Information processing system, information processing method, and information processing program

Abstract

This technology provides support for analyzing errors in demand forecasting for each product. [Solution] The information processing system comprises: an indicator acquisition unit that acquires product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company; an internal information acquisition unit that acquires internal company information about products within the target company; an external information acquisition unit that acquires external company information about products outside the target company; and an interpretation example generation unit that uses a large-scale language model to generate sentences that include interpretation examples based on internal and external company information as examples of interpretations of product-specific indicators.

Description

Technical Field

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

Background Art

[0002] In recent years, it has become important to predict the demand for products. For example, Patent Document 1 describes a technique for predicting the demand for a component using an analysis model constructed based on past operation hours data and operation time data of a device having the component to be predicted and the past number of issued records of the component.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Here, errors may occur between demand predictions and actual results due to various factors. Therefore, it is important to analyze the errors in demand predictions for each product. However, Patent Document 1 does not describe analyzing the errors in demand predictions. Also, there is a problem that specialized knowledge is required for such analysis of errors in demand predictions. Further, even when having specialized knowledge, there are problems such as the possibility of missing information to be considered, time-consuming information collection and organization, and insufficient consideration time in such analysis of errors in demand predictions. Therefore, a technique for supporting the analysis of errors in demand predictions for each product is required.

[0005] The present disclosure has been made in view of the above problems, and an exemplary object thereof is to provide a technique for supporting the analysis of errors in demand predictions for each product.

Means for Solving the Problems

[0006] An information processing system relating to an illustrative aspect of this disclosure comprises: an indicator acquisition means for acquiring product-specific indicators for managing the accuracy of demand forecasts for products handled by a target company; an internal information acquisition means for acquiring internal company information about the products within the target company; an external information acquisition means for acquiring external company information about the products outside the target company; and an interpretation example generation means that uses a large-scale language model to generate sentences that include interpretation examples based on the internal company information and the external company information as interpretation examples of the product-specific indicators.

[0007] An information processing method relating to an illustrative aspect of this disclosure includes: an indicator acquisition process in which at least one processor acquires product-specific indicators for managing the accuracy of demand forecasts for products handled by a target company; an internal information acquisition process in which the at least one processor acquires internal company information about the products within the target company; an external information acquisition process in which the at least one processor acquires external company information about the products outside the target company; and an interpretation example generation process in which the at least one processor uses a large-scale language model to generate a document that includes an interpretation example of the product-specific indicators, which includes an interpretation example based on the internal company information and the external company information.

[0008] An information processing program relating to an exemplary aspect of this disclosure causes at least one processor to execute: an indicator acquisition process for acquiring product-specific indicators for managing the accuracy of demand forecasts for products handled by a target company; an internal information acquisition process for acquiring internal company information about the products within the target company; an external information acquisition process for acquiring external company information about the products outside the target company; and an interpretation example generation process that uses a large-scale language model to generate sentences that include interpretation examples based on the internal company information and the external company information as interpretation examples for the product-specific indicators. [Effects of the Invention]

[0009] One illustrative aspect of this disclosure is that it can provide a technology that supports the analysis of errors in demand forecasting for each product. [Brief explanation of the drawing]

[0010] [Figure 1] This is a block diagram showing the configuration of the information processing system related to this disclosure. [Figure 2] This is a flowchart showing the flow of the information processing method related to this disclosure. [Figure 3] This is a block diagram showing the configuration of the information processing system related to this disclosure. [Figure 4] This is a block diagram showing the configuration of the information processing device related to this disclosure. [Figure 5] This block diagram shows the configuration of the user terminal related to this disclosure. [Figure 6] This is a flowchart showing the flow of the information processing method related to this disclosure. [Figure 7] This flowchart shows the detailed flow of the alert screen generation process related to this disclosure. [Figure 8] This figure shows an example of an alert screen related to this disclosure. [Figure 9] This flowchart shows the detailed flow of the product analysis screen generation process related to this disclosure. [Figure 10] This figure shows an example of the product-specific analysis screen related to this disclosure. [Figure 11] This block diagram shows the hardware configuration of the computer that functions as each device related to this disclosure. [Modes for carrying out the invention]

[0011] The following are examples of embodiments of the present invention. However, the present invention is not limited to the exemplary embodiments shown below, and various modifications are possible within the scope of the claims. For example, embodiments obtained by appropriately combining some or all of the technologies (things or methods) employed in each of the exemplary embodiments shown below may also be included in the scope of the present invention. Furthermore, embodiments obtained by appropriately omitting some of the technologies employed in each of the exemplary embodiments shown below may also be included in the scope of the present invention. In addition, the effects mentioned in each of the exemplary embodiments shown below are examples of effects that can be expected in that exemplary embodiment and do not define the scope of the present invention. That is, embodiments that do not produce the effects mentioned in each of the exemplary embodiments shown below may also be included in the scope of the present invention.

[0012] [First Exemplary Embodiment] A first exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. This exemplary embodiment is the basic form for each of the exemplary embodiments described later. The scope of application of each technology adopted in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technology adopted in this exemplary embodiment can also be adopted in other exemplary embodiments included in this disclosure, to the extent that no particular technical problems occur. Furthermore, each technology shown in the drawings referenced to explain this exemplary embodiment can also be adopted in other exemplary embodiments included in this disclosure, to the extent that no particular technical problems occur.

[0013] (Configuration of Information Processing System 1) The configuration of the information processing system 1 will be described with reference to FIG. 1. FIG. 1 is a block diagram showing the configuration of the information processing system 1. As shown in FIG. 1, the information processing system 1 includes an index acquisition unit 11, an in-company information acquisition unit 12, an out-company information acquisition unit 13, and an interpretation example generation unit 14. The index acquisition unit 11 is an example of a configuration that realizes index acquisition means. The in-company information acquisition unit 12 is an example of a configuration that realizes in-company information acquisition means. The out-company information acquisition unit 13 is an example of a configuration that realizes out-company information acquisition means. The interpretation example generation unit 14 is an example of a configuration that realizes interpretation example generation means. Note that the information processing system 1 may be constituted by a single device or may be constituted by a plurality of devices.

[0014] The index acquisition unit 11 acquires item-specific indexes for managing the accuracy of demand prediction regarding items handled by the target company. The target company is a company that handles items and has introduced the information processing system 1 to manage the accuracy of demand prediction for items by item. The target company may be, for example, a manufacturer that manufactures items, a retailer that sells items to consumers, or an intermediate distributor (so-called wholesaler) that mediates items between manufacturers and retailers, but is not limited thereto.

[0015] Demand prediction is to predict the demand for items. Demand prediction may be performed by a computer using any technique or may be performed manually by an expert. The accuracy of demand prediction refers to how close the demand prediction value indicating the result of demand prediction is to the demand actual value indicating the actual demand. The accuracy of demand prediction is higher as the error of demand prediction is smaller. The error of demand prediction is the difference between the demand prediction value and the demand actual value.

[0016] The item-specific index for managing the accuracy of demand prediction is an index that can be calculated based on the demand prediction value and / or demand actual value regarding the item. The item-specific index may include, for example, an index indicating the error rate of demand prediction regarding the item, an index indicating the trend of the error of demand prediction regarding the item, an index regarding the channel where the demand for the item occurs, etc., but is not limited thereto.

[0017] The in-company information acquisition unit 12 acquires in-company information regarding products within the target company. For example, the in-company information may include information regarding activities performed by the target company regarding the product, information regarding other products in the same classification as the product, and the like.

[0018] The out-company information acquisition unit 13 acquires out-company information regarding products outside the target company. For example, the out-company information may include general information that does not depend on the target company regarding the product.

[0019] The interpretation example generation unit 14 uses a large language model to generate a sentence including an interpretation example based on in-company information and out-company information as an interpretation example of an index for each product. For example, the interpretation example generation unit 14 may generate a prompt including an index for each product, in-company information, and out-company information and input it into the large language model to cause the large language model to output the interpretation example. Further, for example, the interpretation example generation unit 14 may additionally train the large language model using the in-company information and the out-company information. In this case, the interpretation example generation unit 14 may input a prompt including an index for each product to the additionally trained large language model to cause the large language model to output the interpretation example. Further, for example, the interpretation example generation unit 14 may add the in-company information and the out-company information to a knowledge base. In this case, the interpretation example generation unit 14 may search the knowledge base for information regarding the index for each product, and input a prompt including the search result and the index for each product to the large language model to cause the large language model to output the interpretation example.

