WO2003094068A1 - Distribution system, distribution device, and distribution method - Google Patents

Abstract

A distribution computer (10) uses a transaction DB (36) to rank stores related to the commodity to be distributed. This ranking is performed by using sales result of the group (commodity attribute group) to which the commodity belongs in each store. Stores are ranked to S, A, B, and C. For the commodity to be distributed, to which store the commodity is to be distributed and how much of the commodity is to be distributed are decided according to the rank of each store. According to this distribution simulation, commodity is distributed to stores. Moreover, in the case of additional distribution, it is decided according to the processing performed according to the sales result of the commodity in each store.

Description

 Description '' Allocation processing system, allocation processing device and allocation processing method

 The present invention relates to a system, an apparatus, and a method for determining how to allocate an allocation target to a plurality of allocation destinations. In particular, when the same product is sold in multiple stores, it is to determine how to distribute the product to multiple stores. Background art

 In the past, how products were distributed to multiple stores was determined by trial and error based on the experience of the distributor and the experience of the manager of each store. On the other hand, Japanese Unexamined Patent Publication No. 234364/1990 discloses a product assortment system in a store. In order to achieve the most optimal product lineup at each store, we will focus on the characteristics of stores (location conditions, business types, etc.), the characteristics of products that should be stocked at each store, and the characteristics of stores. Considering “the sales performance of individual merchandise at each store”, the merchandise to be displayed at each store is automatically determined.

However, such a system has the following problems. First, when the product to be distributed is sold for the first time at a store (for a new product, etc.), there is no record of sales of the product at each store. Therefore, the above method cannot be used. Second, if the product to be distributed is not sold in the entire store or if it is a rare product, the sales performance of the product is low. Therefore, even when using the above method, the sales performance of each store is not made sail and command means, that can not be it and the child to increase the sales efficiency in each store _c Third, since the actual sales data at each of the multiple stores is difficult for the operator to understand, the operator must determine the allocation method in consideration of the sales results. Is difficult. That is, the operator's intention cannot be easily reflected in the allocation method.

 The present invention solves such a problem and makes it possible to increase the efficiency of handling at the allocation destination, and to distribute the operator's intention to the allocation method easily. It is intended to provide a processing system, apparatus and method. For example, when trying to distribute products to multiple stores, products with no sales records or products with a low sales record will be transferred to stores that are more likely to sell, and products with abundant sales records By allocating to stores that sell more, sales efficiency at each store can be improved. Disclosure of the invention

(1) The distribution processing system of the present invention includes a plurality of distribution destination terminal devices, a distribution processing device, and a distribution execution device. The distribution destination terminal device records the handling result information of the object and performs the distribution processing. The equipment receives and records the handling result information of the object at each distribution destination from each distribution destination terminal device, and newly allocates each distribution object based on the handling result information corresponding to the allocation target. Based on the total amount of the distribution objects to be newly allocated to the prospective destinations, and using the classification determined for each of the prospective distribution destinations, Distribution data indicating whether or not to perform the distribution, and transmitting the generated data to the distribution execution device. The distribution execution device receives the distribution data and distributes the distribution target object based on the distribution data. Execute the process to distribute to It is characterized in.

(2) to (4) The distribution processing device according to the present invention is a device for generating distribution data for determining how to distribute distribution objects to the distribution destinations, wherein Receiving the actual handling information of the target object, and newly allocating each distribution schedule based on the actual handling information corresponding to the allocation target. Classify destinations and make new allocations Receive the total amount of allocation targets, and then use the classification determined for each allocation destination, and assign It is characterized by generating allocation data indicating how to allocate objects.

 Therefore, since the allocation method is determined using the classification based on the actual handling information of each allocation destination, it is possible to improve the handling efficiency of the allocation target in the future. For example, when trying to distribute products to multiple stores, by using a classification based on the sales performance of the product at each store, the sales efficiency of the product as a whole can be improved. As a result, sales can be increased.

 In addition, the operator or the like can easily select an allocation destination by specifying a classification or setting a weight or the like for each classification to determine a distribution amount, thereby facilitating the intention of the operator or the like. Can be reflected in the allocation method. In addition, by using classification, the allocation method can be easily changed according to various circumstances.

 (5) The distribution processing device according to the present invention, wherein the distribution data indicating which distribution target is to be allocated to the distribution target, or how much distribution target is to be allocated to which distribution target. It is characterized by generating. In this way, it is possible to determine, for example, the distribution amount of the distribution object to each store based on the classification.

 (6) The distribution processing device of the present invention is characterized in that the handling result information corresponding to the distribution target is past handling performance information of the distribution target. As a result, when there is appropriate handling information on the distribution target, the distribution target can be more optimally supplied to each distribution destination by using the handling result information. .

(7) The distribution processing device of the present invention is characterized in that the handling result information corresponding to the distribution target is past handling performance information of the entire group to which the distribution target belongs. As a result, even when there is no or only a small amount of handling information on the allocation target, by using the handling performance information of the group to which the allocation target belongs, a more optimal allocation destination can be obtained. Will be supplied with the allocation target. For example, when trying to distribute new or rare products to multiple stores, using the sales performance of the group to which the products belong will enable more optimal product lineup at each store. It can be realized.

 (8) The distribution processing device according to the present invention is characterized in that the distribution data indicating how much the distribution target is distributed to the selected distribution destination selected using the classification determined for the distribution destination. It is characterized in that the data is generated. By selecting the classification, it is possible to determine to which of the allocation destinations the data is to be allocated.

(9) The distribution processing device according to the present invention, wherein the ratio of the handling result information corresponding to the distribution object of each of the selected distribution destinations to the handling result information corresponding to the distribution object of the entire selected distribution destination is determined. Accordingly, the allocation data indicating how much the allocation target is allocated to each of the selected allocation destinations is generated. As a result, it is possible to determine the allocation amount of the allocation target based on the ratio of the handling result information targeting only the selected allocation destination.

(10) The distribution processing device of the present invention distributes a predetermined amount of the above-mentioned distribution object to each of the above-mentioned selective distribution destinations, and performs the above-mentioned selective distribution of the remaining distribution object after the distribution. Depending on the ratio of the handling actual information corresponding to the allocation target of each of the selected distribution destinations to the handling performance information corresponding to the allocation target of the entire destination, how much for each selected allocation destination The method is characterized in that the distribution data indicating whether to distribute is generated.

As a result, even when the number of objects to be allocated is small, at least a predetermined amount is allocated to each of the selective allocation destinations, so that a situation does not occur in which one of the selective allocation destinations is not allocated at all. (11) The allocation processing device of the present invention generates the allocation data indicating how to allocate the allocation target based on the allocation amount or allocation ratio set for the classification. This is the feature.

 As a result, the distribution can be made evenly to each allocation destination of the same classification. Further, the operator can arbitrarily set the distribution amount and the like for each classification, thereby reflecting the operator's intention.

 (12) The distribution processing device according to the present invention is characterized in that, in the group to which the allocation target belongs, the handling result information corresponding to the allocation target and the number of group components calculated from the number of types of the group configuration belonging to the group. It is characterized in that it generates the above-mentioned allocation data indicating how much to allocate, based on its handling capacity. Therefore, by considering the handling capacity per group component, the allocation target can be more optimally supplied to each allocation destination.

