Information processing device, information processing method, and information processing program

Abstract

The goal is to clearly demonstrate to users the concrete benefits of improved demand forecasting accuracy. [Solution] The information processing device includes: a current information acquisition unit that acquires current information related to the current cost of goods distribution; an assumed information acquisition unit that acquires assumed information including accuracy improvement information indicating the expected degree of improvement in the accuracy of demand forecasting for goods, and current improvement information indicating the expected degree of improvement in the current information; and an estimation unit that estimates the effect amount, which indicates the effect of improving the accuracy of demand forecasting, based on the current information and assumed information.

Description

Technical Field

[0001] This disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] In recent years, for companies selling products, it has become important to predict the demand for those products. For example, Patent Document 1 describes a technique for improving the accuracy of product demand prediction.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Here, for example, for a company introducing a technique for improving the accuracy of demand prediction as described in Patent Document 1, there is a problem that the specific effects of introducing the technique are difficult to understand. Therefore, there is a need for a technique that clearly presents the specific effects of improving the accuracy of demand prediction to the user.

[0005] This disclosure has been made in view of the above problems, and an exemplary object thereof is to provide a technique for clearly presenting the specific effects of improving the accuracy of demand prediction to the user.

Means for Solving the Problems

[0006] An information processing device relating to an exemplary aspect of this disclosure includes: current information acquisition means for acquiring current information relating to the current state of costs related to the distribution of goods; assumption information acquisition means for acquiring assumption information including accuracy improvement information indicating the degree of expected improvement in the accuracy of demand forecasting for the goods, and current improvement information indicating the degree of expected improvement in the current information; and estimation means for estimating an effect amount that indicates the effect of improving the accuracy of demand forecasting as a monetary amount, based on the current information and the assumption information.

[0007] An example of an information processing method relating to this disclosure includes: a current information acquisition process in which at least one processor acquires current information relating to the current cost of distribution of a product; an assumption information acquisition process in which the at least one processor acquires assumption information including accuracy improvement information indicating the degree of expected improvement in the demand forecasting accuracy of the product, and current improvement information indicating the degree of expected improvement in the current information; and an estimation process in which the at least one processor estimates the effect amount, which indicates the effect of improving the demand forecasting accuracy as a monetary amount, based on the current information and the assumption information.

[0008] An information processing program relating to an exemplary aspect of this disclosure causes a computer to function as: current information acquisition means for acquiring current information related to the current state of costs related to the distribution of goods; assumption information acquisition means for acquiring assumption information including accuracy improvement information indicating the degree of expected improvement in the accuracy of demand forecasting for the goods, and current improvement information indicating the degree of expected improvement in the current information; and estimation means for estimating the effect amount, which indicates the effect of improving the accuracy of demand forecasting as a monetary amount, based on the current information and the assumption information. [Effects of the Invention]

[0009] One illustrative effect of this disclosure is that it provides a technology that clearly demonstrates to users the concrete benefits of improving the accuracy of demand forecasting. [Brief explanation of the drawing]

[0010] [Figure 1] This is a block diagram showing the configuration of the information processing device 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 device related to this disclosure. [Figure 4] This is a flowchart showing the flow of the information processing method related to this disclosure. [Figure 5] This figure shows an example of a screen related to this disclosure. [Figure 6] This figure shows an example of a screen related to this disclosure. [Figure 7] 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 Device 1) Information processing device 1 is a device that clearly demonstrates to the user the benefits of improved product demand forecasting accuracy. Here, the products targeted by information processing device 1 may be, for example, some or all of the products handled by the target company (an example of a user).

[0014] The configuration of the information processing device 1 will be explained with reference to Figure 1. Figure 1 is a block diagram showing the configuration of the information processing device 1. As shown in Figure 1, the information processing device 1 includes a current information acquisition unit 11, a hypothetical information acquisition unit 12, and a calculation unit 13. The current information acquisition unit 11 is an example of a configuration that realizes the current information acquisition means. The hypothetical information acquisition unit 12 is an example of a configuration that realizes the hypothetical information acquisition means. The calculation unit 13 is an example of a configuration that realizes the calculation means.

[0015] The current situation information acquisition unit 11 acquires current situation information related to the current situation of the costs related to the distribution of products. For example, the current situation information may include the costs themselves related to the distribution of products, or may include various types of information that affect such costs. Examples of the costs themselves related to the distribution of consumption include, but are not limited to, storage costs, transportation costs, labor costs, etc. Also, examples of various types of information that affect the costs include, but are not limited to, out-of-stock rates, etc. Note that it is desirable for the current situation information to be the most recent information (in other words, the latest information), but it is not necessarily limited to the most recent information. Also, part or all of the current situation information may be acquired through input from the user, or may be read from a database.

