JP4139410B2 - An ordering instruction system that indicates the optimal stock quantity / order quantity - Google Patents

Description

  The present invention particularly relates to an ordering instruction system for instructing an optimal stock quantity / order quantity.

  In the retail industry, the business form is generally composed of a product center that sends merchandise such as headquarters to each store and a plurality of sales stores that sell merchandise to customers. We cannot escape from problems such as the existence of uneven inventory and the occurrence of shortages. Although it is possible to reduce the stockout rate by increasing the amount of inventory, problems such as increased inventory risk and the occurrence of uneven inventory are unavoidable. On the other hand, if the inventory quantity is reduced to reduce inventory risk, the problem of an increase in the stockout rate is inevitable. Inventory management methods and order quantity instruction methods are very difficult to meet customer needs without losing sales opportunities and minimizing the risk of holding inventory, and are based on heuristics in the retail industry. There are many cases. For this reason, the labor required for managing the inventory quantity, such as management of past sales results, formulation of a sales strategy, and order quantity instruction, was enormous. In particular, it has been very difficult to manage the optimal inventory quantity under conditions such as many types of merchandise and short merchandise life. The labor burden allocated to manage such optimal inventory is large and has been an issue in improving the efficiency of operations.

Conventionally, a store inventory management system should be owned by a store in accordance with the invention described in Patent Document 1, which is an apparatus for instructing an order quantity by statistical processing from a past order quantity, or according to a shipping cycle divided into predetermined time units. The invention described in Patent Document 2, which is a system in which the stock quantity is changed, has been proposed.
JP 9-259192 A JP 2004-1985

  In the invention described in Patent Document 1, the past order quantity is statistically processed, and the order quantity of the product is calculated by multiplying the basic order quantity by the coefficient for each day of the week and the coefficient for each date. However, the order quantity determination device according to the present invention is limited to the day of the week or the date in the statistical processing using the past order quantity, and only supports fluctuations in the day of the week or the date within the month. There was a problem that it was not possible.

  In the invention described in Patent Document 2, the store inventory amount is optimally maintained by changing the reference inventory amount, which is the inventory amount that the store should have, according to the shipment cycle of the merchandise. However, in the store inventory management system according to the present invention, the maximum sales performance prediction is made from the past sales performance and the reference stock quantity is determined from the shipping cycle. There is a problem in that it is not possible to deal with special demands that may occur due to variable factors, causing shortages.

  The present invention has been made in view of such a situation, and an object thereof is to provide an ordering instruction system for instructing an optimal stock quantity / order quantity that can solve the above-described problems.

