JP6817836B2 - Usage prediction calculation device, usage prediction calculation method, and usage prediction calculation program - Google Patents

Description

The present invention relates to a usage prediction calculation device, a usage prediction calculation method, and a usage prediction calculation program.

Claim 1 and the like of Patent Document 1 describe a system for predicting the future inventory amount of raw materials used for cooking based on the sales situation. In particular, the sales amount of food at each future time point is calculated from the sales data. A system is disclosed that estimates, multiplies the estimated sales by the quantity of raw materials to obtain the estimated consumption of raw materials at each time point, and subtracts the estimated consumption from the initial inventory to obtain the estimated inventory (inventory estimation). See, for example, paragraph 0031).

Japanese Patent No. 3951228

As described above, in Patent Document 1, there is a system that estimates the future sales quantity based on the sales data and obtains the inventory estimated amount from the estimated consumption amount of raw materials, but in recent years, the products have been sold in small stores. When selling, it was necessary to order raw materials and products diligently. For example, when processing and selling food in a small store with limited storage space, it is necessary to order raw materials diligently, so a complicated calculation is performed to estimate the sales quantity from sales data and obtain the estimated inventory amount of raw materials. It is difficult to make each order, and there is a need for a simpler and more accurate method for determining the amount of raw materials used.

The present invention has been made in view of the above problems, and even if the ordering unit is specified to a certain amount at the time of ordering raw materials, the estimated number of uses is gradually determined according to the sales forecast amount suitable for the ordering unit. It is an object of the present invention to provide a usage forecast calculation device, a usage forecast calculation method, and a usage forecast calculation program that can calculate and calculate the number of future inventory forecasts.

In order to solve the above-mentioned problems and achieve the object, the usage prediction calculation device according to the present invention is provided with a storage unit and a control unit, and when ordering raw materials at a store, the future of each delivery date at the store It is a usage forecast calculation device that calculates the usage forecast number for calculating the inventory forecast number, and is a sales forecast master in which store identification information, delivery date information, and sales forecast amount for each delivery date are set in the storage unit. A sales range master in which the sales forecast amount is divided into a plurality of sales ranges and a usage forecast master in which the usage forecast number of the raw materials is set so as to correspond to each sales range are stored. The control unit acquires the sales forecast amount for each delivery date of the sales forecast master, specifies the sales range of the sales range master according to the sales forecast amount, and uses the usage forecast according to the sales range. It is characterized by providing a usage prediction calculation means for acquiring the usage prediction number of the master.

Further, the usage forecast calculation device according to the present invention is further provided with a master maintenance means for maintaining the sales forecast master, the sales range master, and the usage forecast master.

Further, the usage prediction calculation method according to the present invention includes a storage unit and a control unit, and when ordering raw materials at a store, the usage prediction number for calculating the future inventory prediction number for each delivery date at the store is calculated. It is a usage forecast calculation method executed by the usage forecast calculation device for calculating, and in the storage unit, a sales forecast master in which store identification information, delivery date information, and sales forecast amount for each delivery date are set, and the sales. A sales range master in which the forecast amount is divided into a plurality of sales ranges and a usage forecast master in which the estimated number of raw materials used is set so as to correspond to each sales range are stored, and the control The sales forecast amount for each delivery date of the sales forecast master executed by the unit is acquired, the sales range of the sales range master corresponding to the sales forecast amount is specified, and the usage forecast master corresponding to the sales range is specified. It is characterized by including a usage prediction calculation step for acquiring the usage prediction number of.

Further, the usage prediction calculation program according to the present invention includes a storage unit and a control unit, and when ordering raw materials at a store, the usage prediction number for calculating the future inventory prediction number for each delivery date at the store is calculated. It is a usage forecast calculation program to be executed by the usage forecast calculation device for calculation, and the storage unit includes a sales forecast master in which store identification information, delivery date information, and sales forecast amount for each delivery date are set, and the above. A sales range master in which the sales forecast amount is divided into a plurality of sales ranges and a usage forecast master in which the usage forecast number of the raw materials is set so as to correspond to each sales range are stored. The sales forecast amount for each delivery date of the sales forecast master to be executed by the control unit is acquired, the sales range of the sales range master according to the sales forecast amount is specified, and the use according to the sales range. It is characterized by including a usage prediction calculation step for acquiring the usage prediction number of the prediction master.

