Demand forecasting device, demand forecasting method, and demand forecasting program

Abstract

A future inventory prediction unit (22) estimates a future inventory quantity at a supply destination of an article that is subject to prediction under the assumption that, at the supply destination, inventory increases due to orders being placed in accordance with an order placement condition and order quantity indicated by order placement model information (61), and inventory decreases in accordance with a transition of a past inventory quantity indicated by past inventory information (62). A demand prediction unit (23) predicts that demand for the order quantity indicated by the order placement model information (61) occurs at a supplier at the point in time when the order placement condition indicated by the order placement model information (61) is satisfied in the future inventory quantity estimated by the future inventory estimation unit (22).

Description

[Technical field]

[0001] The present disclosure relates to technology for predicting demand. [Background technology]

[0002] In supply chains in the manufacturing or agricultural industries, a series of commercial transactions from the procurement of raw materials to the sale of the final product are carried out by multiple businesses. In these supply chains, methods for predicting demand for products are being considered with the aim of reducing inventory management costs. Here, forecasting demand means predicting future order amounts from product suppliers. Hereinafter, forecasting demand will be referred to as demand forecasting.

[0003] In general demand forecasting technology, predictions are made by learning time-series data such as past order records. Patent Document 1 describes a technology that improves the accuracy of demand forecasting by learning past demand generation trends from order records and adjusting the demand forecasting method. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2022-101879 A Summary of the Invention [Problem to be solved by the invention]

[0005] The method described in Patent Document 1, which estimates long-term trends in demand, such as seasonality or periodicity, from order receipt data and makes forecasts based on these estimates, is unable to make demand forecasts that track small daily fluctuations in demand. The present disclosure aims to enable demand forecasting that tracks small daily fluctuations in demand. [Means for solving the problem]

[0006] The demand forecasting device according to the present disclosure comprises: a future inventory estimation unit that estimates a future inventory amount at a destination of the prediction target product by assuming that an order is placed in accordance with the order conditions and order amount indicated by the order model information, thereby increasing inventory, and that the inventory decreases in accordance with the change in the past inventory amount indicated by the past inventory information; a demand forecasting unit that forecasts that a demand for an order amount indicated by the ordering model information will occur at a supplier at a time point when the ordering condition indicated by the ordering model information is satisfied in the future inventory amount estimated by the future inventory estimation unit; Equipped with. Effect of the Invention

[0007] In the present disclosure, future inventory levels are estimated using past inventory level trends, and demand is predicted from the future inventory levels. This makes it possible to perform demand prediction that tracks small daily demand fluctuations by taking into account recent inventory level fluctuations. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is an explanatory diagram of a target of demand forecasting according to the first embodiment. [Diagram 2] FIG. 1 is a configuration diagram of a demand forecasting system 100 according to a first embodiment. [Diagram 3] FIG. 1 is a configuration diagram of a demand forecasting device 10 according to a first embodiment. [Figure 4] 5 is a flowchart of an input reception process according to the first embodiment. [Diagram 5] FIG. 6 is an explanatory diagram of ordering model information 61 according to the first embodiment. [Figure 6] FIG. 4 is an explanatory diagram of past stock information 62 according to the first embodiment. [Figure 7] 4 is a flowchart of a process at the time of demand forecasting according to the first embodiment. [Figure 8] FIG. 4 is an explanatory diagram of a future stock estimation process according to the first embodiment. [Figure 9] FIG. 6 is an explanatory diagram of a demand forecast result 64 according to the first embodiment. [Figure 10] FIG. 2 is a configuration diagram of a demand forecasting device 10 according to a first modified example. [Figure 11] FIG. 11 is a configuration diagram of a demand forecasting device 10 according to a second embodiment. [Figure 12] FIG. 11 is an explanatory diagram of commercial flow structure information 65 according to the second embodiment. [Figure 13] 13 is a flowchart of a process at the time of demand forecasting according to the second embodiment. [Figure 14] FIG. 11 is an explanatory diagram of a future stock estimation process according to the second embodiment. [Figure 15] FIG. 11 is an explanatory diagram of a target of demand forecasting according to the second embodiment. [Figure 16] FIG. 11 is a configuration diagram of a demand forecasting device 10 according to a third embodiment. [Figure 17] FIG. 13 is an explanatory diagram of logistics information 66 according to the third embodiment. [Figure 18] 13 is a flowchart of a process at the time of demand forecasting according to the third embodiment. [Figure 19] FIG. 13 is an explanatory diagram of a past stock estimation process according to the third embodiment. [Figure 20] FIG. 11 is a configuration diagram of a demand forecasting device 10 according to a fourth embodiment. [Figure 21] FIG. 13 is an explanatory diagram of part configuration information 68 according to the fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Embodiment 1 In the first embodiment, the demand forecast is performed independently for each business operator and each product. Therefore, in the first embodiment, as shown in Fig. 1, the forecast target item, which is the item that is the subject of the demand forecast, is "Part A". Then, an example will be described in which the demand forecast is performed for the demand for "Part A" that arises from "Business A", which is the supply destination of "Part A", to "Business X", which is the supplier of "Part A". Here, when making a demand forecast for "Business B" or "Part B," it is possible to make the demand forecast using the same process as when making a demand forecast for "Part A" arising from "Business A" to "Business X."