 (13) The distribution processing device according to the present invention generates the distribution data indicating how much the distribution target is to be distributed based on the sales forecast value calculated from the actual handling information corresponding to the distribution target. This is the feature. This allows, for example, distribution to be made so that sales efficiency can be improved at each distribution destination and, as a result, sales can be increased.

(14) The distribution processing device according to the present invention is characterized in that the distribution data indicating how much the distribution target is distributed is generated based on the sales forecast value in consideration of the weekend index. . As a result, priority can be given to stores that have a high sales ratio on weekends.

 (15) In the distribution processing apparatus according to the present invention, the handling result information includes at least sales information.

(16) In the distribution processing apparatus according to the present invention, the handling result information is characterized by including at least an occupancy rate calculated from sales information and inventory information. For example, when trying to distribute products to be sold in each store to a plurality of stores, for example, It is possible to determine how to allocate the product based on the 'classification determined based on the actual performance and inventory performance of the product.' (17) The allocation processing method of the present invention uses a computer to receive the actual handling information of the object at each allocation destination, and to perform the allocation based on the actual handling information corresponding to the newly allocated object. Evaluate each allocation destination and make a new allocation Based on the total amount of the allocation target, use the evaluation determined for each allocation destination to allocate The feature is to generate allocation data that shows how to allocate objects. Therefore, the allocation method is determined using the evaluation based on the actual handling information of each allocation destination, so that the efficiency of handling the allocation target in the future can be improved. For example, when trying to distribute a product to multiple stores, by using an evaluation based on the sales performance of the product in each store, the sales efficiency of the product as a whole can be improved. As a result, sales can be increased.

 In the present invention, the “allocation processing device” corresponds to the allocation processing computer 10 in the following embodiment. The “distribution execution device” corresponds to the distribution center / computer 40 in the following embodiment. The “distribution destination terminal device” corresponds to the store computer 50, 52,. 54 in the following embodiment.

The “distribution target” is an article to be distributed to a distribution destination. In the following embodiment, the SKU to be distributed to each store by the headquarters corresponds to the article to be distributed. The concept also includes data that is to be distributed to the distribution destination via a telecommunication line or the like. The “group to which the allocation target belongs” is grouped based on the characteristics of the allocation target, etc. In the following embodiment, the SKU to which the headquarters intends to allocate to each store belongs. The product attribute group falls under this category. This “product attribute group” is grouped based on the characteristics of the product. In the embodiments described below, items (for example, jackets, pullovers, and the like) and those grouped by size correspond. Also with items and sizes This includes items grouped using item subs (eg, nits, fabrics, jerseys, etc.).

 "Handling performance information J is performance information handled by the distribution destination, and in the following embodiment, corresponds to the sales amount, the number of units sold, and the SKU occupancy rate. For example, when the distribution destination is a factory (For example, when allocating parts for production, etc.) also applies to production volume, etc. Not only past ones but also future ones (for example, sales forecasts, planned production quantities, etc.) It is a concept.

 “Distribution destination” and “planned distribution destination” are where the objects to be distributed are allocated, and in the following embodiment, each store corresponds. The concept also includes factories and sales offices, and when the allocation target is data, the concept also includes stores in the Computer Shop Pink Mall. “Selected allocation destination” refers to an allocation destination that has been selected as an allocation destination. In the following embodiment, the distribution destination is a distribution destination selected using the classification determined for the distribution destination, and corresponds to the store of rank s or A selected by the operator. If all ranks (S to C) are selected, all stores correspond.

 The “remaining allocation target” is the remaining allocation target after a predetermined amount is allocated to each of the selected allocation destinations. In the following embodiment, in the 1: 100 allocation method, each of the ranks S and A The distribution target (SKU) after distribution to stores one by one applies.

 A “group component” corresponds to an SKU belonging to a product attribute group or an SKU (operating SKU) that has been sold in a certain amount or more.

 "Capacity per group component" is calculated from the group's handling information and the number of types of group components. In the following embodiment, the number of units sold / the number of SKUs and the It corresponds to the number of sheets / the number of operating SKUs.

The “sales forecast value” is a concept that includes not only sales forecasts of products and the like but also demand forecasts such as electricity consumption. In the following embodiment, the “performance information in the past regarding the entire group to which the allocation target belongs” corresponds to the sales and price of the product attribute group to which the SKU to be allocated belongs.

 `` Receiving the total amount of objects to be newly allocated '' means not only obtaining the total amount from an operator or another computer, but also obtaining information for calculating the total amount. It is a concept that includes the case.

 The “evaluation determined for each allocation destination” is determined based on the actual handling information at each allocation destination. In the following embodiment, the rank set for the store is set to s. ~ C, the reference value (Equation (7)) calculated for each store, “Number of units sold / Number of SKUs” calculated for each store, and “Number of units sold / Number of operating SKUs J”.

 "Recording medium on which a program is recorded" means a flexible disk,

This concept includes CD-ROM, node disk, memory card, R0M, punch card, tape, etc. In addition, the program can be executed by being installed not only on a recording medium on which a program that can be directly executed by a computer is recorded but also on another recording medium (such as a hard disk). It is a concept that includes a recording medium on which such a program is recorded and a recording medium on which an encrypted or compressed program is recorded. "Program" is a concept that includes not only programs that can be directly executed by the CPU, but also source programs, compressed programs, encrypted programs, and so on. is there. BRIEF DESCRIPTION OF THE FIGURES

Figure 1 is a diagram showing the configuration of the allocation processing system.

Figure 2 is a flowchart showing the outline of the processing of the allocation processing system.

Figure 3 is a diagram showing the relationship between SKUs and product attribute groups.

FIG. 4 is a diagram showing a hardware configuration of the distribution processing computer 10 and the data pace server 30. FIG. 5 shows the data of the product DB 34 and the transaction DB 36.

Figure 6 is a flowchart showing the process with store rank.

Figure 7 shows the store rank setting screen.

Figure 8 is a flowchart showing the distribution simulation at the time of the initial distribution.

FIG. 9 is a diagram showing an allocation simulation screen.

Figure 10 is a flowchart showing the normal allocation process.

 Is a flowchart showing the 1: 100 distribution process.

Fig. 12 is a flow chart showing the process for allocating product ranks.

FIG. 13 is a view showing a rank-specific allocation number setting screen.

Figure 14 is a flow chart showing an allocation simulation during additional allocation.

FIG. 15 is a diagram showing an allocation simulation screen.

Figure 16 is a flowchart showing the distribution process based on the composition ratio of the number of units sold.

Figure 17 is a graph showing the relationship between the number of units sold and the SKU occupancy rate, and the number of units sold and the sales amount at each store.

FIG. 18 is a diagram showing a rank-specific allocation number setting screen. '' Figure 19 is a table showing examples of allocation targets and corresponding transaction results information

Figure 20 is a flowchart showing the data aggregation process. BEST MODE FOR CARRYING OUT THE INVENTION

1. Overview of system configuration and processing

Figure 1 shows, as an embodiment, an allocation processing computer 10 that shows the configuration of an allocation processing system when an apparel product with the same brand is allocated to a plurality of stores. The processing computer 20 is installed in the headquarters that distributes products, and the database server 30 is 0305532

10 scan data, and a data base Ichisu (store DB ^32, item D 34) for storing the goods master and each store-by-store sales data, my La Nzaku cane down DB36 to store the inventory data, and the like. The distribution center computer 40 is installed in the distribution center, which is responsible for receiving, shipping, and storing products. Store combi-users 50, 52, and 54 are installed at each of the multiple stores that sell products distributed by the headquarters. Each computer can communicate via the Internet or the like. The outline of the processing of this system is described below.