[0020] (Effect of the information processing system 1) As described above, the information processing system 1 employs a configuration that includes: an indicator acquisition unit 11 that acquires product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company; an internal information acquisition unit 12 that acquires internal company information about products within the target company; an external information acquisition unit 13 that acquires external company information about products outside the target company; and an interpretation example generation unit 14 that uses a large-scale language model to generate sentences that include interpretation examples based on internal and external company information as examples of interpretations of product-specific indicators. Therefore, users who refer to the interpretation examples output from the information processing system 1 can learn interpretation examples that take into account internal and external company information for product-specific indicators for managing the accuracy of demand forecasts for the relevant product. As a result, the information processing system 1 can support the analysis of errors in demand forecasts on a product-by-product basis.

[0021] (Information processing method S1 flow) The flow of the information processing method S1 will be explained with reference to Figure 2. For example, if the information processing system 1 described above is equipped with at least one processor, that at least one processor may execute the information processing method S1. Figure 2 is a flowchart showing the flow of the information processing method S1. As shown in Figure 2, the information processing method S1 includes an indicator acquisition process S11, an in-company information acquisition process S12, an out-of-company information acquisition process S13, and an interpretation example generation process S14.

[0022] In the indicator acquisition process S11, at least one processor (for example, the indicator acquisition unit 11) acquires product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company. The details of the indicator acquisition process S11 have been explained as described for the indicator acquisition unit 11, so a detailed explanation will not be repeated.

[0023] In the internal company information acquisition process S12, at least one processor (for example, the internal company information acquisition unit 12) acquires internal company information regarding products within the target company. The details of the internal company information acquisition process S12 have been explained as described for the internal company information acquisition unit 12, so a detailed explanation will not be repeated.

[0024] In the external information acquisition process S13, at least one processor (for example, the external information acquisition unit 13) acquires external information about products outside the target company. The details of the external information acquisition process S13 are as described for the external information acquisition unit 13, so a detailed explanation will not be repeated.

[0025] In the interpretation example generation process S14, at least one processor (for example, the interpretation example generation unit 14) uses a large-scale language model to generate text that includes interpretation examples based on the internal company information and the external company information, as interpretation examples of product-specific indicators acquired by the indicator acquisition process S11. Details of the interpretation example generation process S14 have been described as described for the interpretation example generation unit 14, so a detailed explanation will not be repeated.

[0026] (Effects of information processing method S1) As described above, the information processing method S1 employs a configuration in which at least one processor performs an indicator acquisition process S11 to acquire product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company; at least one processor performs an internal information acquisition process S12 to acquire internal company information about products within the target company; at least one processor performs an external information acquisition process S13 to acquire external company information about products outside the target company; and at least one processor performs an interpretation example generation process S14 using a large-scale language model to generate text that includes interpretation examples based on internal and external company information as examples of interpretations of product-specific indicators. Therefore, the same effects as the information processing system 1 can be obtained with the information processing method S1.

[0027] [Second exemplary embodiment] A second exemplary embodiment, which is an example of an embodiment of the present invention, will be described in detail with reference to the drawings. Components having the same function as those described in the above-described exemplary embodiment are denoted by the same reference numerals, and their descriptions are omitted as appropriate. The scope of application of each technology adopted in this exemplary embodiment is not limited to this exemplary embodiment. That is, each technology adopted in this exemplary embodiment can also be adopted in other exemplary embodiments included in this disclosure, to the extent that no particular technical problems arise. Furthermore, each technology shown in the drawings referenced to describe this exemplary embodiment can also be adopted in other exemplary embodiments included in this disclosure, to the extent that no particular technical problems arise.

[0028] (Configuration of Information Processing System 1A) Figure 3 is a block diagram showing the configuration of information processing system 1A. Information processing system 1A is a system that supports the analysis of errors in demand forecasting. As shown in Figure 3, information processing system 1A comprises an information processing device 10 and a user terminal 20. The information processing device 10 and the user terminal 20 are connected to each other via a communication line NW. The specific configuration of the communication line NW is not limited to this embodiment, but examples of communication lines NW include wireless LAN (Local Area Network), wired LAN, WAN (Wide Area Network), public telephone network, mobile data communication network, or a combination thereof.

[0029] The information processing device 10 functions as a server that provides a service for analyzing errors in demand forecasting on a product-by-product basis within the target company. For example, the information processing device 10 may be a stationary computer, but is not limited to these. The user terminal 20 is a terminal used by users of the above service within the target company. The user terminal 20 may be, for example, a notebook personal computer, a smartphone, a tablet, etc., but is not limited to these. Furthermore, the user using the user terminal 20 may be, for example, a user who manages products. Furthermore, such a user may have limited knowledge regarding demand forecasting. Furthermore, such a user may have knowledge regarding demand forecasting.

[0030] (Configuration of the information processing device 10) Figure 4 is a block diagram showing the configuration of the information processing device 10. As shown in Figure 4, the information processing device 10 comprises a control unit 110, a storage unit 120, and a communication unit 130. The control unit 110 controls all parts of the information processing device 10. The storage unit 120 stores various information that the control unit 110 refers to. The communication unit 130 communicates with external devices (for example, a user terminal 20, etc.) via a communication line NW. The communication unit 130 transmits data supplied from the control unit 110 to other devices and supplies data received from other devices to the control unit 110.

[0031] (Functional block included in the control unit 110) The control unit 110 includes, in addition to the indicator acquisition unit 11, the in-company information acquisition unit 12, the out-of-company information acquisition unit 13, and the interpretation example generation unit 14 provided by the information processing system 1, a first display control unit 15 and a second display control unit 16. The first display control unit 15 is an example of a configuration that realizes the first display control means. The second display control unit 16 is an example of a configuration that realizes the second display control means.

[0032] The indicator acquisition unit 11 is configured in the same way as the functional block of the same name in the information processing system 1, and is configured as follows: The indicator acquisition unit 11 acquires product-specific indicators for each of the multiple products. For example, the indicator acquisition unit 11 may acquire product-specific indicators for each of the multiple products included in a certain segment. A segment is a division in which multiple products are classified from a predetermined perspective, and may be, but is not limited to, brand, distribution channel, or region where they are sold. Detailed specific examples of the indicators acquired by the indicator acquisition unit 11 in this exemplary embodiment will be described later.

[0033] The internal company information acquisition unit 12 and the external company information acquisition unit 13 are configured in the same way as the functional blocks of the same name provided in the information processing system 1. Detailed specific examples of the information acquired by the internal company information acquisition unit 12 and the external company information acquisition unit 13 in this exemplary embodiment will be described later.

[0034] The interpretation example generation unit 14 is configured in the same way as the interpretation example generation unit 14 provided in the information processing system 1, and is configured as follows. For example, the interpretation example generated by the interpretation example generation unit 14 may include the situation of the error in the demand forecast for a certain product, factors based on internal and external company information regarding the error in the demand forecast, and some or all of the suggestions for dealing with the error in the demand forecast. For example, "situation of the error in the demand forecast" may include information such as the magnitude of the error, the tendency of the error such as whether it is an over-forecast or under-forecast, and changes therein. Also, "factors based on internal and external company information regarding the error in the demand forecast" may include internal or external events that may be factors causing errors in the demand forecast. Also, "suggestions for dealing with the error in the demand forecast" may include examples of actions that the user can take in response to the error.

[0035] Furthermore, for example, the interpretation examples generated by the interpretation example generation unit 14 may include interpretation examples of product-specific indicators for each of the multiple products that satisfy predetermined alert conditions. The alert conditions may be, but are not limited to, product-specific indicators exceeding a threshold (or being above a threshold), falling below a threshold (or being below a threshold), or combinations thereof.

[0036] The first display control unit 15 displays a first screen, which includes product-specific indicators for each of the multiple products, and an example of how to interpret the product-specific indicators that meet the alert conditions, on the display unit 250 of the user terminal 20, which will be described later. The display unit 250 of the user terminal 20 is an example of a display device to which the screen from the first display control unit 15 is displayed.

[0037] For example, the first screen may include product-specific metrics for each of multiple products, including metrics that meet the alert conditions and product-specific metrics that do not meet the alert conditions. Furthermore, metrics that meet the alert conditions and metrics that do not meet the alert conditions may be displayed in different ways. Different display ways may include, but are not limited to, differences in text color, background color, font, font size, text formatting, etc. It is also desirable that the display way for metrics that meet the alert conditions is more emphasized than the display way for metrics that do not meet the alert conditions. When product-specific metrics are displayed in a way that meets the alert conditions, this will also be referred to as an alert being output for the relevant product. An example of how to interpret a product-specific metric for which an alert has been output will also be referred to simply as an example of how to interpret the alert. By displaying both the alert and the example of how to interpret the alert, even users with limited knowledge of demand forecasting can recognize products for which an alert has been output as products for which the accuracy of the demand forecast is poor and which may require revision. Furthermore, for users with expertise in demand forecasting, this system can help reduce omissions or errors in the information they need to consider to identify products that may require revision of their demand forecasts, shorten the time spent on information gathering and organization, and increase the time available for analysis.