In order to solve the above problems, the present invention has the following configuration.
The gist of the invention described in claim 1 is that the sales performance information in which the sales performance of the product in each store is recorded, the warehouse inventory performance information in which the warehouse stock status of the product in the product center is recorded, and the product in each store Inventory / sales performance data acquisition means to which inventory / sales performance data including at least distribution inventory performance information in which the inventory status is recorded is input , and sales of the average value of sales volume over a certain period in the past. And a replenishment constant that is a factor of how much fluctuation the sway width σ, which is the standard deviation of the sales volume, is set as the replenishment range. And a replenishment amount calculating means for calculating an upper limit value by multiplying the addition result by a physical distribution structure factor which is a period until the next ordered product arrives without ordering the addition result, and a fixed period in the past Sales volume The value obtained by multiplying the average value by the campaign coefficient, which is a coefficient of how many times sales can be expected, and the fluctuation width σ, which is the standard deviation of the sales volume, And a value obtained by multiplying a replenishment constant that is a coefficient for determining the replenishment range, and multiplying the addition result by the period until ordering to calculate the predicted sales amount until the ordering, and from the inventory amount of the store stock of the and the inventory amount calculation means for calculating the amount of inventory of the store, Keru you said to each store, the store at the ordering time and the upper limit value before ordering in order time by subtracting the predicted sales volume of up to the order a order instruction means that to calculate the order recommended amount is the difference between the amount, calculates the order recommended amount using the replenishment constant set in advance, the said order the recommended amount of total in each of the store products Compared with the center inventory, the total is the product center. A recommended order quantity adjusting means for subtracting the replenishment constant and recalculating the recommended order quantity until the total is less than or equal to the inventory quantity of the merchandise center. It exists in the ordering instruction | indication system which instruct | indicates the optimal optimal stock quantity / order quantity.
The gist of the invention described in claim 2 is that the sales performance information in which the sales performance of the product in each store is recorded, the warehouse inventory information in which the warehouse stock status of the product in the product center is recorded, and the product in each store Inventory / sales result data acquisition means to which inventory / sales result data including at least distribution inventory result information in which the stock status is recorded are input, and products ordered on the next order date closest to each store arrive at the store The predicted sales volume is calculated based on the sales volume prediction formula using statistical theory based on the sales performance information so that the product does not run out until the next arrival date, and the lower limit of the product volume to be deployed at each store A deployment level determining means for which a value is calculated, and a deployment upper limit determining means for calculating an upper limit value of a product quantity to be deployed in each store based on a replenishment amount determination formula using statistical theory from the lower limit value; A value obtained by multiplying the campaign coefficient is many times coefficient or expected sales of the average value to the average value of the sales volume of the past predetermined period, the deflection width σ width touched is the standard deviation of the sales volume σ A value obtained by multiplying a replenishment constant that is a coefficient of how many times the fluctuation is set as a replenishment range is added, and the predicted sales amount until the order is calculated by multiplying the addition result by a period until the order, Inventory quantity calculating means for subtracting the predicted sales quantity from the store inventory to the ordering to calculate the inventory quantity of the store at the time of ordering, and at each store, the lower limit value at the time of ordering and the lower limit before ordering When the stock quantity of the store is compared and the stock quantity falls below the lower limit value, an order is issued on the next order date, and the upper limit value and the store date at the time of ordering are ordered on the next order date . and the order instruction means for ordering the recommended amount which is the difference between the amount of inventory is calculated The sales volume prediction formula includes a distribution structure coefficient γ that is the minimum required number of days until the arrival date when the product ordered on the next ordering date arrives when the order is not placed on the next ordering date, and the past The actual value μ, which is an average sales amount obtained by dividing the cumulative sales performance for a certain period by a predetermined period, and the standard deviation calculated from the sales performance, the actual value μ, and the predetermined period for the past certain period. The fluctuation width σ as a certain sales fluctuation amount, the campaign coefficient α corresponding to how many times the sales value μ is expected according to the sales strategy, inventory status, campaign, etc., and the fluctuation of the sales amount The replenishment amount determination formula is expressed by Formula 1 including a variation correspondence coefficient β corresponding to the size, and the replenishment amount determination formula is the arrival date on which the product ordered on the next order date arrives when the order is not placed on the next order date. Minimum number of days until Logistics structure coefficient γ as the required number of days, actual value μ that is an average sales amount obtained by dividing the cumulative total of the sales performance in a past fixed period by a predetermined period, the sales performance in the past fixed period, the actual value μ, and the Corresponding to the fluctuation width σ as a sales fluctuation amount, which is a standard deviation calculated from a predetermined period, and how many times the sales amount μ is expected according to the sales strategy, inventory status, campaign, etc. Optimal inventory, which is expressed by Formula 2 using a campaign coefficient α and a replenishment constant A that indicates how much inventory is to be deployed, and the coefficient of the deflection width σ does not depend on each product. It exists in an ordering instruction system that indicates quantity / ordering quantity .
The gist of the invention described in claim 3 resides in the ordering instruction system for instructing the optimum stock quantity / order quantity according to claim 1 or 2 , wherein the coefficient of the deflection width σ is 0 to 2.5 .
The gist of the invention described in claim 4 resides in the ordering instruction system for instructing the optimal stock quantity / order quantity according to claim 1 or 2 , wherein the coefficient of the deflection width σ is 2.5 .
The gist of the invention described in claim 5 is that the sales performance information input to the sales performance data acquisition means is less than a certain period in the past, or the sales performance information in a special situation such as a large sales performance. In the case where an abnormal value is included in the sales performance information, the abnormal value is excluded from the calculation of the predicted sales amount and the calculation of the recommended order amount. The order instructing system for instructing the optimum stock quantity / order quantity according to any one of claims 1 to 4 .
The gist of the invention described in claim 6 is that an order message order quantity indicating means for sending an instruction message and instruction data for instructing a recommended order quantity on the next order date to the information terminal of each store, and sales of the store Depending on the strategy, inventory status, campaign, etc., one or more of the logistics structure coefficient γ, the campaign coefficient α, and the variation correspondence coefficient β constituting the instruction data are adjusted to request an order for the store. Order request reply means for generating the data and sending the generated order request data to the logistics server, the required amount calculated by receiving and totaling the order request data from each store, and the warehouse When the required quantity exceeds the available warehouse inventory, the order request data is configured when the inventory quantity is compared with the available warehouse inventory that can handle the current order. Subtract at least one or more of the physical distribution structure coefficient γ, the campaign coefficient α, and the variation correspondence coefficient β, and recalculate the necessary amount to be less than or equal to the available warehouse inventory amount. 6. The optimal stock quantity / order quantity according to any one of claims 1 to 5, further comprising order quantity determination means for determining the current order quantity of each store and allocating inventory. Exists in the ordering instruction system.
The gist of the invention of claim 7 is that the credit amount data which is the transaction limit amount of each store or an agent that collects each store is referred to for the current order amount determined by the order amount determination means, 7. The optimal inventory quantity / order quantity according to claim 6 , further comprising credit management means for comparing the wholesale total amount generated in each store or the agency according to the order quantity with the transaction limit. It exists in an ordering instruction system for instructing .

