JP2003162564A - Order control system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an order control system capable of controlling orders of goods, while controlling sale in stores and properly maintaining an amount of stock. <P>SOLUTION: The week starting from now on is set as a 39-th week, and the week plus a lead time (42nd week) becomes a control targeted week. When determining the amount of order, the amount of order is determined so that the amount of an inventory at a starting time of the control targeted week (42nd week) becomes equal to the sum of expected sales during designated weeks plus the control targeted week (called 'the forecast stock weeks'). Further, the expected sales on a calculating basis of the amount of order will be revised on actual results by each week. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an order management system, and more particularly to a system capable of managing a balance between sales volume and order volume.

[0002]

2. Description of the Related Art A system for determining an appropriate production amount is disclosed in Japanese Patent Laid-Open No. 6-259438.

Japanese Unexamined Patent Publication (Kokai) No. 6-259438 discloses an attempt to determine an appropriate production amount based on order information from a customer and an inventory amount to minimize the in-process inventory. This system is effective for determining the production amount in a form in which the required amount is presented in advance by the customer, so-called manufacturing industry.

However, while selling at a store,
It has been difficult to use this system for order quantity management in a company that operates a manufacturer to place an order. This is because the system of the above-mentioned conventional technology is premised on the case where the order quantity from the customer is known in advance, and does not assume a form such as immediate sales at a store.

This invention manages sales at stores,
It is an object of the present invention to provide an order management system capable of managing product orders and maintaining an appropriate inventory amount.

[0006]

[Means for Solving the Problems] (1) A management system according to the present invention includes a sales terminal device that accumulates a sales record of a transaction target and sends it to an order management device; When the lead time period is the period from the ordering of the target product to the arrival of the target product, at least the lead time period ahead of the current time point is the management target time point, and the sales record amount of the transaction target and the receipt record Based on the quantity, planned storage quantity, and sales forecast quantity, the inventory management quantity at the future management target time is adjusted so that it corresponds to the total sales forecast quantity from the management target time point to the inventory quantity determination period ahead. It is characterized by including an order management device that generates management data for managing the current order quantity to be received at the target time and sends the management data to the sales terminal device.

[0007] That is, the estimated stock quantity at the future management target time corresponds to the total sales prediction quantity from the management target time point to the inventory quantity determination period ahead, at the present time point when the stock should be received at the management target time point. Manages the order quantity. As a result, it is possible to appropriately manage the order quantity at the present time by using the stock quantity corresponding to the sales forecast quantity before the management target time as an index.

(2) to (4) The order management device according to the present invention is
When the lead time period is the period from the ordering of the target product to the arrival of the product, at least the lead time period ahead from the current time is the management target time,
Based on the actual receipt amount, the expected receipt amount, and the forecast sales amount, the estimated inventory amount at the future management target time corresponds to the total of the forecast sales amount up to the inventory quantity determination period beyond the relevant management target time. It is characterized by managing the current order quantity that should be received at the time of management.

In other words, the estimated stock quantity at the future management target time corresponds to the total sales prediction quantity from the management target time point to the inventory quantity determination period ahead, at the present time when the stock should be received at the management target time point. Manages the order quantity. As a result, it is possible to appropriately manage the order quantity at the present time by using the stock quantity corresponding to the sales forecast quantity before the management target time as an index.

It should be noted that the order quantity can be determined in a department (such as the head office) in which the order management apparatus is located, based on the order management data calculated by the order management apparatus. In this case, the management can be performed regardless of whether or not the sales terminal device exists in the sales department. Further, by sending the order management data to the sales terminal device, it is possible to provide the department with the sales terminal device with information for controlling the order quantity.

(5) The management system according to the present invention corrects or calculates the future sales forecast amount based on the comparison between the sales forecast amount up to the present time and the actual sales amount, and based on the new forecast sales amount. It is characterized by managing the current order quantity.

Therefore, it is possible to manage the order quantity with higher accuracy by using the sales forecast quantity in consideration of the actual results.

(6) The management system according to the present invention is characterized in that the order quantity is managed so that the estimated stock quantity is equal to the total of the predicted sales quantity up to the inventory decision period destination.

Therefore, it is possible to appropriately manage the order quantity at the present time so that the stock quantity is equal to the sales forecast quantity before the management target time.

(7) The management system according to the present invention is characterized in that the order quantity is managed by calculating and outputting the upper limit quantity that can be ordered.

Therefore, by placing an order within the limit of this upper limit based on the judgment of a person or the like, excessive inventory can be prevented.

(8) The management system according to the present invention is characterized in that the stock forecast quantity of all target goods is calculated by excluding the stock quantity of the goods for which future sales cannot be expected.

Therefore, based on the actual inventory quantity,
The order quantity can be determined, and highly accurate order management can be performed.

(9) In the order management method according to the present invention, when the period from the ordering of the target product to the arrival of the product is the lead time period, the management target time is at least the lead time period ahead of the current time, and the transaction target Based on the actual sales amount, the actual receipt amount, the planned receipt amount, and the forecast sales amount, the estimated inventory amount at the future management target time becomes the total of the forecast sales amount from the relevant management time point to the inventory quantity determination period ahead. Correspondingly, it is characterized in that management data for managing the current order quantity to be received at the time of the management target is generated.