 First, the distribution processing computer 10 uses the transaction DB36 to rank each store for the product to be distributed (“Store's rank processing J”) (see FIG. 2 Step S10) This ranking is performed using the sales performance of the product attribute group to which the product belongs in each store, and each store is divided into ranks S, A, B, (: For example, if the product is a “jacket (product number A, size A, color A)”, the product attribute group will be “jacket, size AJ”.

 In the following description, the product identified by the product number, size, and color is shown as SKU, and Fig. 3 shows the relationship between this SKU and product attribute group. This product attribute group is grouped by product type and item size. This item can be, for example, a jacket, a trooper, or a cardigan.

 Then, the allocation processing computer 10 determines whether or not to allocate the SKU to be allocated to which store and to which store the rank of each store is allocated.

• Determined by the processing to be performed based on this (allocation simulation at the time of the initial allocation) (Fig. 2, step S12).

Based on the results of the allocation simulation, SKUs are allocated to each store (step S14 in FIG. 2), and the allocated SKUs are sold in each store (step 2 in FIG. 2). Step S16). Along with this, the store computer 50 and others record sales data. In addition, the tallying computer 20 is used for the distribution center computer, such as sales data from store computers 50, etc. It receives receipt / shipment data from the computer 40 and stores it in the transaction DB 36 of the database server 30 (data aggregation processing) (FIG. 2, step S18).

Further, when a predetermined amount of the SKU is received at the distribution center, the headquarters determines at the store which distribution of the SKU is to be additionally allocated, and how much additional distribution is to be performed, by the distribution processing computer 10 of the SKU. It is determined by the processing executed based on the sales performance of the product attribute group to which it belongs (distribution simulation at the time of additional distribution) (Fig. 2, step S20). Based on the results of this allocation simulation, additional SKUs are allocated to each store, and the additional allocated SKUs are sold at each store (Fig. 2 steps S22, S24, S26) ₀

 The allocation processing method using the allocation simulation at the time of the initial allocation includes (1) normal allocation, (2) 1: 100 allocation, and (3) product rank. Allocation. In addition, there are two types of allocation processing based on the allocation simulation at the time of additional allocation: (4) sales forecast allocation, and (5) allocation based on the composition ratio of sales units.

2. Hardware configuration of each computer

 FIG. 4A shows the hardware configuration of the distribution processing computer 10. The distribution processing computer 10 includes a CPU 102, a hard disk 104, a display 106, a communication unit 108, a memory 110, a keyboard Z mouse 112, a CD-ROM drive 114, and a flexible disk. It has a disk 'drive 116 and so on.

The communication unit 108 communicates with the database server 30, the distribution center computer 40, and the like. The hard disk 104 records an allocation processing program for executing a processing simulation with store rank allocation simulation, an operating system (OS), and the like. The distribution processing program is installed from a CD-R0M118 or the like via the CD-ROM drive 114 or downloaded via a communication line. Figure 4B shows the hardware configuration of the database server 30. The database server 30 includes a CPU 302, a hard disk 304, a communication unit 306, a memory 308, a CD-ROM drive 310, a flexible disk drive 312, and the like. The hard disk 304 records the above-mentioned store DB32, merchandise DB34, transaction DB36, and the like. In the product DB34 shown in Fig. 5A, the brand, product number, retail price, sales year, season, etc., which are standard retail prices, are recorded for each SKU. The transaction DB36 shown in Figure 5B contains the total sales for the week (cumulative sales from Monday), the total sales for the week, and the number of sales for each SKU at each store. The number of sheets loaded and the number of stocks are recorded. • The hardware configuration of the aggregation processing computer 20 is basically the same as that of the distribution processing computer 10 shown in FIG. 4A. However, in the hard disk, an aggregation processing program for receiving sales data from the store computer 50 or the like and recording it in the transaction DB 36 of the database server 30 is recorded. I have.

3. Allocation processing computer 10 processing

 The processing by the allocation processing computer 10 will be described below for the first allocation (3.1) and the additional allocation (3.2).

3.1 At first allocation

 The following describes (1) processing with store rank and (2) distribution simulation by the distribution processing computer 10 at the time of initial distribution.

 (1) Processing with store rank

 Figure 6 shows the flowchart of the process with store rank. The CPU 102 displays a setting period input screen (not shown) on the display 106, and prompts the operator to set the “setting period, brand, sales year, and season” (FIG. 6 steps). S50). This set period is the period of the sales amount extracted from the transaction DB36.

When the operator inputs a setting period such as “37th week to 40th week of 2000” by the operator, the CPU 102 sends the business at each store from the database server 30. The store master and the merchandise master, such as sales data for each product attribute group, are extracted and stored in the hard disk 104 (FIG. 6, steps S51 and S52). Then, a product attribute group setting screen (not shown) is displayed on the display 106, and the operator is prompted to set “item, size” (FIG. 6, step S53). Here, it is assumed that the “item (jacket), size (A)” has been set by the operator (FIG. 6, step S54).

 The CPU 102 extracts the sales amount and the like of the set product attribute group (jacket, size A) in each store in the set period from the data acquired in step S52 in FIG. 6 (step in FIG. 6). Step S55). Then, the total sales amount for each set period (hereinafter referred to as the period sales amount) at each store, the SKU occupancy rate shown in equation (1), and the sales occupancy ratio shown in equation (2) are calculated. This is displayed as the actual data No. on the store rank setting screen shown in Fig. 7 (Fig. 6, steps S55 and S56).

 SKU occupancy == number of SKUs for regular price sales SKUs for store inventory (1) Sales occupancy ratio = period sales amount (or period sales 妆) XSKU occupancy ratio (2)

 In the above formula, the number of SKUs sold at fixed price (the number of operating SKUs) is the number of types of SKUs sold at fixed price in the store, and the number of SKUs in store inventory is the number of SKUs in store. This is the number of types of a certain SKU. In other words, the SKU occupancy rate is an indicator of the sales power of the store.

 The operator 'selects a period attribute and a sales operating ratio in the attribute setting field 510. The pull-down menu of the period attribute is “period sales amount” or “period sales quantity”, and determines which should be considered in ranking stores. The pull-down menu of the sales occupancy ratio is “valid” or “invalid”, and determines whether to consider the SKU occupancy rate when ranking stores.

In this case, it is assumed that the operator selects the period attribute “period sales amount” and the sales utilization ratio “invalid” and clicks the analysis button 520 (FIG. 6). Step S58). The CPU 102 ranks the stores according to the period sales amount (FIG. 6, steps S60 and S62). In other words, the ranking of each store is determined based on the period sales amount of each store, and rank S is ranked higher than 40%, rank A is ranked higher 40-70%, rank B is ranked higher 70-90%, and rank 10 is ranked lower. Rank less than% as Rank C and rank each store. The rank of each store is displayed in the rank column of the store rank setting screen shown in Fig. 7 (Fig. 6 Step ^ S66) ₀

 The case where store ranking is performed based on “period sales quantity”, “period sales amount and SKU occupancy rate”, and “period upper quantity and SKU occupancy rate” will be described later.