[0038] The second display control unit 16 displays a second screen on the display unit 250 of the user terminal 20, which includes product-specific indicators for the selected product and examples of interpretations of those product-specific indicators, in response to an operation to select one of the multiple products included in the first screen. For example, the examples of interpretations included in the second screen may include, as described above, the situation of the error in the demand forecast for that product, factors based on internal and external company information regarding the error in the demand forecast, and some or all of the proposed responses to the error in the demand forecast. For example, if the indicator acquisition unit 11 acquires a time series of product-specific indicators for a predetermined period, the second display control unit 16 may display a second screen on the display unit 250 that includes a graph plotting the time series of product-specific indicators for the selected product and examples of interpretations. For example, a user can refer to the examples of interpretations on the alert screen and select the product for which an alert has been output, thereby confirming the product-specific indicators for that product on the second screen for that product. By displaying both product-specific indicators and examples of interpretations of those product-specific indicators, it is possible to support users with limited knowledge of demand forecasting in analyzing the error in the demand forecast for the relevant product. Furthermore, for users with expertise in demand forecasting, it is possible to provide support such as reducing omissions or errors in the information that should be considered when analyzing the error in demand forecasts for the relevant product, shortening the time required for information gathering and organization, and increasing the time available for analysis.

[0039] (Information stored in memory unit 120) The memory unit 120 stores various types of information referenced by the control unit 110. Examples of such information include demand forecast values, actual demand values, indicators, alert conditions, internal company information, external company information, and large-scale language models. Some or all of this information may be stored in an external device different from the information processing device 10.

[0040] (Demand forecast value) The demand forecast value represents the result of a demand forecast for the products handled by the target company. For example, the demand forecast value is a value that represents the demand expected in a future unit period, and may be the expected sales amount, the expected number of units sold, etc. If the unit period is, for example, one week, the storage unit 120 may store, for example, product identification information, a future period (for example, the second week of April 2024), and the demand forecast value for that period (for example, the expected number of units sold of 120) in association with each other. Note that the unit period is not limited to one week, but may be one day, one month, one quarter, one year, etc. The demand forecast value may be added to the storage unit 120 each time a demand forecast is made for a new future period.

[0041] (Actual demand figures) The actual demand value indicates the past demand for the products handled by the target company. For example, the actual demand value is a value representing demand in a past unit period, and may be, for example, the actual sales amount, the actual number of units sold, etc. If the unit period is, for example, one week, the storage unit 120 may store, for example, product identification information, a past period (for example, the first week of April 2024), and the actual demand value for that period (for example, the actual number of units sold of 100) in association with each other. Note that the unit period is not limited to one week, but may be, for example, one day, one month, one quarter, one year, etc. The actual demand value may be added to the storage unit 120 each time an actual demand value for a new past period is obtained.

[0042] (Indicators by product) Product-specific metrics are indicators used to manage the accuracy of demand forecasts for each product handled by the target company. These product-specific metrics may include, for example, MAPE (Mean Absolute Percentage Error) impact, tracking signals, channel information, landing deviation rate, historical error rate, and some or all of the historical demand comparison. However, the metrics are not limited to these.

[0043] (MAPE Impact) The MAPE impact is an index that weights the error rate of demand forecasts for a given product according to its importance. For example, the MAPE impact is calculated using the following formula (1).

[0044] MAPE impact = [absolute value of the error rate of the product demand forecast] × [product weight] ... (1) Here, the "demand forecast error rate" is calculated using the following equation (2).

[0045] The error rate of the demand forecast = [Difference between the forecasted demand and the actual demand] / [Actual demand] ... (2) Here, " / " indicates division. Also, for example, the "weight of a product" may be defined so that it increases with the sales volume of the product. In this case, the larger the sales volume and the greater the error in demand forecasting, the larger the MAPE impact value will be. In other words, products with a large MAPE impact are those with large demand forecasting errors and large sales volumes. MAPE impact allows us to identify products that should be prioritized for demand forecast revision.

[0046] (Tracking signal) The tracking signal is an indicator that shows the degree to which the error in the demand forecast for a given product continues to be biased in the same direction. Here, the error in the demand forecast is biased in the positive direction when the forecast value is higher than the actual demand value, and in the negative direction when it is lower. "The error continues to be biased in the same direction" means that the error continues to be biased in either the positive or negative direction. For example, the tracking signal is calculated using the following formula (3).

[0047] Tracking signal = [product f-Bias] / [MAD]...(3) Here, MAD represents the mean absolute deviation of the error for the product in question. f-Bias represents the cumulative error of the demand forecast for the product in question, and is calculated, for example, by the following equation (4).

[0048] f-Bias = ([Forecasted Demand] - [Actual Demand]) summation... (4) Here, the sum refers to the sum over a predetermined unit period.

[0049] A positive tracking signal indicates that a larger absolute value means the demand forecast error has been biased in the positive direction for a longer period, increasing the risk of excess inventory for the product in question. Conversely, a negative tracking signal indicates that a larger absolute value means the demand forecast has been biased in the negative direction for a longer period, increasing the risk of stockouts for the product in question. By checking the tracking signal, for example, the person in charge of managing the product in question can make early adjustments to the demand forecast for that product.

[0050] (Channel Information) Channel information is information related to the channels of the product in question. A channel is the distribution route of the product, and specific examples include, but are not limited to, drugstores and department stores. The channels of the product in question can affect the accuracy of demand forecasting. Therefore, channel information can serve as an indicator for managing the accuracy of demand forecasting. Channel information may include, for example, the channel composition ratio that constitutes the actual demand for the product in question (e.g., shipment figures). Channel information may also include, for example, the year-on-year change in actual demand for the product in question by channel. However, channel information is not limited to these examples.

[0051] (Landing deviation rate) The deviation rate indicates the degree to which the predicted final value deviates from the predicted demand value. The predicted final value is, for example, the result of predicting the total demand for the current unit period (for example, this week) up to the end of that unit period (for example, this weekend), based on the actual demand value up to the middle of that unit period. In contrast, the predicted demand value is the result of predicting the demand for the current unit period before it began (or without referring to the actual demand value up to the middle of the current unit period).

[0052] (Past error rate) The historical error rate indicates the error rate of demand forecasts in the past. As mentioned above, the error rate of demand forecasts is calculated, for example, by formula (2) above. If the unit period for calculating the historical error rate is weekly, an example of the historical error rate may be the error rate of the demand forecast for the previous week (hereinafter also referred to as the previous week's error rate).

[0053] (Demand performance compared to past records) The year-on-year change in actual demand is the ratio of the most recent actual demand to the actual demand of the past. The most recent actual demand may be, for example, the moving average of actual demand over a specified period. The year-on-year change in actual demand may also be calculated for each type of distribution channel through which the shipped goods pass. The type of distribution channel may be, for example, if the target company is a manufacturer, the intermediaries, retailers, etc., through which the shipped goods pass. For example, if the comparison period is one year ago, an example of the year-on-year change in actual demand may include either or both of the moving average year-on-year change in wholesale shipments and the moving average year-on-year change in POS (Point of Sale) sales. The moving average year-on-year change in wholesale shipments is the year-on-year change in the moving average of actual shipments from intermediaries to retailers. The moving average year-on-year change in POS sales is the year-on-year change in the moving average of actual sales from retailers to consumers. However, the year-on-year change in actual demand is not limited to the examples described above.

[0054] (Alert conditions) Alert conditions are conditions related to product-specific metrics and are set to output alerts for products where demand forecasts may need to be revised. For example, alert conditions may be set for each type of multiple product-specific metrics. Alternatively, for example, an alert condition may be when the relevant product-specific metric (or its absolute value) exceeds (or falls below) a threshold. Specific examples of alerts output when each type of alert condition is met will be described later.

[0055] (Internal information) As mentioned above, internal company information is information obtained within the target company and may be information specific to that company. For example, internal company information may include either or both of the following: promotional information within the target company related to the product, and sales information for other products within the target company in the same category as the product. Furthermore, internal company information may include some or all of the product information, demand forecasts, actual demand, and actual distribution data related to the product.

[0056] Information indicating a promotion may include, for example, activities to promote the sale of a product, the period during which such activities are conducted, etc. Product information may include the price, attributes, etc. Product demand forecasts or actual demand values ​​may include information for retail sales, wholesale shipments, and manufacturer shipments. Product distribution actual values ​​may include the number of distribution destinations (e.g., number of stores) to which the product was distributed. However, internal company information is not limited to the examples given above. Furthermore, internal company information may be stored for each of multiple products.

[0057] Internal company information may be updated with the latest information at predetermined intervals, or new information may be added. Furthermore, internal company information may be information in which items and values ​​representing the various types of information described above are associated, or it may be a document consisting of natural language text that may contain the various types of information described above (for example, an internal company journal).