In other words, the estimated stock quantity at the future management target time corresponds to the total sales forecast quantity from the management target time point to the inventory quantity determination period ahead, at the present time when the stock should be received at the management target time point. Manages the order quantity. As a result, it is possible to appropriately manage the order quantity at the present time by using the stock quantity corresponding to the sales forecast quantity before the management target time as an index.

In the present invention, "target product" means a product or a product group to be managed in this system. In the embodiment, the target product is an item obtained by grouping a plurality of products.

The "management data" means data used for managing the order quantity, and in the embodiment, the order limit data corresponds to this.

"Merchandise" means an article specified by size, color, design, type, function and the like. It is a concept that includes all items such as food, clothing, and electric appliances. In the embodiment, the description is given for the apparel product. It is also a concept that includes products traded between companies. Furthermore, the concept includes not only products that are traded independently but also products that are traded in association with other products and services.

“Item” refers to a group in which products are roughly classified, and in the embodiment, a dress, a coat,
Suits are applicable.

"Brand" means a set of one or more cohesive items.

The "recording medium on which the program is recorded" means
A recording medium such as a ROM, a RAM, a flexible disk, a CD-ROM, a memory card, and a hard disk recording a program. The concept also includes communication media such as telephone lines and carrier paths. Not only a recording medium such as a hard disk that is connected to a CPU and directly executes a recorded program, but a CD-R that records a program to be executed after once installed in a hard disk or the like.
It is a concept including a recording medium such as OM.

The term "program" is a concept that includes not only a program directly executable by the CPU but also a source format program, a compressed program, an encrypted program, and the like.

[0028]

BEST MODE FOR CARRYING OUT THE INVENTION 1. Overall System Diagram FIG. 1 shows a system configuration when an order management system according to an embodiment of the present invention is applied to order management of apparel products. In this embodiment, the management computer 10
The order management device is configured by. The host computer 6 receives the receipt data and the shipment data from the computer 2 of the distribution center that centrally stores and stores and stores the products. Further, the store cash register device 4 is arranged in each store nationwide, and sends sales data to the host computer 6. The host computer 6 places an order with the maker computer 3.

In this embodiment, data is transferred online between the distribution center computer 2, the store cash register device 4, the maker 3 and the host computer 6, but data is transferred via a recording medium such as a flexible disk. May be sent. Further, the data may be sent by printing out the data on paper or the like at the transfer source and inputting the data at the transfer destination based on the printout.

The host computer 6 receives the data from the distribution center computer 2 and the store cash register apparatus 4, collects the data at a predetermined time every day, and communicates with the database server 9 to update the database 8. The management computer 10 is connected to the database server 9 via a LAN and makes a sales forecast based on the data accumulated in the database server 8.

2. Overview of Business Model FIG. 2 schematically shows the flow of goods and the flow of information when the system of FIG. 1 is applied for order management. Products are received from the manufacturer 19 at the distribution center 12.
Further, the goods are shipped from the distribution center 12 to the stores 14 and 16. Receipt / shipment data indicating the status of receipt / shipment is sent from the distribution center 12 to the head office 18. Each store 14 and 16 sells products. Each store 14, 16 sends sales data to the headquarters 18.

The head office 18 predicts sales based on these receipt / shipment data and sales data. Further, the order quantity is calculated based on the receipt / shipment data, the sales data, and the sales forecast. The head office 18 places an order with the maker 19 according to the calculated order quantity.

3. Host Computer FIG. 3 shows the hardware configuration of the host computer 6. The host computer 6 includes a CPU 20, a hard disk 22, a display 24, a communication unit 26, a memory 28, a keyboard / mouse 30, a CD-ROM drive 32, a printer 34, and a flexible disk drive 36.

The communication section 26 is for communicating with the distribution center computer 2, the store cash register device 4, the maker computer 3, and the management computer 10. The hard disk 22 stores an operating system and a program for data aggregation processing. A database 8 is built on the hard disk 22. In the database 8, aggregated sales / inventory data, product master data indicating product prices, and the like are recorded.

The program for data totalization processing is C
It is installed in the hard disk 22 from the CD-ROM 38 or the like via the D-ROM drive 32. FIG. 4 shows a flowchart of a program for the data totaling process.

In step S1, the CPU 20 receives sales data from the store cash register device 4 of each store (how many products have been sold) and warehousing data from the distribution center computer 2 (how many products have been received). Then, it receives how many pieces have been shipped) and order data (how many products have been ordered) from the sales forecasting computer 10, and stores them in the database 8 of the database server 9. This process is repeated until a predetermined time is reached (step S
2).

When the predetermined time comes, the received data is totaled (step S3). Usually, this aggregation process is often performed at night when sales data and warehousing data are not generated. In the data aggregation process, sales data from each store is aggregated for each product, and the hard disk 2 is used as the number of sales on the day.
Record in 2. Similarly, warehousing data and warehousing data are totaled for each product and recorded in the database 8 of the database server 9. As a result, daily sales, warehousing, and warehousing data are accumulated.