  The ordering instruction system for instructing the optimal stock quantity / order quantity of the present invention statistically manages the risk of missing parts due to sudden fluctuations in demand, and the occurrence probability of missing parts while optimally managing the inventory quantity. Can be minimized. In the optimum inventory quantity management method of the present invention, the labor required for inventory quantity management and order quantity instruction can be greatly reduced as compared with the conventional technique. Accordingly, the present invention has significant effects such as reduction of inventory, reduction of the shortage rate, reduction of partial inventory, and improvement of business efficiency for all retail businesses that handle products that need to be stocked at a plurality of bases.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a schematic diagram of an ordering instruction system according to this embodiment. The ordering instruction system 100 for instructing the optimal inventory quantity / ordering quantity of the present embodiment includes inventory / sales result data acquisition means 101, deployment level determination means 102, deployment upper limit determination means 103, and order instruction means 104. Furthermore, an abnormal value excluding unit 105, an order recommendation amount adjusting unit 106, an order date order amount instruction unit 107, an order request reply unit 108, an order amount determining unit 109, and a credit management unit 110 may be provided.

     The flow of processing in the ordering instruction system 100 for instructing the optimum stock quantity / order quantity of the present embodiment will be described. First, in the ordering instruction system 100, information serving as basic data for calculating the optimum stock quantity and the order quantity is read by the stock / sales performance data acquisition unit 101. The stock / sales performance data acquisition unit 101 may be implemented as a program on hardware including a CPU, a memory, a storage medium, and the like for operating the ordering instruction system 100. The information read here includes sales performance information in which the sales performance of products at each store is recorded, warehouse inventory performance information in which the warehouse status of products at the product center is recorded, and product inventory status at each store. At least distribution inventory performance information. In addition to each information, the read information includes other data representing the distribution of products in each store, product center, and warehouse, and constitutes inventory / sales performance data as a whole. The actual data is read into the ordering instruction system 100 by the inventory / sales actual data acquisition means 101. This stock / sales performance data is read from stock / sales performance data stored in a storage server, a storage device, or a readable storage medium connected directly or via a network with the ordering instruction system 100. / Sales result data acquisition means 101 accesses and reads data. Even if the stock / sales result data is copied and stored in an appropriate location in the storage device of the order instruction system 100, the order instruction system 100 refers to it from the storage location of the stock / sales result data described above. Anyway. This series of processing is preferably performed automatically, but may be performed by receiving an appropriate instruction and operation by the operator of the ordering instruction system 100, instead of being completely automated.

  The sales performance information is information on the sales performance of products at each store, and is a summary of the sales performance of products at each store over a certain period such as daily, weekly, or monthly. An example of sales performance information data is shown in Table 1 below. The sales record information data can be read by the inventory / sales record data acquisition unit 101, and can be calculated by each unit included in the ordering instruction system 100. There is no.

  As for the sales performance information, there are cases where data exists only for a short period of time that is less than the ordering instruction system 100 refers to, or the sales performance may include sales performance in a special situation such as large sales performance. Since it is not preferable to use the data including the sales results in such a special situation for the calculation of the predicted sales amount, which will be described later, such data that can be called an abnormal value of the sales results is provided in the ordering instruction system 100. It is preferable that the abnormal value excluding unit 105 is configured so as to exclude it from being used for calculation of the predicted sales amount and the recommended order quantity. The abnormal value excluding unit 105 may be implemented as a program on any hardware constituting the ordering instruction system 100. As a specific method for determining the abnormal value, refer to the sales performance information that is the original data, and then refer to the average value and the standard deviation when the above-mentioned summation for a certain period is performed. Sales results that deviate significantly from the market, such as data with an average value of ± 3σ or more, may be excluded so that they are not used in the calculation of the predicted sales volume or recommended order volume.

  Warehouse inventory record information is the record of the warehouse inventory status of products in the product center, and is a summary of the inventory results of products in the warehouse over a certain period such as daily, weekly, or monthly. . An example of sales performance information data is shown in Table 2 below. As with the sales performance information, the warehouse inventory performance information data can be read by the inventory / sales performance data acquisition means 101 and can be calculated by each means provided in the ordering instruction system 100 thereafter. For example, there is no restriction on the data format.

  In addition, the distribution inventory record information is a record of the inventory status of goods at each store, and is a summary of the inventory results of products at each store over a certain period of time such as daily, weekly, or monthly. An example of distribution inventory record information data is shown in Table 3 below. Similarly to the sales record information, the distribution inventory record information data can be read by the inventory / sales record data acquisition unit 101 and can be calculated by each unit included in the ordering instruction system 100 thereafter. For example, there is no restriction on the data format.

  Based on the inventory / sales results data read by these inventory / sales results data acquisition means 101, the optimal inventory quantity for each product in each store is determined using statistical theory so that neither shortage nor excess inventory occurs. The recommended order quantity is calculated based on this value. A description of the calculation of the recommended order quantity is shown in FIG. 2 and will be described in detail below.