[0058] (Non-company information) External information, as described above, is information obtained from outside the target company and may be general information not specific to the target company. For example, external information may include one or both of the following: new product launches by competing brands, information on the trends of those competing brands, and market trend information in the market to which the product belongs. External information may also include some or all of the changes in regulations in the industry related to the product and information indicating the external environment of the industry. For example, changes in industry regulations may include price revisions. For example, information indicating the external environment of the industry may include external variables such as weather information, exchange rates, and the number of foreign visitors to Japan. However, external information is not limited to the examples given above.

[0059] External company information may be updated with the latest information at predetermined intervals, or new information may be added. Furthermore, external company information may be information in which items and values ​​indicating the various types of information described above are associated, or it may be a document consisting of natural language text that may contain the various types of information described above (for example, an industry journal, a journal on the external environment, etc.).

[0060] (Large-scale language models) A large-scale language model is a deep learning model designed to perform natural language processing tasks. For example, a large-scale language model may be a pre-trained general-purpose large-scale language model, or it may be a fine-tuned version of such a general-purpose large-scale language model. For example, a large-scale language model may be a model that performs a text generation task, taking a natural language sentence as input and outputting a generated natural language sentence.

[0061] (Configuration of user terminal 20) Figure 5 is a block diagram showing the configuration of the user terminal 20. As shown in Figure 5, the user terminal 20 comprises a control unit 210, a storage unit 220, a communication unit 230, an input unit 240, and a display unit 250. The control unit 210 controls all parts of the user terminal 20. The storage unit 220 stores various information that the control unit 210 refers to. The communication unit 230 communicates with external devices (e.g., an information processing device 10, etc.) of the user terminal 20 via a communication line NW. The communication unit 230 transmits data supplied from the control unit 210 to other devices and supplies data received from other devices to the control unit 210.

[0062] The input unit 240 is configured to receive input from the user terminal 20, and may include, for example, input devices such as a keyboard, mouse, touch panel, camera, and microphone. The display unit 250 is configured to display the screen output from the user terminal 20, and may include, for example, a display. The input unit 240 and the display unit 250 may also be integrally formed as a touch panel or the like. Furthermore, one or both of the input unit 240 and the display unit 250 are not limited to being built into the user terminal 20, but may also be connected externally via an interface such as USB (Universal Serial Bus).

[0063] The control unit 210 includes a UI (User Interface) unit 21. The UI unit 21 provides a user interface for using a service that analyzes errors in demand forecasting. For example, the UI unit 21 receives user operations for using the service and transmits them to the information processing device 10. Also, when the UI unit 21 receives a screen related to the service from the information processing device 10, it displays the received screen on the display unit 250. For example, the UI unit 21 may be implemented by executing an application program for using the service, which is stored in the storage unit 220. The application program may be an application dedicated to the service. Also, if the service is implemented as a web service, the application program may be a general-purpose web browser.

[0064] (Information processing method S1A flow) The information processing system 1A, configured as described above, executes the information processing method S1A. Figure 6 is a flowchart showing the flow of the information processing method S1A. As shown in Figure 6, the information processing method S1A includes steps S101 to S106. In the following description, an example of the first screen will be referred to as the "alert screen," and an example of the second screen will be referred to as the "product-specific analysis screen." However, the names of the first and second screens are not limited to these.

[0065] In step S101, the UI unit 21 of the user terminal 20 receives an operation to instruct the display of an alert screen. For example, the user's operation may be, but is not limited to, an operation on the menu item "Display Alert Screen" on a menu screen (not shown) displayed on the display unit 250. The user's operation may further include an operation to specify multiple products to be targeted on the alert screen. Multiple products may be specified, for example, as a predetermined segment. A segment is a classification of multiple products based on a predetermined perspective, and may be, but is not limited to, brands, distribution channels, sales regions, etc. The user's operation may further include an operation to specify a predetermined past period to be targeted on the alert screen (for example, a predetermined year, a predetermined month, a start date and end date of the period, etc.). The UI unit 21 transmits the information indicated by the received operation (for example, information instructing the display of an alert screen, information indicating multiple products to be included on the alert screen, information indicating a predetermined period, etc.) to the information processing device 10.

[0066] In step S102, the control unit 110 of the information processing device 10 generates an alert screen and sends the generated alert screen to the user terminal 20. Figure 7 is a flowchart showing the detailed flow of the alert screen generation process in step S102. As shown in Figure 7, the alert screen generation process includes steps S201 to S205.

[0067] In step S201, the indicator acquisition unit 11 acquires product-specific indicators for each of the multiple products to be included in the alert screen, including the landing deviation rate, past error rate, tracking signal, and historical demand comparison. For example, the indicator acquisition unit 11 may acquire product-specific indicators for each product by reading them from the storage unit 120. Alternatively, the indicator acquisition unit 11 may acquire product-specific indicators for each product by calculating them based on the demand forecast value and actual demand value stored in the storage unit 120. If the operation to specify multiple products to be included in the alert screen is not accepted in step S101, a predetermined set of multiple products or all products handled by the target company may be applied. Also, if the operation to specify a predetermined period is not accepted in step S101, a predetermined predetermined period may be applied.

[0068] In step S202, the corporate information acquisition unit 12 acquires corporate information. For example, the corporate information acquisition unit 12 may acquire corporate information corresponding to a predetermined period by reading it from the storage unit 120.

[0069] In step S203, the external information acquisition unit 13 acquires external information. For example, the external information acquisition unit 13 may acquire external information corresponding to a predetermined period by reading it from the storage unit 120.

[0070] Steps S201 to S203 do not necessarily have to be executed in this order; they may be executed in a different order, or some or all of them may be executed in parallel.

[0071] In step S204, the first display control unit 15 identifies the indicators that satisfy the alert conditions from among the product-specific indicators for each of the multiple products. In other words, the first display control unit 15 identifies the products for which an alert should be output. The first display control unit 15 also generates an alert screen that includes the product-specific indicators for each of the multiple products, as well as the alert.

[0072] In step S205, the interpretation example generation unit 14 refers to product-specific indicators, internal company information, and external company information for each of the multiple products, and uses a large-scale language model to generate sentences that serve as interpretation examples for the alert. The interpretation example generation unit 14 also includes these interpretation examples in the alert screen and sends the alert screen to the user terminal 20.

[0073] For example, the interpretation example generation unit 14 may generate a prompt that includes product-specific indicators that satisfy the alert conditions for each of several products, internal company information, external company information, and examples. Alternatively, the interpretation example generation unit 14 may input the prompt into a large-scale language model and obtain the text output from the large-scale language model as an interpretation example. Examples to be included in the prompt include examples of product-specific indicators that satisfy the alert conditions for each of any several products, examples of internal company information, examples of external company information, and examples of text that serve as an interpretation example of the alert. Furthermore, examples of text that serve as an interpretation example may include examples of the alert situation, examples of products that should be noted based on the alert, and examples of suggested responses to the alert based on internal or external company information.

[0074] In step S103 of Figure 6, the UI unit 21 of the user terminal 20 displays the received alert screen on the display unit 250.

[0075] (Screen example) Figure 8 shows an example of an alert screen displayed on the display unit 250 in step S103. As shown in Figure 8, screen example G1 is an example of an alert screen for multiple products. Screen example G1 includes areas G11 and G12.

[0076] Area G11 is a list of multiple product-specific metrics for each of several products. These product-specific metrics include landing deviation rate, week-to-week error rate, tracking signal (TS), wholesale shipment moving average year-on-year, and POS moving average year-on-year. Area G11 also includes alerts. Specifically, in Area G11, cells for metrics that do not meet the alert criteria are displayed in white. Cells for metrics that meet the alert criteria are displayed with a diagonal line pattern, highlighting them more than cells that do not meet the criteria. In other words, cells with a diagonal line pattern indicate alerts issued for the corresponding product.

[0077] The alerts included in screen example G1 are named according to the type of product-specific indicator, and are categorized as follows: future alerts, historical alerts, TS alerts, wholesale shipment change alerts, and POS change alerts. The following describes each type of alert.

[0078] (Future Alert) A future alert is issued when the absolute value of the actual deviation rate, which is an example of a product-specific metric, exceeds a threshold. In other words, a future alert is issued when there is a high probability that the demand forecast calculated for the current unit period will deviate significantly from the actual forecast calculated by referring to the actual demand up to a certain point in that unit period. Therefore, a future alert indicates products where the error in the demand forecast for the current unit period (e.g., this week) is likely to be large at a future point in time (e.g., this weekend) when the current unit period ends.

[0079] In example screen G1, the alert condition for generating a future alert is set to, for example, "the absolute value of the landing deviation rate is 20% or more." However, the 20% threshold is just an example and is not limited to this. As a result, the cells for the landing deviation rates of products A, B, and C that meet the alert condition are filled with a diagonal line pattern. In other words, future alerts have been generated for products A, B, and C.