According to the present invention, even if the ordering unit is specified as a fixed quantity at the time of ordering raw materials, the estimated number of uses can be calculated step by step according to the sales forecast amount suitable for the ordering unit, and the future inventory forecast number can be calculated. It plays the effect.

FIG. 1 is a block diagram showing an example of the configuration of the order quantity management device. FIG. 2 is a table diagram showing the relationship between the information stored in the storage unit and the data created based on the information. FIG. 3 is a diagram showing an image of generating store order data by performing inventory simulation on the calendar screen of the order quantity management device. FIG. 4 is a diagram showing an example of an input screen for performing inventory simulation. FIG. 5 is a diagram showing an example of acquiring the number of orders for each delivery date based on the store order data. FIG. 6 is a diagram showing an example of acquiring a usage forecast number using a sales forecast master, a sales range master, and a usage forecast master.

Hereinafter, embodiments of the usage prediction calculation device, the usage prediction calculation method, and the usage prediction calculation program according to the present invention will be described in detail with reference to the drawings. The present invention is not limited to the present embodiment.

[1. Overview]
In a business format that sells food processing (cooking) at small stores, storage space is limited, so it is necessary to place orders for raw materials according to sales on a daily basis.

When ordering raw materials at a conventional small store, the number of used materials is often predicted and ordered based on the feeling of the person in charge at the site, and there is a frequent discrepancy between the appropriate inventory quantity at the store and the actual inventory quantity. , There was a problem that sales opportunity loss and inventory could not fit in the storage space. In addition, it is possible to calculate the proportional raw material usage by simply multiplying the sales amount by a coefficient, but if the ordering unit is specified as a fixed amount (bag), it is converted by the ordering unit. There was a problem that it took time to fix.

Therefore, in the present embodiment, when ordering raw materials at a small store, it is necessary to obtain the amount of raw materials used according to the sales budget in order to simulate the number of stocks in the store in the future. For example, the ordering unit of raw materials is a fixed amount. It provides an order quantity management device, an order quantity management method, and an order quantity management program that can set the value of the raw material usage amount stepwise according to the range of the sales amount, as specified in. Hereinafter, a specific configuration and operation will be described.

[2. Constitution]
The configuration of the order quantity management device 100 according to the present embodiment including the present invention will be described with reference to FIG. FIG. 1 is a block diagram showing an example of the configuration of the order quantity management device 100.

The order quantity management device 100 is a commercially available desktop personal computer. The order quantity management device 100 is not limited to a stationary information processing device such as a desktop personal computer, but is also portable such as a commercially available notebook personal computer, a PDA (Personal Digital Assistants), a smartphone, and a tablet personal computer. It may be a type information processing device.

As shown in FIG. 1, the order quantity management device 100 includes a control unit 102, a communication interface unit 104, a storage unit 106, and an input / output interface unit 108. Each part of the order quantity management device 100 is communicably connected via an arbitrary communication path.

The communication interface unit 104 connects the order quantity management device 100 to the network 300 so as to be communicable via a communication device such as a router and a wired or wireless communication line such as a dedicated line. The communication interface unit 104 has a function of communicating data with another device via a communication line. Here, the network 300 has a function of connecting the order quantity management device 100 and the server 200 so as to be able to communicate with each other, and is, for example, the Internet or a LAN (Local Area Network). The data stored in the storage unit 106, which will be described later, may be stored in the server 200.

An input device 112 and an output device 114 are connected to the input / output interface unit 108. As the output device 114, a speaker or a printer can be used in addition to a monitor (including a home television). In addition to the keyboard, mouse, and microphone, the input device 112 can use a monitor that cooperates with the mouse to realize the pointing device function. In the following, the output device 114 may be referred to as a monitor 114, and the input device 112 may be referred to as a keyboard 112 or a mouse 112.

Various databases, tables, files, and the like are stored in the storage unit 106. In the storage unit 106, a computer program for giving a command to a CPU (Central Processing Unit) in cooperation with an OS (Operating System) to perform various processes is recorded. As the storage unit 106, for example, a memory device such as a RAM (Random Access Memory) or a ROM (Read Only Memory), a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used.