First, the lower limit value of the product quantity to be deployed at each store is calculated. This lower limit value is calculated by the deployment level determination means 102 provided in the ordering instruction system 100. This deployment level determination means 102 only needs to be implemented as a program in the ordering instruction system 100, and calculates the lower limit value with reference to the above-mentioned inventory / sales performance data. This lower limit is calculated at each store so that there is no stock out of the product at the store until the next arrival date when the product ordered on the next order date closest to that day arrives. The lower limit of the quantity is calculated.
For each product in each store, the sales volume for a certain period in the past is calculated from the read inventory / sales performance data. The past fixed period is a period for calculating the sales performance that can be used as a reference for predicting the sales volume of products after the date when the lower limit is calculated, and it may be a fixed period from the day before that day, Further, it may be a period considering a cycle such as a certain period including the day before the quarter or one year ago. Further, the past fixed period does not need to be in units of one day, and may be, for example, tabulation in week units, year units, or tabulation for a short time in one hour units. About this past fixed period, it is preferable that an optimal period is selected according to the property of goods.
Here, the predicted sales volume after the day is calculated by the normal distribution theory which is a statistical theory. In the present embodiment, as an example, prediction of sales volume when the calculation unit of inventory is a daily unit will be described. The forecasted sales volume for the day after the current day is given by the following formula, where μ is the average value of sales volume per week in the above-mentioned fixed period and σ is the standard deviation of sales volume per week in the past fixed period. Indicated by 5.

Each variable in Equation 5 has the following meaning.
First, α is a campaign coefficient. In other words, this is a coefficient indicating how many times the average sales volume μ can be expected to be sold, and this coefficient is set as appropriate according to the sales strategy, inventory status, and the like. In addition, the setting of α can be optimized by comparing the prediction based on the ordering instruction method for instructing the optimal stock quantity / ordering quantity according to the present embodiment with the actual results obtained thereafter and the data history.

  Β is a variation correspondence coefficient. In other words, the actual sales volume is centered on μ and has a variation of the standard deviation σ, but as a prediction of this actual sales volume, the fluctuation of how many times the standard deviation σ corresponds as the prediction range The index is expressed by β. For example, by taking a large value of β, it is possible to cope with a case where the actual sales volume greatly fluctuates from the predicted sales volume. On the other hand, increasing this β means that the deployment level described later, that is, the lower limit of the amount of products deployed at each store is increased, so the stockout rate decreases but the occurrence rate of excess inventory also increases. . Therefore, it is preferable to optimize the setting of β by verifying the inventory level and the shortage rate.

  Γ is a physical distribution structure coefficient. This γ indicates the number of days that each store has to endure only with the product currently in the store when the store does not place an order once on the order date when the product is ordered and a replenishment request is made. In other words, this indicates the number of days that each store must be able to withstand at least this number of days only with the amount of merchandise in the store, that is, the sale must be continued without causing a shortage. Therefore, the setting of γ can also be improved by improving the entire physical distribution system, that is, shortening the number of product shipping days or increasing the frequency of order dates.

  By setting each coefficient to an appropriate value with reference to the target logistics system to which the ordering instruction system 100 of this embodiment is applied, and substituting μ and σ calculated from the sales performance of a certain period in the past. The lower limit value of the product quantity is calculated that each product of each store should always be deployed at least as much as possible.

Next, the upper limit value of the product amount to be deployed at each store is calculated. This upper limit value is calculated by the deployment upper limit determining means 103 provided in the ordering instruction system 100. This deployment upper limit determining means 103 may also be installed in the ordering instruction system 100 as a program. This upper limit value is also calculated with reference to the above-described inventory / sales performance data. The following formula 6 is a calculation formula for calculating the upper limit value. In calculating the upper limit value, the upper limit value of the inventory amount is calculated by the logic of how much σ of the predicted sales amount is expected for each product in each store. In other words, the daily sales volume predicted from the past sales performance is expressed by (μ ± σ) using the normal distribution theory, but if improved by adding the above-mentioned coefficient (αμ ± βσ) It is expressed. However, with this value, when the actual sales volume greatly exceeds the prediction, that is, when the portion corresponding to β in the actual sales volume exceeds the prediction, it is not possible to cope with the shortage. Therefore, the upper limit deployment amount of each product at each store is determined using a predetermined variable A that is larger than β set when the lower limit value is calculated. That is, it is determined how many times σ (= αμ + Aσ) should be arranged so as not to be out of stock. Therefore, the calculation formula of the upper limit value is as shown in the following formula 6. As is clear from the above, the replenishment constant A can also be reduced by setting a large value (= thickly arranged), while at the same time increasing the surplus inventory rate. Therefore, as with each coefficient in the lower limit value, it is preferable that the value of A is optimized from the sales strategy and the record of occurrence of missing items.

Thus, after the deployment lower limit value and the upper limit value of each product in each store are calculated, the stock amount of the store at that time is compared with the calculated lower limit value before each store is ordered. If the store inventory is below the lower limit at this point, the system recommends placing an order for this product on that order date. Here, the recommendation by the system means that an instruction message for recommending an order from each order instruction system 100 to each store is transmitted. More specifically, for example, an order message is sent to the information terminal of each store by means of order date order quantity instruction means 107 by means such as e-mail or FAX. Instruction data indicating the recommended order quantity is added to such an instruction message, and each store can place an order with an optimum order quantity by referring to the instruction message. Here, the recommended order quantity is represented by a difference between the above-described upper limit value of each product of each store and the stock quantity of the product at the time of ordering.
The recommended order quantity data is created for each store by the order instruction means 104 provided in the order instruction system 100, and is automatically transmitted as a message such as an e-mail to the information terminal of each store. Specifically, the order instruction unit 104 may be implemented as a program in a distribution center server of a product center included in the order instruction system 100 or an information terminal of a branch that supervises each store. The program installed in the main server may be referred to from the distribution center server of the product center or the information terminal of the branch. The specific operation of the ordering instruction unit 104 will be described below. In this embodiment, the ordering instruction unit 104 is implemented as a recommended list creation tool, and a logistics person in charge at a branch office operates this tool to create recommended order quantity data and send it to each store. Assumes that. First, in this tool, a special order that is an order not using the order instruction system 100 and an order as needed are dealt with. FIG. 3 is a display screen of the inventory status sheet of this tool. On this screen, the inventory status of the product center is confirmed, and it is confirmed whether the product can handle special orders and occasional orders. From each store, the order data of the special order and the occasional order are transmitted in the form of e-mail attachment, and the order data is read into the order instruction means 104. For this reason, for products with special orders and occasional orders from each store, as shown in FIG. 3, a display such as “replenishment target” is displayed on the screen so that the person in charge can easily determine the target product. Yes. After checking the stock status on this screen, a special order and an order as needed are confirmed by pressing an order confirmation button for each order on the screen as shown in FIG. The special order and the occasional order here are incorporated in the credit calculation described later, but are preferably handled separately from the recommended order quantity described later. By this tool, the lower limit value calculated by the above-described deployment level determination means 102, the upper limit value of the product quantity of each store calculated by the deployment upper limit determination means 103, and the inventory / sales result data of each store are read. The order instructing means 104 calculates the difference between the number of stocks and the upper limit value for products whose store inventory is below the lower limit before placing an order for each store, and uses this list data for each store as recommended order quantity data. It transmits to the information terminal of each store. Here, the recommended order quantity for each store is summed up, and the warehouse inventory performance information is referred to. If this sum exceeds the stock quantity that can be accommodated for the current order at the merchandise center, By adjusting the α, β, and A values set for the product, the recommended order quantity will be recalculated by reducing the above lower and upper limits, and this total will be included in the warehouse inventory range. It is preferable that recommended order quantity adjusting means is provided. The recommended order quantity adjustment means may be implemented on any hardware constituting the order instruction system 100 in the form of a program. The transmission of the recommended order quantity data generated in this way is any medium that can transmit data describing the recommended order product and the recommended order quantity, such as e-mail, FAX, and mail attachment data. There may be. The recommended order quantity data transmitted to each store corresponds to an instruction message and instruction data.

  In response to this instruction message and instruction data, order request data, which indicates how many products are ordered on the order date at each store, is created at each store. The creation of the order request data is performed by an order request reply means provided in the order instruction system 100. This order request replying means may be implemented as a program in the information terminal of each store, and the program is a server that stores the distribution order server of the merchandise center or the ordering instruction system 100 as a whole, for example. Etc., and may be configured to be referred to from the information terminal of each store.

  In the present embodiment, the order request data is created by a tool provided in the information terminal of each store. This tool first displays a screen as shown in FIG. On the screen of this record data import tool, sales record information, warehouse inventory record information, distribution inventory record information, credit data described later, and the like are read into a program that is a tool.

Next, the lower limit value, the upper limit value, and the replenishment amount, that is, the order amount at each store are calculated using this tool. Here, a screen as shown in FIG. 6 is displayed on the information terminal of each store. On this screen, the recommended order quantity is calculated from the numerical values of α, β, and A previously set for each product in the store and the inventory / sales performance data read by the tool by pressing the button for reserve inventory in warehouse. The required amount is displayed on the screen. The meaning of each numerical value on the screen of FIG. 6 will be described.
Here, the number of usable items indicates the amount that can be used for the current order in the warehouse inventory, and the amount of products that can be shipped from the warehouse, that is, the product center to each store, for each product.
The required number indicates the amount of products necessary for the current order when each product is deployed at the deployment level set on this screen. Therefore, if this required number exceeds the available number for a certain product, it indicates that an order cannot be made at that time. This determination is performed by the determination flag shown in FIG. This determination flag is displayed as 0 when the required number exceeds the available number, and 1 when the required number is less than the available number, so that the user of this tool can easily determine these in the order quantity. Judgment can be made.
The setting σ in FIG. 6 is the replenishment constant A described above. Further, the weighting coefficient is the campaign coefficient α described above. The set delivery frequency is the above-described physical distribution structure coefficient γ. The ability value is an average sales amount μ calculated from sales performance information, and in the present embodiment, indicates how much the product can be sold on average per week. The current remaining number indicates the remaining amount remaining in the product center when the maximum amount (= only the amount required by each store) is shipped from the product center as a warehouse. The remaining days indicate the number of inventory days when the product center performs shipment for the current order quantity. If this value is large, it indicates that there is sufficient warehouse inventory. It is shown that. The status is the margin of the warehouse inventory determined from various conditions such as the actual value, the remaining number of days and the remaining days, and this status display allows the user of this tool to easily grasp the warehouse inventory status. It has become.
The number of unrefillable items indicates the total amount of products that cannot be refilled with the contents of the current ordering by comparing the available number and the required number. Therefore, as will be described later, the user of this tool changes the settings for each product to adjust the order quantity so that the replenishment number becomes 0, and creates order request data.

  The user of this tool creates the order request data that is the current order quantity by changing the settings of the replenishment constant A, the campaign coefficient α, the fluctuation response coefficient β, and the logistics structure coefficient γ while referring to this screen. It will be. A specific method for adjusting each value will be described. As described above, the user of this tool adjusts each value for a product whose determination flag is 0 on the screen of FIG. 6, that is, a product whose required quantity as the current order quantity exceeds the available number of warehouse stock. By doing so, the required number of orders is reduced, and the current order quantity is determined. First, in the case of a low-stock product, the number of orders can be appropriately reduced by lowering the value of the distribution structure coefficient γ. Next, when the general required number is exceeded, the replenishment constant A is gradually decreased (lower limit value 0) and recalculation is performed, whereby the order quantity can be appropriately reduced. This is synonymous with reducing the amount of deployment. Further, the order quantity can be reduced appropriately by gradually reducing the campaign coefficient α (lower limit 0) and recalculating. Here, if both the replenishment constant A and the campaign coefficient α are set to 0, the necessary number becomes 0, so that the current order can be canceled. In addition, in this tool, by inputting a weighting coefficient (= campaign coefficient α) of −1 on this screen, for the store where the product is missing, the product is automatically reduced to the available number in the order of ability value. Can now be deployed (final deployment). With these adjustment methods, the current order quantity is adjusted so that the number of unfillable items becomes zero.

  The adjustment method as described above may be performed when the determination flag is not 0. In other words, a product with sufficient inventory in the warehouse can be ordered more than the amount recommended by the system depending on the situation of each store such as sales strategy and store inventory level. In this case, contrary to the adjustment method as described above, the order quantity can be increased this time by increasing the set values of the replenishment constant A, the campaign coefficient α, the variation correspondence coefficient β and the physical distribution structure coefficient γ.

  After performing the adjustment as described above, the recalculation is performed by the tool by pressing the recalculation button, and the result of the adjustment is displayed. Here, the final confirmation of the number that cannot be replenished is performed again by pressing the button to reflect the result of inventory allocation in FIG. 6, and a warning message is displayed if there is a product that cannot be replenished due to insufficient inventory. . If there is no problem in this process, the button for creating replenishment data in FIG. 6 is pressed to create order request data that is a list of the current order quantity of the store. Thereby, order request data is generated. At this time, a list of various achievements of the replenishment target product as shown in FIG. 7 is displayed on the right side of the screen of FIG. 6, and this list can be output to a printer or the like. . In each store, the order record and store inventory record can be managed by printing out and storing this list.

  As described above, the order request data transmitted from each store is transmitted to the logistics server. The logistics server may have a function of the main server of the ordering instruction system 100, or may be provided in the system separately from the main server. Here, the order request data transmitted from each store is tabulated by a tool as illustrated in FIG. For example, on the screen of FIG. 8, the order request data transmitted from each store is read and aggregated by pressing a data acquisition button. At this time, the required quantity that is the current order quantity of each product calculated from the aggregated result is compared with the available warehouse inventory quantity that is the quantity that can be handled for the current order out of the warehouse inventory quantity. Can exceed the available warehouse inventory quantity, it is also possible to use the tool as illustrated in FIG. 6 again so that the necessary quantity falls within the range of the available warehouse inventory quantity (order quantity determination means). . Then, after the current order is confirmed, by pressing the center total list output button on the screen of FIG. 8, the center total list for ordering shipment to the product center as a warehouse can be output as data. . The data of the output summary list for the center is transmitted to the distribution center server or information terminal of the product center, and the current ordering operation is completed.

  When the above-described order request data is aggregated, the credit data may be referred to for each store or for each agency that supervises each store. Credit data refers to the upper limit of the transaction amount set individually for each store or each agency. As described above, when ordering request data is created at each store and when the store data is aggregated, credit data for each store and each agency is also referred to as shown in FIG. Here, the credit management means 110 provided in the ordering instruction system 100 calculates and compares the upper limit of the amount of transaction that can be credited with the wholesale total amount generated in each store or each agency by the current ordering. In the case where a credit or excess store or agency occurs, the store or agency corresponding to the “credit surplus” column on the screen of FIG. 8 is displayed. Here, after selecting a store or an agent whose transaction is desired to be stopped, an order for the store can be excluded from the result of counting the current order by pressing an adjacent credit excess store addition button. Thereby, it is possible to prevent transactions exceeding the credit. In addition, for a store or agency where the transfer from the store has been confirmed and the excess credit has been eliminated, select the store or agency in the “After Confirmation of Transfer” window in the lower column, and By pressing the order stop release button, it is possible to change the count result so as not to exclude the order of the store. Then, in order to generate order confirmation data to be used for the credit management system for the current order finally confirmed, the order confirmation data output button in FIG. 8 may be pressed. As a result, order confirmation data is generated from the contents of the order confirmed this time.

  By introducing the ordering instruction system 100 of the present embodiment, various improvements are expected as compared with the ordering method in the conventional system. For example, in the conventional ordering method, the optimal inventory amount and the upper limit of inventory at each store are not clearly stated, and the portion that relies on the intuition of store managers is large. In such a case, it often happened that the sales opportunities were missed. By introducing the ordering instruction system 100 of this embodiment, the lower limit value and the upper limit value of the optimum stock quantity are clearly specified for each product in each store, and the prediction of how long the stock quantity will be sold. In addition to reducing the burden on store staff, benefits such as optimization of inventory levels and efficient use of sales opportunities can be expected. In addition, the merchandise center also has an advantage that the efficiency of operations can be improved because the inventory quantity that can be shipped and the order allocation quantity are confirmed and the order list is automatically generated. In addition, the credit management can be done by the system, which can save a lot of labor.

  The ordering instruction system for instructing the optimal stock quantity / order quantity of the present invention statistically manages the risk of missing parts due to sudden fluctuations in demand, and the occurrence probability of missing parts while optimally managing the inventory quantity. Can be minimized. In the optimum inventory quantity management method of the present invention, the labor required for inventory quantity management and order quantity instruction can be greatly reduced as compared with the conventional technique. Therefore, for retailers in general that handle products that need to have inventory at multiple locations, it has significant effects such as reducing inventory, reducing the shortage rate, reducing unbalanced inventory, and improving operational efficiency. As a result, it can greatly contribute to the improvement of sales because it improves satisfaction and reduces management risk.

Schematic diagram of an ordering instruction system in an embodiment of the present invention Explanatory drawing about calculation of the recommended order quantity in the embodiment of the present invention FIG. 3 is an exemplary diagram of a commodity center inventory status confirmation screen according to an embodiment of the present invention. FIG. 4 is a view showing an example of a confirmation screen for special orders and occasional orders in the embodiment of the present invention. FIG. 4 is an exemplary diagram of a result data import tool screen in the embodiment of the present invention. FIG. 4 is an exemplary diagram of an order request data creation tool screen in the embodiment of the present invention. FIG. 4 is a view showing an example of a list display screen of an order request data creation tool in an embodiment of the present invention. FIG. 3 is an exemplary diagram of an order request data totaling screen and a credit management tool screen in the embodiment of the present invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Order instruction | indication system which instruct | indicates optimal stock quantity / order quantity 101 Stock / sales performance data acquisition means 102 Deployment level determination means 103 Deployment upper limit determination means 104 Order instruction means 105 Abnormal value exclusion means 106 Order recommended quantity adjustment means 107 Order date ordering Quantity instruction means 108 Order request reply means 109 Order quantity confirmation means 110 Credit management means

Claims (7)

Sales performance information in which the sales performance of products at each store is recorded, warehouse inventory performance information in which the warehouse stock status of the products in the product center is recorded, and distribution inventory performance information in which the product stock status in each store is recorded Inventory / sales performance data acquisition means to which inventory / sales performance data including at least
A value obtained by multiplying the average value of the sales volume for a certain period in the past by a campaign coefficient, which is a factor of how many times sales can be expected, and the deflection width σ, which is the standard deviation of the sales volume, The distribution structure, which is the period from the addition of the replenishment constant, which is a coefficient of how many times the fluctuation is taken as the replenishment range, to the arrival of the next ordered product instead of the current order. Replenishment amount calculating means for calculating an upper limit value by multiplying by a coefficient;
A value obtained by multiplying the average value of the sales volume for a certain period in the past by a campaign coefficient, which is a factor of how many times sales can be expected, and the deflection width σ, which is the standard deviation of the sales volume, A value obtained by multiplying a replenishment constant that is a coefficient of how many times the fluctuation is set as a replenishment range is added, and the predicted sales amount until the order is calculated by multiplying the addition result by a period until the order, Stock quantity calculating means for subtracting the predicted sales quantity from the store inventory to the order and calculating the store inventory at the time of ordering;
Ordering instruction means for calculating a recommended ordering amount that is a difference between the upper limit value and the stock amount of the store at the time of ordering before each ordering in each store,
The recommended order quantity is calculated using the preset replenishment constant, the total recommended order quantity at each store is compared with the inventory quantity at the product center, and the total exceeds the inventory quantity at the product center. And the recommended stock quantity adjusting means for reducing the replenishment constant and recalculating the recommended order quantity until the total becomes equal to or less than the stock quantity of the merchandise center. / An ordering instruction system that indicates the order quantity. Sales performance information in which the sales performance of products at each store is recorded, warehouse inventory performance information in which the warehouse stock status of the products in the product center is recorded, and distribution inventory performance information in which the product stock status in each store is recorded Inventory / sales performance data acquisition means to which inventory / sales performance data including at least
Based on the sales volume prediction formula using statistical theory based on the sales performance information so that the product ordered at the next next order date of each store arrives at the store until the next arrival date. A predicted sales amount is calculated, and a deployment level determination means for calculating a lower limit value of the product amount to be deployed in each store,
A deployment upper limit determination means for calculating an upper limit value of the product quantity to be deployed in each store based on a replenishment amount determination formula using statistical theory from the lower limit value,
A value obtained by multiplying the average value of the sales volume for a certain period in the past by a campaign coefficient, which is a factor of how many times sales can be expected, and the deflection width σ, which is the standard deviation of the sales volume, A value obtained by multiplying a replenishment constant that is a coefficient of how many times the fluctuation is set as a replenishment range is added, and the predicted sales amount until the order is calculated by multiplying the addition result by a period until the order, Stock quantity calculating means for subtracting the predicted sales quantity from the store inventory to the order and calculating the store inventory at the time of ordering;
In each of the stores, before the ordering, the lower limit value and the inventory amount of the store at the time of ordering are compared, and when the inventory amount falls below the lower limit value, instructing the order on the next order date, Ordering instruction means for calculating a recommended order quantity which is a difference between the upper limit value and the inventory quantity of the store at the time of ordering on the next order date;
The sales volume prediction formula is:
In the case of not placing an order on the next order date, the distribution structure coefficient γ, which is the minimum required number of days until the arrival date on which the product ordered on the next order date arrives,
Ability value μ which is an average sales amount obtained by dividing the cumulative total of the sales results of a certain period in the past by a predetermined period,
A runout width σ as a sales fluctuation amount that is a standard deviation calculated from the sales performance in the past certain period, the ability value μ and the predetermined period;
Depending on the sales strategy, inventory status, campaign, etc., the campaign coefficient α corresponding to how many times the sales value μ is expected,
It is expressed by Equation 1 including a fluctuation correspondence coefficient β corresponding to the magnitude of fluctuation in sales volume,
The replenishment amount determination formula is:
In the case of not placing an order on the next order date, the distribution structure coefficient γ, which is the minimum required number of days until the arrival date on which the product ordered on the next order date arrives,
Ability value μ which is an average sales amount obtained by dividing the cumulative total of the sales results of a certain period in the past by a predetermined period,
A runout width σ as a sales fluctuation amount that is a standard deviation calculated from the sales performance in the past certain period, the ability value μ and the predetermined period;
Depending on the sales strategy, inventory status, campaign, etc., the campaign coefficient α corresponding to how many times the sales value μ is expected,
It is expressed by Formula 2 using the replenishment constant A that represents how thick the inventory is to be deployed, and
The ordering instruction system for instructing the optimum stock quantity / order quantity, wherein the coefficient of the deflection width σ does not depend on each product.
The ordering instruction system for instructing the optimal stock quantity / ordering quantity according to claim 1 or 2, wherein a coefficient of the deflection width σ is 0 to 2.5. 3. The ordering instruction system for instructing the optimum stock quantity / order quantity according to claim 1, wherein a coefficient of the deflection width σ is 2.5. The sales performance when the sales performance information input to the sales performance data acquisition means is less than a certain period in the past, or when the sales performance information includes sales performance in a special situation such as large sales performance. 5. The apparatus according to claim 1, further comprising: an abnormal value excluding unit that excludes the abnormal value from the calculation of the predicted sales amount and the calculation of the recommended order quantity when the information includes an abnormal value . An ordering instruction system for instructing the optimum stock quantity / ordering quantity according to item 1 . An order message order quantity instruction means for sending an instruction message and instruction data for instructing a recommended order quantity on the next order date to the information terminal of each store;
Depending on the sales strategy, inventory status, or campaign of the store, one or more of the physical distribution structure coefficient γ, the campaign coefficient α, and the variation correspondence coefficient β constituting the instruction data Order request reply means for generating order request data for a store and sending the generated order request data to a logistics server;
The required amount calculated by receiving and summing up the order request data from each store is compared with the available warehouse stock amount that can correspond to the current order out of the warehouse stock amount, and the required amount corresponds to the correspondence Subtracting at least one of the physical distribution structure coefficient γ, the campaign coefficient α, and the variation corresponding coefficient β constituting the order request data when the available warehouse inventory amount is exceeded, 1 through claim, characterized by comprising the order amount determination means, wherein the required amount adaptable warehouse the inventory and re-calculated to be the following order quantity of current each store is confirmed inventory provision is made 5. An ordering instruction system for instructing the optimum stock quantity / order quantity according to any one of 5 above. For the current order quantity determined by the order quantity determination means, credit data that is the transaction limit of each store or the agency that collects each store is referred to, and each store or the agency is determined according to the current order quantity. Credit management means for comparing the wholesale total amount occurring in the transaction amount with the transaction limit amount;
The order instruction system for instructing the optimum stock quantity / order quantity according to claim 6 .