Further, for each product, the cumulative sales for the week (cumulative sales from Monday), the cumulative number of purchases so far, the cumulative number of sales, and the number of stocks are calculated. These data are recorded in the database 8 of the database server 9 (step S4).

FIG. 5 shows an example of recorded data. As shown in the figure, each product is specified by a combination of a brand and a product number. In this embodiment,
One brand contains multiple products, and
The case where multiple brands exist will be described.

FIG. 5 shows the sales accumulated in this way.
An example of inventory data is shown. The number of sales for each week is the total number of sales for each product from Monday to the day of the week. In the figure, the product number "62421" is "0 sheets" for the first week, ... "31 sheets" for the 30th week, and 31st.
It is shown that the number of sales is “40” for the week and “48” for the 32nd week. Note that the cumulative number of sales for the week (here, the 32nd week) will be fixed on Sunday night.

The cumulative number of purchases is the total number of arrivals of the product. The cumulative number of sales is the total number of sales up to the present. The stock quantity is the stock calculated by the cumulative purchase quantity-sales quantity-adjusted quantity. This stock quantity is also updated daily. The adjusted number refers to the number of items in which the inventory has decreased due to factors other than sales, such as the number of damaged products and lost products. Data of such products are also sent from each store.

The sales start week is a record of the first week when the number of sales is not 0 (that is, the first sales week).

Further, in the database 8, not only the sales / inventory data for this year as described above, but also the sales result data before the last year are recorded. Figure 6 shows an example of sales performance data for the previous year. Although not shown, sales performance data for the years prior to last year is also recorded.

4. Hardware Configuration of Management Computer FIG. 7 shows the hardware configuration of the management computer.
The basic configuration is similar to that of the host computer. However, a program for sales forecast, a program for order management, and the like are recorded on the hard disk 54.

The condition setting process, the sales plan creating process, the sales forecasting process, and the necessary order quantity determining process performed by the management computer will be described below in this order.

5. Condition Setting FIG. 8 shows a flowchart of the sales forecast / order quantity calculation processing program recorded in the hard disk 52 of the management computer 10.

First, the CPU 50 displays a screen for setting various conditions on the display 54 and prompts for input (step S
21). FIG. 9 shows a screen for setting conditions. On this screen, the production lead time (the period from ordering to receipt) and the expected stock week count can be entered for each item.

In the item column, "PO", "VE", "C"
Symbols indicating items such as "D" and "JK" are shown. Here, "PO" is a pullover, "VE" is the best, "CD" is a cardigan, and "JK" is a jacket. For each item, the operator
Enter the lead time in weeks. In the figure, a lead time of 3 weeks is input for the pullover “PO”. For the jacket "JK", a lead time of 4 weeks is entered. These lead times are used when determining the order quantity.

Furthermore, for each item, in the "expected inventory week number" field, enter the number of weeks of sales corresponding to the inventory. In the figure, for pullover “PO”, it is instructed to determine the inventory quantity so that the inventory corresponding to the sales for four weeks is held. As for jackets, it is instructed to determine the inventory quantity so as to have inventory equivalent to sales for 5 weeks.

Each of the above information is recorded in the hard disk 52 and used in the sales forecast / order quantity determination process.

6. Initial Sales Plan Creation Process After setting the conditions as described above, the sales plan is calculated (FIG. 8, step S215). This initial sales plan is
You can do it once at the beginning of the year (or at the end of the previous year).

FIG. 1 is a flowchart of the sales plan creation process.
It shows in 0. Further, FIG. 11 is a diagram showing the contents of data processing at that time. These data are recorded in the database 8.

The CPU 50 of the management computer 10 collects sales performance data for each week for each item for the past three years.
It is acquired from the database 8 (step S71). Also, the sales result data obtained by summing all the items is acquired.

FIG. 11 shows the sales record of all the acquired items and the sales record of one piece for one brand. For items other than one piece,
Illustration is omitted. Also, in FIG. 11, 35 weeks-
52 weeks (35W to 52W), 1 week to 4 weeks (01W to 04W) are shown, and other weeks are not shown. Similar data was obtained for other brands, but the illustration is omitted. In the figure, "98 sales" in the "Total" column
Shows the total sales of all items in 1998, "99 sales" shows the same sales of 1999, and "00 sales" shows the same sales of 2000. Also, "O
In the “P” column, “98 sales” indicates the sales result of one piece for the fiscal year 1998, “99 sales” indicates the sales result for the same fiscal year 1999, and “00 sales” indicates the sales result for the same fiscal year 2000.

Next, the CPU 50 weights the sales results of the past three years. In this embodiment, the weighting average is performed by setting the weight last year to 5, last year 3 to 3 and 3 years ago to 2. This suggests that the most recent data will be more reliable for this year's forecast. The weighted average of sales results is not shown.