The storage unit 106 includes a sales forecast master 106a, a sales range master 106b, a usage forecast master 106c, delivery number data 106d, and store inventory data 106e. Of these, the sales forecast master 106a, the sales range master 106b, and the usage forecast master 106c are included in the first master and are used when calculating the usage forecast number of raw materials. Further, the delivery number data 106d and the store inventory data 106e may be stored in the storage unit 106 as shown in FIG. 1, but it is preferable that the delivery number data 106d and the store inventory data 106e are input by the operator when the order number management device 100 is used.

Each item included in the above-mentioned three masters and the above-mentioned two data stored in the storage unit 106 will be described in detail mainly with reference to FIGS. 2, 3 and 6. FIG. 2 is a table diagram showing the relationship between the information stored in the storage unit and the data created based on the information. FIG. 3 is a diagram showing an image of generating store order data by performing inventory simulation on the calendar screen of the order quantity management device. Further, FIG. 6 is a diagram showing an example of acquiring the usage forecast number using the sales forecast master, the sales range master, and the usage forecast master.

The sales forecast master 106a is a master that stores the sales forecast amount for each target day at each store. As shown in FIGS. 2 and 6, the sales forecast master 106a has "store code (store identification information)", "fiscal year / month", "target date (delivery date information)", and "amount (sales forecast information)". Etc. are included. The identification information may be a store CD (identification code) such as a list of letters, numbers, or alphabets, or a specific name (for example, a specific store name, company name, department name, etc.). It may be, and the same applies to the following.

Of the items included in the sales forecast master 106a, the store identification information is information for identifying each store by a store code or the like, and for example, the alphabet of the initial letter of the identification code is different depending on the store. Is preferable. For example, as shown in FIG. 6, in a certain store, P00001 starting with the acronym P is assigned as a store CD. In addition, in stores of another series, it is possible to easily identify by shaking the store CD that starts with a different acronym such as Q or R, and in different stores of the same series, it is possible to identify by changing the number at the end. .. Further, the sales forecast master 106a stores the sales forecast amount for each target date (here, from September 9, 2014 to September 9, 2014), which is the delivery date in the fiscal year and month.

The sales range master 106b is a master for giving a certain range (range) to the expected sales amount and specifying the corresponding sales range with respect to the expected sales amount in a certain range. As shown in FIGS. 2 and 6, the sales range master 106b includes items such as “sales range”, “sales amount From”, and “sales amount To”. In the sales range master shown in FIG. 6, four sales ranges from 0 to 3 are set according to the sales amount.

Among the items included in the sales range master 106b, for example, as shown in the sales range master of FIG. 6, the sales range 0 has a sales amount From 0 yen to a sales amount To of 999,999 yen. The sales range 1 has a sales amount from ¥ 1,000,000 and a sales amount To is ¥ 1,499,999, and the sales range 2 has a sales amount from ¥ 1,500,000. The amount To is in the range of ¥ 1,999,999, and the sales range 3 is in the range of the sales amount From from ¥ 2,000,000 to the sales amount To in the range of ¥ 999,999,999. The relationship between the sales range and the sales amount can be set arbitrarily, but if the range is set at the timing when the ordering unit of raw material usage (for example, brown sugar bag) changes depending on the sales range, efficient ordering becomes possible. ..

The usage forecast master 106c is a master for acquiring the usage forecast number corresponding to the sales range specified by the sales range master 106b. As shown in FIGS. 2 and 6, the usage prediction master 106c includes items such as “store code (store identification information)”, “sales range”, “product code”, and “predicted usage number”. In the usage forecast master shown in FIG. 6, if the sales range is specified while the store code and the product code are specified, the number of usage forecasts corresponding to the sales range can be acquired.

For each item included in the usage forecast master 106c, when forecasting the usage of raw material usage, the estimated number of usage in the sales amount differs depending on the store and product, so after specifying the store code and product code, the sales range The expected number of uses is set according to the sales range of the master 106b. In this way, the order quantity management device 100 uses the sales forecast master 106a, the sales range master 106b, and the usage forecast master 106c to calculate the usage forecast number of the raw materials according to the sales forecast of the store.

The number of deliveries data 106d is data for extracting the number of deliveries scheduled to arrive for each date on the calendar. As shown in FIG. 2, the delivery number data 106d includes "store code (store identification information)", "delivery date (delivery date information)", "order date", "product code", "order quantity", and "order". Includes items such as "lead time".