[0016] The assumed information acquisition unit 12 acquires assumed information including accuracy improvement information indicating the degree of assumed improvement in the demand prediction accuracy regarding products, and current situation improvement information indicating the degree of assumed improvement in the current situation information. The demand prediction accuracy refers to how close the demand prediction value indicating the result of the demand prediction of a product is to the demand actual value indicating the actual demand for the product. The accuracy improvement information may be, for example, the degree of assumed improvement in the demand prediction accuracy if actions for improving the demand prediction accuracy are hypothetically taken in the target company. The current situation improvement information may be, for example, the degree of assumed improvement in the current situation information if the demand prediction accuracy is hypothetically improved.

[0017] Also, the assumed information may be acquired through input from the user. For example, the assumed information may be information input through consultation between the user of the target company and an expert in demand prediction. Note that the assumed information is not limited to input from the user, and information determined in advance or information calculated by a predetermined algorithm may also be acquired.

[0018] The calculation unit 13 calculates an effect amount that indicates, as an amount of money, the effect of improving demand prediction accuracy based on the current situation information and the assumed information. For example, the effect amount may include costs that are expected to be reduced due to the improvement of demand prediction accuracy, revenues that are expected to increase due to the improvement of demand prediction accuracy, and the like. For example, the calculation unit 13 may calculate the effect amount using a calculation model that takes the current situation information and the assumed information as inputs and outputs the effect amount. The calculation model may be composed of one or more functions, or may be a machine learning model generated by machine learning.

[0019] (Effect of the information processing apparatus 1) As described above, in the information processing apparatus 1, a current situation information acquisition unit 11 that acquires current situation information related to the current situation of costs related to the distribution of products, an assumed information acquisition unit 12 that acquires assumed information including accuracy improvement information indicating the degree of assumed improvement in demand prediction accuracy regarding products and current situation improvement information indicating the degree of assumed improvement in the current situation information, and a calculation unit 13 that calculates an effect amount that indicates, as an amount of money, the effect of improving demand prediction accuracy based on the current situation information and the assumed information are provided. Here, such an effect amount is easy for the user to understand as a specific effect of improving demand prediction accuracy. Therefore, according to the information processing apparatus 1, there is an effect that the specific effect of improving demand prediction accuracy can be presented to the user in an easy-to-understand manner.

[0020] (Flow of the information processing method S1) The flow of the information processing method S1 will be described with reference to FIG. 2. FIG. 2 is a flowchart showing the flow of the information processing method S1. For example, when the information processing apparatus 1 includes at least one processor, the information processing apparatus 1 executes the information processing method S1. As shown in FIG. 2, the information processing method S1 includes a current situation information acquisition process S11, an assumed information acquisition process S12, and a calculation process S13.

[0021] In the current information acquisition process S11, at least one processor (for example, the current information acquisition unit 11) acquires current information related to the current cost of goods distribution. Details of the current information acquisition process S11 will not be repeated as they have been described above for the current information acquisition unit 11.

[0022] In the assumed information acquisition process S12, at least one processor acquires assumed information, which includes accuracy improvement information indicating the expected degree of improvement in the demand forecast accuracy for the product, and current improvement information indicating the expected degree of improvement in the current information. Details of the assumed information acquisition process S12 are as described above for the assumed information acquisition unit 12 and will not be repeated.

[0023] In calculation process S13, at least one processor calculates the effect amount, which represents the effect of improving demand forecasting accuracy, based on current information and assumed information. Details of calculation process S13 will not be repeated as they have been described above for the calculation unit 13.

[0024] (Effects of information processing method S1) As described above, the information processing method S1 employs a configuration that includes: a current information acquisition process S11 in which at least one processor acquires current information related to the current cost of goods distribution; an assumption information acquisition process S12 in which at least one processor acquires assumption information including accuracy improvement information indicating the expected degree of improvement in the accuracy of demand forecasting for goods, and current improvement information indicating the expected degree of improvement in current information; and an estimation process S13 in which at least one processor estimates the effect amount, which indicates the effect of improving the accuracy of demand forecasting, based on the current information and assumption information. For this reason, the same effect as the information processing device 1 can be obtained with the information processing method S1.

[0025] [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.