 (2) Distribution simulation

 Figure 8 shows the allocation simulation method (a) normal allocation, (b) 1: 100 allocation, and (c) commodity rank allocation for the allocation simulation using the allocation processing computer 10 during the initial allocation. Will be described separately. The allocation method at the time of the additional allocation described later may be used as the allocation method at the time of the initial allocation.

(a) Normal allocation

 The CPU 102 displays the distribution simulation screen shown in FIG. 9 on the display 106, and prompts the operator to input an SKU to be distributed (step S100 in FIG. 8). The operator inputs the SKU to be allocated in the SKU input field 600. The product attribute group to which this SKU belongs is “Jacket, size AJ” set above.

The CPU 102 calculates sales data (jacket, size A) of the product attribute group (jacket, size A) to which the SKU belongs from transaction DB36, product DB34, store rank, Extract and display the total allocable amount (total allocation number) of the SKU, detailed SKU information, and the item “JK (jacket)” corresponding to the SKU (Fig. 8, steps S102, S104) . The detailed information on SKUs is the miniature picture, “Material”, the standard retail price in the store “Price”, the number of storage at the distribution center (PK), and the number of orders to the distribution center. This is the number after subtracting the number received (order remaining) (see SKU mini-picture display column 6'10, SKU detailed information column 620).

The total number of allocated sheets is “ΡΚ (30) + order remaining (60) = 90”. The item “JK (jacket)” corresponding to the SKU is displayed in the item column 630. The operator sets the total number of distribution sheets, distribution target stores or distribution processing method (FIG. 8, step S106). The total allocated number can be set by the operator by clicking the allocated number change button 640 and inputting a numerical value in the total allocated number setting field 650. The store to be allocated can be selected from “S store only, S'A store, S'A'B store, all store distribution” from the pull-down menu in the store selection column 660. The distribution processing method can be changed to 1: 100 distribution or commodity rank distribution by clicking the 1: 100 distribution command button 670 or the commodity rank button 680. it can. Here, it is assumed that the operator sets only the distribution target store rs. A store without changing the total distribution number “90”.

 When the distribution target store “SA store” is selected, the CPU 102 shifts to a normal distribution process shown in FIG. 10 (steps S108 and S110 in FIG. 8). 1: 100 Allocation command button 670, Rank button 680 Power S If the item is not clicked, it is determined to be normal allocation.

 The CPU 102 calculates the period sales amount for the product attribute group of each rank S and A store against the period sales amount for the product attribute group “jacket, size A” of the entire store of ranks S and A. Calculate the percentage (percentage of period sales amount) (Fig. 10, step S200). During this period, the total number of pieces distributed is “90” according to the composition ratio of the sales amount, and the number of pieces to be distributed to each store is determined. (Steps S202 and S204 in Fig. 10). In other words, the number of pieces distributed to a certain store is a value obtained by rounding the value a calculated by the equation (3) to an integer.

 Total distribution quantity X Composition ratio of period sales amount of the store == Calculated value a

(3) The composition ratio of the period sales amount of each store is calculated from the period sales amount of only the distribution target stores (ranks S and A), not the entire stores (ranks s to c). The numerical value in the lower column of the total allocation number setting column 650 is the total value of the allocation number for each store.

 As described above, the number of pieces to be distributed to each store is determined. In the above description, when the given total number of allocated sheets is different from the total number of allocated sheets, the total number of allocated sheets is used. However, the number of pieces to be distributed to each store may be adjusted by the calculation process of the CPU 102 such that the total number of pieces to be distributed matches the total number of pieces to be distributed (in the following example, The same applies to).

(b) 1: 100 allocation

 Fig. 11 shows a flow chart of the processing for 1: 100 rooster S in step S112 of Fig. 8. The CPU 102 has a total allocation number of “90” and distribution target stores “S · A stores”

In the state 1: 100 When distribution command Potassium emission 670 forehead click, 1 11: 100 shifts the allocation process (FIG. 8 stearyl-up S106, S108, Slll, S112) 0.

The CPU 102 allocates one card from each of the ranks S and A, starting from the upper rank (step S300 in FIG. 11). It is determined whether or not the remaining distribution number (total distribution number per rank S, the number of stores in A) is 0 (step S302 in FIG. 11). In this embodiment, assuming that the number of remaining distributions is not 0, the ranks S and A are compared with the period sales amount of the product attribute group “jacket, size A” of the entire store of ranks S and A. Calculate the ratio of the period sales amount (composition ratio of the period sales amount) for the product attribute group of each store (Fig. 11, step S304). In accordance with the composition ratio of the sales amount during this period, the distribution number of the remaining distribution is determined to determine the distribution number for each store, which is displayed in the distribution number column of each store shown in Figure 9. (Steps S306 and S308 in FIG. 11) In other words, the number of sheets to be distributed to a certain store is a value obtained by rounding up the 'value' b calculated by Expression (4) to an integer. 1 + Remaining number of distributions X Composition ratio of the period's sales amount for the store = Calculated value b ...

 (c) Product rank allocation

 FIG. 12 shows a flowchart of the merchandise rank allocation processing in step S114 of FIG. CPU102 has a total of “90 cards” and stores to be allocated! When the commodity rank order button 680 is clicked in the state of “S · A store”, the process proceeds to the commodity rank distribution processing shown in FIG. 12 (steps S106, S108, and S108 in FIG. 8). S114)

 The CPU 102 displays the rank-specific allocation number setting screen shown in FIG. 13A, and prompts the operator to set the allocation number of each rank (FIG. 12, step S400). In this case, the operator sets the number of allocations in rank S to "5j," the number of allocations to rank A "4," the number of allocations to rank B "0," and the number of allocations to rank C "0j." I do.

 The CPU 102 is activated when the operator clicks the total value calculation button.

(FIG. 12, step S402), the total number of allocations to each store is calculated based on the set number of allocations for each rank based on equation (5), and the window shown in FIG. 13B is obtained. Is displayed (Fig. 12, step S404).

 Total allocated number = S stores X 5 + A stores X4

 + Number of stores in B X0 + Number of stores in C X0 (5)

 When the operator clicks the distribution execution command “0KJ” (Step S406 in FIG. 12) by the operator, the CPU 102 displays the distribution number for each store according to the set distribution number for each rank in FIG. Displayed in the distribution number column for each store shown

(Fig. 12, step S408). As a result, the distribution can be evenly distributed to stores in the same rank.

-With this distribution method, the operator adjusts the number of distributions so that the total number of distributions matches (or approximates) the total number of distributions. Note that a combination of the number of distributions in each rank may be prepared in advance, and the CPU 102 may select and present the number of distributions that best matches the total number of distributions. 3.2 Additional allocation

 The result (distribution data) 'of the above-mentioned distribution simulation at the time of the first distribution is transferred to the distribution center computer 40. The distribution center outputs distribution data using the distribution center computer 40, and performs a shipping operation for allocating SKUs to each store based on the output data. Each store sells SKUs allocated from the distribution center. Accompanying this, the aggregation computer 20 receives the sales data from the store computer 50 and stores it in the transaction DB 36 of the database server 30 (data aggregation processing). ). In the following, the distribution simulation by the distribution processing computer 10 at the time of additional distribution will be described separately for (a) sales forecast distribution and (b) distribution based on the composition ratio of the number of units sold. . The above allocation method at the time of the initial allocation may be used as the allocation method at the time of the additional allocation.