Of the items included in the delivery quantity data 106d, the ordering date is the date on which the product is ordered, and the date obtained by back-calculating the ordering lead time from the delivery date is the ordering deadline. Must be set before. In the present embodiment, in order to determine the number of orders based on the delivery date, the number of orders is input and controlled by the order deadline. In addition, as shown in FIG. 2, the arrival of goods before the inventory date is acquired from the arrival details data which is the arrival record data.

The store inventory data 106e is data for performing inventory forecasting based on the contents of the latest store inventory. As shown in FIG. 2, the store inventory data 106e includes items such as “store code (store identification information)”, “inventory date (delivery date information)”, “product code”, and “inventory number”.

Of each item included in the store inventory data 106e, the inventory date is the latest store inventory date, and based on this inventory number, from the next day onward, "inventory forecast number up to the previous day" + "delivery number"-"use Let the calculated value of "Forecast" be the inventory forecast value. As described above, in the order quantity management device 100, the "usage forecast" obtained from the sales forecast master 106a, the sales range master 106b, and the usage forecast master 106c, and the "delivery quantity data 106d" and the "arrival details data" acquired from the above-mentioned delivery quantity data 106d. By simulating the planned number of stocks for each date on the calendar screen based on the inventory contents of the store inventory data 106e using "number of deliveries", the number of orders for each delivery date can be determined.

The control unit 102 is a CPU or the like that collectively controls the order quantity management device 100. The control unit 102 has an internal memory for storing a control program such as an OS, a program that defines various processing procedures, required data, and the like, and performs various information processing based on these stored programs. Execute. Here, the control unit 102 functionally conceptually includes (1) a master maintenance unit 102a as a master maintenance means, (2) a usage prediction calculation unit 102b as a usage prediction calculation means, and (3) a delivery number calculation means. It includes a delivery number calculation unit 102c, (4) an inventory forecast calculation unit 102d as an inventory forecast calculation means, (5) a display unit 102e as a display means, and the like. Of these, (a) a process of determining the number of orders while simulating on a calendar executed by the usage forecast calculation unit 102b, the number of deliveries calculation unit 102c, the inventory forecast calculation unit 102d, and the display unit 102e, and (b). The process of calculating the estimated number of usages step by step according to the range of the estimated sales amount executed by the master maintenance unit 102a and the usage forecast calculation unit 102b is divided into the following [3. Specific example of processing] will be described in detail.

[3. Specific example of processing]
Specific examples of the processing according to the present embodiment will be described in detail with reference to FIGS. 2 to 6. FIG. 3 is a diagram showing an image of generating store order data by performing inventory simulation on the calendar screen of the order quantity management device. FIG. 4 is a diagram showing an example of an input screen for performing inventory simulation. FIG. 5 is a diagram showing an example of acquiring the number of orders for each delivery date based on the store order data.

(B) Order quantity management process for performing inventory simulation on the screen Here, the outline of the process in the present embodiment will be described. In this embodiment, for example, in the case of a business format in which food processing (cooking) is sold in a small store, it is necessary to place an order for raw materials every day so that the raw materials are always in proper stock in a limited storage space. There is. Therefore, the order quantity management device 100 according to the present embodiment performs inventory simulation on the calendar screen shown in FIG. 4 as shown below, calculates the estimated number of raw materials used for each delivery date in the store, and delivers the product. Calculate the number of deliveries scheduled to arrive on a daily basis, calculate the future inventory forecast based on the contents of the latest store inventory, and determine the number of orders with the date when the order lead time is calculated back from the delivery date as the order deadline. .. As described above, the order quantity management device 100 according to the present embodiment prevents loss of sales opportunity and excess inventory by reducing the deviation between the appropriate inventory quantity and the actual inventory quantity. In the store shown in the screen example of FIG. 4, the target date is September 2014, the raw material product CD is 00000102 brown sugar, and the appropriate stock of the store is 30 bags.

[Usage forecast calculation process]
As shown in FIG. 4, the usage forecast calculation unit 102b extracts the number of usage forecasts based on the sales forecast for each date with the date on the calendar as the "delivery date" in order to enable the inventory simulation on the calendar. , The display unit 102e displays the numerical value of "usage prediction". Here, the number of usage forecasts is not limited to the calculation using the sales forecast master 106a, the sales range master 106b, and the usage forecast master 106c described in (b) below. For example, a master (first master) that allows the estimated number of raw materials to be used can be extracted according to the estimated sales amount of the store may be used, or a certain coefficient is multiplied by the estimated sales amount of the store. You may calculate the expected number of uses with.