[0080] Note that the list shown in area G11 is sorted in descending order of landing deviation rate, so future alerts are output for the top three cells corresponding to products that have exceeded the threshold.

[0081] (Past alerts) A historical alert is issued when the absolute value of the previous week's error rate, which is an example of a product-specific metric, exceeds a threshold. In other words, a historical alert is issued when there is a discrepancy between the demand forecast value calculated for a past unit period and the actual demand value for that unit period. Therefore, historical alerts indicate products where the demand forecast error was large in a past unit period (for example, the previous week).

[0082] In example screen G1, the alert condition for outputting past alerts is set to, for example, "the absolute value of the previous week's error rate is 20% or more." However, the 20% threshold is just an example and is not limited to this. As a result, the cells for the previous week's error rate of products A, C, and D that meet the alert condition are filled with a diagonal line pattern. In other words, past alerts have been output for products A, C, and D.

[0083] As mentioned above, the list shown in area G11 is sorted in descending order of landing deviation rate. If the alert screen shown in example screen G1 targets multiple products other than products A to H, then, for example, past alerts may have been generated for other products that are not displayed. For example, the user may sort the list shown in area G11 in descending order of previous week error rate (for example, by clicking / tapping a cell containing the text "previous week error rate"). By performing this operation, the user can identify products for which past alerts have been generated, in descending order of previous week error rate.

[0084] (TS Alert) A TS alert is issued when the absolute value of a tracking signal, which is an example of a product-specific metric, exceeds a threshold. In other words, a TS alert indicates a product where the error in demand forecasting continues to be biased in a particular direction.

[0085] In example screen G1, the alert condition for generating a TS alert is set to, for example, "the absolute value of the tracking signal is 3.2 or greater." However, the threshold of 3.2 is just an example and is not limited to this. As a result, the tracking signal cells for products A, C, and H that meet this alert condition are filled with a diagonal line pattern. In other words, a TS alert has been generated for products A, C, and H.

[0086] As mentioned above, the list shown in area G11 is sorted in descending order of landing deviation rate. If the alert screen shown in example screen G1 targets multiple products other than products A to H, then, for example, TS alerts may also be output for other products that are not displayed. For example, the user may sort the list shown in area G11 in descending order of tracking signal (for example, by clicking / tapping a cell containing the letters "TS"). By performing this operation, the user can recognize the products for which TS alerts have been output, in descending order of tracking signal.

[0087] (Wholesale shipment change alert) The wholesale shipment change alert is issued when the absolute value of the year-on-year moving average of wholesale shipments, which is an example of a product-specific indicator, exceeds a threshold. In other words, the wholesale shipment change alert indicates products where the actual wholesale shipment value deviates from the year-on-year change. For products for which there is no record of the previous year's wholesale shipment value to compare with, the rate of change of the moving average of the actual wholesale shipment value may be applied instead of the year-on-year moving average of wholesale shipments.

[0088] In example screen G1, the alert condition for generating a wholesale shipment change alert is set to, for example, "the absolute value of the moving average year-on-year change in wholesale shipments is 15% or more." However, the 15% threshold is just an example and is not limited to this. Since none of products A to H meet the alert condition, none of the cells for the moving average year-on-year change in wholesale shipments are filled with a diagonal line pattern. In other words, no wholesale shipment change alert is generated in area G11.

[0089] As mentioned above, the list shown in area G11 is sorted in descending order of the landing deviation rate. If the alert screen shown in example screen G1 targets multiple products other than products A to H, for example, wholesale shipment change alerts may be output for other products that are not displayed. For example, the user may sort the list shown in area G11 in descending order of wholesale shipment moving average year-on-year (for example, by clicking / tapping a cell containing the text "Wholesale Shipment Moving Average Year-on-Year"). By performing this operation, the user can identify the products for which wholesale shipment change alerts have been output, in descending order of wholesale shipment moving average year-on-year.

[0090] (POS change alert) A POS change alert is issued when the absolute value of the POS moving average year-on-year change, which is an example of a product-specific metric, exceeds a threshold. In other words, a POS change alert indicates products where the actual POS value deviates from the previous year's figures. For products where there are no previous year's records to compare with the actual sales figures from retailers to consumers, the moving average change rate of the actual sales figures may be applied instead of the POS moving average year-on-year change.

[0091] In example screen G1, the alert condition for generating a POS change alert is set to, for example, "the absolute value of the POS moving average year-on-year change is 15% or more." However, the 15% threshold is just an example and is not limited to this. Since none of products A to H meet the alert condition, none of the cells for the POS moving average year-on-year change are filled with a diagonal line pattern. In other words, no POS change alert is generated in area G11.

[0092] As mentioned above, the list shown in area G11 is sorted in descending order of the landing deviation rate. If the alert screen shown in example screen G1 targets multiple products other than products A to H, for example, POS change alerts may be output for other products that are not displayed. For example, the user may sort the list shown in area G11 in descending order of POS moving average year-on-year (for example, by clicking / tapping a cell containing the text "POS moving average year-on-year"). By performing this operation, the user can recognize the products for which POS change alerts have been output, in descending order of POS moving average year-on-year.

[0093] (Example of interpretation) Area G12 contains sentences that serve as examples of how to interpret each type of alert described above. Among the example sentences, the sentence "Analyze the forecast error (in other words, the error in demand forecasting) from products A, C, etc., where the landing deviation rate (future alert) and the previous week error rate (past alert) are deviating in the same direction, revise the demand forecast, and check inventory dynamics" shows the interpretation and suggestion for future alerts and past alerts. In addition, the sentence "Also check TS alerts and prioritize checking products A, C, H, etc., which have a high risk of stockouts or excess inventory" shows the interpretation and suggestion for TS alerts. Furthermore, the sentence "There will be a new product launch in the XX business next week. After the launch, there is a possibility of fluctuations in consumer demand, so pay attention to POS alerts and wholesale shipment alerts" shows a suggestion regarding POS alerts and wholesale shipment alerts based on internal company information.

[0094] As shown in the alert screen in example G1, users can identify high-priority products that should have their demand forecasts revised by combining multiple types of alerts. Furthermore, since the alert screen displays interpretation examples for these multiple types of alerts, even users with limited knowledge of demand forecasting can easily identify high-priority products that should have their demand forecasts revised. In addition, example G1 can support users with knowledge of demand forecasting by reducing omissions or errors in the information they need to consider to identify high-priority products that should have their demand forecasts revised, shortening the time spent on information gathering and organization, and increasing the time available for analysis.

[0095] In step S104 of Figure 6, the UI unit 21 of the user terminal 20 accepts a user operation to specify one of several products included in the alert screen. This user operation is performed to specify the product to be targeted on the product-specific analysis screen. For example, in the example screen G1 shown in Figure 8, the user may refer to "Products A and C whose landing deviation rate (future alert) and previous week error rate (past alert) are deviating in the same direction" included in the interpretation example of area G12 and perform an operation to specify product A or C. The operation to specify a product may be, for example, clicking / tapping a cell containing the text "product A" or "product C," but is not limited to this.

[0096] Furthermore, the user's operation may also include specifying a predetermined past period to be targeted on the product analysis screen (for example, a predetermined year, a predetermined month, the start date and end date of the period, etc.). The UI unit 21 transmits information indicated by the received operation (for example, information instructing the display of the product analysis screen, information indicating the specified product, information indicating the predetermined period, etc.) to the information processing device 10.

[0097] In step S105, the control unit 110 of the information processing device 10 generates a product-specific analysis screen and transmits the generated product-specific analysis screen to the user terminal 20. Figure 9 is a flowchart showing the detailed flow of the product analysis screen generation process in step S105. As shown in Figure 9, the product analysis screen generation process includes steps S301 to S305.

[0098] In step S301, the indicator acquisition unit 11 acquires the following product-specific indicators for the specified product: the landing deviation rate, the historical error rate, the tracking signal, and the historical demand comparison. For example, the indicator acquisition unit 11 may acquire the time series of each indicator for the relevant product over a predetermined period by reading it from the storage unit 120. Alternatively, the indicator acquisition unit 11 may acquire the time series of each indicator for the relevant product over a predetermined period by calculating it based on the demand forecast value and actual demand value stored in the storage unit 120. If the operation to specify a predetermined period in step S104 is not accepted, a predetermined period determined in advance may be applied.

[0099] In step S302, the corporate information acquisition unit 12 acquires corporate information. For example, the corporate information acquisition unit 12 may acquire corporate information corresponding to a predetermined period by reading it from the storage unit 120.

[0100] In step S303, the external information acquisition unit 13 acquires external information. For example, the external information acquisition unit 13 may acquire external information corresponding to a predetermined period by reading it from the storage unit 120.

[0101] Steps S301 to S303 do not necessarily have to be executed in this order; they may be executed in a different order, or some or all of them may be executed in parallel.