[0010] In the first embodiment, the demand forecast can be performed for each unit period, which is an arbitrary time unit, such as daily or weekly. In the following, an example will be described in which the unit period is one day and the demand forecast is performed on a daily basis.

[0011] ***Configuration Description*** The configuration of the demand forecasting system 100 according to the first embodiment will be described with reference to FIG. The demand forecasting system 100 includes a demand forecasting device 10 , an input terminal 51 , and an output terminal 52 .

[0012] The demand forecasting device 10 is a computer such as a server. The demand forecasting device 10 receives order model information 61 and past inventory information 62 from an input terminal 51, performs demand forecasting, and outputs a demand forecast result 64 to an output terminal 52.

[0013] The input terminal 51 is a terminal for operating the demand forecasting device 10. Specific examples of the input terminal 51 include a PC, a tablet, a smartphone, and the like. PC is an abbreviation for Personal Computer. The demand forecasting device 10 may also function as the input terminal 51. Furthermore, there may be multiple input terminals 51.

[0014] The output terminal 52 is a terminal for outputting the processing contents by the demand forecasting device 10 to an inventory planner. Specific examples of the output terminal 52 include a PC, a tablet, a smartphone, and the like. The input terminal 51 may also serve as the output terminal 52. In addition, there may be multiple output terminals 52.

[0015] The configuration of the demand forecasting device 10 according to the first embodiment will be described with reference to FIG. The demand forecasting device 10 is a computer. The demand prediction device 10 includes the following hardware components: a processor 11, a memory 12, a storage 13, and a communication interface 14. The processor 11 is connected to other hardware components via signal lines and controls the other hardware components.

[0016] The processor 11 is an IC that performs processing. IC is an abbreviation for Integrated Circuit. Specific examples of the processor 11 include a CPU, a DSP, and a GPU. CPU is an abbreviation for Central Processing Unit. DSP is an abbreviation for Digital Signal Processor. GPU is an abbreviation for Graphics Processing Unit.

[0017] The memory 12 is a storage device that temporarily stores data. Specific examples of the memory 12 include SRAM and DRAM. SRAM is an abbreviation for Static Random Access Memory. DRAM is an abbreviation for Dynamic Random Access Memory.

[0018] The storage 13 is a storage device that stores data. A specific example of the storage 13 is an HDD. HDD is an abbreviation for Hard Disk Drive. The storage 13 may also be a portable recording medium such as an SD (registered trademark) memory card, CompactFlash (registered trademark), NAND flash, a flexible disk, an optical disk, a compact disk, a Blu-ray (registered trademark) disk, or a DVD. SD is an abbreviation for Secure Digital. DVD is an abbreviation for Digital Versatile Disk.

[0019] The communication interface 14 is an interface for communicating with an external device. Specific examples of the communication interface 14 include Ethernet (registered trademark), USB, and HDMI (registered trademark) ports. USB is an abbreviation for Universal Serial Bus. HDMI is an abbreviation for High-Definition Multimedia Interface.

[0020] The demand forecasting device 10 includes, as functional components, a reception unit 21, a future stock estimation unit 22, a demand forecasting unit 23, and an output unit 24. The functions of the functional components of the demand forecasting device 10 are realized by software. The storage 13 stores a program that realizes the function of each functional component of the demand prediction device 10. The program is loaded into the memory 12 by the processor 11 and executed by the processor 11. In this way, the function of each functional component of the demand prediction device 10 is realized.

[0021] In the process of operation of the demand forecasting device 10, the storage 13 stores order model information 61, past stock information 62, future stock information 63, and demand forecast results 64.

[0022] 3 shows only one processor 11. However, there may be a plurality of processors 11, and the plurality of processors 11 may cooperate to execute programs that realize the respective functions.

[0023] ***Explanation of Operation*** The operation of the demand forecasting device 10 according to the first embodiment will be described with reference to FIGS. An operation procedure of the demand forecasting device 10 according to the embodiment 1 corresponds to a demand forecasting method according to the embodiment 1. Moreover, a program for realizing the operation of the demand forecasting device 10 according to the embodiment 1 corresponds to a demand forecasting program according to the embodiment 1.

[0024] The operation of the demand forecasting device 10 includes processing at the time of input reception and processing at the time of demand forecasting.

[0025] The input reception process according to the first embodiment will be described with reference to FIG. (Step S101: Reception process) The reception unit 21 receives input of the order model information 61 and past stock information 62 from the input terminal 51. However, the order model information 61 is necessary only at the first reception, and the reception unit 21 does not necessarily need to receive the order model information 61 every time the input reception process is executed.

[0026] The ordering model information 61 according to the first embodiment will be described with reference to FIG. The ordering model information 61 includes one or more sets of business name, ordering model, ordering conditions, order quantity, and procurement lead time. The ordering conditions are conditions for placing an order, and an order is placed when the ordering conditions are met. The order quantity is the amount to be ordered when the ordering conditions are met. The procurement lead time is the period from when an order for a product is placed to when the product arrives and is managed as inventory. For example, assume that business operator A's ordering model is the reorder point method. In this case, information corresponding to the reorder point method includes an order point indicating ordering conditions and an order quantity. Therefore, a set of information on business operator A, the reorder point method, the reorder point and order quantity, and the procurement lead time is set in the ordering model information 61. The reorder point method is an ordering method in which an order is placed when the inventory level falls below a certain threshold value called the reorder point.

[0027] With reference to FIG. 6, the past stock information 62 according to the first embodiment will be described. The past stock information 62 includes one or more pairs of a date, a business name, a product name, and a stock amount.

[0028] (Step S102: Storage process) The reception unit 21 writes the order model information 61 and past stock information 62 to the storage 13. However, the order model information 61 is recorded only when it is received in step S101. In this embodiment, the ordering model information 61 and the past stock information 62 are written to the storage 13. However, the ordering model information 61 and the past stock information 62 may be written to a storage device provided outside the demand forecasting device 10, instead of the storage 13.

[0029] The demand forecasting process according to the first embodiment will be described with reference to FIG. (Step S201: Read process) The future stock estimation unit 22 reads out information on business operator A, which is a supply destination of part A, which is the prediction target product, from the order model information 61 stored in the storage 13. Specifically, the future stock estimation unit 22 reads out the order model, order point, order amount, and procurement lead time of business operator A. In addition, the future stock estimation unit 22 reads out information on the stock amount of part A of the supply destination business operator A from the past stock information 62 stored in the storage 13. Specifically, the future stock estimation unit 22 reads out the date and stock amount of part A of business operator A for the most recent reference period.

[0030] (Step S202: Future inventory estimation process) The future stock estimation unit 22 estimates the future stock amount at the supply destination, business operator A, based on the ordering model information 61 and past stock information 62 read out in step S201. At this time, the future stock estimation unit 22 estimates the future stock amount by assuming that the inventory will increase as a result of ordering at business operator A according to the ordering conditions and order amounts indicated in the ordering model information 61, and that the inventory will decrease in accordance with the trend in the past stock amount indicated in the past stock information 62. In the case of business operator A, the ordering conditions are the ordering point.

[0031] This will be specifically described with reference to FIG. The future stock estimation unit 22 calculates the transition of the future stock amount for each day during the prediction period starting from the day after the day to which the process is executed, based on the order model information 61 and the past stock information 62 read in step S201. Then, the future stock estimation unit 22 writes the transition of the future stock amount for each day in the storage 13 as future stock information 63. The future inventory estimation unit 22 sets each day in the prediction period starting from the day after the day to which the processing execution time belongs as the target day, in order from the oldest to the newest. The future inventory estimation unit 22 calculates the inventory amount on the target day by adding the inventory amount that will increase on the target day to the inventory amount on the day before the target day, and subtracting the inventory amount that will decrease on the target day. In this way, the future inventory estimation unit 22 estimates the inventory amount for each day during the prediction period. If the ordering conditions are met on the day before the target day by the procurement lead time, the future inventory estimation unit 22 sets the order quantity to be the inventory amount to be increased on the target day. Here, since the ordering model is the reorder point method, if the inventory amount on the day before the procurement lead time is equal to or less than the reorder point indicated by the ordering model information 61, the inventory amount to be increased is an amount equal to the order quantity indicated by the ordering model information 61. If the ordering conditions are not met on the day before the target day by the procurement lead time, the future inventory estimation unit 22 sets the inventory amount to be increased on the target day to 0. The future stock estimation unit 22 calculates a statistical value of the amount of inventory decrease per day from the transition of the amount of inventory for the most recent reference period read in step S201. The future stock estimation unit 22 assumes that the statistical value is the amount of inventory decrease on the target day. Values ​​such as the average value and the median value are used as the statistical value.

[0032] (Step S203: Demand forecast processing) The demand forecasting unit 23 calculates a demand forecast value for each day during the forecast period. Then, the demand forecasting unit 23 writes the demand forecast value for each day into the storage 13 as a demand forecast result 64. As shown in Fig. 9, the demand forecast result 64 includes a set of a date, a business name, a product name, and a demand amount. Specifically, the demand forecasting unit 23 predicts that when the future inventory amount estimated in step S202 satisfies the ordering conditions indicated by the ordering model information 61, demand for the order amount indicated by the ordering model information 61 will arise for the supplier, business operator X.

[0033] (Step S204: Output process) The output unit 24 outputs the demand forecast result 64 to the output terminal 52 .

[0034] ***Advantages of the First Embodiment*** As described above, the demand forecasting device 10 according to the first embodiment estimates future inventory amounts using past changes in inventory amounts, and forecasts demand from the future inventory amounts. This makes it possible to perform demand forecasting that tracks small daily demand fluctuations by taking into account the most recent fluctuations in inventory amounts. That is, the demand forecasting device 10 does not forecast demand using the order record of business operator X, but forecasts demand based on daily inventory information of business operator A, which is the supply destination. This makes it possible to detect demand fluctuations before they are reflected in the order record and to follow small daily demand fluctuations. In other words, by taking into account the most recent fluctuations in inventory, it becomes possible to make highly accurate demand forecasts without waiting for the order record to accumulate, even when the market environment changes significantly.

[0035] ***Other configurations*** <Variation 1> In the first embodiment, each functional component is realized by software. However, as a first modification, each functional component may be realized by hardware. The following describes the first modification in terms of differences from the first embodiment.

[0036] The configuration of a demand forecasting device 10 according to the first modification will be described with reference to FIG. When each functional component is realized by hardware, the demand prediction device 10 includes an electronic circuit 15 instead of the processor 11, the memory 12, and the storage 13. The electronic circuit 15 is a dedicated circuit for realizing the functions of each functional component, the memory 12, and the storage 13.

[0037] The electronic circuit 15 may be a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, or an FPGA. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array. Each functional component may be realized by one electronic circuit 15, or each functional component may be distributed across multiple electronic circuits 15.

[0038] <Variation 2> As a second modification, some of the functional components may be realized by hardware, and other functional components may be realized by software.

[0039] The processor 11, the memory 12, the storage 13, and the electronic circuit 15 are collectively referred to as a processing circuit. In other words, the functions of the respective functional components are realized by the processing circuit.

[0040] Embodiment 2 The second embodiment differs from the first embodiment in that the inventory reduction amount is determined based on the result of demand forecast for downstream businesses in the flow between businesses of the forecast target product. In the second embodiment, this difference will be explained, and the explanation of the same points will be omitted.

[0041] ***Configuration Description*** The configuration of a demand forecasting device 10 according to the second embodiment will be described with reference to FIG. The demand forecasting device 10 differs from that shown in FIG.

[0042] ***Explanation of Operation*** The input reception process according to the second embodiment will be described with reference to FIG. (Step S101: Reception process) The reception unit 21 receives input of the order model information 61, past inventory information 62, and also commercial distribution structure information 65 from the input terminal 51. However, the order model information 61 is necessary only at the time of the initial reception, and the reception unit 21 does not necessarily need to receive the order model information 61 every time the input reception process is executed.

[0043] Referring to FIG. 12, the commercial flow structure information 65 according to the second embodiment will be described. The commercial distribution structure information 65 indicates the flow between businesses of part A, which is the prediction target product. The commercial distribution structure information 65 includes the name of the business, the name of the upstream business, and the name of the downstream business. The upstream business name indicates the business upstream of the business indicated by the business name. The downstream business name indicates the business downstream of the business indicated by the business name. The upstream business is the supplier that supplies part A to the business indicated by the business name. The downstream business is the supply destination to which the business indicated by the business name supplies part A.

[0044] (Step S102: Storage process) The reception unit 21 writes the commercial distribution structure information 65 in addition to the order model information 61 and past inventory information 62 to the storage 13. However, the order model information 61 is recorded only when it is received in step S101.

[0045] The demand forecasting process according to the second embodiment will be described with reference to FIG. (Step S211: Downstream search process) The future inventory estimation unit 22 refers to the trade distribution structure information 65 stored in the storage 13 and searches for businesses downstream of the business A that is the supply destination of the part A that is the target product for prediction. Specifically, the future stock estimation unit 22 identifies businesses indicated by the downstream business names of business A in the commercial flow structure information 65. The future stock estimation unit 22 identifies businesses indicated by the downstream business names of each identified business. This is repeated until there are no businesses indicated by downstream business names. This allows all businesses downstream of business A to be searched for. In the case of the commercial flow structure information 65 shown in Fig. 12, business operators C and D are identified as business operators downstream of business operator A. Business operator F is identified as a business operator downstream of business operator C. Since there is no business operator downstream of business operator D, the search is terminated. Since there is no business operator downstream of business operator F, the search is terminated.

[0046] (Step S212: Read process) The future stock estimation unit 22 reads out the order model information 61 and the past stock information 62 for the business operators (here, business operators C, D, and F) searched for in step S211, in addition to the business operator A. Specifically, the future stock estimation unit 22 sets business operator A and each business operator found in step S211 as the target business operators. The future stock estimation unit 22 reads out information on the target business operators from the ordering model information 61. In addition, the future stock estimation unit 22 reads out information on the inventory amount of part A of the target business operators from the past stock information 62.

[0047] The processes in steps S213 and S214 are executed by selecting target businesses in order starting from downstream businesses.

[0048] (Step S213: Future inventory estimation process) The future stock estimation unit 22 estimates the future stock amount of the target business operator based on the ordering model information 61 and the past stock information 62 read out in step S212. Specifically, the future stock estimation unit 22 sets each day in the prediction period starting from the day after the day to which the processing execution time belongs as the target day in order from the earliest day, as in the first embodiment. The future stock estimation unit 22 calculates the inventory amount on the target day by adding the inventory amount that will increase on the target day to the inventory amount on the day before the target day, and subtracting the inventory amount that will decrease on the target day. However, in the second embodiment, if there is no downstream business operator of the target business operator, the future stock estimation unit 22 takes the statistical value to be the amount of stock to be reduced on the target day, as in the first embodiment. On the other hand, if there is a downstream business operator of the target business operator, the future stock estimation unit 22 takes the demand of the business operator immediately downstream as the amount of stock to be reduced on the target day, as shown in FIG. 14. In FIG. 14, the ordering model is the reorder point method. Note that, if there are multiple business operators immediately downstream, the future stock estimation unit 22 takes the sum of the demands of the multiple business operators as the amount of stock to be reduced on the target day.

[0049] A specific example will be described with reference to FIG. Here, the target business operator is selected from downstream businesses. Therefore, first, business operator F or business operator D is selected as the target business operator. After the processing for business operator F is completed, business operator C is selected as the target business operator. After the processing for business operators C and D is completed, business operator A is selected as the target business operator.

[0050] For business operators F and D, there are no downstream business operators. Therefore, the daily inventory amount is calculated in the same manner as in embodiment 1. For business operators C and A, there are downstream business operators. Therefore, the demand of the business operators immediately downstream is treated as the inventory amount that decreases on the target day, and the daily inventory amount is calculated. When calculating business operator C's future inventory, the daily inventory reduction amount of business operator C is determined based on the results of a demand forecast for orders placed by business operator F to business operator C. When calculating business operator A's future inventory, the daily inventory reduction amount of business operator A is determined based on the results of a demand forecast for orders placed by business operators C and D to business operator A.

[0051] (Step S214: Demand forecast processing) The demand forecasting unit 23 predicts that when the future inventory amount estimated in step S213 satisfies the ordering conditions indicated by the ordering model information 61, demand for the order amount indicated by the ordering model information 61 will occur for the business operator immediately upstream.

[0052] The process in step S215 is the same as the process in step S204 in FIG.

[0053] ***Effects of the second embodiment*** As described above, the demand forecasting device 10 according to the second embodiment determines the inventory reduction amount based on the result of the demand forecast for the downstream business in the flow between business operators of the forecast target product. This makes it possible to accurately estimate the future inventory amount of the supply destination business operator. As a result, highly accurate demand forecasting becomes possible.

[0054] ***Other configurations*** <Variation 3> For downstream businesses of business A, demand forecasting may be performed using a known method other than the method described in the first and second embodiments. When forecasting demand from business A to business X, the demand from downstream businesses to business A, predicted by some method, may be used as the inventory reduction amount of business A.

[0055] Embodiment 3 The third embodiment differs from the second embodiment in that the inventory amount on the day to which the processing is to be performed is estimated by referring to the logistics information 66 indicating the transition that occurs in the logistics process for the prediction target item. In the third embodiment, this difference will be explained, and the explanation of the same points will be omitted. Here, a case where a function is added to the first embodiment will be described. However, it is also possible to add a function to the second embodiment.

[0056] ***Configuration Description*** The configuration of a demand forecasting device 10 according to the third embodiment will be described with reference to FIG. 3 in that the demand forecasting device 10 includes, as a functional component, a past stock estimation unit 25. The function of the past stock estimation unit 25 is realized by software or hardware, similar to the other functional components. 3 in that distribution information 66 and past inventory information 67 are stored in the storage 13.

[0057] ***Explanation of Operation*** The input reception process according to the third embodiment will be described with reference to FIG. (Step S101: Reception process) The reception unit 21 receives input of the order model information 61 and the logistics information 66 from the input terminal 51. However, the order model information 61 is necessary only at the first reception, and the reception unit 21 does not necessarily need to receive the order model information 61 every time the input reception process is executed.

[0058] The logistics information 66 according to the third embodiment will be described with reference to FIG. The logistics information 66 indicates the transitions that occur in the logistics process for the prediction target product. The logistics information 66 includes the date, the business name, the product name, the event name, and the quantity. Here, the event name is the name of the event. An event is a product transition that occurs in the logistics process, such as the production, shipping, and arrival of a product. The quantity is the number of products that transition in an event.

[0059] (Step S102: Storage process) The reception unit 21 writes the ordering model information 61 and the logistics information 66 into the storage 13. However, the ordering model information 61 is recorded only when it is received in step S101.

[0060] The demand forecasting process according to the third embodiment will be described with reference to FIG. (Step S221: Read process) The future stock estimation unit 22 reads out the information of the business operator A from the order model information 61 stored in the storage 13. The future stock estimation unit 22 also reads out the physical distribution information 66 stored in the storage 13.

[0061] (Step S222: Past inventory estimation process) The past stock estimation unit 25 estimates the stock amount of part A, which is the prediction target item of the supply destination company A, for each day of the most recent reference period up to the day to which the process execution time belongs, by referring to the logistics information 66. The past stock estimation unit 25 writes the estimated daily stock amount in the storage 13 as past stock information 67. A specific description will be given with reference to FIG. 19. The past stock estimation unit 25 sets each day of the most recent reference period up to the day to which the processing execution time belongs as the target day, starting from the oldest. The past stock estimation unit 25 sets an initial value to the stock amount on the day before the oldest day in the most recent reference period. The past stock estimation unit 25 calculates the stock amount on the target day by adding the stock amount that increases on the target day indicated by the logistics information 66 to the stock amount on the day before the target day, and subtracting the stock amount that decreases on the target day indicated by the logistics information 66, to the stock amount on the day before the target day. In this way, the stock amount on the day to which the processing execution time belongs is estimated. The inventory amount to be increased on the target day is the quantity of part A arriving at business operator A on the target day in logistics information 66. The inventory amount to be decreased on the target day is the quantity of part A shipped from business operator A on the target day in logistics information 66.

[0062] (Step S223: Future inventory estimation process) The future stock estimation unit 22 uses the stock amount indicated by the past stock information 67 estimated in step S222 as the past stock amount indicated by the past stock information 62 to estimate the future stock amount at operator A in the same manner as in the first embodiment.

[0063] The processes in steps S224 and S225 are the same as those in steps S203 and S204 in FIG.

[0064] ***Effects of the Third Embodiment*** As described above, the demand forecasting device 10 according to the third embodiment estimates the inventory amount on the day on which the processing execution time falls by referring to the logistics information 66, and estimates the future inventory amount. This makes it possible to estimate the future inventory amount of business operator A even when it is not possible to obtain information on the inventory amount on the day on which the processing execution time falls for business operator A. As a result, it is possible to perform demand forecasting even when it is not possible to obtain information on the inventory amount on the day on which the processing execution time falls for business operator A.

[0065] Embodiment 4 The fourth embodiment differs from the third embodiment in that the inventory amount on the day to which the process is executed is estimated by using the transitions that occur in the logistics process for the used product, which is a product produced using the prediction target product as a part. In the fourth embodiment, this difference will be explained, and the explanation of the same points will be omitted.

[0066] ***Configuration Description*** The configuration of a demand forecasting device 10 according to the fourth embodiment will be described with reference to FIG. The demand forecasting device 10 differs from that shown in FIG.

[0067] ***Explanation of Operation*** The input reception process according to the fourth embodiment will be described with reference to FIG. (Step S101: Reception process) The reception unit 21 receives input of the order model information 61, logistics information 66, and parts configuration information 68 from the input terminal 51. However, the order model information 61 is necessary only at the time of the first reception, and the reception unit 21 does not necessarily need to receive the order model information 61 every time the input reception process is executed.

[0068] The parts configuration information 68 according to the fourth embodiment will be described with reference to FIG. The parts configuration information 68 indicates the quantity of part A, which is a prediction target item used in a using product. The parts configuration information 68 includes a product name, a part name, and a quantity. The product name is the name of the using product. The part name is the name of a part, such as part A, used in the using product. The quantity is the number of parts used in the using product.

[0069] (Step S102: Storage process) The reception unit 21 writes the order model information 61, the logistics information 66, and the parts configuration information 68 into the storage 13. However, the order model information 61 is recorded only when it is received in step S101.

[0070] The demand forecasting process according to the fourth embodiment will be described with reference to FIG. (Step S221: Read process) The future stock estimation unit 22 reads out the information of the business operator A from the order model information 61 stored in the storage 13. The future stock estimation unit 22 also reads out the logistics information 66 and the part configuration information 68 stored in the storage 13.

[0071] (Step S222: Past inventory estimation process) As in the third embodiment, the past stock estimation unit 25 sets each day of the most recent reference period up to the day to which the process execution time belongs as a target day, starting from the oldest day, and estimates the stock amount for the target day. At this time, the past stock estimation unit 25 refers to the logistics information 66 to determine whether or not business operator A is producing a used product that has part A as a component. If business operator A is not producing a used product that has part A as a component, the past stock estimation unit 25 estimates the stock amount for the target day in the same manner as in embodiment 3. If business operator A is producing a used product that has part A as a component, the past stock estimation unit 25 identifies the stock amount that will decrease on the target day as follows, and estimates the stock amount for the target day. Other than the method of identifying the stock amount that will decrease on the target day, it is the same as embodiment 3. Instead of obtaining the quantity of part A to be shipped from logistics information 66, past stock estimation unit 25 calculates the production and shipping quantities of products using part A that are produced based on part A. Past stock estimation unit 25 specifies, from part configuration information 68, the quantity of part A used in the production of the products using part A or the quantity of part A shipped after being incorporated into the products using part A, and regards this quantity as the inventory reduction amount.

[0072] A specific example will be described with reference to FIG. When determining the shipping volume of part A, the past stock estimation unit 25 first refers to the logistics information 66 and determines whether or not business operator A is producing a product that uses part A as a component, such as product A or product B. For example, if business operator A is producing product B, the past stock estimation unit 25 identifies the production or shipping volume of product B on the target day from the logistics information 66. Then, the past stock estimation unit 25 identifies the quantity of part A used in product B from the part configuration information 68, and calculates the total amount of part A used in the production or shipping of product B. The past stock estimation unit 25 regards the calculated total amount as the inventory amount that will decrease on the target day.

[0073] ***Effects of the fourth embodiment*** As described above, the demand forecasting device 10 according to the fourth embodiment estimates the inventory amount on the day to which the process execution time belongs, by using the transitions that occur in the logistics process for the used products, which are products produced using the prediction target products as parts. This makes it possible to appropriately estimate the inventory amount of the prediction target products whose tracking is lost in the logistics information 66. In other words, even if the tracking of the prediction target products is lost in the logistics information 66 due to a change in shape during the distribution process, etc., it becomes possible to appropriately estimate the inventory amount.

[0074] In addition, the word "part" in the above description may be read as a "circuit," "step," "procedure," "processing," or "processing circuit."

[0075] The above describes the embodiments and modifications of the present disclosure. Some of these embodiments and modifications may be combined and implemented. Also, one or some of them may be partially implemented. Note that the present disclosure is not limited to the above embodiments and modifications, and various modifications are possible as necessary. [Explanation of symbols]

[0076] 10 demand forecasting device, 11 processor, 12 memory, 13 storage, 14 communication interface, 15 electronic circuit, 21 reception unit, 22 future inventory estimation unit, 23 demand forecasting unit, 24 output unit, 25 past inventory estimation unit, 51 input terminal, 52 output terminal, 61 ordering model information, 62 past inventory information, 63 future inventory information, 64 demand forecast result, 65 supply flow structure information, 66 logistics information, 67 past inventory information, 68 parts configuration information.

Claims

1. A demand forecasting device that forecasts demand that will occur for each unit period, a future inventory estimation unit which estimates a future inventory amount at a destination of a prediction target product, assuming that inventory will increase as a result of orders being placed in accordance with the ordering conditions and order amount indicated by the ordering model information, and inventory will decrease in accordance with the trend in past inventory amount indicated by the past inventory information, and which estimates the inventory amount for each unit period during the prediction period, starting from the unit period next to the unit period to which the processing is executed, in order from the oldest to the newest, by adding the inventory amount that will increase in the target unit period to the inventory amount in the unit period preceding the target unit period and subtracting the inventory amount that will decrease in the target unit period to calculate the inventory amount in the target unit period; a demand forecasting unit that forecasts that a demand for an order amount indicated by the ordering model information will occur at a supplier at a time point when the ordering condition indicated by the ordering model information is satisfied in the future inventory amount estimated by the future inventory estimation unit; Equipped with The future inventory estimation unit calculates a statistical value of the inventory reduction amount per unit period from the trend in inventory amount indicated by the past inventory information, and regards the statistical value as the inventory amount that will be reduced in the target unit period.

2. A demand forecasting device that forecasts demand that will occur for each unit period, a future inventory estimation unit which estimates a future inventory amount at a destination of a prediction target product, assuming that inventory will increase as a result of orders being placed in accordance with the ordering conditions and order amount indicated by the ordering model information, and inventory will decrease in accordance with the trend in past inventory amount indicated by the past inventory information, and which estimates the inventory amount for each unit period during the prediction period, starting from the unit period next to the unit period to which the processing is executed, in order from the oldest to the newest, by adding the inventory amount that will increase in the target unit period to the inventory amount in the unit period preceding the target unit period and subtracting the inventory amount that will decrease in the target unit period to calculate the inventory amount in the target unit period; a demand forecasting unit that forecasts that a demand for an order amount indicated by the ordering model information will occur at a supplier at a time point when the ordering condition indicated by the ordering model information is satisfied in the future inventory amount estimated by the future inventory estimation unit; a past inventory estimation unit that estimates an inventory amount of the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time belongs, by referring to logistics information indicating a transition occurring in a logistics process for the prediction target product at the supply destination; Equipped with The future inventory estimation unit is a demand forecasting device that estimates a future inventory amount by using the inventory amount estimated by the past inventory estimation unit as the past inventory amount indicated by the past inventory information.

3. The future inventory estimation unit determines that the order quantity is an increased inventory quantity for the target unit period if the order condition is satisfied in a unit period that is a procurement lead time before the target unit period. The demand forecasting device according to claim 1 or 2.

4. The demand forecasting device forecasts demand that will occur for the supply source, which is an upstream business of the target business, in order from a downstream business in a flow between businesses of the prediction target product, and The future inventory estimation unit determines, when the target business operator has no downstream business operators, that the statistical value is the inventory amount that decreases in the target unit period, and when the target business operator has downstream business operators, that the demand of the downstream business operators is the inventory amount that decreases in the target unit period. The demand forecasting device according to claim 1 .

5. The past inventory estimation unit sets an initial value to the inventory amount in the unit period before the reference period of the unit period to which the processing execution time belongs, and estimates the inventory amount in the unit period to which the processing execution time belongs by calculating the inventory amount in the target unit period by adding the inventory amount that increases in the target unit period indicated by the logistics information to the inventory amount in the unit period before the target unit period indicated by the logistics information and subtracting the inventory amount that decreases in the target unit period indicated by the logistics information, for the unit period from the next unit period before the reference period to the unit period to which the processing execution time belongs. The demand forecasting device according to claim 2.