[Delivery number calculation process]
As shown in FIG. 4, the number of deliveries calculation unit 102c extracts and displays the number of deliveries scheduled to arrive for each date, with the date on the calendar as the "delivery date" in order to enable inventory simulation on the calendar. The numerical value of "the number of deliveries" is displayed by the part 102e. As shown in FIGS. 1, 2 and 4, the number of deliveries is extracted by the "number of orders" in the number of deliveries data, and for the arrival of goods before the maximum inventory date, the "load" of the arrival details data, which is the arrival record data. Extract by referring to "number". Regarding the relationship between the "number of orders" and the "number of deliveries", if an order is placed for the "number of orders" on the "order date", the products will be delivered on the "delivery date" deviated by the "order lead time". Therefore, the "number of deliveries" on the "delivery date" is the same as the "number of orders".

[Inventory forecast calculation process]
The inventory forecast calculation unit 102d makes an inventory forecast based on the contents of the latest store inventory. As shown in FIG. 2, the content of the latest store inventory is that the “inventory date” of the store inventory data is the latest store inventory date, and the “number of inventory” of this “inventory date” is the content of the store inventory. The inventory forecast calculation unit 102d predicts the inventory from the next day onward based on this "inventory quantity", obtains the calculated value of "inventory forecast on the previous day" + "number of deliveries"-"use forecast" on the delivery date, and delivers the product. The "inventory forecast" of the day is calculated, and as shown in FIG. 4, the numerical value of the "inventory forecast" corresponding to the "delivery date" of the date on the calendar is displayed. For example, the inventory forecast as of September 6, 2014 (Saturday) is
Inventory forecast = "Inventory forecast of the previous day" + "Number of deliveries"-"Usage forecast"
= 29 + 20-20
= 29
Will be.

On the calendar screen shown in FIG. 4, numerical values of "usage forecast", "number of deliveries", and "inventory forecast" are input according to the "delivery date". Further, when the "delivery date" of the calendar screen shown in FIG. 4 is from 1st to 4th, the order is confirmed and the details cannot be changed, so they are displayed in gray. Furthermore, the "★ 31" in the "Inventory Forecast" on September 2 indicates that the stock of brown sugar was 31 bags in the latest inventory. Therefore, from September 1st to 2nd, it will be set based on the delivery record and sales record. Further, the "ordering date" on the calendar screen shown in FIG. 4 is initially blank, and only the date before the "ordering deadline" can be input. This "order deadline" is automatically displayed by "delivery date"-"lead time". Since the "lead time" differs depending on the day of the week for the convenience of delivery, it may be set in the calendar master setting for the "order deadline". Further, the number of usage forecasts displayed in the "usage forecast" column of FIG. 4 is the usage forecast according to the "(sales) amount" of the sales forecast master when the sales forecast master and the usage forecast master shown in FIG. 2 are used. The "estimated number of uses" of the master is displayed.

[Recalculation of inventory forecast based on inventory results]
The order quantity management device 100 according to the present embodiment always makes an inventory forecast based on the inventory quantity of the latest store inventory data, so that the error between the appropriate inventory quantity and the actual inventory quantity is minimized. Therefore, when the "recalculation button" in FIG. 4 is pressed, the order quantity management device 100 acquires the "inventory date" corresponding to the "store code" and the "product code" in the "store inventory data" in FIG. Then, each of the following items is recalculated for each date on the calendar, and the inventory forecast calculation unit 102d reacquires the inventory forecast number.

[Acquisition of delivery quantity]
In the delivery number calculation unit 102c, the “delivery date” of the delivery number data shown in FIG. 2 is related to the inventory date.
Delivery date <= ★ In the case of the details of the maximum inventory date The “number of shipments” (arrival record data) in the arrival details data shown in FIG.
Delivery date> ★ For the details of the maximum inventory date If the "order quantity" of the delivery quantity data shown in Fig. 2 exists, it is displayed as the "delivery quantity", and if the "order quantity" does not exist, the "delivery quantity" Do not display as.