 No

 (a) Sales forecast distribution

 Fig. 14 shows the flow chart of the allocation simulation during additional allocation. When the operator inputs the SKU to be allocated by the operator (steps S500 and S502 in FIG. 14), the CPU 102 obtains the sales quantity of the SKU for a predetermined period from the transaction DB36. Then, the reference value shown in equation (7) is calculated from the current week's sales forecast value shown in equation (6), and this is displayed together with the sales data (the distribution simulation in FIG. 15). (See the reference value display field on the screen.) (Fig. 14, steps S504, S506). In addition, the reference number is rounded up to the whole number and displayed in the distribution number column of each store. The numerical value displayed in the distribution number column is the distribution number for each store.

 In this 'distribution method', the total number of distributions at each store is the total number of distributions. When the total allocated number is given, the total allocated number may be allocated to each store according to the ratio of the allocated number of each store calculated above.

 Formula (6)

Current Week Sales Forecast = {Prel Xa + Pre2 Xb + Pre 3 Xc + Pre4Xd} / (a + b + c + 'd)

Prel: Sales volume of the week before one week a: Weight of Prel Pre2: Sales volume of the week two weeks ago b: Weight of Pre2 Pre3: Sales volume of the week three weeks ago c: Weight of Pre3 Pre4: Four weeks Previous week's sales quantity d: Weight of Pre4 Formula (7)

 Reference value = this week's sales forecast value Z digestion rate-1 (stock quantity + number of shipments + number of sales this week) Here, the digestion rate is the cumulative number of sales of the relevant SKU at each store. , The rate divided by the total number of purchases. The number of consignments is the number of unordered SKUs at each store that have been ordered.

 Note that this week's sales forecast value is calculated by taking into account the weekend index (the ratio of the sales volume on Saturday and Sunday to the sales volume per week, which is the ratio of sales volume on Saturday and Sunday), which is the sales ratio on Saturday and Sunday during the set period. Then, the reference value may be calculated (see Equation (8)). As a result, it is possible to increase the priority of a store having a high sales ratio on the weekend and to concentrate the store on the store with priority. Formula (8)

 Current Week Sales Forecast

 = {Prel Xa + Pre2Xb + Pre3 Xc + Pre4Xd} / (a + b + c + d) X Weekend index

 Prel: Sales volume of the week before one week a: Weight of Prel Pre2: Sales volume of the week two weeks ago b: Weight of Pre2 Pre3: Sales volume of the week three weeks ago c: Weight of Pre3 Pre4: Four weeks ago Weekly sales volume d: Weight of Pre4 Note that the weights a to d of Prel and the digestion rate may be set arbitrarily by the operator.

(b) Allocation by sales composition

FIG. 16 shows a flow chart of the distribution process based on the composition ratio of the number of units sold in step S508 in FIG. CPU 102 is allocated SKUs during initial allocation Calculate the ratio of the total number of units sold for the relevant SKU in each store for the five weeks including the current week (the composition ratio of the number of units sold during the period for each store) for the relevant SKU (Figure) 16 step S600). By allocating the additional distribution number according to the composition ratio of the sales number during this period, the distribution number for each store is determined, and the distribution simulation screen shown in Fig. 15 is displayed. (Steps S602 and S604 in FIG. 16). In other words, the number of sheets to be distributed to a certain store is a value obtained by rounding up the calculated value c of Expression (9) to an integer.

 Additional allocation number X Composition ratio of period sales number of the store = Calculation value c —— (9)

 The result (allocation data) of the allocation simulation at the time of this additional allocation is transferred to the distribution center computer 40. The distribution center outputs distribution data using the distribution center computer 40, and performs a shipping operation for additionally allocating SKUs to each store based on the output data. Each store sells additional SKUs from the distribution center.

 4. Other examples

 4.1 Other Examples of Processing with Store Rank

(1) In the above embodiment, stores are ranked based on the “period sales amount” of the product attribute group to which the SKU belongs. It may be based on “amount and SKU occupancy rate” and “period sales volume and SKU occupancy rate”. The case of ranking stores based on “period sales volume and SKU occupancy rate” will be described with reference to FIG. 17A. The abscissa indicates the number of units sold per store of the product attribute group during the period, and the ordinate indicates the SKU occupancy rate of the store in the product attribute group. Each store is represented by a plot. The ranking of each store is determined based on the sales occupancy ratio (period sales units XSKU occupancy rate). Rank S is ranked in the top 40% or more, rank A in the top 40 to 70%, and rank A in the top 70 to 90%. B, bottom 10% Rank less than Rank C for each store. Curves 800, 802, 804, and 806 show the sales occupancy ratio between the ranks. For comparison, Figure 17B shows the case where stores are ranked based on “period sales volume”.

 When the SKU occupancy rate is considered in this way, stores with a large number of sales but a low SKU occupancy rate have a lower rank. Conversely, stores with a small sales volume but a high SKU occupancy rate have a higher rank. Go up. In other words, the latter stores with higher sales efficiency have higher ranks, so by increasing the amount allocated to these stores, sales can be increased.

 The “number of SKUs sold” on the vertical axis in FIG. 17B is the number of types of SKUs that generated sales during the set period. In addition, instead of the SKU occupancy rate, the store may be ranked using the inventory turnover rate or the like.

 (2) In the above embodiment, stores are ranked based on the sales amount of the product attribute group to which the SKU to be distributed belongs. However, it is not limited to this. For example, the store may be ranked based on the sales amount or the like of the SKU. The store may be ranked based on the sales amount of the SKU similar to the SKU. In addition, the stores may be ranked based on the sales amount of a product attribute group similar to the product attribute group to which the SKU belongs.

 (3) In the above embodiment, the pull-down menu of the store selection field 660 on the distribution simulation screen shown in FIG. 9 indicates that “only S stores, S 'A stores, S · A · B stores, You can select the store to be allocated from “Store allocation”. However, the present invention is not limited to this. For example, only stores in Rank B may be selected.

 4.2 Other Examples of Allocation Simulation (Initial Allocation, Additional Allocation)

(1) In the above embodiment, in the normal allocation process and the 1: 100 allocation process, the sales amount (period) of the product attribute group to which the SKU to be allocated belongs Based on the sales amount composition ratio), the number of distributions to each store is calculated (step S202 in FIG. 10, step S306 in FIG. 11). From the power of sales, the sales volume (period) of the product attribute group to which the SKU to be distributed belongs

The distribution number for each store may be calculated based on 'the composition ratio of the number sold.'

 Alternatively, the number of pieces to be distributed to each store may be calculated based on the sales amount or the number of pieces of SKU to be distributed. Alternatively, the number of pieces to be distributed to each store may be calculated based on the sales amount or the number of pieces of SKU similar to the SKU. Alternatively, the number of pieces to be distributed to each store may be calculated based on the sales amount or the number of pieces of product attribute groups similar or related to the product attribute group to which the SKU to be distributed belongs.

 (2) In the above embodiment, in the sales forecast distribution processing and the distribution processing based on the composition ratio of the number of units sold, the reference value based on the number of units sold of the SKU to be distributed or the composition ratio of the period unit sales is used. Then, the number of sheets to be distributed to each store is calculated (step S506 in FIG. 14, step S602 in FIG. 16). However, the number of distributions for each store may be calculated based on the sales amount of the SKU to be distributed.