Next, the weekly index for each week is calculated based on the weighted and averaged sales results for each week (step S73). Here, the weekly index is a weighted average of the sales results of each week, and the average sales per week is calculated. The average sales result is set to 100 and the sales results of each week are indexed. . In other words, it is an index showing how much sales power the item has in the week.

If 100, the week has average sales strength of the item throughout the year, and 10
A value of 0 or above indicates that the week is stronger than average sales strength. Also, if it is 100 or less, it means that the week is weaker than the average sales strength. In FIG. 11, the “index” column of the “total” column shows the weekly index of all items, and the “index” column of the “OP” column shows the weekly index of one piece.

Next, the operator of the management computer 10
The annual sales plan amount of the brand is input from the keyboard 60 (step S74).

In response to this, the CPU 50 calculates the sales plan amount for each week, which is the total of all items of the brand. Here, the annual sales plan amount is distributed by the week index, and the sales plan amount for each week is calculated (step S75). The calculation result is shown in the “01 plan” column of the “total” column of FIG. 11.

Next, the operator of the management computer 10
Enter the sales ratio of each item for the brand throughout the year.

In response to this, the CPU 50 causes the step S7.
The annual sales plan amount input in 4 is distributed to the annual sales plan amount for each item according to the above sales ratio (step S77). The value calculated in this way is the “TOT” in the “01 plan” column in the “OP” column in FIG.
AL ”line.

Next, the CPU 50 distributes the annual sales plan amount for each item by each week according to the week index of the item, and calculates the weekly sales plan amount for each item (step S78). However, in this embodiment, the weekly sales planned amount for each item is not used as it is as the planned amount. This is because if the weekly sales plan amount for each item is used, an error occurs between the total weekly sales plan amount for all items (the amount in the “01 plan” column of the “total” column). Therefore, the sales ratio of the items for each week is calculated as follows, and the weekly sales plan amount (the amount in the “01 plan” column) of the total of all items is distributed by this to prevent an error. .

For the above purpose, the CPU 50 sums up the weekly sales plan amount for each item ("01 plan 1" in the "OP" column) for all items, and the weekly sales plan amount for all items ("Total" column). “01 plan 1”) is calculated. Furthermore, based on the weekly sales plan amount of all of this item total and the weekly sales plan amount for each item,
The item ratio (“composition ratio” in the “OP” column) for each week is calculated (step S79).

Thereafter, the CPU 50 calculates the weekly sales plan amount of all items in total (price in the "01 plan" column of the "total" column) by the item ratio ("composition ratio" in the "OP" column) for each week. The items are distributed and the weekly sales plan amount for each item is calculated (step S80). This is shown in "01 Plan 2" in the "OP" column of FIG.

As described above, the total of all items,
The sales plan amount for each item for each week is calculated and recorded in the hard disk 52. Although the sales plan for one brand is calculated in the above, when a plurality of brands are managed, the same process is performed for all of these brands. The same applies to the following processing.

7. Sales Forecasting Process As described above, after once formulating the sales plan, each process of sales forecasting, required order quantity calculation, and necessary order quantity output is executed every week (FIG. 8, steps S22, S23, S2).
4). Here, first, the sales forecasting process will be described.

Hard disk 5 of management computer 10
In 2, a sales forecast processing program is recorded. A flowchart of this sales forecast processing program is shown in FIG.

This sales forecasting program is executed every predetermined management period. In this embodiment, since the management is performed on a weekly basis, it is executed at the beginning of each week (Monday).

First, the CPU 50 acquires sales record data from the database 9. Here, the sales results for the entire brand (that is, the total items of the brand) and the weekly sales results for each item up to the previous week are acquired.

For example, if this week is the 39th week, the sales record before the 38th week is acquired. FIG. 13 shows the acquired sales performance data. "35W" and "36" in the "TOTAL" column
The data in the "W", "37W", and "38W" rows are weekly sales performance data for the entire brand. In FIG. 13, 34
Data before the week are omitted. Also, select "35" in the "OP" column.
The data in the "W", "36W", "37W", and "38W" rows are weekly sales performance data for One Piece. In addition, in FIG.
Data of other items are omitted.

Next, the CPU 50 calculates a prediction coefficient for modifying the initial plan (step S92). In this embodiment, the deviation between the initial plan and the actual result is made into a prediction coefficient by the following formula.

Prediction coefficient = (J1 * 2 + J2 + J3 + J4) /
(P1 * 2 + P2 + P3 + P4) Here, J1, J2, J3, and J4 are the results of 1 week ago, 2 weeks ago, 3 weeks ago, and 4 weeks ago, respectively. P1, P2, P3, P4 are
The plans are 1 week ago, 2 weeks ago, 3 weeks ago, and 4 weeks ago, respectively. Note that * indicates multiplication.

In the example of FIG. 13, 0.94 is calculated as the prediction coefficient for the entire item. In addition, 0.71 is calculated as the prediction coefficient for one piece.
That is, in this example, the actual result is below the plan, and therefore it is indicated that the future sales forecast needs to be revised downward from the plan.

