Store Processing Plan Information T10 Store ID T11 Day T12 time zone T13 Number of order slots T14 Number of delivery slots T2 Calculation Formula Master T21 indicator name T22 Order Processing Performance Information T23 Store Processing Plan Information T24 formula NW Network

Claims

1. An information processing system comprising one or more processors and memory, The one or more processors described above are capable of performing the following steps: In a specific step, the system identifies the store that will process the customer's order at the online supermarket, as specified by the user. In the first acquisition step, order processing performance information is acquired that shows the processing performance for each order processed by the designated store during the target period, for orders where the designated store was the order processing center. In the output step, the order processing performance information is used to output a supply index, which is an indicator showing the processing performance of the store for orders during the target period. Information processing system.

2. The one or more processors mentioned above are capable of further executing the second acquisition step, In the second acquisition step, store processing plan information is acquired, which is predetermined as the processing capacity of the store during the target period. In the output step, the supply indicator is output using the order processing performance information and the store processing plan information. The information processing system according to claim 1.

3. Display terminal for displaying the supply indicator The information processing system according to claim 1, including the following:

4. The aforementioned order processing information includes information regarding product availability or information regarding the time required for delivery. The aforementioned supply indicator is an indicator relating to the procurement or delivery performance of goods ordered by the aforementioned store during the aforementioned period. The information processing system according to claim 1.

5. The aforementioned store processing plan information includes the number of order slots, The one or more processors mentioned above are: In the output step, the number of orders obtained from the order processing performance information of the store during the target period is used to output the occupancy rate, which represents the ratio of the number of orders to the number of order slots, as the supply indicator. The information processing system according to claim 2.

6. The aforementioned order processing performance information includes, for each order, at least one of the number of items to be picked and the number of items to be packed, and at least one of the picking time and the packing time. The one or more processors mentioned above are: In the output step, the order processing performance information for the store during the target period is used to output the number of items picked per hour, the number of items packed per hour, or the number of pick-pack items packed per hour as the supply indicator. The information processing system according to claim 1.

7. The aforementioned order processing information includes the number of out-of-stock items and the number of items ordered for each order. The one or more processors mentioned above are: In the output step, the stockout rate, which represents the ratio of the number of out-of-stock items to the number of ordered items, is output as the supply indicator, using the order processing performance information of the store during the target period. The information processing system according to claim 1.

8. The one or more processors mentioned above are: In the first acquisition step described above, For each order ID corresponding to the store and period specified by the user, obtain order element information indicating the processing history associated with that order ID. Based on the aforementioned order element information, the order processing record information corresponding to the order ID is obtained. The order element information includes at least one of the following: number of items ordered, pick start time and pick completion time, pack start time and pack completion time, number of items to be picked, number of items to be packed, receipt time, delivery start time, delivery completion time, out-of-stock information, and cancellation information. The information processing system according to claim 1.

9. The aforementioned store processing plan information includes at least one of the following: the number of order slots and the number of delivery slots. The information processing system according to claim 2.

10. The one or more processors mentioned above are: In the aforementioned specific step, upon receiving a designation from the user for a store group including multiple stores, the multiple stores included in the store group are identified as the designated stores. Output the supply indicators for the aforementioned multiple stores. The information processing system according to claim 1.

11. The one or more processors mentioned above are: In the output step, the display of the supply indicator for stores other than the store to which the user is related is restricted. The information processing system according to claim 1.

12. The one or more processors mentioned above are: In the output step, a demand indicator, which is an indicator showing the demand of the store based on the order processing performance information, is output in addition to the supply indicator. The information processing system according to claim 1.

13. The one or more processors described above are further capable of performing a storage step and a calculation step. In the storage step, upon receiving a calculation formula including parameters from the user, the calculation formula is stored as the calculation formula for the supply index. In the calculation step, The parameters are obtained from the order processing performance information, The supply index is calculated by applying the acquired parameters to the calculation formula. The information processing system according to claim 1.

14. The one or more processors described above are capable of further executing the goal management step, In the aforementioned goal management step, The user inputs the target value, Output a difference index based on the difference between the target value and the supply index. The information processing system according to claim 1.

15. The aforementioned one or more processors are capable of performing further analysis steps. In the analysis step, the analysis information output in response to inputting the input information, which includes multiple supply indicators, into the artificial intelligence model is obtained. In the output step, the analysis information is output. The information processing system according to claim 1.

16. The aforementioned one or more processors are capable of performing further analysis steps. In the analysis step described above, it is determined whether or not an anomaly in the supply indicator has been detected based on supply indicators corresponding to multiple target periods or supply indicators corresponding to multiple stores. The information processing system according to claim 1.

17. The one or more processors mentioned above are: In the aforementioned specific step, in response to receiving the designation of multiple departments from the user, the multiple departments of the designated store are identified. In the output step, the supply indicator is output for each of the multiple departments. The information processing system according to claim 1.

18. The aforementioned one or more processors are capable of performing further analysis steps. In the aforementioned analysis step, We collect the browsing history of multiple customers on the online supermarket application, Based on the aforementioned behavioral history, the opportunity loss index for the store during the target period is calculated. In the output step, the opportunity loss index is output. The information processing system according to claim 1.

19. The information processing system performs each step described in any one of claims 1 to 18. Information processing methods.

20. A program for causing a computer, which comprises one or more processors and memory, to perform each of the steps described in any one of claims 1 to 18.

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