[0026] (Configuration of Information Processing Device 1A) The configuration of the information processing device 1A will be explained with reference to Figure 3. Figure 3 is a block diagram showing the configuration of the information processing device 1A. The information processing device 1A includes a control unit 110, a storage unit 120, a communication unit 130, an input unit 140, and a display unit 150. The control unit 110 includes a current information acquisition unit 11, an assumed information acquisition unit 12, and a calculation unit 13, which are provided by the information processing device 1, as well as an output unit 14. The output unit 14 is an example of a configuration that realizes an output means. The storage unit 120 stores the calculation model.

[0027] The communication unit 130 communicates with external devices of the information processing device 1A via a communication line. 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.

[0028] The input unit 140 is configured to receive input to the information processing device 1A, and may include, for example, an input device such as a keyboard, mouse, touch panel, camera, or microphone. The display unit 150 is configured to display the screen output from the information processing device 1A, and may include, for example, a display. The input unit 140 and the display unit 150 may also be integrally formed as a touch panel or the like. Furthermore, one or both of the input unit 140 and the display unit 150 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).

[0029] (Functional block of the control unit 110) The current information acquisition unit 11 is configured in the same manner as in the exemplary embodiment 1. In this exemplary embodiment, the current information acquired by the current information acquisition unit 11 includes sales volume, current stockout rate, downward pressure ratio of demand, cost ratio, production / procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs.

[0030] Sales volume may be, for example, annual sales figures, or sales figures for other unit periods. The demand downside ratio indicates the percentage of actual demand that fell short of the forecast. The cost ratio indicates the ratio of cost to sales revenue of the product. Production and procurement lead time includes the period from the start of production to completion, and the period required for delivery from the production site to the consumption site. If there are multiple products, it may be a statistical value (average, minimum, maximum) of the production and procurement lead time for each product. Storage-related expenses indicate costs related to the storage of goods, and may include, for example, costs related to storage locations (warehouses, etc.). Specific examples of transportation-related expenses include, but are not limited to, intra-company transportation costs and sales transportation costs. Personnel-related expenses include personnel costs related to demand forecasting for the product. Specific examples of personnel-related expenses include, but are not limited to, the unit price of managers involved in demand forecasting, the unit price of demand planners involved in demand forecasting, the time required to calculate demand forecast accuracy, the forecasting work hours of managers or demand planners, and the number of demand planners.

[0031] The assumed information acquisition unit 12 is configured in the same manner as in the exemplary embodiment 1. In this exemplary embodiment, among the assumed information acquired by the assumed information acquisition unit 12, the accuracy improvement information includes the assumed improvement rate of demand forecast accuracy that is expected to be achieved by each of the multiple actions that can be taken to improve demand forecast accuracy. The "assumed improvement rate of demand forecast accuracy" will also be referred to as the "assumed improvement rate of demand forecast accuracy" below.

[0032] Actions include, but are not limited to, the use of accuracy management functions to manage the accuracy of demand forecasts, the use of demand fluctuation alert functions to provide alerts based on demand fluctuations, and the use of LLM error analysis functions to support error analysis of demand forecasts using LLM (Large-Scale Language Models). For example, in the accuracy management function, a screen visualizing various indicators for managing the accuracy of demand forecasts may be displayed on the user terminal. In the demand fluctuation alert function, an alert may be issued when the various indicators meet certain conditions. In the LLM error analysis function, for example, examples of interpretations using LLM for the various indicators may be provided. Other examples of actions include improving the demand forecasting model and introducing a demand forecasting system. However, the types and content of actions are not limited to the examples given above.

[0033] Furthermore, in this exemplary embodiment, the current improvement information among the assumed information acquisition unit 12 acquires includes part or all of the assumed improvement rate for stockouts and the assumed reduction rate for work hours. The assumed improvement rate for stockouts indicates the degree of improvement expected in the stockout rate if demand forecasting accuracy were to improve. The assumed reduction rate for work hours indicates the degree to which work hours related to demand forecasting would be reduced if demand forecasting accuracy were to improve.

[0034] Furthermore, the assumed information acquired by the assumed information acquisition unit 12 may include, in addition to accuracy improvement information and current situation improvement information, other information related to costs associated with the distribution of goods. Examples of such other information include, but are not limited to, the degree to which stockouts lead to lost opportunities and the procurement and transportation costs of goods.

[0035] Furthermore, when both current information and projected information are obtained through user input, current information is information that users can easily input based on records, etc., whereas projected information is information that needs to be inferred and input because it concerns the future or because records are difficult to obtain. For example, such inferences may be made by a person or by a computer.

