JP2015108928A - Information processing device, information processing system, information processing method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an information processing device, an information processing system, an information processing method and program that appropriately maintain a safe inventory quantity in an inventory management of products.SOLUTION: An information processing device 100 comprises: a parameter acquisition unit 102 that acquires an individual parameter as to a number of individual sales of a target product and a carton parameter as to a number of carton sales of the target product; and an inventory calculation unit 104 that generates a probability distribution of a sales likely quantity of the target product in a prescribed sales likely period as to the individual sales and the carton sales using the individual parameter and the carton parameter, and calculates a safe inventory quantity separately used in a periodic ordering method as to the individual sales and the carton sales on the basis of each of the probability distributions.

Description

  The present invention relates to an information processing device, an information processing system, an information processing method, and a program.

  An example of a technique for managing the inventory of products is described in Patent Document 1. This document describes that in the inventory simulation method, when calculating the order quantity from the predicted demand quantity of each product, the appropriate inventory quantity is calculated using the normal distribution or Poisson distribution based on the predicted demand quantity. Yes. In addition, it is stated that the normal distribution is useful when the number of sales per day is several tens or more, while the Poisson distribution is useful for few products and new products with small daily sales. Yes.

JP 2010-86278 A

However, when the Poisson distribution is used for few products, new products, etc., and the normal distribution is used for products with more than tens of sales, as in the technology described in the above document, the forecast required for certain products There was a problem that the demand amount often deviated from the actual results.
The inventor of the present invention, even if it is the same product, may be sold in different sales units, such as individual sales to sell the product alone and carton sales to sell a plurality of products together, In this case, we focused on the difference in sales characteristics (situation) between individual sales and carton sales. Then, the inventor of the present invention finds that the demanded demand demand is often deviated from the actual results in the products sold in such two types of sales units, and calculates the probability distribution of the sales volume for each sales form. By finding it, I found that the prediction result approximated the actual results. Here, the carton sale means a sale form in which a plurality of identical products are sold together, and may be called box sale, case sale, dozen sale, or the like. “Carton sales” does not limit the types of products sold.
The idea of calculating the predicted demand amount by obtaining the probability distribution of the sales amount for each sales form such as individual sales and carton sales was not found in the technique described in the above-mentioned literature.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide an information processing apparatus capable of improving the accuracy of calculation of the estimated sales amount and appropriately maintaining the safety stock amount in the inventory management of products, To provide an information processing system, an information processing method, and a program.

According to the present invention, the parameter acquisition means for acquiring the individual parameters relating to the individual sales quantity of the target product and the carton parameters relating to the carton sales quantity of the target product;
Using the individual parameters and the carton parameters, the individual sales and the carton sales are each generated with a probability distribution of the expected sales amount of the target product in a predetermined sales prospect period, and the individual sales are based on each probability distribution. And an inventory calculating means for calculating a safety stock amount used in the periodic ordering method separately for the carton sales,
An information processing apparatus is provided.

  According to this invention, the probability distribution of the expected sales amount is generated separately for the individual sales and the carton sales, and the safety stock amount is calculated from each probability distribution. Therefore, the probability distribution is not divided into the individual sales and the carton sales. Compared with the case of obtaining, it is possible to obtain a value close to the actual result, and in the inventory management of products, it is possible to appropriately maintain the safety stock amount that is excessively retained to prevent the shortage.

According to the present invention, a store terminal that holds the sales amount of individual sales of target products for a predetermined period and the sales volume of carton sales of the target products;
A server that collects and holds the sales volume of the individual sales and the sales volume of the carton sales from the store terminal,
The server
An information processing system for realizing at least a part of the information processing apparatus of the present invention is provided.

According to the present invention, an information processing apparatus
Obtain individual parameters for the quantity of individual sales of the target product and carton parameters for the quantity of carton sales of the target product,
Using the individual parameters and the carton parameters to generate probability distributions for the individual sales and the carton sales, respectively;
Based on each probability distribution, an information processing method is provided for calculating the safety stock amount used in the periodic ordering method separately for the individual sales and the carton sales.

According to the present invention, a computer
Obtaining individual parameters relating to the quantity of individual sales of the target product and carton parameters relating to the quantity of carton sales of the target product;
Using the individual parameters and the carton parameters to generate probability distributions for the individual sales and the carton sales, respectively.
A procedure for calculating a safety stock amount used in the periodic order method separately for the individual sales and the carton sales based on each probability distribution;
A program for executing the above is provided.

  It should be noted that any combination of the above-described constituent elements and a conversion of the expression of the present invention between a method, an apparatus, a system, a recording medium, a computer program, etc. are also effective as an aspect of the present invention.

  The various components of the present invention do not necessarily have to be independent of each other. A plurality of components are formed as a single member, and a single component is formed of a plurality of members. It may be that a certain component is a part of another component, a part of a certain component overlaps with a part of another component, or the like.

  Further, although a plurality of procedures are described in order in the information processing method and the computer program of the present invention, the described order does not limit the order in which the plurality of procedures are executed. For this reason, when the information processing method and the computer program of the present invention are implemented, the order of the plurality of procedures can be changed within a range that does not hinder the contents.

  Furthermore, the plurality of procedures of the information processing method and the computer program of the present invention are not limited to being executed at different timings. For this reason, another procedure may occur during the execution of a certain procedure, or some or all of the execution timing of a certain procedure and the execution timing of another procedure may overlap.

  According to the present invention, there are provided an information processing apparatus, an information processing system, an information processing method, and a program for appropriately maintaining a safe stock quantity in inventory management of products.

It is a functional block diagram which shows the logical structure of the information processing apparatus which concerns on embodiment of this invention. It is a figure for demonstrating the periodic order method in the inventory management of goods. It is a figure for demonstrating the Poisson distribution used at the time of calculation of an estimated sales amount in the information processing apparatus which concerns on embodiment of this invention. It is a figure which shows an example of the probability distribution of the Poisson distribution used by the information processing apparatus which concerns on embodiment of this invention at the time of sales amount calculation, and a cumulative probability distribution. It is a figure for demonstrating the relationship between the probability distribution by the Poisson distribution of the sales amount, and a track record calculated in the information processing apparatus which concerns on embodiment of this invention. It is a block diagram which shows the hardware constitutions of the computer which implement | achieves the information processing apparatus which concerns on embodiment of this invention. It is a flowchart which shows an example of operation | movement of the information processing apparatus which concerns on embodiment of this invention. It is a functional block diagram which shows the logical structure of the information processing apparatus which concerns on embodiment of this invention. It is a functional block diagram which shows the logical structure of the information processing apparatus which concerns on embodiment of this invention. In merchandise inventory management, it is a figure for demonstrating the normal distribution used at the time of calculation of an estimated sales amount. It is a figure for demonstrating the safe stock amount calculation method using normal distribution in merchandise inventory management. It is a flowchart which shows an example of operation | movement of the information processing apparatus which concerns on embodiment of this invention. It is a figure which shows the structural example of the information processing system which concerns on embodiment of this invention.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same reference numerals are given to the same components, and the description will be omitted as appropriate.

(First embodiment)
FIG. 1 is a functional block diagram showing a logical configuration of the information processing apparatus 100 according to the embodiment of the present invention.
An information processing apparatus 100 according to an embodiment of the present invention includes a parameter acquisition unit 102 that acquires an individual parameter related to an individual sale quantity of a target product and a carton parameter related to a carton sale quantity of the target product, and an individual parameter and a carton parameter. Are used to generate probability distributions of the estimated sales volume of the target product for the specified sales forecast period for individual sales and carton sales, and based on each probability distribution, separately for individual sales and carton sales, using the periodic order method. An inventory calculation unit 104 that calculates a safety stock amount to be used.

The information processing apparatus of the present invention calculates the safety stock amount used in the periodic ordering method with high accuracy.
Hereinafter, the periodic ordering method will be described with reference to FIG.
In the periodic ordering method, the ordering cycle from ordering to the next ordering is a fixed interval, and the ordering quantity differs for each ordering cycle.
For example, as shown in FIG. 2, when the order of the target product is fixed to two patterns of (1) Friday order and Wednesday delivery, and (2) Tuesday order and Saturday delivery, inventory management is performed according to the periodic order method. . Here, the arrival quantity of the product delivered on Wednesday by the Friday order is the planned shipment quantity for the period until it is delivered on Saturday by the next Tuesday order (shown as “procurement period T” in the figure).

In this specification, an order cycle from ordering to the next ordering is called an ordering interval O, and a period obtained by combining the ordering interval O and a procurement period T is called a sales prospect period. In the example shown in the figure, the estimated sales period is 8 days.
In the periodic ordering method, the demand forecast for this expected sales period (O + T) is made, and the stock quantity at the time of ordering and the quantity not yet received (for example, the planned arrival of the previous Tuesday order at the time of ordering on Friday) Based on this, the order quantity can be determined. At this time, it is possible to prevent an out-of-stock condition by securing an extra inventory in consideration of fluctuations in the shipping amount. Such stock is called “safety stock”, and this safety stock quantity A is also taken into consideration when determining the order quantity.