[0102] In step S304, the second display control unit 16 generates an example sentence for interpretation using a large-scale language model, referencing the time series of product-specific indicators related to the product, internal company information, and external company information. The example sentence for interpretation includes the status of the error in the demand forecast for the product, the factors related to the error in the demand forecast based on internal and external company information, and suggestions for addressing the error in the demand forecast.

[0103] For example, the interpretation example generation unit 14 may generate a prompt that includes a time series of product-specific indicators for a specified product, internal company information, external company information, and examples, and input it into a large-scale language model. Alternatively, the interpretation example generation unit 14 may input the prompt into the large-scale language model and obtain the text output from the large-scale language model as an interpretation example. Examples to be included in the prompt include examples of time series of product-specific indicators for any product, examples of internal company information, examples of external company information, and examples of text that serve as interpretation examples. Examples of text that serve as interpretation examples include examples of the situation regarding errors in demand forecasts for any product, examples of factors related to the demand forecast, and examples of proposed solutions to the errors in the demand forecast.

[0104] In step S305, the second display control unit 16 generates a product-specific analysis screen that includes a time series of product-specific indicators for the specified product, as well as an example of interpretation. The second display control unit 16 also transmits the product-specific analysis screen to the user terminal 20.

[0105] In step S106 of Figure 6, the UI unit 21 of the user terminal 20 displays the received product-specific analysis screen on the display unit 250.

[0106] (Screen example) Figure 10 shows an example of a product-specific analysis screen displayed on the display unit 250 in step S106. Here, it is assumed that the operation to specify product A was performed on the alert screen shown in Figure 8. As shown in Figure 10, screen example G2 is an example of a product-specific analysis screen for the specified product A. Screen example G2 includes areas G21 to G25. Area G21 includes a graph showing the trend of MAPE impact for product A over a predetermined period. Area G22 includes a graph showing the trend of tracking signals for product A over a predetermined period. Area G23 includes a graph showing the trend of channel composition ratio of shipment results for product A over a predetermined period. Area G24 includes a graph showing the trend of year-on-year comparison of shipment results by channel for product A over a predetermined period.

[0107] Area G25 includes example sentences for interpretation. Among the example sentences, the sentence "For product A, TS is rising again, indicating an over-forecast trend" indicates the situation of forecast error for product A. Also, the sentence "There has been no significant change in the channel composition ratio" indicates the channel-specific situation for analyzing forecast error for product A. These sentences, which show the situation, allow even users with limited knowledge of demand forecasting to easily grasp the situation of forecast error and channel information shown in the graphs in areas G21-G24. In addition, among the example sentences, the sentence "Since year-on-year growth has not recovered in the main mass-market sales, the impact of price increases may be continuing" indicates a factor in the forecast error. Such sentences that show the factors in forecast error allow even users with limited knowledge of demand forecasting to easily grasp the factors in demand forecast error considering internal and external company information. Also, among the example sentences, the sentence "Please check the POS trends and interview the sales department to update the demand forecast" indicates a suggestion for addressing the demand forecast error. By presenting such proposals, even users with limited knowledge of demand forecasting can easily address errors in demand forecasts for the relevant product. Furthermore, as shown in example screen G2, users with knowledge of demand forecasting can be supported in reducing omissions or errors in the information that should be considered when analyzing errors in demand forecasts for the relevant product, shortening the time spent on information gathering and organization, and increasing the time available for analysis.

[0108] (Variation 1) The interpretation example generation unit 14 may generate interpretation examples for the alert screen and / or for the product-specific analysis screen using a knowledge base in addition to a large-scale language model, as follows. In this modified example, the internal and external company information acquired by the internal company information acquisition unit 12 and the external company information acquisition unit 13 is added to the knowledge base (not shown). This updates the knowledge base to the latest state. The knowledge base may be stored in the storage unit 120 or in an external device different from the information processing device 10.

[0109] For example, the interpretation example generation unit 14 may search a knowledge base updated to the latest state for information on product-specific indicators that satisfy the alert conditions for each of multiple products, in order to generate an interpretation example for the alert screen. Alternatively, the interpretation example generation unit 14 may input the search results and a prompt including the time series of each indicator into a large-scale language model. As a result, the large-scale language model outputs a sentence that serves as an interpretation example for the alert.

[0110] Furthermore, for example, the interpretation example generation unit 14 may search for time-series information on product-specific indicators for a specified product from a knowledge base that has been updated to the latest state in order to generate interpretation examples for the product-specific analysis screen. The interpretation example generation unit 14 may also input the search results and prompts containing the time-series information for each indicator to the large-scale language model. As a result, the large-scale language model outputs sentences that serve as interpretation examples for product-specific indicators for that product.

[0111] For example, in this modified example, in step S202 or S203, or step S302 or S303, further processing may be performed to add the acquired internal and external company information to the knowledge base. Furthermore, steps S202 and S203 do not need to be performed after receiving the operation to instruct the display of the alert screen (S101), but may be performed at any time (for example, periodically). Also, steps S302 and S303 do not need to be performed after receiving the operation to specify the product for which the product-specific analysis screen should be displayed (S104), but may be performed at any time (for example, periodically).

[0112] (Modification 2) The interpretation example generation unit 14 may generate interpretation examples on the alert screen and / or on the product-specific analysis screen by further training the large-scale language model as follows. In this modified example, the large-scale language model is further trained using the internal and external company information acquired by the internal company information acquisition unit 12 and the external company information acquisition unit 13. This updates the large-scale language model to the latest state.

[0113] For example, the interpretation example generation unit 14 may input the indicators that satisfy the alert conditions from among the product-specific indicators for each of the multiple products into a large-scale language model that has been updated to the latest state in order to generate an interpretation example for the alert screen. As a result, the large-scale language model outputs a sentence that will serve as an interpretation example for the alert.

[0114] Furthermore, for example, the interpretation example generation unit 14 may input a time series of product-specific indicators for a specified product into a large-scale language model that has been updated to the latest state in order to generate interpretation examples for the product-specific analysis screen. As a result, the large-scale language model outputs sentences that serve as interpretation examples for the product-specific indicators for that product.

[0115] Furthermore, in this modified example, for example, in step S202 or S203, or step S302 or S303, a process may be performed to further train a large-scale language model using the acquired internal and external company information. Also, steps S202 and S203 do not need to be performed after receiving the operation to instruct the display of the alert screen (S101), but may be performed at any time (for example, periodically). Also, steps S302 and S303 do not need to be performed after receiving the operation to specify the product for which the product-specific analysis screen should be displayed (S104), but may be performed at any time (for example, periodically).

[0116] (Variation 3) The product analysis screen is not necessarily displayed only after transitioning from the alert screen. For example, the product analysis screen may be displayed in response to any operation that specifies a product, or it may be displayed for pre-configured target products.

[0117] (Effects of Information Processing System 1A) As described above, the Information Processing System 1A employs a structure in which the interpretation examples include the status of errors in demand forecasting for a product, factors based on internal and external company information regarding said errors in demand forecasting, and some or all of the proposed responses to said errors in demand forecasting. Therefore, in addition to the effects achieved by Information Processing System 1, Information Processing System 1A provides the effect of easily understanding the status and factors of errors in demand forecasting, and easily responding to errors in demand forecasting.

[0118] Furthermore, in the information processing system 1A, the indicator acquisition unit 11 acquires product-specific indicators for each of the multiple products, and the interpretation examples include interpretation examples of indicators that satisfy predetermined alert conditions among the product-specific indicators for each of the multiple products. Therefore, in addition to the effects achieved by the information processing system 1, the information processing system 1A provides the effect of easily understanding the status of products corresponding to product-specific indicators that satisfy the alert conditions (in other words, products for which alerts have been output).

[0119] Furthermore, the information processing system 1A employs a configuration that includes a first display control unit 15 which displays a first screen on a display device that includes product-specific indicators for each of the multiple products, as well as interpretation examples of product-specific indicators that satisfy the alert conditions, and a second display control unit 16 which, in response to an operation to specify one of the multiple products included in the first screen, displays a second screen on the display device that includes product-specific indicators for the specified product, as well as interpretation examples of those product-specific indicators. Therefore, in addition to the effects achieved by the information processing system 1, the information processing system 1A provides the effect of easily analyzing the error in demand forecasting shown by product-specific indicators for the specified product by referring to the interpretation examples included in the alert screen.

[0120] Furthermore, in Information Processing System 1A, the internal company information is configured to include either or both promotional information within the target company related to the product, and sales information for other products within the target company in the same category as the product. Therefore, in addition to the effects achieved by Information Processing System 1, Information Processing System 1A provides users with the benefit of being able to present interpretation examples of the error in demand forecasts shown by product-specific indicators, taking into account either or both promotional information within the target company related to the product, and sales information for other products within the target company in the same category as the product.