[0036] The estimation unit 13 is configured in the same manner as in Exemplary Embodiment 1. In this exemplary embodiment, the estimation unit 13 estimates the effect amount for each of the multiple actions. The details of the actions are as described above and will not be repeated. The estimation unit 13 also estimates the effect amount for each of the multiple effects. Here, the effect of improving demand forecasting accuracy includes, as multiple effects, some or all of the effect of reducing opportunity loss, the effect of reducing inventory, the effect of reducing storage and logistics costs, and the effect of improving operational efficiency. The estimation unit 13 estimates the effect amount by using the estimation model described later.

[0037] The output unit 14 outputs the effect amount. For example, the output unit 14 may display a screen including the effect amount on the display unit 150. Alternatively, for example, the output unit 14 may output a breakdown of the effect amount based on multiple actions. Alternatively, for example, the output unit 14 may output a breakdown of the effect amount based on multiple effects.

[0038] (Calculation model) The estimation model is a model that takes current information and assumed information as input and outputs the effect amount. For example, it may be a set of function expressions or a machine learning model. For example, the estimation model may be configured to output the effect amount for each of multiple actions. Alternatively, the estimation model may be configured to output the effect amount for each of multiple effects.

[0039] (Information processing method S1A flow) The information processing device 1A, configured as described above, executes the information processing method S1A. Figure 4 is a flowchart showing the flow of the information processing method S1A. As shown in Figure 4, the information processing method S1A includes steps S101 to S105.

[0040] Step S101 is an example of the current information acquisition process. In step S101, the current information acquisition unit 11 acquires the current information. Step S102 is an example of the expected information acquisition process. In step S102, the expected information acquisition unit 12 acquires the expected information. Note that the processes in steps S101 and S102 are not limited to being executed in this order, but may be performed in a different order, or at least partially in parallel.

[0041] Figure 5 shows an example of the screen displayed on the display unit 150 in steps S101 to S102. In the example screen 1 shown in Figure 5, area G11 is the area for inputting current information. Area G12 is the area for inputting assumed information.

[0042] Input objects G11a to G11f are, for example, text fields, and specifically, the following current information is entered into them: Input object G11a contains the annual sales volume. Input object G11b contains the current stockout rate. Input object G11c contains the percentage of demand underscores. Input object G11d contains the number of demand planners. Input object G11e contains the weekly working hours related to demand forecasting. Input object G11f contains the time spent calculating indicators for managing demand forecasting accuracy. Input objects G11a to G11f exemplified in area G11 are just examples, and other input objects for entering current information may be included in area G11. Also, input objects G11a to G11f are not limited to text fields; they may also be numerical selection lists, etc., but are not limited to these.

[0043] Input objects G12a to G12d are, for example, text fields, and specifically, the following assumed information is entered: Input object G12a contains the assumed improvement rate of demand forecast accuracy if the accuracy management function is hypothetically utilized as an action. Input object G12b contains the assumed improvement rate of demand forecast accuracy if the demand fluctuation alert function is hypothetically utilized as an action. Input object G12c contains the assumed improvement rate of demand forecast accuracy if the LLM error analysis function is hypothetically utilized as an action. Input object G12d contains the assumed improvement rate of stockouts if demand forecast accuracy is hypothetically improved. Input objects G12a to G12d exemplified in area G12 are just examples, and area G12 may contain input objects for entering other assumed information. Also, input objects G12a to G12d are not limited to text fields, but may also be selection lists that allow users to select desired options, etc., but are not limited to these.

[0044] Furthermore, in the example screen G1, the operation object G13 accepts an operation to instruct the calculation of the effect amount. This concludes the explanation of the example screen G1, and we will refer back to Figure 4 to continue the explanation from step S103 onwards.

[0045] Steps S103 and S104 in Figure 4 are an example of the calculation process. In step S103, the calculation unit 13 calculates the effect amount for each of the multiple actions. As an example, the calculation unit 13 inputs current information and assumed information into the calculation model to obtain the effect amount for each action output from the calculation model.

[0046] In step S104, the calculation unit 13 calculates the effect amount for each of the multiple effects. As an example, the calculation unit 13 inputs current information and assumed information into the calculation model to obtain the effect amount for each effect output from the calculation model. Note that the processes in steps S103 and S104 are not limited to being executed in this order, and may be performed in a different order, or at least partially in parallel.