The order quantity can be obtained by the following equation (1).
Order quantity = Expected sales quantity + Safety stock quantity
-(Inventory quantity at the time of ordering + Quantity not yet received for ordering) ... Formula (1)

Hereinafter, the safety stock amount will be described. As mentioned above, the safety stock is to secure extra stock for the purpose of preventing the product from being out of stock because there is a variation in the shipment amount of the product, This is not preferable because it increases the cost of storage and management. For this reason, it is extremely important to keep the safety stock amount appropriate for inventory management.
In the present embodiment, the inventory calculation unit 104 in FIG. 1 calculates this safety stock quantity.

The parameter acquisition unit 102 acquires individual parameters related to the quantity of individual sales of the target product and carton parameters related to the quantity of carton sales of the target product.
In the present invention, the “target product” means a product sold in a plurality of different sales units, such as individual sales in which individual products are sold individually and carton sales in which a predetermined number of products are sold together. If the product is sold in such a plurality of sales units, the product type of the “target product” is not limited. The product types of “target products” include, for example, bottles of tobacco, beer, juice, tea, water, beverages in various containers such as cans, paper packs, plastic bottles, gums, candy, and other sweets. There are grocery products, bath products, detergents, stationery and other daily goods.

  The “target product” in the present invention means a product of a unit for inventory management or ordering, and is distinguished by at least one of a brand (brand) name and a product name, for example. The “target product” includes not only the brand name and product name, but also the size, capacity, packaging form (main body / refill, soft pack / box type, etc.), material, color, pattern, taste, fragrance (menthol) , Floral, mint, etc.), ingredients (tar value, nicotine value, presence / absence of caffeine, etc.), presence / absence of options, target age, target sex, production (origin) place, manufacturer, sales period, sales area, etc. In addition, it may be a distinguished item. For example, the “target product” may be identified by a product item code.

In the present invention, the “target product” as described above is a processing target, and the safety stock quantity and the order quantity are calculated for each target product. In the present invention, a plurality of target products can be targeted, and a safety stock quantity and an order quantity can be calculated for each group of a plurality of target products.
For example, a plurality of products of a certain brand family can be used as target products, or products of different brands of menthol system can be used as target products.

  Note that the present invention does not exclude the case where the calculation target range of the safety stock quantity and the order quantity is not classified by brand or brand group as described above. For example, in the case of soy milk that has multiple products with different tastes such as strawberry flavor and matcha flavor, the information processing apparatus of the present invention collects the product type of “soy milk” from a certain manufacturer regardless of the type of taste. The safety stock quantity and the order quantity can be calculated as targets. According to such a configuration, it is possible to place an order with a product type “soy milk” of a manufacturer from a store and select the brand or taste type of the product as appropriate and provide the store to the store. . Alternatively, the safety stock quantity and the order quantity can be calculated for a group of products of different brands that are bundled in units different from the brand, such as product attributes such as manufacturers.

  In addition, the number of products contained in one carton can be considered in various ways. For example, in the case of beer, one package of 6 cans and one box of 24 cans (or 4 packages (6 cans / pack)). As for carton sales, there are several different sales forms.

  In the information processing apparatus 100 according to the present embodiment, parameters relating to the sales quantity are obtained for each of two types of sales forms, that is, individual sales and carton sales, and a probability distribution of expected sales quantities is generated, respectively, and safety stock quantities are calculated. This is described as an example. However, the information processing apparatus of the present invention obtains the parameters related to the sales quantity for each of the different sales forms (one can, one package, one box, etc.) and generates a probability distribution of the expected sales quantity. And the form which calculates each safe stock quantity can be included.

Here, the individual parameter and the carton parameter are information necessary for generating a probability distribution of the expected sales amount of the target product in a predetermined expected sales period. As will be described later, the contents of each parameter differ depending on the method for obtaining the probability distribution of the expected sales amount.
In the present specification, for example, a configuration for obtaining a probability distribution of an expected sales amount using a Poisson distribution and a normal distribution (to be described later in another embodiment) is described, but the present invention is not limited to this, and various methods are used. Can be adopted.

The inventory calculation unit 104 uses the individual parameter and the carton parameter acquired by the parameter acquisition unit 102 to generate a probability distribution of the expected sales amount of the target product in the predetermined sales prospect period for the individual sales and the carton sales, respectively. Then, the inventory calculation unit 104 calculates the safety stock amount used in the periodic ordering method separately for individual sales and carton sales based on the generated probability distributions.
As described above, in the present invention, the individual sales and the carton sales are divided to obtain the probability distribution indicating the variation in the estimated sales volume, and the safety stock quantity is calculated by adopting the periodic ordering method. Since the estimated sales volume can be estimated by separately considering the situation and the sales situation in carton sales, the safety stock quantity can be calculated with high accuracy as a result.

In the information processing apparatus 100 of the present embodiment, the parameter acquisition unit 102 acquires an average sales amount of individual sales of the target product in a predetermined period as an individual parameter, and an average of carton sales of the target product in the predetermined period as a carton parameter. Get sales volume.
The inventory calculation unit 104 generates Poisson distributions for individual sales and carton sales using the average sales amounts for individual sales and carton sales, and calculates the occurrence probability for each estimated sales amount obtained from each generated Poisson distribution. The estimated sales amount in which the cumulative probability of the individual sales and the cumulative probability of the carton sales satisfy the required probability regarding the shortage of the target product is calculated as each safety stock quantity of the individual sales and the carton sales.

Here, the required probability is a probability required for a shortage of the target product, and in that probability, a shortage prevention rate indicating a probability that the demand for the product for a certain period can be handled without causing a stockout, Alternatively, a shortage rate indicating the probability that the demand cannot be met due to out of stock is indicated. Note that the absence of a product leads to an improvement in service, so the missing item prevention rate is also called a service rate.
Here, the shortage prevention rate and the shortage rate have the following relationship.
Out-of-stock prevention rate α = 1−Out-of-stock rate β
Further, the shortage rate β is obtained by the following formula.
Out-of-stock rate β = Out-of-stock quantity / Total demand quantity (3)

<Poisson distribution>
Here, the Poisson distribution will be described with reference to the drawings.
FIG. 3 is a diagram for explaining the Poisson distribution used when calculating the estimated sales amount in the information processing apparatus of the present invention.
The Poisson distribution is a distribution P (x) indicating a probability that an event appears x times when a population average λ within a predetermined period is given as a parameter. It is known that this Poisson distribution is particularly applicable to an event with a small number of appearances.
FIG. 3A shows an example of Poisson distribution for each parameter λ. The horizontal axis k represents the sales volume, and the vertical axis represents the occurrence probability for each sales volume. As the population average λ increases (for example, when the parameter λ = 10), it can be seen that the Poisson distribution shows a shape close to the normal distribution.
FIG. 3B shows a cumulative probability distribution obtained by accumulating occurrence probabilities for each sales amount obtained by the Poisson distribution shown in FIG.

FIG. 4 is a table showing the probability distribution of the Poisson distribution and the cumulative probability distribution when the average sales amount in the predetermined period is five.
How to read this table is, for example, “The probability of selling two in a predetermined period is 8.4% of the row indicated by T1 in the figure, and the probability that the sales volume is two or less is 12.5. %. ” In addition, the probability that the average sales amount is five and the product is sufficient (not missing) within a predetermined period is 61.6% of the row indicated by T2 in the figure. In addition, the probability of selling 11 pieces within a predetermined period is 0.8% of the row indicated by T3 in the figure, and the probability that the sales amount is 11 or less is 99.5%.

  For example, in a store, for each product, by setting the probability that the product Y within a certain period will not be missing (hereinafter referred to as the missing item prevention rate), the sales volume that satisfies the missing item prevention rate is predicted from the Poisson distribution. can do. For example, the probability of selling 10 pieces is 1.8% of the row indicated by T4 in the figure, and the probability that the sales volume is 10 pieces or less is 98.6%. Therefore, the shortage prevention rate of 98% or more is satisfied. If the sales amount is 10 and this is the safety stock amount, it is possible to prevent out of stock with a probability of 98% or more.

Fig. 5 is a diagram showing the probability distribution and the actual results of the Poisson distribution of the sales volume when cigarettes are taken as an example and when individual sales and carton sales are not divided, and when individual sales and carton sales are divided. is there. The line graph shows the probability distribution by the Poisson distribution of the sales volume, and the bar graph shows the actual sales volume.
FIG. 5A is a diagram comparing the probability distribution based on the Poisson distribution of sales volume and the actual results when individual sales and carton sales are not separated. FIG. 5B and FIG. 5C are diagrams when individual sales and carton sales are separated. Fig. 5 (b) is a diagram comparing the probability distribution by the Poisson distribution with the actual sales volume for the individual sales volume, and Fig. 5 (c) shows the probability distribution and the actual results by the Poisson distribution for the carton sales volume. FIG.