[0121] Furthermore, in Information Processing System 1A, the external information is structured to include either or both of the following: new product launches by competing brands, trends of those competing brands, and market trend information to which the product belongs. Therefore, in addition to the effects achieved by Information Processing System 1, Information Processing System 1A can provide users with examples of interpretations of the demand forecast error shown by product-specific indicators, taking into account either or both of the new product launches by competing brands, trends of those competing brands, and market trend information to which the product belongs.

[0122] Furthermore, in Information Processing System 1A, the internal company information is configured to include some or all of the product information, demand forecast values, actual demand values, and actual distribution values ​​related to the product. Therefore, in addition to the effects achieved by Information Processing System 1, Information Processing System 1A can provide users with examples of interpretations of the demand forecast error shown by product-specific indicators, taking into account some or all of the product information, demand forecast values, actual demand values, and actual distribution values ​​related to the product.

[0123] Furthermore, in Information Processing System 1A, the external information is structured in such a way that it includes some or all of the information regarding changes in regulations in the industry related to the product, and information indicating the external environment of the industry. Therefore, in addition to the effects achieved by Information Processing System 1, Information Processing System 1A can provide users with examples of interpretations of the errors in demand forecasts shown by product-specific indicators, taking into account some or all of the information regarding changes in regulations in the industry related to the product, and information indicating the external environment of the industry.

[0124] [Examples of implementation using software] Some or all of the functions of the information processing system 1, the information processing device 10, and the user terminal 20 (hereinafter also referred to as "each of the above devices") may be implemented by hardware such as integrated circuits (IC chips) or by software.

[0125] In the latter case, each of the above devices is implemented, for example, by a computer that executes instructions for a program, which is software that realizes each function. An example of such a computer (hereinafter referred to as computer C) is shown in Figure 11. Figure 11 is a block diagram showing the hardware configuration of computer C, which functions as each of the above devices.

[0126] Computer C comprises at least one processor C1 and at least one memory C2. Memory C2 stores a program P that causes computer C to operate as each of the above-mentioned devices. In computer C, processor C1 reads program P from memory C2 and executes it, thereby realizing each of the above-mentioned devices.

[0127] For processor C1, for example, a CPU (Central Processing Unit), GPU (Graphic Processing Unit), DSP (Digital Signal Processor), MPU (Micro Processing Unit), FPU (Floating Point Number Processing Unit), PPU (Physics Processing Unit), TPU (Tensor Processing Unit), quantum processor, microcontroller, or a combination thereof can be used. For memory C2, for example, flash memory, HDD (Hard Disk Drive), SSD (Solid State Drive), or a combination thereof can be used.

[0128] Computer C may also be equipped with RAM (Random Access Memory) for loading program P at runtime and for temporarily storing various data. Furthermore, computer C may be equipped with communication interfaces for sending and receiving data with other devices. Additionally, computer C may be equipped with input / output interfaces for connecting input / output devices such as keyboards, mice, displays, and printers.

[0129] Furthermore, program P can be recorded on a non-temporary, tangible recording medium M that is readable by computer C. Such a recording medium M could be, for example, tape, disk, card, semiconductor memory, or programmable logic circuitry. Computer C can acquire program P via such a recording medium M. Program P can also be transmitted via a transmission medium. Such a transmission medium could be, for example, a communication network or broadcast waves. Computer C can also acquire program P via such a transmission medium.

[0130] Furthermore, each of the above functions of each of the above devices may be implemented by a single processor in a single computer, by multiple processors in a single computer working together, or by multiple processors in each of multiple computers working together. In addition, the programs for implementing each of the above functions in each of the above devices may be stored in a single memory in a single computer, distributed and stored in multiple memories in a single computer, or distributed and stored in multiple memories in each of multiple computers.

[0131] [Additional Note A] This disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope of the claims.

[0132] (Note A1) A means for obtaining product-specific indicators to manage the accuracy of demand forecasts for products handled by the target company, An internal information acquisition means for acquiring internal company information regarding the said product within the said target company, An external information acquisition means for acquiring external information about the product outside of the target company, An interpretation example generation means that uses a large-scale language model to generate sentences that include interpretation examples based on internal company information and external company information as examples of interpretations of the product-specific indicators, An information processing system equipped with the following features.

[0133] (Appendix A2) The aforementioned interpretation example includes, in part or in whole, the circumstances of the error in the demand forecast for the said product, the factors based on the said internal and said external information regarding the error in the demand forecast, and the proposed solutions to the error in the demand forecast. The information processing system described in Appendix A1.

[0134] (Note A3) The indicator acquisition means acquires the product-specific indicator for each of the multiple products, The above interpretation example includes an interpretation example of an indicator among the product-specific indicators for each of the multiple products that satisfies a predetermined alert condition, The information processing system described in Appendix A1 or A2.

[0135] (Note A4) A first display control means that displays on a display device a first screen including the product-specific indicators for each of the plurality of products, and an example of how to interpret the product-specific indicators that satisfy the alert conditions, The information processing system described in Appendix A3 further comprises: a second display control means that, in response to an operation to select one of the plurality of products included in the first screen, displays on the display device a second screen including product-specific indicators for the selected product and an example of how to interpret the product-specific indicators.

[0136] (Note A5) The aforementioned internal company information includes either or both of the following: promotional information within the target company related to the aforementioned product, and sales information for other products within the target company in the same category as the aforementioned product. The information processing system described in any one of the appendices A1 through A4.

[0137] (Note A6) The aforementioned external information includes one or both of the following: new product launches by competing brands of the aforementioned product, information on the trends of the aforementioned competing brands, and market trend information in the market to which the aforementioned product belongs. The information processing system described in any one of the appendices A1 through A5.

[0138] (Note A7) The aforementioned internal company information includes some or all of the product information, demand forecasts, actual demand figures, and actual distribution figures related to the aforementioned product. An information processing system described in any one of the appendices A1 through A6.

[0139] (Note A8) The aforementioned external information includes some or all of the information relating to changes in regulations in the industry concerning the aforementioned products, and the external environment of the aforementioned industry. An information processing system described in any one of the appendices A1 through A7.

[0140] [Additional Notes B] This disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope of the claims.

[0141] (Note B1) At least one processor performs an indicator acquisition process to obtain product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company, The at least one processor performs an internal information acquisition process to acquire internal company information regarding the product within the target company, The at least one processor performs an external information acquisition process to acquire external information about the product outside the target company, The at least one processor performs an interpretation example generation process that uses a large-scale language model to generate sentences that include interpretation examples based on the internal company information and the external company information as examples of interpretations of the product-specific indicators, Information processing methods including

[0142] (Note B2) The aforementioned interpretation example includes, in part or in whole, the circumstances of the error in the demand forecast for the said product, the factors based on the said internal and said external information regarding the error in the demand forecast, and the proposed solutions to the error in the demand forecast. The information processing method described in Appendix B1.

[0143] (Note B3) In the aforementioned indicator acquisition process, the at least one processor acquires the product-specific indicator for each of the multiple products, The above interpretation example includes an interpretation example of an indicator among the product-specific indicators for each of the multiple products that satisfies a predetermined alert condition, The information processing method described in Appendix B1 or B2.

[0144] (Note B4) The at least one processor performs a first display control process which displays a first screen on a display device that includes the product-specific indicators for each of the plurality of products, and an example of how to interpret the product-specific indicators that satisfy the alert conditions. The information processing method according to Appendix B3, further comprising: a second display control process in which at least one processor, in response to an operation to specify one of the plurality of products included in the first screen, displays on the display device a second screen including product-specific indicators for the specified product and an example of interpretation of the product-specific indicators.

[0145] (Note B5) The aforementioned internal company information includes either or both of the following: promotional information within the target company related to the aforementioned product, and sales information for other products within the target company in the same category as the aforementioned product. The information processing method described in any one of the appendices B1 to B4.

[0146] (Note B6) The aforementioned external information includes one or both of the following: new product launches by competing brands of the aforementioned product, information on the trends of the aforementioned competing brands, and market trend information in the market to which the aforementioned product belongs. The information processing method described in any one of the appendices B1 through B5.

[0147] (Note B7) The aforementioned internal company information includes some or all of the product information, demand forecasts, actual demand figures, and actual distribution figures related to the aforementioned product. The information processing method described in any one of the appendices B1 to B6.

[0148] (Note B8) The aforementioned external information includes some or all of the information relating to changes in regulations in the industry concerning the aforementioned products, and the external environment of the aforementioned industry. The information processing method described in any one of the appendices B1 through B7.

[0149] [Additional Note C] This disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope of the claims.