Next, the CPU 50 calculates a sales forecast (correction plan) in which the future sales plan is corrected based on the calculated prediction coefficient (steps S93, S94). In FIG. 13, the calculated sales forecast of the entire brand is shown below the “39W” line in the “actual revision plan” column. Also,
The calculated sales forecast for One Piece is shown below the "39W" line in the "Modified Plan 1" column.

When the sales forecasts of the respective items calculated as described above are summed up for all the items, the sales forecasts calculated for the entire brand may not match. That is, an error may occur. Therefore, in this embodiment, this error is prevented as follows.

First, the calculated sales forecast "correction plan 1" for each item for each week (herein referred to as "item week-specific correction plan 1") is summed up for all items, and this total (here, item week-specific correction plan 1) is summed up. The composition ratio for each item is calculated based on the modified plan 1. That is,
The item composition ratio is calculated according to the following formula (step S95).

Item Composition Ratio = Item Weekly Revised Plan 1 / Item Weekly Revised Plan 1 Total In FIG.
The calculated item composition ratio is shown in the "weekly item composition ratio" column.

Next, the CPU 50 predicts the sales of the entire brand for each week calculated in step S93 "actual revision plan" (herein referred to as brand total weekly revision plan).
Are distributed to each item according to the item composition ratio (step S96). That is, the item weekly correction plan 2 is calculated according to the following formula.

Item Weekly Revised Plan 2 = Brand Total Weekly Revised Plan * Item Composition Ratio In FIG. 13, the “Item Revised Plan 2” column shows the calculated item weekly revised plan 2.

As described above, the sales plan is corrected and the future sales forecast is calculated.

8. Required Order Quantity Calculation Process Next, the CPU 50 calculates the required order quantity for each item based on the sales forecast. FIG. 22 schematically shows the concept for calculating the required order quantity in this embodiment. Items to be ordered from this week (39th week) will be received 42 weeks (leading controllable week) after the lead time LT. This lead time LT is set in step S21 of FIG.

In this embodiment, from this week (39th week),
When the week (42 weeks) ahead of the lead time LT of the item starts, the order quantity of this week is set so that the inventory matches the forecast sales for the last 4 weeks. The number of weeks before which the inventory has the forecast sales is called the forecast inventory week number. That is, in this embodiment, the forecast inventory week number is set to "4". In other words, based on the sales forecast, the stock is secured in an amount that can cover the sales up to four weeks ahead.

FIG. 14 shows a flow chart of the necessary order quantity calculation processing program. In this embodiment, all the stocks of the products included in the item are not used as the standard for calculating the appropriate stock amount. This is because some of the products included in the items may not be expected to sell in the future. Therefore, if it is attempted to control the appropriate amount of inventory, including the inventory of such products (called non-operating inventory), the inventory of the products actually required cannot be secured. Therefore, such a dead line product (non-operating product) is determined and excluded from the calculated inventory amount.

As shown in FIG. 14, first, step S1
After determining the non-operational product in 01, step S10
The required order quantity is calculated below 2.

(1) Non-working inventory determination process First, the non-working product determination process of step S101 will be described. The flowchart of the program is shown in FIG.
And shown in FIG.

First, the CPU 50 generates basic data for making a judgment. FIG. 17 shows a flowchart of the judgment basic data calculation process. First, the CPU 50
Actual data is acquired from the database 8 of the host computer 6 for all products (step S121).

Next, the brand to be processed first is selected (step S122). For example, the one with the smallest brand number is selected as the brand to be processed. Next, the products included in the brand are sorted in ascending order (that is, in ascending order) from the products with the smallest number of sales in the previous week in the brand (step S123). FIG. 18 shows an example of sorted data. As shown in the figure, the products constituting the brand number “162” are sorted in ascending order of the number of sales in the previous week. In the figure, the cumulative number of purchases, the total number of sales, the number of stocks, the sales start week, and the like are data acquired from the database 8 of the host computer 6.

Next, in the sorted state, the previous week's sales figures are sequentially added up (step S124). That is, for each product, when the previous week's sales numbers are arranged in ascending order for each brand, the total of the previous week's sales numbers from the beginning to the relevant product number (called the brand cumulative previous week's sales number) is calculated. In the figure, this is shown in the column of "BR cumulative sales last week".

Subsequently, the brand sales composition ratio is calculated based on the following formula.

Brand sales composition ratio = (brand cumulative previous week sales-previous week sales) / brand total previous week sales Here, the brand total previous week sales means the total of the previous week's sales of all the products of the brand. .

In another embodiment, the following formula may be used.

Brand sales composition ratio = brand cumulative previous week sales / brand total previous week sales number In FIG. 18, the “BR sales composition ratio” column shows the brand sales composition ratio.

Subsequently, the stock cost, the stock week number, the digestion rate, etc. are calculated (step S125). The upper price is acquired from the product master and multiplied by the number of stocks to calculate the upper stock price.
Further, the number of stocks is divided by the number of sales last week, and the number of weeks of stock is calculated as the number of stock weeks. Further, for reference, the total sales amount is divided by the total purchase amount to calculate the digestion rate.