FIG. 5A shows that there is a difference between the probability distribution (theoretical value) based on the Poisson distribution of sales volume and the actual results, and it is difficult to predict the sales volume accurately using the Poisson distribution. On the other hand, in FIG. 5 (b) and FIG. 5 (c), the probability distribution (theoretical value) based on the Poisson distribution of the sales volume is almost the same, and the sales volume is larger than that in the case of FIG. 5 (a). It can be seen that the accuracy of prediction is improved.
As described above, according to the present invention, the probability distribution of the sales amount is obtained separately for individual sales and carton sales, and the safety stock amount is calculated based on each probability distribution. Therefore, the accurate safety stock amount is calculated. be able to.

FIG. 6 is a block diagram showing a hardware configuration of a computer 60 that implements the information processing apparatus 100 according to the embodiment of the present invention.
An information processing apparatus 100 according to an embodiment of the present invention includes, for example, a CPU (Central Processing Unit) 62, a ROM (Read Only Memory) 64, a RAM (Random Access Memory) 66, an I, as shown in FIG. / O (Input / Output) 68, and can be realized by a computer 60 connected to an operation input device 74 such as a keyboard and a mouse, a display device 72 such as a display, and an output device (not shown) such as a printer. The CPU 62 is connected to each element via a bus 69 and controls the entire computer 60 together with each element.

  The information processing apparatus of the present invention can be realized by a server computer, a personal computer, a tablet terminal, a smartphone, or a computer corresponding to them. The information processing apparatus of the present invention is not limited to realizing the functions of the components shown in FIG. 1 with a single computer. A plurality of computers may share the functions to realize the information processing apparatus of the present invention. The information processing apparatus of the present invention may be configured by a virtual server or the like.

Each component of the information processing apparatus 100 in FIG. 1 includes a CPU 62 in FIG. 6, a memory (RAM 66), a program 70 that realizes the components in FIG. 1 loaded in the memory, and a storage unit such as a hard disk that stores the program 70. (ROM 64) and an arbitrary combination of hardware and software of an arbitrary computer 60 having a network connection interface (I / O 68). It will be understood by those skilled in the art that there are various modifications to the implementation method and apparatus. FIG. 1 shows a block of logical functional units, not a configuration of hardware units.
In FIG. 1, the configuration of parts not related to the essence of the present invention is omitted and is not shown.
The ROM 64 and the RAM 66 may be other devices having an auxiliary storage function such as a flash memory, a hard disk, and a CD (Compact Disc).

  In the present invention, each CPU 62 of a single computer or a plurality of computers 60 executes the computer program 70 of the present invention, thereby performing various processing operations corresponding to the information processing method of the present invention. Various units of the processing apparatus are realized as various functions.

  The computer program 70 according to the embodiment of the present invention stores, in the computer 60, the individual parameter relating to the individual sale quantity of the target product and the procedure for obtaining the carton parameter relating to the carton sale quantity of the target product, the individual parameter and the carton parameter. To generate probability distributions for individual sales and carton sales, respectively, and to calculate the safety stock used in the periodic order method separately for individual sales and carton sales based on each probability distribution It is described to let you.

  The computer program 70 of this embodiment may be recorded on a recording medium readable by the computer 60. The recording medium is not particularly limited, and various forms can be considered. The program 70 may be loaded from a recording medium into the memory of the computer 60, or may be downloaded to the computer 60 through a network and loaded into the memory.

In the configuration as described above, an information processing method by the information processing apparatus 100 according to the present embodiment will be described below.
FIG. 7 is a flowchart illustrating an example of the operation of the information processing apparatus 100 according to the present embodiment.
In the information processing method according to the embodiment of the present invention, the information processing apparatus 100 acquires the individual parameter relating to the individual sale quantity of the target product and the carton parameter relating to the carton sale quantity of the target product (step S101). Using the parameters and carton parameters, probability distributions are generated for individual sales and carton sales, respectively (step S103), and based on each probability distribution, the safety stock used in the periodic order method separately for individual sales and carton sales. The amount is calculated (step S105).

  More specifically, first, in the information processing apparatus 100, the parameter acquisition unit 102 acquires an individual parameter related to the individual sales quantity of the target product and a carton parameter related to the carton sales quantity of the target product (step S101). As described above, in the present embodiment, the parameter acquisition unit 102 acquires the average sales amount of the individual sales of the target product in the predetermined period as the individual parameter, and the average of the carton sales of the target product in the predetermined period as the carton parameter. Get sales volume.

  Then, the inventory calculating unit 104 generates probability distributions for individual sales and carton sales using the individual parameters and carton parameters (step S103). As described above, in the present embodiment, the inventory calculation unit 104 generates a Poisson distribution for individual sales and carton sales using the average sales amounts of individual sales and carton sales, respectively.

  Then, the inventory calculation unit 104 calculates the safety stock amount used in the periodic ordering method separately for individual sales and carton sales based on each probability distribution (step S105). As described above, in the present embodiment, the inventory calculation unit 104 determines that the cumulative probability of individual sales and the cumulative probability of carton sales obtained by accumulating the occurrence probability for each estimated sales amount obtained from each generated Poisson distribution are the target products. The estimated sales volume that satisfies the required probability of missing items (for example, the missing item prevention rate) is calculated as each safety stock quantity for individual sales and carton sales.

Based on the safety stock of individual sales and carton sales determined in this way, the quantity is converted into at least one of the unit of the single product and the unit of the carton that combines multiple products. The safety stock amount of the entire product may be obtained.
Note that the start timing of this flowchart is not particularly limited. It may be started by a user activation instruction, or may be automatically started on a predetermined date.

In addition, because many users prefer to purchase products, the top brands with a high expected sales volume are always purchased by only a minority user, so the lower brands with a low sales forecast volume are always low, and the middle sales prospects. It is roughly classified into medium stocks in quantity.
Products often have different sales volume characteristics depending on the brand or series of brands. In the present invention, a plurality of target products are set as processing targets, and the plurality of target products are grouped by, for example, an average sales amount.
The request probability is preferably set for each product or group. For example, it is possible to lower the stockout rate β for the upper brands and increase the stockout rate β for the middle and lower brands.

In addition, the information processing apparatus 100 according to the present embodiment may further include a reception unit (not illustrated) that receives a request probability that is set according to the estimated sales amount for each target product or for each group.
The reception unit can be realized by, for example, the operation input device 74 of FIG. In addition, a table in which a request probability is predetermined for each target product or group may be used, or a value predetermined by a program may be used.

  As described above, according to the information processing apparatus 100 of the embodiment of the present invention, the probability distribution of the expected sales amount is generated separately for individual sales and carton sales, and the safety stock amount is calculated from each probability distribution. Therefore, compared with the case of obtaining probability distribution without dividing individual sales and carton sales, it is possible to obtain values close to actual results with high accuracy, and in order to prevent missing items in product inventory management, it is retained excessively. There is an effect that it is possible to keep the safe stock amount appropriately.

(Second Embodiment)
FIG. 8 is a functional block diagram showing a logical configuration of the information processing apparatus 200 according to the embodiment of the present invention.
The information processing apparatus 200 according to the embodiment of the present invention is further different from the above embodiment in that the order quantity is calculated based on the safety stock quantity obtained in the above embodiment.
The information processing apparatus 200 of the present embodiment can also include the configuration of the information processing apparatus 100 of the above-described embodiment of FIG. 1, but is omitted in FIG.

The information processing apparatus 200 according to the embodiment of the present invention further includes an information acquisition unit 206 and an order quantity calculation unit 208.
The information acquisition unit 206 uses the conversion unit that is one of the individual sales unit and the carton sales unit, and the estimated sales amount of the individual sales and the expected sales amount of the carton sales, the stock quantity at the time of ordering, and the ordering in the sales period. Acquire information on the amount of goods not yet received.
The order quantity calculation unit 208 converts the safety stock quantity of individual sales or carton sales into the conversion unit, and based on the periodic order method, the converted safety stock quantity, the other safety stock quantity, and the estimated sales quantity of individual sales. The order quantity is calculated from the estimated sales volume of the carton sale, the stock quantity at the time of order placement, and the unreceived quantity ordered.

The order quantity Q during the expected sales period can be obtained by the following equation (4).
Order quantity Q = (D1 + D2) + (A1 + A2) − (S1 + S2) Expression (4)
Where D1 is the estimated sales volume for individual sales, D2 is the estimated sales volume for carton sales, A1 is the safety inventory volume for individual sales, A2 is the safety inventory volume for carton sales, S1 is the inventory quantity at the time of ordering, and S2 is already ordered This is the amount not yet received.