[0150] (Note C1) A program that makes a computer function as an information processing system, The aforementioned computer, A means for obtaining product-specific indicators to manage the accuracy of demand forecasts for products handled by the target company, An internal information acquisition means for acquiring internal company information regarding the said product within the said target company, An external information acquisition means for acquiring external information about the product outside of the target company, An interpretation example generation means that uses a large-scale language model to generate sentences that include interpretation examples based on internal company information and external company information as examples of interpretations of the product-specific indicators, An information processing program that functions as such.

[0151] (Note C2) The aforementioned interpretation example includes, in part or in whole, the circumstances of the error in the demand forecast for the said product, the factors based on the said internal and said external information regarding the error in the demand forecast, and the proposed solutions to the error in the demand forecast. The information processing program described in Appendix C1.

[0152] (Note C3) The indicator acquisition means acquires the product-specific indicator for each of the multiple products, The above interpretation example includes an interpretation example of an indicator among the product-specific indicators for each of the multiple products that satisfies a predetermined alert condition, The information processing program described in Appendix C1 or C2.

[0153] (Note C4) A first display control means that displays on a display device a first screen including the product-specific indicators for each of the plurality of products, and an example of how to interpret the product-specific indicators that satisfy the alert conditions, The aforementioned computer, The information processing program described in Appendix C3 further functions as a second display control means that, in response to an operation to select one of the multiple products included in the first screen, displays a second screen on the display device that includes product-specific indicators for the selected product and examples of interpretations of the product-specific indicators.

[0154] (Note C5) The aforementioned internal company information includes either or both of the following: promotional information within the target company related to the aforementioned product, and sales information for other products within the target company in the same category as the aforementioned product. An information processing program described in any one of the appendices C1 to C4.

[0155] (Appendix C6) The aforementioned external information includes one or both of the following: new product launches by competing brands of the aforementioned product, information on the trends of the aforementioned competing brands, and market trend information in the market to which the aforementioned product belongs. An information processing program described in any one of the appendices C1 to C5.

[0156] (Note C7) The aforementioned internal company information includes some or all of the product information, demand forecasts, actual demand figures, and actual distribution figures related to the aforementioned product. An information processing program described in any one of the appendices C1 to C6.

[0157] (Note C8) The aforementioned external information includes some or all of the information relating to changes in regulations in the industry concerning the aforementioned products, and the external environment of the aforementioned industry. An information processing program described in any one of the appendices C1 through C7.

[0158] [Additional Note D] This disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope of the claims.

[0159] (Note D1) It comprises at least one processor, and the at least one processor is An indicator acquisition process to obtain product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company, An internal information acquisition process that acquires internal company information regarding the product within the target company, An external information acquisition process that acquires external information about the product outside of the target company, An interpretation example generation process that uses a large-scale language model to generate sentences that include interpretation examples based on internal company information and external company information as examples of interpretations of the product-specific indicators, An information processing system that performs [this action].

[0160] The information processing system may also include memory. Furthermore, the memory may store programs that cause at least one processor to execute each of the aforementioned processes.

[0161] (Note D2) The aforementioned interpretation example includes, in part or in whole, the circumstances of the error in the demand forecast for the said product, the factors based on the said internal and said external information regarding the error in the demand forecast, and the proposed solutions to the error in the demand forecast. The information processing system described in Appendix D1.

[0162] (Note D3) In the aforementioned indicator acquisition process, the at least one processor acquires the product-specific indicator for each of the multiple products, The above interpretation example includes an interpretation example of an indicator among the product-specific indicators for each of the multiple products that satisfies a predetermined alert condition, The information processing system described in Appendix D1 or D2.

[0163] (Note D4) A first display control process that displays on a display device a first screen including the product-specific indicators for each of the plurality of products, and an example of how to interpret the product-specific indicators that satisfy the alert conditions; The aforementioned at least one processor, The information processing system described in Appendix D3, further comprising: a second display control process that, in response to an operation to select one of the multiple products included in the first screen, displays on the display device a second screen including product-specific indicators for the selected product and examples of interpretations of the product-specific indicators.

[0164] (Note D5) The aforementioned internal company information includes either or both of the following: promotional information within the target company related to the aforementioned product, and sales information for other products within the target company in the same category as the aforementioned product. An information processing system described in any one of the appendices D1 to D4.

[0165] (Note D6) The aforementioned external information includes one or both of the following: new product launches by competing brands of the aforementioned product, information on the trends of the aforementioned competing brands, and market trend information in the market to which the aforementioned product belongs. An information processing system described in any one of the appendices D1 to D5.

[0166] (Note D7) The aforementioned internal company information includes some or all of the product information, demand forecasts, actual demand figures, and actual distribution figures related to the aforementioned product. An information processing system described in any one of the appendices D1 to D6.

[0167] (Note D8) The aforementioned external information includes some or all of the information relating to changes in regulations in the industry concerning the aforementioned products, and the external environment of the aforementioned industry. An information processing system described in any one of the appendices D1 through D7.

[0168] [Additional Note E] This disclosure includes the technologies described in the following appendices. However, the present invention is not limited to the technologies described in the following appendices, and various modifications are possible within the scope of the claims.

[0169] (Note E1) A program that makes a computer function as an information processing system, To the aforementioned computer, An indicator acquisition process to obtain product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company, An internal information acquisition process that acquires internal company information regarding the product within the target company, An external information acquisition process that acquires external information about the product outside of the target company, An interpretation example generation process that uses a large-scale language model to generate sentences that include interpretation examples based on internal company information and external company information as examples of interpretations of the product-specific indicators, A non-temporary recording medium that stores an information processing program that executes that program. [Explanation of Symbols]

[0170] 1. 1A Information Processing System 10 Information Processing Devices 11 Indicator acquisition part 12 Corporate Information Acquisition Department 13 External Information Acquisition Department 14. Interpretation Example Generation Unit 15. First Display Control Unit 16. Second Display Control Unit 20 User Terminals 21 UI section 110, 210 Control Unit 120, 220 storage section 130, 230 Communications Department 240 Input section 250 Display section C1 Processor C2 Memory

Claims

1. A means for obtaining product-specific indicators to manage the accuracy of demand forecasts for products handled by the target company, An internal information acquisition means for acquiring internal company information regarding the said product within the said target company, An external information acquisition means for acquiring external information about the product outside of the target company, An interpretation example generation means that uses a large-scale language model to generate sentences that include interpretation examples based on internal company information and external company information as examples of interpretations of the product-specific indicators, An information processing system equipped with the following features.

2. The aforementioned interpretation example includes, in part or in whole, the circumstances of the error in the demand forecast for the said product, the factors based on the said internal and said external information regarding the error in the demand forecast, and the proposed solutions to the error in the demand forecast. The information processing system according to claim 1.

3. The indicator acquisition means acquires the product-specific indicator for each of the multiple products, The above interpretation example includes an interpretation example of an indicator among the product-specific indicators for each of the multiple products that satisfies a predetermined alert condition, The information processing system according to claim 1.

4. A first display control means that displays on a display device a first screen including the product-specific indicators for each of the plurality of products, and an example of how to interpret the product-specific indicators that satisfy the alert conditions, The information processing system according to claim 3, further comprising: a second display control means that, in response to an operation to select one of the plurality of products included in the first screen, displays on the display device a second screen including product-specific indicators for the selected product and an example of interpretation of the product-specific indicators.

5. The aforementioned internal company information includes either or both of the following: promotional information within the target company related to the aforementioned product, and sales information for other products within the target company in the same category as the aforementioned product. The information processing system according to claim 1.

6. The aforementioned external information includes one or both of the following: new product launches by competing brands of the aforementioned product, information on the trends of the aforementioned competing brands, and market trend information in the market to which the aforementioned product belongs. The information processing system according to claim 1.

7. The aforementioned internal company information includes some or all of the product information, demand forecasts, actual demand figures, and actual distribution figures related to the aforementioned product. The information processing system according to claim 1.

8. The aforementioned external information includes some or all of the information relating to changes in regulations in the industry concerning the aforementioned products, and the external environment of the aforementioned industry. The information processing system according to claim 1.

9. At least one processor performs an indicator acquisition process to obtain product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company, The at least one processor performs an internal information acquisition process to acquire internal company information regarding the product within the target company, The at least one processor performs an external information acquisition process to acquire external information about the product outside the target company, The at least one processor performs an interpretation example generation process that uses a large-scale language model to generate sentences that include interpretation examples based on the internal company information and the external company information as examples of interpretations of the product-specific indicators, Information processing methods including

10. At least one processor, An indicator acquisition process to obtain product-specific indicators for managing the accuracy of demand forecasts for products handled by the target company, An internal information acquisition process that acquires internal company information regarding the product within the target company, An external information acquisition process that acquires external information about the product outside of the target company, An interpretation example generation process that uses a large-scale language model to generate sentences that include interpretation examples based on internal company information and external company information as examples of interpretations of the product-specific indicators, An information processing program that executes [something].

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