 Also, the number of pieces to be distributed to each store may be calculated based on the number of pieces or the sales amount of the product attribute group to which the SKU to be distributed belongs. Alternatively, the number of copies to be distributed to each store may be calculated based on the number of sales or the sales amount of the product attribute group similar or related to the product attribute group to which the SKU to be distributed belongs.

(3) In the above embodiment, in the 1: 100 allocation process, the operator selected the one for each of the ranks S and A, and distributed one by one from the upper rank (see the figure). 11 step S300) may distribute the prescribed amount. Further, instead of allocating from the top rank, the allocation may be performed in descending order of the sales amount or the number of sales. (4) In the above embodiment, in the commodity rank distribution process, the operator is caused to input the rank-specific distribution number on the rank-specific distribution number setting screen shown in FIG. 13A (see FIG. 12 step). S400). From the low power S, the allocation number setting screen for each rank shown in FIG. 18 may be used. In this case, the number of distributions for each rank is set in advance, and the operator is allowed to select a desired item. Further, instead of the number of allocations by rank, the allocation ratio by rank may be used.

 (5) In the above embodiment, the allocation processing method at the time of the first time and at the time of addition is “normal allocation, 1: 100 allocation, product rank allocation, sales forecast allocation, allocation based on the composition ratio of the number of units sold”. Is described as an example. However, it is not limited to these. For example, the number of units sold per type of SKU is calculated using the number of units sold for the product attribute group to which the SKU to be distributed belongs and the number of types of SKUs (number of SKUs) belonging to the product attribute group (see Fig. 3). (Number of units sold / Number of SKUs) may be calculated for each store and distributed based on this calculated value.

 In addition, it belongs to the product attribute group and is sold in a certain amount or more

Using the number of types of SKUs (for example, one or more sold) (the number of operating SKUs), the number of units sold per type of SKU (the number of units sold / the number of operating SKUs) is calculated for each store. The distribution may be based on the calculated value. As a result, it is possible to realize an allocation process in consideration of the sales power per SKU type. It is also possible to execute a distribution simulation using “number of sales / number of SKUs” and “number of sales / number of operating SKUs” without ranking stores.

(6) In the above embodiment, the case where the operator has not set the total number of allocated sheets has been described. However, on the distribution simulation screen shown in FIG. 9, the setting is made by clicking the distribution number change button 640 and inputting a numerical value in the total distribution number setting field 650 '. You may. (7) In the above embodiment, the case where the number of sales for 5 weeks including the current week is used in the sales forecast distribution at the time of additional distribution and the distribution based on the composition ratio of the sales volume will be described as an example. I have. However, the present invention is not limited to this period, and the operator may be able to set the period arbitrarily. Further, the period may not be set, and may be a cumulative total of the number of sales units so far.

 (8) In the above embodiment, the number of distributions to each store is calculated using the reference value calculated by the equation (7). Instead of the reference value, the distribution prediction value for the current week ( = (This week's sales forecast value / digestion rate) may be used to calculate the number of pieces to be distributed to each store.

 (9) In the above embodiment, at the time of additional allocation, the store is not ranked, and the allocation simulation is performed using the reference value. However, an allocation simulation may be performed on the ranked stores by using a reference value.

(10) In the above embodiment, the value obtained by rounding up the calculated values of Expressions (3) and (4) to an integer is used as the distribution number for each store. However, a numerical value obtained by rounding down the calculated value to an integer, or an integer value closest to the calculated value may be used as the number of sheets to be distributed to each store. Similarly, instead of a numerical value obtained by rounding up the reference value calculated by Expression (7) to an integer, a numerical value rounded down to an integer may be used as the distribution number for each store.

4.3 Other Examples

(1) In the above embodiment, the product attribute groups are grouped by item (for example, jacket, pullover, cardigan, etc.) and size. However, the present invention is not limited to this, and may be grouped using other elements (for example, colors). In addition, items may be grouped together with items and sizes using items' subs (for example, nits, fabrics, jerseys, etc.). By using this item / sub, it is possible to form a product attribute group having characteristics closer to the SKU to be allocated. In addition, the product attribute group may be formed only of the item, only the item 'sub, or only the size. For example, when allocating “jersey” type SKUs, use item attribute groups formed by item sub jersey j without setting items.

 In addition, a plurality of product attribute groups may be set. For example, by setting a plurality of items or item 'subs, sales data of a product attribute group may be increased and useful.

 (2) In the above embodiment, the SKU, which is the product specified by the product number, size, and color, is associated as the allocation target, and the handling result information corresponding to the allocation target is It describes the sales amount of the product attribute group (jacket, size A) in association with it. However, the handling performance information corresponding to the allocation object may be the handling performance information of an object having characteristics related to or similar to other characteristics such as the type, property, and function of the allocation object. Figure 19 shows an example of the allocation target and the handling result information corresponding to the allocation target.

 (3) In the above-described embodiment, a case has been described in which the distribution simulation determines how many products are to be distributed to which stores. However, the present invention is also applied to a case where only the store to be distributed (a distribution destination) is determined or a product to be distributed only (a distribution amount) is determined. be able to.

 (4) In the above-described embodiment, a case in which merchandise is physically distributed to a plurality of stores is described as an example.However, data is used as an object to be distributed using a telecommunication line. The present invention can also be applied to the delivery of programs and programs. Also, the present invention can be applied to a case where products are distributed to a plurality of product placement areas in the same store or the like. For example, in the same store, the same product is distributed to the first to fifth floors.

(5) In the above embodiment, the data aggregation processing is performed by using a computer (aggregation processing computer 20) that is separate from the allocation processing computer 10. However, the allocation processing computer 10 may perform the data aggregation processing.

 (6) In the above embodiment, the case where apparel products are distributed to each store is described as an example. However, the present invention is applicable to general products (food, electric products, etc.). And can be. The items to be distributed are not limited to the items to be sold at each store. It can also be applied to products that are traded between companies.

 (7) In the above embodiment, the store is described as an example in association with the distribution destination, but the present invention is not limited to this. For example, it may be a factory, a sales office, a distribution center, or the like.

 (8) In the above embodiment, the result of distribution simulation (distribution data) is transferred to the distribution center computer 40. You may transfer them to the store computers 50, 52, 54 while you work. In this case, each store may issue a product shipping instruction to a distribution center or the like based on the distribution data. In addition, each store may issue a product shipping command within the range of the number of sheets to be distributed to the store indicated in the distribution data.

 (9) In the above embodiment, the distribution center computer 40 transmits the receipt / shipment data to the aggregation processing computer 20 of the headquarters. You may send it to Similarly, the store computers 50, 52, and 54 transmit the sales data to the aggregation processing computer 20 of the headquarters, but the documents that output the sales data may be sent to the headquarters.

 (10) In the above embodiment, the distribution processing computer 10 is an aggregation processing computer 20, a logistics center computer 40, and a store computer.

By using it with 50 mag, the case where the above-mentioned distribution simulation and the process with store rank are executed is described as an example. However, the distribution processing computer 10 alone may execute the distribution simulation and the process with store rank. (11) In the above-described embodiment, an example in which apparel products having the same brand are allocated is described. However, this is not limited to the case where brands are the same.