  Note that the estimated sales amount D1 for individual sales and the estimated sales amount D2 for carton sales are, for example, the average sales amounts for individual sales and carton sales for the target product acquired by the parameter acquisition unit 102 of the above embodiment. It is also possible to use the estimated number of sales days. Alternatively, the information acquisition unit 206 acquires the individual sales amount and monthly carton sales amount of the target product for any month, and calculates the average sales amount per business day divided by the number of store business days in the month, Each of the average sales volume may be obtained by multiplying the estimated sales days.

  Similarly to the information processing apparatus 100 of the above embodiment, the information processing apparatus 200 of the present embodiment is also realized by an arbitrary combination of hardware and software of the computer 60 shown in FIG. In the information processing apparatus 200, the CPU 62 executes various processing operations corresponding to the computer program 70, thereby realizing the various units in FIG. 8 as various functions. FIG. 8 shows a block of logical functional units, not a configuration of hardware units.

  Further, in the present embodiment, the information processing apparatus 200 includes a plurality of target products as processing targets, and the plurality of target products are grouped by average sales amount, and the order quantity calculated by the order quantity calculation unit 208 is Determine whether or not fractions will be generated in terms of order units (for example, in carton units). If fractions occur, perform processing specified according to the expected sales volume for each target product or group, An order quantity adjustment unit 212 that rounds off the order quantity can be further provided.

This means that, for example, when an order is placed in units of cartons instead of units, the order quantity calculated in units of units is converted into units of cartons. At this time, for example, if the order quantity is 23, it becomes 2.3 carton and a fraction is generated. In such a case, the influence on the inventory amount varies greatly depending on whether the fraction is rounded up or down. For example, if it is a higher brand, there is no problem even if it is rounded up. However, in the case of a lower brand product, if it is rounded up, the stock may become excessive depending on the scale of the store.
Therefore, in this embodiment, the order quantity adjustment unit 212 needs to appropriately adjust the fraction of the order quantity.

The order quantity adjustment unit 212 can perform at least one of the following processes (a1) to (a5).
(A1) Processing for automatically rounding up fractions (a2) Processing for automatically rounding down fractions (a3) Processing for incrementing or rounding down fractions according to a received user instruction a4) Processing for automatically changing the request probability regarding the shortage of the target product within a range corresponding to the fraction so that no fraction is generated (a5) Accepting and accepting user designation of the width of the request probability regarding the shortage of the target product Processing to change the range of request probability according to specified user

  Further, in the information processing apparatus 200, the order quantity adjustment unit 212 determines, for each target product or each group, whether or not the expected sales amount is equal to or less than a predetermined value, and the target that is determined that the expected sales amount is not equal to or less than the predetermined value. The process (a1) is performed on the product or group, and at least one of the processes (a2) to (a5) is performed on the target product or group for which the estimated sales amount is determined to be a predetermined value or less. it can.

For example, it is possible to perform processing (a1) for rounding up fractions for the upper brands and processing (a2) for rounding down fractions for the middle and lower brands.
The fraction adjustment process by the order quantity adjustment unit 212 can be performed either manually or automatically.
Also, in (a4) and (a5), if the request probability has a certain width and is automatically raised and lowered, the fraction can be eliminated. Moreover, it is good also as a structure which shows the recommended value (value for rounding up and the value for rounding down) of the request | requirement probability that a fraction does not appear to a user. The user can change the request probability with reference to the recommended value.

Further, when the order quantity has a fraction in relation to the order unit, the information may be presented to the user when the fraction is within a predetermined range. For example, for a product of 10 cartons, if the fraction is in the range of 6 to 8, a product name (including brand name) and order quantity list may be presented to the user. The user can check the list, determine a fraction processing method for each product (brand), and accept a change in request probability.
Further, for example, for products (subordinate brands) that are less than a predetermined sales quantity, the fraction may be automatically rounded off.

In (a3) above, in a configuration in which the user is inquired whether to round up or round down, the following procedure may be used.
The user is notified that fraction adjustment is necessary (step S201). Then, the target product list is presented to the user so that the lower brand product is higher (step S203). Then, the user is inquired whether or not to round off the fraction for each target product (step S205). The fraction of the target product that has received an instruction to round down the fraction from the user is rounded down (step S207).
Alternatively, the following procedure may be used instead of steps S203 to S207.
The target product list is presented to the user so that the higher brand product is higher (step S213). Then, the user is inquired whether to round up the fraction for each target product (step S215). The fraction of the target product that has received an instruction to raise the fraction from the user is incremented (step S217).

Moreover, the conditions which require fraction adjustment are illustrated below.
(B1) An upper limit (total stocker amount) of the quantity that can be stored as stock in the store is set so as not to place an order beyond the capacity of the storage location, and the total of the ordered quantity and the predicted inventory quantity at the time of delivery of the order is If the stocker amount is exceeded, the fraction is adjusted.
(B2) The upper limit of the order amount is set, and when the order amount exceeds the upper limit, the fraction is adjusted.
The total order amount is not particularly limited, and may be the target product, the total amount at the time of order placement, the monthly unit, or the semi-annual unit.

If fraction adjustment is necessary under the above conditions, as described above, the processing of (a3) can be performed, or the fraction adjustment processing can be automatically performed.
When the fraction adjustment process is automatically performed, the following procedure can be used.
The rounding down process is automatically performed in order from the lower brand product (step S221). The process in step S221 is repeated until the total stocker amount (or a predetermined upper limit amount) is reached or less (step S223).
Alternatively, the rounding process is automatically performed in order from the top brand product (step S231). The processing in step S231 is repeated until a predetermined total stocker amount (or a predetermined upper limit amount) is exceeded, the product advance processing when it is exceeded is canceled, and the remaining products are rounded down (step S233).

Furthermore, the information processing apparatus 200 of this embodiment includes a presentation unit 210.
The presentation unit 210 displays information indicating at least one of the correspondence relationship between the safety stock amount and the request probability together with the safety stock amount, and the relationship between the order amount and the request probability together with the order amount, for each target product. And at least one of each group.

  Various methods of presenting information by the presentation unit 210 are conceivable. For example, the information can be displayed or printed out on an output device such as a display device 72 or a printer (not shown) connected to the computer 60 and presented to the user. Alternatively, the information data can be stored in a recording medium or a storage device and provided to the user, or the user can access the storage device in which the information data is stored via a network to refer to or download the information. Or provide it. Various timings of presentation are also conceivable and are not particularly limited.

  As described above, according to the information processing apparatus 200 according to the embodiment of the present invention, the same effect as the above embodiment can be obtained, and furthermore, the probability distribution obtained separately for individual sales and carton sales is used. Since the order quantity is calculated based on the calculated safety stock quantity, it is possible to place an order with an appropriate order quantity.

(Third embodiment)
FIG. 9 is a functional block diagram showing a logical configuration of the information processing apparatus 300 according to the embodiment of the present invention.
The information processing apparatus 300 according to the embodiment of the present invention is different from the above embodiment in that the probability distribution of the expected sales amount of the target product within a predetermined period is switched from the Poisson distribution to the normal distribution according to a predetermined switching condition. Is different.
The information processing apparatus 300 according to the present embodiment has the same configuration as the information processing apparatus 100 according to the above-described embodiment illustrated in FIG. 1, and further includes a determination unit 320. Further, the information processing apparatus 300 according to the present embodiment may further include a configuration similar to that of the information processing apparatus 200 according to the above-described embodiment illustrated in FIG. Note that the parameter acquisition unit 302 and the inventory calculation unit 304 of the present embodiment are different from the parameter acquisition unit 102 and the inventory calculation unit 104 of the above embodiment in addition to the parameters used for the Poisson distribution as shown below. The difference is that the parameters used for the acquisition are acquired and used for the inventory calculation process.

The information processing apparatus 300 according to the embodiment of the present invention includes a determination unit 320 that determines, for each sales unit of individual sales and carton sales, whether or not to switch the Poisson distribution to a normal distribution based on a predetermined switching condition. Further prepare.
For the sales unit determined to be switched to the normal distribution by the determination unit 320, the parameter acquisition unit 302 uses the individual sales amount (actual) of the target product in a predetermined period or the carton sales of the target product as the individual parameter or carton parameter. The average sales volume calculated from the sales volume and the standard deviation σ thereof are respectively acquired.
Further, for the sales unit determined to be switched to the normal distribution by the determination unit 320, the inventory calculation unit 304 switches the Poisson distribution to the normal distribution, and uses the average sales amount (predetermined period) μ and its standard deviation σ. Each of the normal distributions indicating the probability distribution of the sales potential amount of the target product in the sales potential period is generated. Then, the inventory calculation unit 304 obtains a safety coefficient k that satisfies a required probability (shortage prevention rate α or shortage rate β) related to the shortage of the target product from the normal distribution, the safety coefficient k, the standard deviation σ, and a predetermined value The safety stock quantity A is calculated based on the estimated sales period (T + O).

In the information processing apparatus 300 according to the present embodiment, the determination unit 320 determines that the average sales amount of the target product is greater than or equal to a predetermined value as a switching condition for switching the Poisson distribution to the normal distribution.
For example, in this embodiment, when the average sales amount is 10 or more, the distribution is switched to the normal distribution.
Or, for products whose average sales volume is constantly known for each product or group, for example, the upper brands have a large average sales volume, so that the target product is a higher distribution in a normal distribution. Switching conditions for switching may be used.

<Normal distribution>
Hereinafter, a method for obtaining the probability distribution of the expected sales amount with the normal distribution will be described with reference to the drawings.
FIG. 10 and FIG. 11 are diagrams for explaining a normal distribution used when calculating the estimated sales amount in general merchandise inventory management.
The normal distribution is a probability distribution (shown as “probability density” in the figure) indicating the probability that an event will occur x times when the average sales amount μ within a predetermined period and its standard deviation σ are given as parameters. . FIG. 10 shows each probability distribution when the parameter average sales amount μ is the same and the standard deviation σ is different.
Note that the daily sales volume within a predetermined period can be used for calculating the standard deviation σ.

ここで、Ａは、安全在庫量、ｋは安全係数、（Ｔ＋Ｏ）は販売見込み期間、σは平均販売量μの標準偏差である。 When calculating the safety stock quantity using the regular ordering method using the normal distribution, the following formula (5) can be used.

Here, A is the safety stock quantity, k is the safety coefficient, (T + O) is the expected sales period, and σ is the standard deviation of the average sales quantity μ.

This will be further described with reference to FIG.
FIG. 11A shows a normal distribution in which α is the average sales amount μ and the standard deviation σ is 1. The probability p (α) when the standard deviation σ is larger than α is referred to as a risk rate at which the average sales amount μ is greater than or equal to α. For example, in the figure, a danger rate of 2.3% when α is 2 is shown.
Here, when the standard deviation of the average daily shipping amount is σ and the normal distribution of FIG. 11A is applied, as shown in FIG. 11B, from the stock amount at the time of ordering, within the procurement period, Shipments will decrease while fluctuating. In the case of a theoretical value that constantly decreases with the average daily shipment, it decreases as shown by the broken line. However, since the sales amount actually fluctuates with a certain probability according to the normal distribution, the stock amount may fluctuate above and below the theoretical value indicated by the broken line as shown in the actual results. Therefore, it is necessary to prepare a safety stock so as not to cause a shortage even when the shipment amount is the largest and the inventory amount is the smallest.

  For example, when the risk rate is 2.3%, α is 2, and this α corresponds to the safety coefficient k in the above equation (5). The safety factor k can be determined from the required probability. For example, when the shortage prevention rate is 97%, the shortage rate is less than 3%. The safety factor is 2. When the shortage prevention rate is 99%, the shortage rate is less than 1%, and therefore a safety factor 2.33 is set to a risk rate of 1.0% that satisfies this requirement.

Further, in the information processing apparatus 300 of the present embodiment, a plurality of target products may be included in the processing target, and the plurality of target products may be grouped by average sales amount.
The inventory calculation unit 304 can calculate the safety stock quantity using the request probability set for each target product or each group.

Since the request probabilities differ between the upper issue, the middle issue, and the lower issue, the request probability is set for each issue category (for example, higher / middle / lower) by the reception unit of the above embodiment, and the inventory calculation unit 304 It is preferably used when calculating the safety stock quantity.
For example, since the shortage rate may be high for items with a small expected sales volume, the shortage prevention rate for lower brands may be lower than that for higher brands.

  In the information processing apparatus 300 according to the present embodiment, the determination unit 320 can perform determination processing for each sales unit for each target product or each group.

FIG. 12 is a flowchart showing an example of the operation of the information processing apparatus 300 according to the embodiment of the present invention.
As illustrated in FIG. 12, in the information processing apparatus 300, the determination unit 320 determines, based on a predetermined switching condition, whether to switch the Poisson distribution to a normal distribution for each sales unit of individual sales and carton sales. (Step S301). Here, it is determined whether the average sales amount is 10 or more for each of the individual sales and the carton sales.

For the sales form of the sales unit whose average sales amount is 10 or more, the inventory calculation unit 304 performs processing for switching the Poisson distribution to the normal distribution, generating the normal distribution, and calculating the safety stock amount (step) S303). At this time, the average sales amount respectively acquired as the individual parameter and the carton parameter by the parameter acquisition unit 302 and its standard deviation are used.
On the other hand, for the sales form of the sales unit whose average sales amount is less than 10, the inventory calculation unit 304 generates a Poisson distribution and calculates the safety inventory amount (step S305). Note that when the safety stock quantity is calculated by using different distributions for the individual sales and the carton sales, both the processes of step S303 and step S305 are executed.

  Therefore, for stocks with an average sales volume of 10 or more, the safety stock quantity is calculated using a normal distribution, and for stocks with a low or medium price with an average sales volume of less than 10, safety stock is calculated using a Poisson distribution. The amount can be calculated. By performing this determination for each sales unit of individual sales and carton sales, it is possible to improve the calculation accuracy of the safety stock quantity.

  As described above, according to the information processing apparatus 300 according to the embodiment of the present invention, the same effect as the above embodiment can be obtained, and further, according to the average sales amount, the product (brand or group), etc. For each individual sale and carton sale, the probability distribution is obtained by switching the Poisson distribution and the normal distribution, and the safety stock quantity is calculated, so that the accuracy of the safety stock quantity can be further improved.

(Fourth embodiment)
FIG. 13 is a diagram illustrating a configuration example of the information processing system according to the embodiment of the present invention.
In the embodiment of the present invention, a configuration example of a system using the information processing apparatus of the present invention will be described.
In the configuration example of FIG. 13A, the server 420 realizes the function of the information processing apparatus of the present invention, and passes information related to product sales on the store side to the server 420 side. And at least one of the order quantity is calculated and presented to the store user.
The presentation method is not particularly limited. For example, the presentation method may be reported as a report to a terminal or system on the store side, or the information is taken in and displayed on a portable terminal (not shown) on the server side to the store user. May be presented.

In the configuration example of FIG. 13B, the function of the information processing apparatus of the present invention is realized in a terminal or system on the store side. For example, it can be installed as an application program in a store terminal or a computer of the system, or incorporated as a tool such as Microsoft Excel (registered trademark) of Microsoft Corporation.
13A and 13B may be combined and part of the functions of the information processing apparatus according to the present invention may be shared by the store terminal 410 and the server 420.

  The information processing system in FIG. 13A includes a store terminal 410 that holds a sales amount of an individual product for a predetermined period and a sales amount of a carton sale of the target product, and an individual sales amount from the store terminal 410 and And a server 420 that collects and holds the sales volume of carton sales.

  The store terminal 410 holds the sales amount of individual sales of the target product and the sales amount of carton sales of the target product in a sales information database (shown as “sales information DB” in the figure) 412 for a predetermined period. The store terminal 410 is constituted by, for example, a personal computer, a server computer, a tablet terminal, and the like, and is realized by any combination of computer hardware and software.

  Store terminal 410 is connected to server 420 via, for example, network 402. The sales amount of the individual sale of the target product and the sales amount of the carton sale of the target product for a predetermined period held by the store terminal 410 are transmitted to the server 420 via the network 402. The connection between the store terminal 410 and the server 420 may be at least one of wireless and wired, and the connection means is not particularly limited. Information may be transmitted and received by transmitting information from the store terminal 410 to the server 420, or by requesting information from the server 420 to the store terminal 410. The timing for transmitting and receiving information is not particularly limited.

Further, the means for transferring information between the store terminal 410 and the server 420 is not limited to that via the network 402, and for example, it is transferred via a portable recording medium such as a CD or a USB (Universal Serial Bus) memory. It may be a thing.
The server 420 stores and manages information on the sales amount acquired from the store terminal 410 in a management information database (shown as “management information DB” in the figure) 422.

The server 420 realizes at least a part of functions of the information processing apparatus of the present invention.
For example, the server 420 includes the configuration of the information processing apparatus 100 or the information processing apparatus 300 according to the above-described embodiment, and the parameter acquisition unit 102 (or parameter acquisition unit 302) acquires various parameters from the store terminal 410. Based on this, the inventory calculation unit 104 (or the inventory calculation unit 304) may calculate the safe stock quantity and output the result to the store terminal 410. At this time, the parameter for calculating the safety stock amount may be acquired from the store terminal 410, but information provided in advance from the store as data may be held in the server 420 and used.