[Get usage forecast]
The usage forecast calculation unit 102b refers to the “(sales forecast) amount” based on the “store code”, “fiscal year / month”, and “target date (delivery date)” of the sales forecast master shown in FIGS. 2 and 6. Then, the sales range corresponding to the "sales amount From" and the "sales amount To" set in the sales range master is acquired. The usage forecast calculation unit 102b acquires the "usage forecast number" based on the "store code", "sales range", and "product code" of the usage forecast master shown in FIG.

[Acquisition of inventory forecast]
In the inventory forecast calculation unit 102d, the “inventory date” of the store inventory data shown in FIG. 2 is related to the delivery date.
Delivery date <= ★ In the case of the details of the maximum inventory date If the "inventory number" exists by referring to the "store code", "inventory date" and "product code" in the store inventory data shown in Fig. 2.
Display an integer (rounded down to the nearest whole number) of (Inventory quantity / Package quantity). Items for which store inventory has been performed and the number of inventories are displayed are marked with "★" as shown in FIG.
In the store inventory data shown in FIG. 2, if the "inventory number" does not exist by referring to the "store code", "inventory date" and "product code",
Display the calculated value of "Inventory forecast of the previous day" + "Number of deliveries"-"Usage forecast".
Delivery date> ★ For details of the maximum inventory date Display the calculated value of "Inventory forecast of the previous day" + "Number of deliveries"-"Usage forecast".

In this way, the order quantity management device 100 according to the present embodiment can perform inventory simulation on the calendar screen, and obtains the number of deliveries on the future delivery date by simulating the future inventory forecast quantity. , It is possible to generate store order data for placing an order using the number of orders corresponding to the number of deliveries acquired within the order deadline obtained by back-calculating the lead time from the delivery date (see FIGS. 3 and 5). In particular, since inventory is predicted at a store based on the number of inventories on the latest store inventory date, it is possible to manage the number of orders in which the difference between the appropriate inventory quantity of the store and the actual inventory quantity is unlikely to occur (see FIG. 2). ). Furthermore, when the actual inventory data is acquired, the difference between the appropriate inventory quantity of the store and the actual inventory quantity can be further reduced by recalculating the past and future inventory simulations based on the latest actual inventory data. ..

(B) Gradual usage forecast number calculation process according to the range of sales forecast amount The order quantity management device 100 according to this embodiment is used to simulate the future store inventory number, and therefore, the raw material according to the store sales budget. It is necessary to find the expected number of uses. As shown in FIGS. 2 and 6, the usage forecast calculation unit 102b uses the sales forecast master 106a, the sales range master 106b, and the usage forecast master 106c. Then, in order to enable inventory simulation on the calendar, the usage forecast calculation unit 102b sets the date on the calendar as the "delivery date" and sets the number of usage forecasts based on the sales forecast for each date as shown in FIG. It is extracted and the numerical value of "usage prediction" is displayed by the display unit 102e.

When calculating the usage forecast number, the usage forecast calculation unit 102b sets the “store code”, “fiscal year / month”, and “target date (delivery date)” of the sales forecast master 106a as, for example, 2014 as shown in FIG. If you specify September 6, 2014, you will get ¥ 1,600,000, which is the estimated sales amount on the delivery date. Then, the usage forecast calculation unit 102b specifies the sales range according to the range from the “sales amount From” to the “sales amount To” of the sales range master 106b for ¥ 1,600,000 of the sales forecast amount. Here, the sales range 2 is specified. Further, the usage forecast calculation unit 102b specifies the "sales range" and the "product code" specified as the "store code" of the usage forecast master 106c, so that the "usage forecast number" corresponding to the "sales range" is obtained. "20" is acquired as. The acquired estimated usage number "20" corresponds to the usage amount of the raw material extracted according to the sales amount predicted on the delivery date of September 6, 2014.

As described above, the order quantity management device 100 according to the present embodiment is divided into four stages of sales ranges even if the sales forecast amount changes linearly by using the sales range master 106b. Only the estimated number of usage can be obtained in stages. This is different from the conventional method of simply multiplying the sales amount by a coefficient to obtain the proportional number of raw material usage forecasts. The reason why the order quantity management device 100 of the present embodiment adopts the sales range master 106b is that even if the raw material is not a certain amount or more, such as brown sugar in a bag shown in FIG. 4, the order cannot be placed. By setting the sales range according to the ordering unit, it is possible to obtain the expected number of uses suitable for the ordering. Maintenance of the sales forecast master 106a, the sales range master 106b, and the usage forecast master 106c is performed using the master maintenance unit 102a.