Next, in step S126, it is determined whether the above process has been performed for all brands. If there are remaining brands to be processed, the next brand is selected as a target (step S127) and step S127.
123 and subsequent steps are executed again.

When the processing for all the brands to be processed is completed, the generation processing of the judgment basic data is ended. As a result, judgment basic data as shown in FIG. 18 is generated for each brand. In addition, when the judgment basic data is generated, the product flagged as a non-operational product is excluded from the product master. That is, the judgment basic data is created only for the operational product.

When the calculation process of the judgment basic data is completed,
Next, a judgment process is performed. 19 and 20 show flowcharts of the determination process.

First, in step S131, the CPU
50 selects one brand to be processed. Next, one product to be processed is selected from the brands (step S132).

For the product, the following judgment is made based on the judgment basic data as shown in FIG. First, it is determined whether the development period of the product is 4 weeks or more (step S133). This can be judged by whether or not the sales start week of the judgment basic data plus 4 weeks is smaller than the current week. If the deployment period is less than 4 weeks, regardless of sales results, etc.
We do not select it as a non-operational product. this is,
This is because there is a possibility that an accurate judgment may not be possible because the period for judging the actual results is short. Note that the judgment reference number of weeks here is a preset number of weeks.

If the development period is 4 weeks or more, the process proceeds to step S134. In step S134, whether or not the number of sales in the previous week is greater than 0 (whether or not there is sales)
Is judged. When the number of sales in the previous week is 0, the product is selected as a non-operation product and is described in the judgment column of the judgment basic data (step S137). For example, in FIG. 18, the product with the product number 03801 is determined to be a non-working product under the above conditions, and “* A” is recorded in the determination column to indicate this.

In step S134, if the previous week's sales quantity is not 0, it is determined whether or not the stock week count is 6 weeks or more (step S135). If the stock week count is less than 6 weeks, it is not determined that the product is a non-operation product.

If the stock week count is 6 weeks or more, it is determined that the product is a non-working product, and the process proceeds to step S136. This is because the balance between sales and inventory for the previous week was too bad.

In step S136, it is determined whether the brand cumulative sales composition ratio of the product is 10% or less. Unless it is 10% or less, it is not determined that it is a non-operational product.

If it is 10% or less, the product is determined to be a non-operational product, and "* B" is recorded in the judgment column. For example, in FIG. 18, the product code “03330” corresponds to this.

Even if the number of stock weeks is large,
If the cumulative sales ratio of the brand is larger than 10%, it is not considered as a non-operational product for the following reason. In other words, in the case of products with a large brand sales composition ratio, if the number of sales in the previous week did not increase due to a shortage of inventory, there are cases where the number of weeks in inventory will increase despite the expected future sales. is there.

In this embodiment, step S13
Whether it is determined to be non-operational according to the condition 4
In order to discriminate whether or not it is determined to be non-operational according to the condition of 36, the former is recorded as ★ A and the latter is recorded as ★ B.

The above-mentioned judgment conditions regarding the number of weeks of inventory and the cumulative sales composition ratio are input and designated by the operator in advance.

When the processing for one product is completed as described above, the process proceeds to step S138 to determine whether or not all the products of the brand have been processed. If there is a product to be processed, the next product is set as the target product (step S139), and step S133 and the subsequent steps are repeated.

When the above process is completed for all products of the brand, the process proceeds to step S140, and it is determined whether or not all brands are processed. If there is a brand to be processed, the next brand is set as the target brand (step S141), and step S132 and subsequent steps are repeated.

When the processing for all brands is completed, a non-working product list as shown in FIG. 21 is generated based on the description in the judgment column and recorded in the hard disk 52 (step S142).

The person in charge of each brand looks at this non-working product list (on the screen or printout) and inputs an approval that the listed product is a non-working product. If the brand manager denies the non-operational product, the product is removed from the non-operational product. CPU
In this way, the 50 determines the non-working product and the working product.

In this embodiment, the non-working product list is confirmed with the approval of the brand manager.
The non-operation product list calculated by U50 may be used as it is.

Although the non-operational product is judged on the basis of the number of sheets, it may be judged on the basis of the amount of money.

(2) Required Order Quantity Calculation Process After determining the non-working products as described above, the necessary order quantity calculation process of FIG. 14 and step S102 and thereafter is executed.

FIG. 22 shows an outline of calculation of the required order quantity in this embodiment. In the figure, this week starting from now is set to 39 weeks. In addition, the lead time from ordering to receipt is 4 weeks. In other words, the products ordered today are expected to arrive within 42 weeks. The lead time is preset by inputting for each brand and each item.

In this embodiment, the week ahead of the lead time (42 weeks in this case) is set as the management target week. That is,
The one ordered this week is the week ahead of the lead time (42 weeks)
Because it will not arrive unless it becomes.

In determining the order quantity, the stock quantity at the start of the managed week (42 weeks) should be equal to the total sales forecast for the predetermined number of weeks ahead (called the expected stock week number). , The order quantity has been decided. Note that this expected stock week count is input in advance and set (FIG. 9).
reference). In this figure, it is 4 weeks.

The sales forecast, which is the basis for calculating the order quantity, is revised weekly based on the actual results. Therefore, an appropriate order can be placed.

The above processing will be described with reference to the flowcharts of FIGS. First, the operating inventory and order data for each brand item are acquired. That is,
The CPU 50 acquires, from the database 8, the inventory amount, the already ordered amount, and the like of the operating products excluding the non-operating products out of the products belonging to each item, and totals each item (step S102).

FIG. 16 shows the calculated hard disk 52.
An example of the data recorded in is shown below. Here, only "one piece" is shown as an item, and other items are not shown. Further, FIG. 16 shows one brand, but similar tables are created for other brands.

Here, this week starting from now is set to 39 weeks. The stock amount of One Piece at the end of last week (38th week) (only active products) appears in the "38th week" row in the "Inventory plan 2" column. In addition, the scheduled arrival week and the amount of money for the one piece that has been ordered but has not been received are recorded in the "stocking" column. Also in this case, non-operated products are excluded from the calculation. In the figure, in the 39th week (this week)
It is shown that dresses worth 4,235 thousand yen will be received in 41 weeks worth 23,308 thousand yen.

Next, the CPU 50 calculates a target proper inventory amount for each weekend (step S103).
That is, the appropriate inventory amount for each weekend is calculated by summing the forecast sales amounts for the number of forecast inventory weeks ahead of the week.
In this embodiment, the expected inventory week number is 5 weeks. For example, the proper inventory amount for 39 weekends is the total amount (54,6) of the sales forecast amounts (“Revised Plan 2”) for 40 to 44 weeks.
It has become 0,000 yen. In the same way, the appropriate stock amount after 40 weeks is also calculated. This proper inventory amount is recorded in the "inventory plan 1" column.

Next, the operating stock amount for 38 weekends (line "38W" in the column "Inventory plan 2"), planned purchase amount ("planned purchase")
Column), based on the sales forecast amount (“Revision plan 2” column),
Calculate the inventory amount for 39 weekends (step S10)
4). In other words, if no new order is placed, the stock amount will be calculated in consideration of the stock of last weekend and the sales forecast of this week. The calculated inventory amount (52,838 thousand yen) is recorded in the "39W" row of the "Inventory plan 2" column.

Further, on the basis of this stock amount, the weekend stock amount is similarly calculated for 40 weeks or less. That is, the calculation is performed as “inventory plan 2” = “previous week inventory plan 2” + “purchase schedule” − “correction plan 2”.

Next, the appropriate inventory amount for each weekend (“inventory plan 1”) and the expected inventory amount (“inventory plan 2”),
Based on the estimated sales amount (“correction plan 2”), the purchase amount to be purchased for each week is calculated (step S10).
5). This is recorded in the "purchase plan" column. That is,
The calculation is performed as "purchase plan" = "stock plan 1 of this week"-"stock plan 2 of previous week" + "correction plan 2".

After the purchase amount to be purchased for each week is calculated in this way, the lead time is slid forward by the number of weeks (step S106). In this embodiment, since the lead time is “3 weeks”, the data in the “purchase plan” column is shifted 3 weeks ago and recorded as the data in the “ordering frame” column. In this way, in 39 weeks (this week), the amount to be ordered for one piece (5,310 thousand yen) can be obtained as the required order quantity.

Similar processing is performed for other items. The same applies to other brands.

The data thus calculated is printed out in the form of a table as shown in FIG. 16 and distributed to the brand manager (FIG. 8, step S2).
4). Note that this data may be transmitted online to the brand manager's computer (not shown). It may also be distributed by a medium such as a flexible disk.

The brand manager decides the order quantity of the commodities composing each item within the range of the ordering frame,
Input to the management computer 10. This ordering data is
It is given from the management computer 10 to the maker computer 3 via the host computer 6.

In addition, in this embodiment, the brand manager determines the order quantity of the commodities composing each item within the calculated order limit. But the CPU
According to 50, the order quantity of each product may be automatically determined according to the ordering frame according to a predetermined standard.

9. Other Embodiments (1) In the above embodiment, the order quota is calculated for each item, but sales forecast is made for each individual product, and the order quota is calculated for each individual product. Good.

(2) In the above embodiment, the unit of week is
I calculate sales forecasts, actual results, order quotas, etc.
It may be calculated in units of months, years, hours, and the like.

(3) In the above embodiment, the sales forecast, the actual result,
Although the processing is performed for the amount of money such as the ordering frame, the processing may be performed for the number of sheets or the like.

(4) In the above embodiment, the non-working inventory is not used as a basis for calculating the ordering frame, but the ordering frame is set based on all the stocks without distinguishing the non-working stock and the working stock. It may be calculated.

(5) In the above embodiment, the apparel product has been described, but it can be applied to other foods, daily necessities, and the like. It is also applicable to products that are traded between companies.

(6) In the above embodiment, when determining the order quantity, the order quantity is set so that the stock quantity at the start of the managed week becomes equal to the total sales forecast for the future expected stock weeks. Has been decided. However, the order quantity may be determined so as to have a predetermined relationship with the sales forecast for the expected number of stock weeks, for example, 50% or 75%.

(7) In the above embodiment, as the lead time period, the lead time in the case where the production is performed and the product is delivered after the order is placed is used. However, the present invention can also be applied to products that have been manufactured in advance, with the lead time period being the period from placing an order to delivering the product.

[Brief description of drawings]

FIG. 1 is a diagram showing an entire system.

FIG. 2 is a diagram showing an outline of a business model.

FIG. 3 is a diagram showing a hardware configuration of a host computer.

FIG. 4 is a diagram showing a data totaling process.

FIG. 5 is a diagram showing sales / inventory data.

FIG. 6 is a diagram showing sales / inventory data.

FIG. 7 is a diagram showing a hardware configuration of a management computer.

FIG. 8 is a diagram showing a flowchart of a sales forecast / order quantity calculation process.

FIG. 9 is a diagram showing a setting screen.

FIG. 10 is a diagram showing a flowchart of a process of creating an initial sales plan.

FIG. 11 is a diagram showing initial sales plan data.

FIG. 12 is a diagram showing a flowchart of sales forecast processing.

FIG. 13 is a diagram showing sales forecast data.

FIG. 14 is a diagram showing a flowchart of required order quantity calculation processing.

FIG. 15 is a diagram showing a flowchart of required order quantity calculation processing.

FIG. 16 is a diagram showing required order quantity data.

FIG. 17 is a diagram illustrating a flowchart of determination basic data calculation processing.

FIG. 18 is a diagram showing judgment basic data.

FIG. 19 is a diagram showing a flowchart of determination processing.

FIG. 20 is a diagram showing a flowchart of determination processing.

FIG. 21 is a diagram showing a non-operation product list.

FIG. 22 is a diagram showing a concept of calculating a required order quantity.

[Explanation of symbols]

2 ... Logistics center computer 3 Maker computer 4 ... Store cashier 6 ... Host computer 8 ... Database server 10 ... Management computer

Claims (9)

[Claims] 1. A management system for managing an order quantity, comprising a sales terminal device for accumulating and selling transaction results of a transaction target and an order management device, and accumulating and storing receipt results for a transaction object to the order management device. When the lead-time period is the period from the ordering of the target product to the arrival of the target product, the management target is at least the lead time period ahead of the current time, and the actual sales volume of the transaction target, the actual receipt volume, Based on the planned storage amount and the forecasted sales amount, the estimated inventory amount at the future management target time corresponds to the total forecasted sales amount from the relevant management target time point to the future of the inventory quantity determination period. Order management, which includes an order management device that generates management data that manages the current order quantity that should be received in the store, and sends the management data to the sales terminal device. Stem. 2. An order management device for managing an order quantity, wherein when the period from the ordering of the target product to the arrival of the product is a lead time period, at least the lead time period ahead of the current time point is the management target time point. Based on the actual sales volume, the actual storage volume, the planned storage volume, and the sales forecast volume of the transaction target, the estimated inventory amount at the future management target time is the sales forecast from the management target time point to the inventory amount determination period ahead. An order management apparatus that manages the current order quantity that should be received at the management target time so as to correspond to the total quantity. 3. An order management program for managing an order quantity using a computer, wherein the lead time period is at least the lead time period ahead when the period from the ordering of the target product to the arrival is the lead time period. Based on the actual sales volume, actual storage volume, planned storage volume, and forecast sales volume of the transaction target, the estimated inventory volume at the future management point is the inventory volume determination period ahead of the relevant management point. A program that causes a computer to perform processing for managing the current order quantity that should be received at the time of the management target so as to correspond to the total sales forecast quantity up to. 4. A recording medium on which the program according to claim 3 is recorded. 5. The system, device, program or recording medium according to any one of claims 1 to 4, wherein a future sales forecast amount is corrected or calculated based on a comparison between the sales forecast amount up to the present time and the actual sales amount. , Characterized by managing the current order quantity based on the new sales forecast quantity. 6. The system, apparatus, program or recording medium according to claim 1, wherein the order quantity is managed so that the expected stock quantity is equal to the total of the predicted sales quantity up to the inventory decision period destination. What is characterized by: 7. The system, apparatus, program or recording medium according to any one of claims 1 to 6, wherein the management of the ordered quantity is to calculate and output an upper limit quantity that can be ordered. thing. 8. The system, apparatus, program or recording medium according to claim 1, excluding the stock quantity of products for which future sales are not expected,
It is characterized by calculating the expected inventory of all target products. 9. An order management method for managing an order quantity using a computer, wherein the lead time period is at least the lead time period ahead when the period from the ordering of the target product to the arrival is the lead time period. Based on the actual sales volume, actual storage volume, planned storage volume, and forecast sales volume of the transaction target, the estimated inventory volume at the future management point is the inventory volume determination period ahead of the relevant management point. The order management method is characterized by generating management data for managing the current ordered quantity to be received at the time of the management so as to correspond to the total sales forecast quantity up to.