The server 420 may further include the configuration of the information processing apparatus 200 of the above embodiment, calculate the order quantity, and output the result to the store terminal 410. At this time, as information for calculating the order quantity, information held by the server 420 may be used, or may be acquired from the store terminal 410 as necessary.
According to this configuration, information relating to sales is automatically acquired from the store terminal 410, and the server 420 can calculate and provide at least one of the safety stock amount and the order amount to the store.

  Further, in the information processing system of the present embodiment, the server 420 includes information on the safety stock quantity, information on the order quantity, safety stock quantity, and information indicating a correspondence relationship between the safety stock quantity and the request probability concerning the shortage of the target product. , And at least one of the information indicating the correspondence between the order quantity and the request probability together with the order quantity for each target product and at least one of each target product group for a predetermined period in the store terminal An information providing unit (not shown) to be provided is further provided.

  There are various ways of providing information by the information providing unit. For example, the information may be displayed on the monitor of the server 420 or the terminal on the server side, or the information may be stored in a recording medium and delivered to a store. Information may be transmitted as a report to server 420 via network 402. The format of the report is not particularly limited, and may be data, a file, a document, or an email as long as it is a form that can be received and referenced on the store side. Further, information may be requested from the store side to the server 420 or may be automatically transmitted from the server 420 to the store side.

  In the configuration example of FIG. 13B, the shop terminal 410 realizes at least a part of the functions of the information processing apparatus of the present invention. Since the store terminal 410 holds various information necessary for calculating the safety stock quantity or the order quantity, the store terminal 410 can acquire the information and calculate the safety stock quantity or the order quantity.

  As described above, according to the information processing system according to the embodiment of the present invention, the same effect as that of the above embodiment can be obtained, and the function of the information processing apparatus of the present invention can be applied to various system configurations. And various services can be provided to the user.

  As mentioned above, although embodiment of this invention was described with reference to drawings, these are the illustrations of this invention, Various structures other than the above are also employable.

<Correction based on event>
For example, in an information processing apparatus according to another embodiment, the parameter acquisition unit sets a correction parameter set according to the degree of influence on the sales quantity of an event that affects the sales quantity of the target product, at least for individual sales and carton sales. Either one of the parameters may be further acquired, and at least one of the individual parameter and the carton parameter may be corrected using the correction parameter.

For example, an event table is prepared, and correction parameters for correcting parameters at the time of the event are set for the target product or group. For example, a correction value for weighting such as 1.2 times the average sales amount at the time of an event is set. Since the degree of influence on individual sales and carton sales is further different depending on the type of event, it is preferable that each event can be set.
For example, at the end of the year or at the time of bonus payments, beer cartons are likely to be sold more than individual beers, so the correction parameter for carton sales should be set to a greater weight than individual sales. It can be carried out.

  Further, the parameter acquisition unit acquires the correction parameter together with the schedule of the event, detects the event time based on the calendar information, and uses the correction parameter corresponding to the detected event, and the individual parameter and the carton parameter. At least one of them may be automatically corrected.

  In addition, the parameter acquisition unit, for each event group divided into groups based on the event attributes, a correction that is set according to the target product or group that affects the sales volume due to the event, and the degree of influence on the sales volume of the event The information associated with the parameter is further acquired for at least one of individual sales and carton sales, and the correction parameter associated with the product or group corresponding to the event is used to obtain at least one of the individual parameter and the carton parameter. Either one may be corrected.

Here, the attributes of the event include, for example, the attributes of the customer group affected by the event (gender, age, occupation, marital / unmarried, etc.), and the attribute of the event venue (region (business district or residential) Locality, resort area, etc.), climate, weather (including forecast), etc.) or a combination thereof.
For example, in the event group related to kindergarten and elementary school, such as athletic meet, the consumption of fathers' generation will increase, so the weight of correction parameters for products for men in their 30s and 40s will be larger than other brands, It is also possible to make settings such as making the weight of correction parameters for products of brands for middle-aged and senior women larger than those of other brands, with the ground as an event group.

  In addition, when calculating the average sales volume based on the sales volume including the event, etc., by dividing the influence of the event on the sales volume by the weight value of the correction parameter based on the above event schedule, It is possible to determine the average sales volume excluding the impact of.

While the present invention has been described with reference to the embodiments and examples, the present invention is not limited to the above embodiments and examples. Various changes that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention.
In addition, when acquiring and using the information regarding a user in this invention, this shall be done legally.

Hereinafter, examples of the reference form will be added.
1. Information processing device
Obtain individual parameters for the quantity of individual sales of the target product and carton parameters for the quantity of carton sales of the target product,
Using the individual parameters and the carton parameters to generate probability distributions for the individual sales and the carton sales, respectively;
An information processing method for calculating a safety stock amount used in the periodic ordering method separately for the individual sales and the carton sales based on each probability distribution.
2. 1. In the information processing method described in
The information processing apparatus is
In the conversion unit that is one of the sales unit of the individual sales and the carton sales, the estimated sales volume of the individual sales and the expected sales volume of the carton sales, the stock quantity at the time of ordering, and the order completed in the sales forecast period Get information about undelivered quantities,
The safety stock quantity of the individual sale or the carton sale is converted into the conversion unit, and based on the periodic order method, the converted safety stock quantity, the other safety stock quantity, and the expected sales quantity of the individual sale, An information processing method for calculating an order quantity from an estimated sales quantity of the carton sale, the stock quantity at the time of order placement, and the ordered quantity not yet received.
3. 1. Or 2. In the information processing method described in
The information processing apparatus is
When acquiring the parameter, as the individual parameter, to obtain the average sales amount of the individual sale of the target product in a predetermined period, as the carton parameter, to obtain the average sales amount of the carton sale of the target product in the predetermined period,
When calculating the safety stock amount, a Poisson distribution is generated for each of the individual sales and the carton sales using the average sales amounts of the individual sales and the carton sales, and sales obtained from the generated Poisson distributions. The individual sales and the carton sales safety are determined as the individual sales and the carton sales, respectively, with the cumulative probability of the individual sales and the cumulative probability of the carton sales in which the occurrence probability for each expected quantity is accumulated satisfying the required probability regarding the shortage of the target product. An information processing method for calculating each stock quantity.
4). 3. In the information processing method described in
further,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The information processing apparatus is
When calculating the safety stock amount,
An information processing method for calculating the safety stock quantity using the request probability set for each target product or each group.
5. 4). In the information processing method described in
The information processing apparatus is
For each sales unit of the individual sales and the carton sales, determine whether to switch the Poisson distribution to a normal distribution based on a predetermined switching condition,
For sales units determined to switch to the normal distribution,
When obtaining the parameters,
As the individual parameter or the carton parameter, obtain the sales amount of the individual product of the target product in the predetermined period or the average sales amount calculated from the sales amount of the carton sale of the target product, and the standard deviation thereof, respectively.
When calculating the safety stock amount,
By switching the Poisson distribution to a normal distribution, using the average sales amount and the standard deviation, respectively, generate a normal distribution indicating a probability distribution of the sales potential amount of the target product in the sales potential period,
An information processing method for obtaining a safety coefficient satisfying a required probability related to a shortage of the target product from the normal distribution, and calculating a safety stock amount based on the safety coefficient, the standard deviation, and the predetermined expected sales period, respectively. .
6). 5. In the information processing method described in
The information processing apparatus is
An information processing method in which, when performing the determination, the switching condition for switching the Poisson distribution to a normal distribution is that the average sales amount of the target product is equal to or greater than a predetermined value.
7). 6). In the information processing method described in
The information processing apparatus is
An information processing method for performing the determination process for each sales unit for each target product or for each group when performing the determination.
8). 3. To 7. In the information processing method according to any one of the above,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The information processing apparatus further includes:
Information indicating at least one of the correspondence relationship between the safety stock amount and the request probability regarding the shortage of the target product, and the correspondence relationship between the order amount and the request probability, together with the order amount. An information processing method for presenting at least one of each target product and each group.
9. 3. To 8. In the information processing method according to any one of the above,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The information processing apparatus is
An information processing method for receiving a request probability relating to a shortage of the target product, which is set for each target product or for each group according to the estimated sales amount.
10. 3. Thru 9. In the information processing method according to any one of the above,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The information processing apparatus is
The calculated order quantity is converted into an order unit to determine whether or not a fraction is generated. If a fraction occurs, it is specified for each target product or each group according to the expected sales quantity. An information processing method for rounding off the fraction of the order quantity.
11. 10. In the information processing method described in
The information processing apparatus is
When adjusting the order quantity,
(A) a process of automatically rounding up the fraction;
(B) a process of automatically rounding down the fractions;
(C) A process of accepting a user instruction to round up or round down the fraction, and rounding up or rounding down the fraction according to the accepted instruction.
(D) a process of automatically changing a request probability relating to a shortage of the target product within a range corresponding to the fraction so that the fraction does not appear;
(E) a process of accepting a user specification of a request probability range related to a shortage of the target product, and changing the request probability range according to the received user specification;
An information processing method for performing at least one of the processes.
12 11. In the information processing method described in
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The information processing apparatus is
When adjusting the order quantity, for each target product or each group, it is determined whether the expected sales quantity is a predetermined value or less,
For the target product or group determined that the expected sales amount is not less than or equal to the predetermined value, the process (a) is performed,
An information processing method for performing at least one of the processes (b) to (e) on a target product or group for which the estimated sales amount is determined to be equal to or less than a predetermined value.
13. 1. To 12. In the information processing method according to any one of the above,
further,
Including a plurality of the target products as processing targets;
The plurality of target products are grouped by average sales volume,
The information processing apparatus is
An information processing method for calculating at least one of the safety stock quantity and the order quantity for each target product or each group.
14 1. Thru 13. In the information processing method according to any one of the above,
The information processing apparatus is
When obtaining the parameters,
A correction parameter set in accordance with the degree of influence on the sales volume of the event that affects the sales volume of the target product is further acquired for at least one of the individual sales and the carton sales,
An information processing method for correcting at least one of the individual parameter and the carton parameter using the correction parameter.
15. 14 In the information processing method described in
The information processing apparatus is
When obtaining the parameters,
Obtaining the correction parameters together with the schedule of the event;
Based on the calendar information, detect the event time,
An information processing method for correcting at least one of the individual parameter and the carton parameter using the correction parameter corresponding to the detected event.
16. 14 Or 15. In the information processing method described in
Including a plurality of the target products as processing targets;
The plurality of target products are grouped by average sales volume,
The information processing apparatus is
When obtaining the parameters,
For each event group that is grouped based on the event attributes, link the target product or group that has an impact on the sales volume due to the event and the correction parameter that is set according to the degree of influence on the sales volume of the event Further acquiring at least one of the individual sales and the carton sales,
An information processing method for correcting at least one of the individual parameter and the carton parameter using the correction parameter associated with a target product or group corresponding to an event.
17. 1. To 16. In the information processing method according to any one of the above,
The information processing method in which the target product is tobacco or a beverage in a container.