4.4 Aggregation Processing Computer 20 Processing ·

 FIG. 20 shows a flow chart of the data summarizing process by the summarizing computer 20 shown in FIG. The CPU of the aggregation processing computer 20 calculates the sales data from the store computers 50, 52, and 54 of each store (how many SKUs are sold, how many SKUs are sold, and the data from the distribution center computer 40). Receiving incoming / outgoing data (how many SKUs have been received and how many have been collected) and receiving order data (how many SKUs have been ordered) from the operator, the database server 30 This is stored in the transaction DB 36 (step S800 in FIG. 20), and this process is repeated until a predetermined time comes (step S802 in FIG. 20).

 At a predetermined time, the sales data of each store is totaled for each SKU, and recorded as the number of sales of the day in the transaction DB 36 of the database server 30 (step S804 in FIG. 20). Similarly, incoming data and outgoing data are collected for each SKU and recorded in the transaction DB36. As a result, daily sales data and the like are accumulated.

 In addition, for each SKU in each store, the total sales for the week (cumulative sales from Monday), the total sales for the week, the number of purchases, the number of stocks, etc. are calculated ( This is recorded in the transaction DB36 (see FIG. 5B) of the database server 30 (FIG. 20 step S808).

Claims

Range of request

1. In a distribution processing system including a plurality of distribution destination terminal devices, a distribution processing device, and a distribution execution device,

 5 The destination terminal device records the actual transaction information of the object,

 The distribution processor

 Receives and records information on the actual results of handling of the object at each distribution destination from each distribution destination terminal device,

 0 Classify each allocation destination based on the handling result information corresponding to the allocation target to be newly allocated,

 Receiving the total amount of the allocation target to be newly allocated, and using the classification determined for each allocation destination, the relevant allocation to each allocation destination.How to allocate the target Is generated and transmitted to the distribution execution unit,

15 The distribution execution device, upon receiving the distribution data, executes a process for allocating the distribution target to the distribution destination based on the distribution data. System.

2. In the system of claim 1,

 0 The allocation data indicating which allocation target is to be allocated to the allocation target, or how much allocation target is allocated to which allocation target is generated. .

3. In the system of claim 1 or claim 2,

 5. The handling result information corresponding to the allocation target is the past handling performance information of the allocation target in the past.

4. In the system of claim 1 or claim 2, The handling performance information corresponding to the allocation target is past handling performance information for the entire group to which the allocation target belongs.

5 5. In the system of claim 1 or claim 2,

 Generating the allocation data indicating how much the allocation target is allocated to the selected allocation destination selected by using the classification determined for the allocation destination.δ. thing. 0

6. The system of claim 5,

 · 'Handling performance information corresponding to the allocation target of each of the selected distribution destinations with respect to handling performance information corresponding to the allocation target of the entire selected distribution destination.

'The distribution data indicating how much the distribution target is distributed to each of the selected distribution destinations according to the report ratio is generated. Five

 7. In the system of claim 5,

 A predetermined amount of the distribution object is distributed to each of the selected distribution destinations, and, regarding the remaining distribution object after the distribution, handling result information corresponding to the distribution object of the selected distribution destination as a whole. Generating the allocation data indicating how much to allocate to each of the selected allocation destinations in accordance with the ratio of the handling performance information corresponding to the allocation target of each of the selected 0 allocation destinations. Things to do.

8. In the system of claim 1 or claim 2,

 5. The method according to claim 1, wherein the allocation data indicating how to allocate the allocation target is generated based on an allocation amount or an allocation ratio set for the classification.

9. In the system of claim 1 or claim 2, How much to allocate based on the handling performance information corresponding to the allocation target of the group to which the allocation target belongs and the handling capacity per group configuration calculated from the number of types of the group configuration belonging to the group It is characterized in that the above-mentioned distribution data indicating whether or not to distribute the object is generated.

10 In the system of claim 1 or claim 2,

 The distribution data indicating how much the distribution target is to be distributed is generated based on the sales forecast value calculated from the transaction result information corresponding to the distribution target.

1 1. In the system of claim 10,

 'Based on the sales forecast value considering the weekend index, the distribution data indicating how much the distribution target is distributed is generated.

1 2. In the system of claim 1 or claim 2,

 The handling result information is characterized by including at least sales information.

 0

 1 3. In the system of claim 1 or claim 2,

 The handling result information includes at least an occupancy rate calculated from sales information and inventory information. 5 1 4. An allocation processing device that generates allocation data for determining how to allocate an allocation target to each allocation destination,

Receiving information on the actual performance of the target at each distribution destination, classifying the respective distribution destinations based on the actual performance information corresponding to the new distribution target, Based on the total amount of allocation target to be newly allocated, each allocation destination is decided.How to allocate the allocation target to each allocation destination using the classification A distribution processing apparatus that generates distribution data indicating whether the distribution processing is performed.

15. The apparatus of claim 14,

 Generating the allocation data indicating which allocation target is to be allocated to the allocation target or how much the allocation target is allocated to which allocation target;

1 6. In the device of claim 14 or claim 15,

 The handling result information corresponding to the allocation target is the past handling information of the allocation target in the past.

17. In the device of claim 14 or claim 15,

 The service performance information corresponding to the allocation object is past service performance information of the entire group to which the allocation object belongs.

18. In the device of claim 14 or claim 15,

 A method for generating the distribution data indicating how much the distribution target is distributed to the selected distribution destination selected using the classification determined for the distribution destination.

1 9. The apparatus of claim 18,

In accordance with the ratio of the handling performance information corresponding to the allocation target of each of the selected distribution destinations to the handling performance information corresponding to the allocation target of the entire selected distribution destination, Generating the allocation data indicating whether only the objects to be allocated are to be allocated.

20. The apparatus of claim 18 wherein:

 In addition to allocating a predetermined amount of the allocation target to each of the selective allocation destinations, handling the remaining allocation target after the allocation corresponding to the allocation target of the five selection allocation destinations. Generating the allocation data indicating how much to allocate to each of the selected allocation destinations in accordance with the ratio of the handling performance information corresponding to the allocation target of each of the selected allocation destinations to the performance information. Features. 0 2 1. In the device of claim 14 or claim 15,

 And generating the allocation data indicating how to allocate the allocation target based on the allocation amount or allocation ratio set for the classification. 5 2 2. In the device of claim 14 or claim 15,

 How much to allocate based on the handling performance information corresponding to the allocation target of the group to which the allocation target belongs and the handling capacity per group configuration derived from the number of types of group configuration belonging to the group A feature of generating the distribution data indicating whether or not the object is distributed.

2 3. In the device of claim 4 or claim 15,

 The distribution data indicating how much the distribution target is to be distributed is generated based on the sales forecast value calculated from the handling result information corresponding to the distribution target.

24. The apparatus of claim 23, The distribution data indicating how much the distribution target is to be distributed is generated based on the sales forecast value in consideration of the weekend index.

25. In the device of claim 14 or claim 15,

 The handling result information is characterized by including at least sales information.

26. In the device of claim 14 or claim 15,

 The above-mentioned handling result information is characterized by including at least an occupancy rate calculated from sales information and stock information.

2 7. Receiving information on the actual handling of the target materials at each distribution destination, and newly allocating the distribution destinations based on the actual handling information corresponding to the allocation targets.

 Newly allocate the distribution target. Based on the total amount of the distribution target, using the classification determined for each distribution destination, how to distribute the distribution target to each of the above allocation destinations A program that causes a computer to execute the process of generating distribution data indicating whether or not the data is distributed.