More specifically, for example, the estimated number of brown sugar used, which is a raw material required to produce caramel popcorn, is
When the sales budget is 0 yen to less than 1 million yen ... 10 bags When the sales budget is 1 million yen to less than 1.5 million yen ... 15 bags When the sales budget is 1.5 million yen to less than 2 million yen ... 20 bags Can be set as follows.

[Application example 1 of sales range master]
The above setting example of the sales range master 106b was used when calculating the estimated number of raw materials used, but the present invention is not necessarily limited to this. For example, as an example other than the above, it can be applied to the case of setting royalties for franchise agreements (fixed amount method). Specifically, when setting royalties for sales of a store, a fixed amount of royalties may be set stepwise according to the sales range of the store.
When the monthly sales amount is 0 yen to less than 3 million yen ... 100,000 yen When the monthly sales amount is 3 million yen to less than 5 million yen ... 150,000 yen When the monthly sales amount is 5 million yen or more・ ・ It can be set as 200,000 yen.

[Application example 2 of sales range master]
In the case of franchise agreement royalties (combination of fixed and variable), when setting royalties for store sales, the minimum royalties (fixed amount) and sales are set according to the store's sales range. It may be set by multiplying by a stepwise percentage.
When the monthly sales amount is 0 yen to less than 30 million yen ... Minimum royalty 100,000 yen (fixed amount) + sales amount x 30% (variable amount)
If the monthly sales amount is between 30 million yen and less than 50 million yen ... Minimum royalty 100,000 yen (fixed amount) + sales amount x 28% (variable amount)
When the monthly sales amount is 5 million yen or more ... Minimum royalty 100,000 yen (fixed amount) + sales amount x 25% (variable amount)
Can be set as follows.

[4. Other embodiments]
In addition to the above-described embodiments, the present invention may be implemented in various different embodiments within the scope of the technical ideas described in the claims.

For example, of each of the processes described in the embodiments, all or part of the processes described as being automatically performed may be performed manually, or all the processes described as being performed manually. Alternatively, a part thereof can be automatically performed by a known method.

In addition, the processing procedure, control procedure, specific name, information including parameters such as registration data and search conditions of each processing, screen examples, and database configuration shown in this specification and drawings are not specified unless otherwise specified. Can be changed arbitrarily.

Further, with respect to the order quantity management device 100, each component shown in the figure is a functional concept and does not necessarily have to be physically configured as shown in the figure.

For example, with respect to the processing functions included in the order quantity management device 100, particularly each processing function performed by the control unit 102, all or any part thereof is realized by the CPU and a program interpreted and executed by the CPU. It may be realized as hardware by wired logic. The program is recorded on a non-temporary computer-readable recording medium including a programmed instruction for causing the information processing apparatus to execute the process described in the present embodiment, and the number of orders is managed as necessary. It is read mechanically by the device 100. That is, a computer program for giving instructions to the CPU in cooperation with the OS and performing various processes is recorded in a storage unit 106 such as a ROM or an HDD (Hard Disk Drive). This computer program is executed by being loaded into the RAM, and constitutes the control unit 102 in cooperation with the CPU.

Further, this computer program may be stored in an application program server connected to the order quantity management device 100 via an arbitrary network, and all or a part thereof can be downloaded as needed. Is.

Further, the program for executing the process described in the present embodiment may be stored in a non-temporary computer-readable recording medium, or may be configured as a program product. Here, the "recording medium" includes a memory card, a USB (Universal Serial Bus) memory, an SD (Secure Digital) card, a flexible disk, a magneto-optical disk, a ROM, an EPROM (ErasaBSEProgrammaBSe ReadOnly Memory), and an EEPROM (registration). Trademarks) (Electrically Erasabse and ProgramRead Only Memory), CD-ROM (Compact Disk Read Only Memory), MO (Magnet-Optical Disk), MO (Magnet-Optical Disk), Digital Disk, DVD (Digital), DVD (Digital) It shall include any "portable physical medium".

Further, the "program" is a data processing method described in any language or description method, regardless of the format such as source code or binary code. The "program" is not necessarily limited to a single program, but is distributed as a plurality of modules or libraries, or cooperates with a separate program represented by the OS to achieve its function. Including things. A well-known configuration and procedure can be used for a specific configuration and reading procedure for reading the recording medium in each device shown in the embodiment, an installation procedure after reading, and the like.

Various databases and the like stored in the storage unit are memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and storage means such as optical disks, and are used for various processes and website provision. Stores programs, tables, databases, files for web pages, etc.

Further, the order quantity management device 100 may be configured as an information processing device such as a known personal computer or workstation, or may be configured as the information processing device to which an arbitrary peripheral device is connected. Further, the order quantity management device 100 may be realized by mounting software (including a program or data) for realizing the processing described in the present embodiment on the information processing device.

Furthermore, the specific form of dispersion / integration of the device is not limited to that shown in the figure, and all or part of the device may be functionally or physically in any unit according to various additions or the like. It can be distributed and integrated. That is, the above-described embodiments may be arbitrarily combined and implemented, or the embodiments may be selectively implemented.

The present invention is particularly useful in industries such as food processing (cooking) sales where it is necessary to frequently place orders and manage inventory in small stores with limited storage space.

100 Order quantity management device 102 Control unit 102a Master maintenance unit 102b Usage forecast calculation unit 102c Delivery number calculation unit 102d Inventory forecast calculation unit 102e Display unit 104 Communication interface unit 106 Storage unit 106a Sales forecast master 106b Sales range master 106c Usage forecast master 106d Number of deliveries data 106e Store inventory data 108 Input / output interface 112 Input device 114 Output device 200 Server 300 Network

Claims (4)

Equipped with a storage unit and a control unit
It is a usage forecast calculation device that calculates the usage forecast number for calculating the future inventory forecast number for each delivery date at the store when ordering raw materials at the store.
In the storage unit
A sales forecast master in which store identification information, delivery date information, and sales forecast amount for each delivery date are set,
The sales range master, which is set by dividing the sales forecast amount into a plurality of sales ranges,
A usage forecast master in which the estimated number of raw materials used is set so as to correspond to each sales range.
Is stored,
The control unit
Acquire the sales forecast amount for each delivery date of the sales forecast master, specify the sales range of the sales range master according to the sales forecast amount, and acquire the usage forecast number of the usage forecast master according to the sales range. To have a usage prediction calculation means
A usage prediction calculation device characterized by. Further provided with master maintenance means for maintaining the sales forecast master, the sales range master, and the usage forecast master.
The usage prediction calculation device according to claim 1. Equipped with a storage unit and a control unit
This is a usage forecast calculation method executed by a usage forecast calculation device that calculates the usage forecast number for calculating the future inventory forecast number for each delivery date at the store when ordering raw materials at the store.
In the storage unit
A sales forecast master in which store identification information, delivery date information, and sales forecast amount for each delivery date are set,
The sales range master, which is set by dividing the sales forecast amount into a plurality of sales ranges,
A usage forecast master in which the estimated number of raw materials used is set so as to correspond to each sales range.
Is stored,
Executed by the control unit,
Acquire the sales forecast amount for each delivery date of the sales forecast master, specify the sales range of the sales range master according to the sales forecast amount, and acquire the usage forecast number of the usage forecast master according to the sales range. Including the usage forecast calculation step,
A usage prediction calculation method characterized by. Equipped with a storage unit and a control unit
When ordering raw materials at a store, it is a usage forecast calculation program to be executed by a usage forecast calculation device that calculates the usage forecast number for calculating the future inventory forecast number for each delivery date at the store.
In the storage unit
A sales forecast master in which store identification information, delivery date information, and sales forecast amount for each delivery date are set,
The sales range master, which is set by dividing the sales forecast amount into a plurality of sales ranges,
A usage forecast master in which the estimated number of raw materials used is set so as to correspond to each sales range.
Is stored,
To be executed by the control unit
Acquire the sales forecast amount for each delivery date of the sales forecast master, specify the sales range of the sales range master according to the sales forecast amount, and acquire the usage forecast number of the usage forecast master according to the sales range. Including the usage forecast calculation step,
A usage prediction calculation program characterized by.