18. On the computer,
Obtaining individual parameters relating to the quantity of individual sales of the target product and carton parameters relating to the quantity of carton sales of the target product;
Using the individual parameters and the carton parameters to generate probability distributions for the individual sales and the carton sales, respectively.
A procedure for calculating a safety stock amount used in the periodic order method separately for the individual sales and the carton sales based on each probability distribution;
A program for running
19. 18. In the program described in
In the conversion unit that is one of the sales unit of the individual sales and the carton sales, the estimated sales volume of the individual sales and the expected sales volume of the carton sales, the stock quantity at the time of ordering, and the order completed in the sales forecast period The procedure to get information about undelivered quantity,
The safety stock quantity of the individual sale or the carton sale is converted into the conversion unit, and based on the periodic order method, the converted safety stock quantity, the other safety stock quantity, and the expected sales quantity of the individual sale, A procedure for calculating an order quantity from the estimated sales quantity of the carton sale, the stock quantity at the time of order placement, and the unreceived quantity ordered.
A program that causes a computer to execute.
20. 18. Or 19. In the program described in
In the procedure for obtaining the parameter, a procedure for obtaining an average sales amount of individual sales of the target product in a predetermined period as the individual parameter, and a procedure for obtaining an average sales amount of carton sales of the target product in the predetermined period as the carton parameter. ,
In the procedure of calculating the safety stock amount, a Poisson distribution is generated for each of the individual sales and the carton sales using the average sales amounts of the individual sales and the carton sales, and obtained from the generated Poisson distributions. The individual sales and the carton sales are defined as the individual sales and the carton sales, respectively, in which the cumulative probability of the individual sales and the cumulative probability of the carton sales in which the occurrence probabilities for each expected sales amount are accumulated satisfy the required probability regarding the shortage of the target product. The procedure to calculate each safety stock quantity,
A program that causes a computer to execute.
21. 20. In the program described in
further,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
In the procedure for calculating the safety stock amount,
The program for making a computer perform the procedure which calculates the said safety stock quantity using the said request | requirement probability set for every said object goods or every said group.
22. 21. In the program described in
A procedure for determining whether to switch the Poisson distribution to a normal distribution for each sales unit of the individual sales and the carton sales based on a predetermined switching condition,
About the sales unit determined to be switched to the normal distribution by the determination procedure,
In the procedure for obtaining the parameter,
The individual parameter or the carton parameter, a procedure for obtaining the individual sales amount of the target product in the predetermined period or the average sales amount calculated from the sales amount of the carton sale of the target product, and the standard deviation thereof, respectively.
In the procedure for calculating the safety stock amount,
A procedure for switching the Poisson distribution to a normal distribution and generating a normal distribution indicating a probability distribution of the sales potential of the target product in the sales forecast period using the average sales volume and the standard deviation, respectively.
A procedure for obtaining a safety factor satisfying a required probability related to a shortage of the target product from the normal distribution, and calculating a safety stock amount based on the safety factor, the standard deviation, and the predetermined sales prospect period,
A program that causes a computer to execute.
23. 22. In the program described in
In the determination procedure, a program that sets the average sales amount of the target product to be a predetermined value or more as the switching condition for switching the Poisson distribution to a normal distribution.
24. 23. In the program described in
The determination means is a program for performing the determination process for each sales unit for each target product or each group.
25. 20. To 24. In the program described in any one of the above,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
Information indicating at least one of the correspondence relationship between the safety stock amount and the request probability regarding the shortage of the target product, and the correspondence relationship between the order amount and the request probability, together with the order amount. A procedure for presenting at least one of each target product and each group,
A program that causes a computer to execute.
26. 20. To 25. In the program described in any one of the above,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
A procedure for receiving a request probability relating to a shortage of the target product, which is set according to the estimated sales amount for each target product or for each of the groups,
A program that causes a computer to execute.
27. 20. Thru 26. In the program described in any one of the above,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The order quantity calculated by the procedure for calculating the order quantity is converted into an order unit to determine whether or not a fraction is generated, and when a fraction occurs, for each target product or for each group, A procedure for performing the processing specified according to the expected sales volume and rounding off the fraction of the order quantity;
A program that causes a computer to execute.
28. 27. In the program described in
In the procedure for adjusting the order quantity,
(A) a process of automatically rounding up the fraction;
(B) a process of automatically rounding down the fractions;
(C) A process of accepting a user instruction to round up or round down the fraction, and rounding up or rounding down the fraction according to the accepted instruction.
(D) a process of automatically changing a request probability relating to a shortage of the target product within a range corresponding to the fraction so that the fraction does not appear;
(E) a process of accepting a user specification of a request probability range related to a shortage of the target product, and changing the request probability range according to the received user specification;
A procedure for performing at least one of the processes of
A program that causes a computer to execute.
29. 28. In the program described in
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
In the procedure for adjusting the order quantity, for each target product or each group, a procedure for determining whether or not the expected sales amount is a predetermined value or less,
A procedure for performing the process of (a) for a target product or group that is determined that the expected sales amount is not less than a predetermined value;
A procedure for performing at least one of the processes (b) to (e) for the target product or group for which the estimated sales amount is determined to be equal to or less than a predetermined value;
A program that causes a computer to execute.
30. 18. Thru 29. In the program described in any one of the above,
further,
Including a plurality of the target products as processing targets;
The plurality of target products are grouped by average sales volume,
A program for causing a computer to execute a procedure for calculating at least one of the safety stock quantity and the order quantity for each target product or each group.
31. 18. Thru 30. In the program described in any one of the above,
In the procedure for obtaining the parameter,
A procedure for further obtaining a correction parameter set in accordance with the degree of influence on the sales volume of an event that affects the sales volume of the target product for at least one of the individual sales and the carton sales;
A procedure for correcting at least one of the individual parameter and the carton parameter using the correction parameter;
A program that causes a computer to execute.
32. 31. In the program described in
In the procedure for obtaining the parameter,
A procedure for acquiring the correction parameter together with a schedule of the event;
Procedure to detect event time based on calendar information,
A step of correcting at least one of the individual parameter and the carton parameter using the correction parameter corresponding to the detected event;
A program that causes a computer to execute.
33. 31. Or 32. In the program described in
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
In the procedure for obtaining the parameter,
For each event group that is grouped based on the event attributes, link the target product or group that has an impact on the sales volume due to the event and the correction parameter that is set according to the degree of influence on the sales volume of the event For further acquiring information on at least one of the individual sales and the carton sales,
A procedure for correcting at least one of the individual parameter and the carton parameter using the correction parameter associated with the target product or group corresponding to the event,
A program that causes a computer to execute.
34. 18. Thru 33. In the program described in any one of the above,
The target product is a cigarette or a beverage in a container.