6. The logistics information indicates a transition occurring in a logistics process for a used product, which is a product produced by using the prediction target product as a part, The past stock estimation unit refers to part configuration information indicating the number of the prediction target items used in the use product, and takes into consideration the usage amount of the prediction target items calculated from the production volume of the use product, to identify the inventory amount to be reduced in a unit period of the target. The demand forecasting device according to claim 5.

7. A demand forecasting method for forecasting demand occurring in each unit period, comprising: the computer estimates future inventory levels at the destination of the prediction target item, assuming that inventory will increase as orders are placed in accordance with the ordering conditions and order levels indicated in the ordering model information, and that inventory will decrease in accordance with the trends in past inventory levels indicated in the past inventory information, and estimates inventory levels for each unit period during the prediction period, starting from the unit period next to the unit period to which the processing is executed, beginning with the oldest, by adding the inventory level that will increase in the target unit period to the inventory level in the unit period preceding the target unit period and subtracting the inventory level that will decrease in the target unit period to the inventory level in the unit period preceding the target unit period; The computer predicts that a demand for the order amount indicated by the ordering model information will occur at a supplier at a time when the estimated future inventory amount satisfies the ordering condition indicated by the ordering model information, and A demand forecasting method in which a computer calculates a statistical value of the inventory reduction amount per unit period from the trend in inventory amount indicated by the past inventory information, and regards the statistical value as the inventory reduction amount in the target unit period.

8. A demand forecasting method for forecasting demand occurring in each unit period, comprising: the computer estimates future inventory levels at the destination of the prediction target item, assuming that inventory will increase as orders are placed in accordance with the ordering conditions and order levels indicated in the ordering model information, and that inventory will decrease in accordance with the trends in past inventory levels indicated in the past inventory information, and estimates inventory levels for each unit period during the prediction period, starting from the unit period next to the unit period to which the processing is executed, beginning with the oldest, by adding the inventory level that will increase in the target unit period to the inventory level in the unit period preceding the target unit period and subtracting the inventory level that will decrease in the target unit period to the inventory level in the unit period preceding the target unit period; The computer predicts that a demand for the order amount indicated by the ordering model information will occur at a supplier at a time when the estimated future inventory amount satisfies the ordering condition indicated by the ordering model information, and a computer refers to logistics information indicating a transition occurring in a logistics process for the prediction target product at the supply destination, and estimates an inventory amount at the supply destination for each unit period of a past reference period up to the unit period to which the processing execution time belongs; A demand forecasting method in which a computer estimates future inventory amounts using an estimated inventory amount as the past inventory amount indicated by the past inventory information.

9. A demand forecasting program for forecasting demand occurring in each unit period, a future inventory estimation process for estimating a future inventory amount at a destination of a prediction target product, on the assumption that inventory will increase as a result of orders being placed in accordance with the ordering conditions and order amounts indicated by the ordering model information, and inventory will decrease in accordance with the trend in past inventory amounts indicated by the past inventory information, the future inventory estimation process being for each unit period during a prediction period starting from the unit period next to the unit period to which the process is executed, beginning from the oldest, and estimating the inventory amount for each unit period during the prediction period by adding the inventory amount that will increase in the target unit period to the inventory amount in the unit period preceding the target unit period and subtracting the inventory amount that will decrease in the target unit period to the inventory amount in the unit period preceding the target unit period; a demand forecasting process for forecasting that a demand for an order amount indicated by the ordering model information will occur at a supplier at a time point when the ordering condition indicated by the ordering model information is satisfied in the future inventory amount estimated by the future inventory estimation process; The computer functions as a demand forecasting device that performs the following: In the future inventory estimation process, a demand forecasting program calculates a statistical value of the inventory reduction amount per unit period from the trend in inventory amount indicated by the past inventory information, and regards the statistical value as the inventory amount that will decrease in the target unit period.

10. A demand forecasting program for forecasting demand occurring in each unit period, a future inventory estimation process for estimating a future inventory amount at a destination of a prediction target product, on the assumption that inventory will increase as a result of orders being placed in accordance with the ordering conditions and order amounts indicated by the ordering model information, and inventory will decrease in accordance with the trend in past inventory amounts indicated by the past inventory information, the future inventory estimation process being for each unit period during a prediction period starting from the unit period next to the unit period to which the process is executed, beginning from the oldest, and estimating the inventory amount for each unit period during the prediction period by adding the inventory amount that will increase in the target unit period to the inventory amount in the unit period preceding the target unit period and subtracting the inventory amount that will decrease in the target unit period to the inventory amount in the unit period preceding the target unit period; a demand forecasting process for forecasting that a demand for an order amount indicated by the ordering model information will occur at a supplier at a time point when the ordering condition indicated by the ordering model information is satisfied in the future inventory amount estimated by the future inventory estimation process; a past inventory estimation process for estimating an inventory amount of the supply destination for each unit period of a past reference period up to the unit period to which the process execution time belongs, by referring to logistics information indicating a transition occurring in the process of logistics for the prediction target product at the supply destination; The computer functions as a demand forecasting device that performs the following: A demand forecasting program in which, in the future inventory estimation process, the inventory amount estimated by the past inventory estimation process is regarded as the past inventory amount indicated by the past inventory information, and a future inventory amount is estimated.

Images