[0047] Step S105 is an example of output processing. In step S105, the output unit 14 outputs the effect amount and a breakdown of the effect amount. For example, the output unit 14 may output a breakdown of the effect amount based on each action, a breakdown of the effect amount based on each effect, and the sum of these effect amounts.

[0048] Figure 6 shows an example of a screen displayed on the display unit 150 in step S105. Screen example 2 shown in Figure 6 is displayed in response to the operation object G13 receiving an operation in screen example G1. In other words, when the operation object G13 is operated, the screen of the display unit 150 transitions from screen example G1 to screen example G2. In screen example G2, table G21 is a table showing the breakdown and total of effect amounts, with multiple actions on the vertical axis and multiple effects on the horizontal axis. In screen example G2, the multiple actions applied are the utilization of the accuracy management function, the utilization of the demand fluctuation alert function, and the utilization of the LLM error analysis function as described above. In addition, the multiple effects applied are the effects from reducing opportunity losses, the effects from reducing inventory, the effects from reducing storage and logistics costs, and the effects from improving operational efficiency as described above. Furthermore, graph G22 visualizes the breakdown of effect amounts by action based on table G21. Furthermore, graph G23 visualizes the breakdown of effect amounts by effect based on table G21. Screen example G2 allows users to understand in detail, as concrete monetary values, the multiple effects obtained by taking each action that improves demand forecasting accuracy.

[0049] Furthermore, the calculation unit 13 may calculate the effect amount for each predetermined classification, and the output unit 14 may output the effect amounts for classifications that affect the balance sheet and those that affect the income statement in a way that allows for identification. For example, the predetermined classifications may be classifications based on the actions described above, or classifications based on the effects described above. For example, in table G21 of screen example G2, cells that affect the balance sheet and cells that affect the income statement may be displayed in different ways (e.g., different colors, different patterns, etc.).

[0050] (Effects of information processing equipment) As described above, the information processing device 1A further includes an output unit 14 that outputs the amount of effect, and the accuracy improvement information includes the expected improvement rate of demand forecast accuracy expected from each of the multiple actions that can be taken to improve demand forecast accuracy, the calculation unit 13 calculates the amount of effect for each of the multiple actions, and the output unit 14 outputs a breakdown of the amount of effect based on the multiple actions.Therefore, with the information processing device 1A, in addition to the effect achieved by the information processing device 1, the user can specifically recognize in monetary terms how much effect each action has when each action is taken to improve demand forecast accuracy.

[0051] Furthermore, the information processing device 1A is further equipped with an output unit 14 that outputs the amount of the effect, and the effect includes some or all of the effects of reducing opportunity losses, reducing inventory, reducing storage and logistics costs, and improving operational efficiency as multiple effects, and the estimation unit 13 estimates the amount of the effect for each of the multiple effects, and the output unit 14 outputs a breakdown of the amount of the effect based on the multiple effects.Therefore, with the information processing device 1A, in addition to the effect achieved by the information processing device 1, the user can specifically recognize in monetary terms how much of each of the multiple effects will result from the improvement in demand forecasting accuracy.

[0052] Furthermore, the information processing device 1A is further equipped with an output unit 14 that outputs the amount of effect, and the estimation unit 13 estimates the amount of effect for each predetermined classification, and the output unit 14 outputs the amount of effect for classifications that affect the balance sheet and the amount of effect for classifications that affect the income statement in a distinguishable manner. As a result, with the information processing device 1A, in addition to the effects achieved by the information processing device 1, the user can specifically recognize in monetary terms the extent to which the improvement in demand forecasting accuracy affects the balance sheet and the income statement.

[0053] Furthermore, the information processing device 1A employs a configuration in which current information includes sales volume, current stockout rate, downward pressure on demand, cost ratio, production and procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs. Therefore, in addition to the effects achieved by the information processing device 1, the information processing device 1A provides the effect of being able to estimate the amount of the effect with greater accuracy.

[0054] Furthermore, the information processing device 1A employs a configuration in which the current improvement information includes part or all of the expected improvement rate for stock shortages and the expected reduction rate for working hours. Therefore, with the information processing device 1A, in addition to the effects achieved by the information processing device 1, it is possible to estimate the amount of the effect with greater accuracy.

[0055] (modified version) The information processing devices 1 and 1A are not limited to a single computer, but may be composed of multiple computers. For example, the information processing devices 1 and 1A may include a server and a user terminal connected via a network. In this case, for example, the user terminal may acquire current information and projected information and transmit it to the server, the server may transmit the estimated effect amount calculated based on the current information and projected information to the user terminal, and the user terminal may display the effect amount.

[0056] [Examples of implementation using software] Some or all of the functions of the information processing devices 1 and 1A (hereinafter also referred to as "the above devices") may be implemented by hardware such as integrated circuits (IC chips) or by software.

[0057] 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 7. Figure 7 is a block diagram showing the hardware configuration of Computer C, which functions as each of the above devices.

[0058] 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.

[0059] 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.

[0060] 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.

[0061] 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.

[0062] 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.

[0063] [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.

[0064] (Note A1) A means for acquiring current information related to the current state of costs involved in the distribution of goods, An assumed information acquisition means for acquiring assumed information including accuracy improvement information indicating the expected degree of improvement in the demand forecasting accuracy for the said product, and current improvement information indicating the expected degree of improvement in the said current information, A calculation means for estimating the effect amount, which represents the effect of improving the accuracy of the demand forecast, based on the aforementioned current information and the aforementioned assumed information, An information processing device equipped with the following features.

[0065] (Appendix A2) The system further includes an output means for outputting the aforementioned effect amount, The accuracy improvement information includes the expected improvement rate of the demand forecast accuracy that can be expected from each of the multiple actions that can be taken to improve the demand forecast accuracy, The aforementioned calculation means calculates the amount of the effect for each of the multiple actions, The output means outputs a breakdown of the effect amount based on the multiple actions. The information processing device described in Appendix A1.

[0066] (Note A3) The system further includes an output means for outputting the aforementioned effect amount, The aforementioned effects include, in part or in whole, some of the effects of reducing opportunity losses, reducing inventory, reducing storage and logistics costs, and improving operational efficiency. The estimation means estimates the amount of the effect for each of the multiple effects, The output means outputs a breakdown of the effect amount based on the multiple effects. The information processing device described in Appendix A1 or A2.

[0067] (Note A4) The system further includes an output means for outputting the aforementioned effect amount, The aforementioned calculation means calculates the amount of the effect for each predetermined classification, The output means outputs, in a manner that allows for the identification of the effect amounts of classifications that affect the balance sheet and the effect amounts of classifications that affect the income statement. An information processing device as described in any one of the appendices A1 to A3.

[0068] (Note A5) The aforementioned current information includes sales volume, current stockout rate, percentage of downward demand, cost ratio, production / procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs. An information processing device as described in any one of the appendices A1 to A4.

[0069] (Note A6) The aforementioned information on current improvements includes, in part or in whole, the expected improvement rate of stock shortages and the expected reduction rate of working hours. An information processing device as described in any one of the appendices A1 to A5.

[0070] [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.

[0071] (Note B1) At least one processor performs a current information acquisition process to acquire current information related to the current cost of goods distribution, The at least one processor performs an assumption information acquisition process which acquires assumption information including accuracy improvement information indicating the expected degree of improvement in the demand forecasting accuracy for the product, and current improvement information indicating the expected degree of improvement in the current information. The at least one processor performs an estimation process to estimate the effect amount, which represents the effect of improving the accuracy of the demand forecast, based on the current information and the assumed information. Information processing methods including

[0072] (Note B2) The at least one processor further includes output processing to output the amount of the effect, The accuracy improvement information includes the expected improvement rate of the demand forecast accuracy that can be expected from each of the multiple actions that can be taken to improve the demand forecast accuracy, In the calculation process described above, the at least one processor calculates the effect amount for each of the multiple actions, In the output processing, the at least one processor outputs a breakdown of the effect amount based on the plurality of actions. The information processing method described in Appendix B1.

[0073] (Note B3) The at least one processor further includes output processing to output the amount of the effect, The aforementioned effects include, in part or in whole, some of the effects of reducing opportunity losses, reducing inventory, reducing storage and logistics costs, and improving operational efficiency. In the calculation process described above, the at least one processor calculates the amount of the effect for each of the multiple effects, In the output processing, the at least one processor outputs a breakdown of the effect amount based on the plurality of effects. The information processing method described in Appendix B1 or B2.

[0074] (Note B4) The at least one processor further includes output processing to output the amount of the effect, In the calculation process described above, at least one processor calculates the effect amount for each predetermined classification, In the output processing described above, the at least one processor outputs, in a manner that allows for the identification of the effect amounts of classifications that affect the balance sheet and the effect amounts of classifications that affect the income statement. The information processing method described in any one of the appendices B1 to B3.

[0075] (Note B5) The aforementioned current information includes sales volume, current stockout rate, percentage of downward demand, cost ratio, production / procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs. The information processing method described in any one of the appendices B1 to B4.

[0076] (Note B6) The aforementioned information on current improvements includes, in part or in whole, the expected improvement rate of stock shortages and the expected reduction rate of working hours. The information processing method described in any one of the appendices B1 through B5.

[0077] [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.

[0078] (Note C1) A program that makes a computer function as an information processing device. The aforementioned computer, A means for acquiring current information related to the current state of costs involved in the distribution of goods, An assumed information acquisition means for acquiring assumed information including accuracy improvement information indicating the expected degree of improvement in the demand forecasting accuracy for the said product, and current improvement information indicating the expected degree of improvement in the said current information, A calculation means for estimating the effect amount, which represents the effect of improving the accuracy of the demand forecast, based on the aforementioned current information and the aforementioned assumed information, An information processing program that functions as such.

[0079] (Note C2) The aforementioned computer, The aforementioned effect amount is further configured to function as an output means for outputting the effect amount. The accuracy improvement information includes the expected improvement rate of the demand forecast accuracy that can be expected from each of the multiple actions that can be taken to improve the demand forecast accuracy, The aforementioned calculation means calculates the amount of the effect for each of the multiple actions, The output means outputs a breakdown of the effect amount based on the multiple actions. The information processing program described in Appendix C1.

[0080] (Note C3) The aforementioned computer, The aforementioned effect amount is further configured to function as an output means for outputting the effect amount. The aforementioned effects include, in part or in whole, some of the effects of reducing opportunity losses, reducing inventory, reducing storage and logistics costs, and improving operational efficiency. The estimation means estimates the amount of the effect for each of the multiple effects, The output means outputs a breakdown of the effect amount based on the multiple effects. The information processing program described in Appendix C1 or C2.

[0081] (Note C4) The aforementioned computer, The aforementioned effect amount is further configured to function as an output means for outputting the effect amount. The aforementioned calculation means calculates the amount of the effect for each predetermined classification, The output means outputs, in a manner that allows for the identification of the effect amounts of classifications that affect the balance sheet and the effect amounts of classifications that affect the income statement. An information processing program described in any one of the appendices C1 to C3.

[0082] (Note C5) The aforementioned current information includes sales volume, current stockout rate, percentage of downward demand, cost ratio, production / procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs. An information processing program described in any one of the appendices C1 to C4.

[0083] (Appendix C6) The aforementioned information on current improvements includes, in part or in whole, the expected improvement rate of stock shortages and the expected reduction rate of working hours. An information processing program described in any one of the appendices C1 to C5.

[0084] [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.

[0085] (Note D1) It comprises at least one processor, and the at least one processor is A current information acquisition process that acquires current information related to the current cost of product distribution, An assumption information acquisition process that acquires assumption information including accuracy improvement information indicating the expected degree of improvement in the demand forecast accuracy for the said product, and current situation improvement information indicating the expected degree of improvement in the said current situation information, Based on the aforementioned current information and the aforementioned assumed information, a calculation process is performed to estimate the effect amount, which represents the effect of improving the accuracy of the demand forecast as a monetary value. An information processing device that performs the following actions.

[0086] The information processing device may also include memory. Furthermore, the memory may store a program that causes at least one processor to execute each of the aforementioned processes.

[0087] (Note D2) The aforementioned at least one processor, Further output processing is performed to output the aforementioned effect amount. The accuracy improvement information includes the expected improvement rate of the demand forecast accuracy that can be expected from each of the multiple actions that can be taken to improve the demand forecast accuracy, In the calculation process described above, the at least one processor calculates the effect amount for each of the multiple actions, In the output processing, the at least one processor outputs a breakdown of the effect amount based on the plurality of actions. The information processing device described in Appendix D1.

[0088] (Note D3) The aforementioned at least one processor, Further output processing is performed to output the aforementioned effect amount. The aforementioned effects include, in part or in whole, some of the effects of reducing opportunity losses, reducing inventory, reducing storage and logistics costs, and improving operational efficiency. In the calculation process described above, the at least one processor calculates the amount of the effect for each of the multiple effects, In the output processing, the at least one processor outputs a breakdown of the effect amount based on the plurality of effects. The information processing device described in Appendix D1 or D2.

[0089] (Note D4) The aforementioned at least one processor, Further output processing is performed to output the aforementioned effect amount. In the calculation process described above, at least one processor calculates the effect amount for each predetermined classification, In the output processing described above, the at least one processor outputs, in a manner that allows for the identification of the effect amounts of classifications that affect the balance sheet and the effect amounts of classifications that affect the income statement. An information processing device as described in any one of the appendices D1 to D3.

[0090] (Note D5) The aforementioned current information includes sales volume, current stockout rate, percentage of downward demand, cost ratio, production / procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs. Information processing devices as described in Appendix D1 to D4.

[0091] (Note D6) The aforementioned information on current improvements includes, in part or in whole, the expected improvement rate of stock shortages and the expected reduction rate of working hours. An information processing device as described in any one of the appendices D1 to D5.

[0092] [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.

[0093] (Note E1) A program that makes a computer function as an information processing device. To the aforementioned computer, A current information acquisition process that acquires current information related to the current cost of product distribution, An assumption information acquisition process that acquires assumption information including accuracy improvement information indicating the expected degree of improvement in the demand forecast accuracy for the said product, and current situation improvement information indicating the expected degree of improvement in the said current situation information, Based on the aforementioned current information and the aforementioned assumed information, a calculation process is performed to estimate the effect amount, which represents the effect of improving the accuracy of the demand forecast as a monetary value. A non-temporary recording medium that stores an information processing program that executes that program. [Explanation of Symbols]

[0094] 1. 1A Information Processing Device 11 Current Information Acquisition Unit 12. Unit for acquiring assumed information 13. Estimation Department 14 Output section 20 User Terminals 110 Control Unit 120 Storage section 130 Communications Department 140 Input section 150 Display section C1 Processor C2 Memory

Claims

1. A means for acquiring current information related to the current state of costs involved in the distribution of goods, An assumed information acquisition means for acquiring assumed information including accuracy improvement information indicating the expected degree of improvement in the demand forecasting accuracy for the said product, and current improvement information indicating the expected degree of improvement in the said current information, A calculation means for estimating the effect amount, which represents the effect of improving the accuracy of the demand forecast, based on the aforementioned current information and the aforementioned assumed information, An information processing device equipped with the following features.

2. The system further includes an output means for outputting the aforementioned effect amount, The accuracy improvement information includes the expected improvement rate of the demand forecast accuracy that can be expected from each of the multiple actions that can be taken to improve the demand forecast accuracy, The aforementioned calculation means calculates the amount of the effect for each of the multiple actions, The output means outputs a breakdown of the effect amount based on the multiple actions. The information processing apparatus according to claim 1.

3. The system further includes an output means for outputting the aforementioned effect amount, The aforementioned effects include, in part or in whole, some of the effects of reducing opportunity losses, reducing inventory, reducing storage and logistics costs, and improving operational efficiency. The estimation means estimates the amount of the effect for each of the multiple effects, The output means outputs a breakdown of the effect amount based on the multiple effects. The information processing apparatus according to claim 1.

4. The system further includes an output means for outputting the aforementioned effect amount, The aforementioned calculation means calculates the amount of the effect for each predetermined classification, The output means outputs, in a manner that allows for the identification of the effect amounts of classifications that affect the balance sheet and the effect amounts of classifications that affect the income statement. The information processing apparatus according to claim 1.

5. The aforementioned current information includes sales volume, current stockout rate, percentage of downward demand, cost ratio, production / procurement lead time, storage-related costs, transportation-related costs, and some or all of the personnel-related costs. The information processing apparatus according to claim 1.

6. The aforementioned information on current improvements includes, in part or in whole, the expected improvement rate of stock shortages and the expected reduction rate of working hours. The information processing apparatus according to claim 1.

7. At least one processor performs a current information acquisition process to acquire current information related to the current cost of goods distribution, The at least one processor performs an assumption information acquisition process which acquires assumption information including accuracy improvement information indicating the expected degree of improvement in the demand forecasting accuracy for the product, and current improvement information indicating the expected degree of improvement in the current information. The at least one processor performs an estimation process to estimate the effect amount, which represents the effect of improving the accuracy of the demand forecast, based on the current information and the assumed information. Information processing methods including

8. Computers, A means for acquiring current information related to the current state of costs involved in the distribution of goods, An assumed information acquisition means for acquiring assumed information including accuracy improvement information indicating the expected degree of improvement in the demand forecasting accuracy for the said product, and current improvement information indicating the expected degree of improvement in the said current information, A calculation means for estimating the effect amount, which represents the effect of improving the accuracy of the demand forecast, based on the aforementioned current information and the aforementioned assumed information, An information processing program that functions as such.

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