60 Computer 62 CPU
64 ROM
66 RAM
68 I / O
69 Bus 70 Computer program 72 Display device 74 Operation input device 100 Information processing device 102 Parameter acquisition unit 104 Inventory calculation unit 200 Information processing device 206 Information acquisition unit 208 Order quantity calculation unit 210 Presentation unit 212 Order quantity adjustment unit 300 Information processing device 302 Parameter acquisition unit 304 Inventory calculation unit 320 Determination unit 402 Network 410 Store terminal 420 Server

Claims (21)

Parameter acquisition means for acquiring individual parameters related to the quantity of individual sales of the target product and carton parameters related to the quantity of carton sales of the target product;
Using the individual parameters and the carton parameters, the individual sales and the carton sales are each generated with a probability distribution of the expected sales amount of the target product in a predetermined sales prospect period, and the individual sales are based on each probability distribution. And an inventory calculating means for calculating a safety stock amount used in the periodic ordering method separately for the carton sales,
An information processing apparatus comprising: The information processing apparatus according to claim 1,
In the conversion unit that is one of the sales unit of the individual sales and the carton sales, the estimated sales volume of the individual sales and the expected sales volume of the carton sales, the stock quantity at the time of ordering, and the order completed in the sales forecast period An information acquisition means for acquiring information about the unreceived quantity;
The safety stock quantity of the individual sale or the carton sale is converted into the conversion unit, and based on the periodic order method, the converted safety stock quantity, the other safety stock quantity, and the expected sales quantity of the individual sale, An order quantity calculating means for calculating an order quantity from the estimated sales quantity of the carton sale, the inventory quantity at the time of order placement, and the ordered unreceived quantity;
An information processing apparatus further comprising: The information processing apparatus according to claim 1 or 2,
The parameter acquisition means acquires an average sales amount of individual sales of the target product in a predetermined period as the individual parameter, and acquires an average sales amount of carton sales of the target product in the predetermined period as the carton parameter,
The inventory calculation means generates a Poisson distribution for the individual sales and the carton sales by using the average sales amounts of the individual sales and the carton sales, and each estimated sales amount obtained from each generated Poisson distribution. The cumulative sales probability of the individual sales and the cumulative probability of the carton sales satisfying the required probability of the shortage of the target product are defined as the respective safety stock quantities of the individual sales and the carton sales. Information processing device for calculating each. The information processing apparatus according to claim 3.
further,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The inventory calculation means includes
An information processing apparatus that calculates the safety stock quantity using the request probability set for each target product or each group. The information processing apparatus according to claim 4,
For each sales unit of the individual sales and the carton sales, further comprising a determination means for determining whether to switch the Poisson distribution to a normal distribution based on a predetermined switching condition,
About the sales unit determined to be switched to the normal distribution by the determination means,
The parameter acquisition means includes
As the individual parameter or the carton parameter, obtain the sales amount of the individual product of the target product in the predetermined period or the average sales amount calculated from the sales amount of the carton sale of the target product, and the standard deviation thereof, respectively.
The inventory calculation means includes
By switching the Poisson distribution to a normal distribution, using the average sales amount and the standard deviation, respectively, generate a normal distribution indicating a probability distribution of the sales potential amount of the target product in the sales potential period,
An information processing apparatus that obtains a safety coefficient satisfying a required probability related to a shortage of the target product from the normal distribution, and calculates a safety stock amount based on the safety coefficient, the standard deviation, and the predetermined expected sales period, respectively. . The information processing apparatus according to claim 5,
The information processing apparatus, wherein the determination unit sets the average sales amount of the target product to be a predetermined value or more as the switching condition for switching the Poisson distribution to a normal distribution. The information processing apparatus according to claim 6,
The information processing apparatus that performs the determination process for each sales unit for each target product or each group. The information processing apparatus according to any one of claims 3 to 7,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
Information indicating at least one of the correspondence relationship between the safety stock amount and the request probability regarding the shortage of the target product, and the correspondence relationship between the order amount and the request probability, together with the order amount. An information processing apparatus further comprising a presentation unit that presents at least one of each of the target products and each of the groups. The information processing apparatus according to any one of claims 3 to 8,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
An information processing apparatus further comprising an accepting unit configured to accept a request probability related to a shortage of the target product set for each target product or each group according to the estimated sales amount. The information processing apparatus according to any one of claims 3 to 9,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The order quantity calculated by the order quantity calculation means is converted into an order unit to determine whether or not a fraction is generated. When a fraction occurs, the sales prospect is calculated for each target product or for each group. An information processing apparatus further comprising order quantity adjusting means for performing processing specified according to the quantity and rounding off the fraction of the order quantity. The information processing apparatus according to claim 10,
The order quantity adjusting means is
(A) a process of automatically rounding up the fraction;
(B) a process of automatically rounding down the fractions;
(C) A process of accepting a user instruction to round up or round down the fraction, and rounding up or rounding down the fraction according to the accepted instruction.
(D) a process of automatically changing a request probability relating to a shortage of the target product within a range corresponding to the fraction so that the fraction does not appear;
(E) a process of accepting a user specification of a request probability range related to a shortage of the target product, and changing the request probability range according to the received user specification;
An information processing apparatus that performs at least one of the processes. The information processing apparatus according to claim 11,
Including a plurality of the target products as processing targets;
A plurality of the target products are grouped by the average sales amount,
The order quantity adjusting means determines whether the estimated sales quantity is a predetermined value or less for each target product or each group,
For the target product or group determined that the expected sales amount is not less than or equal to the predetermined value, the process (a) is performed,
An information processing apparatus that performs at least one of the processes (b) to (e) for a target product or group for which the estimated sales amount is determined to be equal to or less than a predetermined value. The information processing apparatus according to any one of claims 1 to 12,
further,
Including a plurality of the target products as processing targets;
The plurality of target products are grouped by average sales volume,
An information processing apparatus that calculates at least one of the safety stock quantity and the order quantity for each target product or each group. The information processing apparatus according to claim 1,
The parameter acquisition means includes
A correction parameter set in accordance with the degree of influence on the sales volume of the event that affects the sales volume of the target product is further acquired for at least one of the individual sales and the carton sales,
An information processing apparatus that corrects at least one of the individual parameter and the carton parameter using the correction parameter. The information processing apparatus according to claim 14,
The parameter acquisition means includes
Obtaining the correction parameters together with the schedule of the event;
Based on the calendar information, detect the event time,
An information processing apparatus that corrects at least one of the individual parameter and the carton parameter by using the correction parameter corresponding to the detected event. The information processing apparatus according to claim 14 or 15,
Including a plurality of the target products as processing targets;
The plurality of target products are grouped by average sales volume,
The parameter acquisition means includes
For each event group that is grouped based on the event attributes, link the target product or group that has an impact on the sales volume due to the event and the correction parameter that is set according to the degree of influence on the sales volume of the event Further acquiring at least one of the individual sales and the carton sales,
An information processing apparatus that corrects at least one of the individual parameter and the carton parameter using the correction parameter associated with the target product or group corresponding to the event. The information processing apparatus according to any one of claims 1 to 16,
The target product is an information processing apparatus that is a cigarette or a beverage in a container. A store terminal that holds the sales amount of the target product for a predetermined period and the sales amount of the carton sale of the target product;
A server that collects and holds the sales volume of the individual sales and the sales volume of the carton sales from the store terminal,
The server
An information processing system for realizing at least a part of the information processing apparatus according to claim 1. The information processing system according to claim 18,
Including a plurality of the target products as processing targets;
The plurality of target products are grouped by average sales volume,
The server
Information related to safety stock, information related to order quantity, information indicating the safety stock quantity, information indicating the correspondence relationship between the safety stock quantity and the required probability regarding the shortage of the target product, and the order quantity together with the order quantity and Information providing means for providing the store terminal with at least one of information indicating a correspondence relationship with the request probability for each target product and for each group of the target products in a predetermined period An information processing system further comprising: Information processing device
Obtain individual parameters for the quantity of individual sales of the target product and carton parameters for the quantity of carton sales of the target product,
Using the individual parameters and the carton parameters to generate probability distributions for the individual sales and the carton sales, respectively;
An information processing method for calculating a safety stock amount used in the periodic ordering method separately for the individual sales and the carton sales based on each probability distribution. On the computer,
Obtaining individual parameters relating to the quantity of individual sales of the target product and carton parameters relating to the quantity of carton sales of the target product;
Using the individual parameters and the carton parameters to generate probability distributions for the individual sales and the carton sales, respectively.
A procedure for calculating a safety stock amount used in the periodic order method separately for the individual sales and the carton sales based on each probability distribution;
A program for running

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