28. In the program of claim 27,

 The method according to claim 1, wherein the allocation data indicating which allocation target is allocated to the allocation target or how much the allocation target is allocated to which allocation target is generated.

29. In the program of claim 27 or claim 28,

The handling result information corresponding to the allocation target is past handling performance information of the allocation target in the past.

30.In the program of claim 27 or claim 28, the handling performance information corresponding to the allocation target is past handling performance information for the entire group to which the allocation target belongs. Those that are characterized by

3 1. In the program of claim 27 or claim 28,

 The computer executes the process of generating the allocation data indicating how much the allocation target is allocated to the selected allocation destination selected using the classification determined for the allocation destination. It is characterized by having

3 2. In the program of claim 31,

 According to the ratio of the handling performance information corresponding to the allocation target of each of the selected distribution destinations to the handling performance information corresponding to the allocation target of the entire selected distribution destination, the number of the selected distribution destinations is A computer is configured to execute a process of generating the allocation data indicating whether or not the allocation target is allocated as much as possible.

3 3. In the program of claim 31,

 A predetermined amount of the distribution object is distributed to each of the selected distribution destinations, and, with respect to the remaining distribution object after the distribution, handling result information on the distribution object of the selected distribution destination as a whole. The process of generating the allocation data indicating how much to allocate to each of the selected allocation destinations in accordance with the ratio of the handling result information corresponding to the allocation target of each of the selected allocation destinations for the It is characterized by being executed by a computer.

3 4. In the program of claim 27 or claim 28, Causing the computer to execute the process of generating the allocation data indicating how to allocate the allocation target based on the allocation amount or allocation ratio set for the classification. Features.

5 3 5. In the program of claim 27 or claim 28,

 How much to allocate based on the handling performance information corresponding to the allocation target of the group to which the allocation target belongs and the handling capacity per group configuration calculated from the number of types of group configuration belonging to the group A computer, which causes the 0 computer to execute a process of generating the allocation data indicating whether or not the object is to be allocated.

36. In the program of claim 27 or claim 28,

'' The computer executes the process of generating the allocation data indicating how much the allocation target is allocated based on the sales forecast value calculated from the handling result information corresponding to the allocation target. It is characterized by having

37. In the program of claim 36,

 A process for generating the distribution data indicating how much to distribute the distribution object based on the sales forecast value in consideration of the weekend index, by a computer.

38. The program according to claim 27 or claim 28, wherein the handling result information includes at least sales information.

39. The program according to claim 27 or claim 28, wherein the handling result information includes at least an occupancy rate calculated from sales information and stock information. of. • 4 0. Receiving actual performance information of the object at each distribution destination, and newly allocating. Classifying each allocation destination based on the actual processing information corresponding to the allocation target,

 New allocation is performed. Based on the total amount of the allocation target, and using the classification determined for each allocation destination, A recording medium on which a program for causing a computer to execute a process of generating distribution data indicating whether to distribute to a computer is recorded.

41. The recording medium of claim 40,

 Causing the computer to execute the process of generating the allocation data indicating which allocation target is to be allocated to the allocation target or how much the allocation target is allocated to which allocation target. The program is characterized by recording a program for

4 2. In the recording medium of claim 40 or claim 41,

 The service performance information corresponding to the distribution target is past performance information of the distribution target in the past. 4 3. In the recording medium of claim 40 or claim 41,

 The handling performance information corresponding to the allocation target is past handling performance information for the entire group to which the allocation target belongs. 44. In the recording medium of claim 40 or claim 41,

A method for generating the distribution data indicating how much the distribution target is distributed to the selected distribution destinations selected using the classification determined for the distribution destinations.

45. The recording medium of claim 44.

 According to the ratio of the handling performance information corresponding to the allocation target of each of the selected distribution destinations to the handling performance information corresponding to the allocation target of the selected distribution destination as a whole, for each of the selected allocation destinations. A program for causing a computer to execute the process of generating the allocation data indicating how much the allocation target is to be allocated.

46. The recording medium of claim 44, wherein

 A predetermined amount of the distribution object is distributed to each of the selected distribution destinations, and, regarding the remaining distribution object after the distribution, handling result information corresponding to the distribution object of the selected distribution destination as a whole. The process of generating the distribution data indicating how much to allocate to each of the selected distribution destinations in accordance with the ratio of the handling performance information corresponding to the distribution target object of each of the selected distribution destinations for the A program that records programs to be executed by a computer.

47. In the recording medium of claim 40 or claim 41,

 A program for causing a computer to execute processing for generating the allocation data indicating how to allocate an allocation target based on an allocation amount or an allocation ratio set for the classification. Recorded.

48. In the recording medium of claim 40 or claim 41,

How much to allocate based on the handling performance information corresponding to the allocation target of the group to which the allocation target belongs and the handling capacity per group configuration calculated from the number of types of group configuration belonging to the group A program for causing a computer to execute a process of generating the allocation data indicating whether or not to allocate an object is recorded.

49. In the recording medium of claim 40 or claim 41,

 To cause the computer to execute the process of generating the distribution data indicating how much the distribution target is to be distributed, based on the sales forecast value calculated from the handling result information corresponding to the distribution target. It is characterized by having recorded the program of.

50. The recording medium according to claim 49,

 A program for causing the computer to execute the process of generating the allocation data indicating how much the allocation target is to be allocated based on the sales forecast value taking the weekend index into consideration has been recorded. Features characterized by and.

5.1. In the recording medium of claim 40 or claim 41,

 The above-mentioned handling result information is characterized by including at least sales information.

5 2. In the recording medium of claim 40 or claim 41,

 The handling result information is characterized by including at least an occupancy rate calculated from sales information and inventory information.

5 3. Using a computer,

 Receiving information on the actual handling of the target at each distribution destination, and newly allocating. Evaluating each allocation destination based on the actual handling information corresponding to the target,

New allocation To receive the total amount of objects to be allocated, and using the evaluation determined for each allocation destination, how to assign the 'allocation' object to each allocation destination An allocation processing method characterized by generating allocation data indicating whether to allocate.

5 4. A distribution processing system including a plurality of distribution destination terminal devices, a distribution processing device, and a distribution execution device,

 Each distribution destination terminal device

 5 Equipped with a first storage means for recording the handling result information of the object,

 The distribution processing device,

 A second storage means for receiving and recording the handling result information of the object at each distribution destination from each distribution destination terminal device;

 Classifying each of the distribution destinations based on the handling result information corresponding to the newly allocated object to be distributed, which is stored by the second storage means.

 New allocation is performed. The total amount of the allocation target is received. A generator that generates distribution data indicating how to distribute objects;

 Transmission means for transmitting the distribution data generated by the generation means to the distribution execution device,

 The allocation execution device,

 Executing means for receiving the distribution data transmitted by the transmission means, and executing a process for allocating the object to be allocated to the allocation destination based on the distribution data;

 A distribution processing system comprising:

5 5. An allocation processor for deciding how to allocate the allocation objects to each allocation destination,

Receiving means for receiving the handling result information of the object at each distribution destination, and classifying each allocation destination based on the handling performance information received by the receiving means and corresponding to the new allocation target Classification means and, The new allocation is performed. The total amount of the allocation target is received, and the allocation target is allocated to the allocation target using the classification determined for each allocation destination by the classification means. Means for generating allocation data indicating how to allocate;

A distribution processing device comprising: