JP2007026335A - Evaluation index forecast visualization method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To reduce a time spent for simulation by visualizing an evaluation index related to the stock management of SCM, and selecting a target stock needing SCM improvement measures. <P>SOLUTION: An ordering plan DB 302 stores an ordering plan about each period of each the target stock. A stock prediction DB 304 stores stock prediction data. An evaluation index forecast calculation processing part 70 by an ordering system recommendation plan calculates a forecast value of the evaluation index of each the target stock in reference to the data. A selection support processing part 80 extracts the target stock satisfying a given extraction condition, and displays the ordering plan. The selection support processing part 80 calculates and displays forecast values of the evaluation index about the plurality of ordering plans for simulating the ordering plan. The original ordering plan can be corrected by the ordering plan satisfying the plurality of target evaluation indexes. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to SCM (Supply Chain Management), which is a corporate activity from order receipt to shipment, and in particular, in order to support effective implementation of SCM, the estimated value of an evaluation index is visualized. The present invention relates to a technique for visualizing a change in an evaluation index by changing a condition related to SCM.

  In corporate activities, rapid reform of SCM (Supply Chain Management) is important from the perspective of optimizing the entire company in response to increasingly severe changes in the external environment. As a procedure for reform, companies set management target figures according to their corporate characteristics. In addition to grasping and analyzing the current SCM, we will formulate SCM reform measures to achieve the management target figures. In order to quickly determine this reform measure, it is necessary to efficiently visualize changes in evaluation indices with respect to changes in conditions.

  In addition, there exists a technique etc. which were described in patent document 1, for example as a thing relevant as this kind of technique.

JP 2000-129625 A

  It is possible to accumulate the performance of evaluation indexes related to SCM inventory management. However, since the prospects of the evaluation index regarding inventory management and the like are not visible, it is a fact that measures for improving the efficiency of SCM cannot be judged accurately or simulation takes time.

  As described above, the conventional technique cannot provide a prospect of an evaluation index related to inventory management. Therefore, as a result of implementing measures for SCM, there is a problem that the evaluation index related to inventory management cannot be quickly verified as compared with the target value and accurate SCM measures cannot be taken. It was.

  An object of the present invention is to provide a technique for visualizing an evaluation index related to inventory management and shortening the time required for simulation by selecting a target inventory that requires SCM improvement measures.

  The present invention refers to a storage means for storing an ordering proposal for each period of each target inventory and a storage means for storing inventory forecast data, and a plurality of evaluation indexes for a specific period of each target inventory. Calculate the expected value, extract the target inventory that satisfies the given extraction conditions, display the order proposal, and calculate the estimated value of the evaluation index for multiple order proposals that simulate the order proposal. It is characterized by an evaluation index prospect visualization technology that allows an original ordering plan to be modified by an ordering plan that satisfies a plurality of target evaluation indexes.

  According to the present invention, it is possible to immediately visualize the change in the evaluation index when the ordering plan for the target inventory item is changed. Further, according to the present invention, the target inventory can be narrowed down according to the extraction condition, and the time required for the simulation can be shortened.

  Hereinafter, an embodiment of the present invention will be described in detail using an SCM as an example with reference to the drawings.

  FIG. 1 is a block diagram illustrating a configuration example of an evaluation index line-of-sight visualization system according to an embodiment of the present invention. In FIG. 1, 10 is an input device, 20 is a display device, 30 is a processing device, 40 is a storage device, and 50 is an output device.

  60 is a performance display processing unit, 70 is an evaluation forecast calculation processing unit based on an ordering system recommended plan, 80 is a selection support processing unit for an order plan correction target product, and 90 is an evaluation index forecast calculation processing unit based on an order manual correction plan. . The processing device 30 includes a CPU and a memory. The processing units 60 to 90 are programs stored in the memory of the processing device 30 and executed by the CPU.

  100 is a demand performance system, 110 is a demand prediction system, 120 is an ordering system, 130 is an inventory system, and 140 is an inventory prediction system. The systems 100 to 140 are external systems connected to the present system. The visualization system stores data received from these external systems in a database (DB) of the storage device 40.

  300 is a demand performance database (DB), 301 is a demand prediction DB, 302 is an order proposal DB, 303 is an inventory performance DB, 304 is an inventory prediction DB, 305 is a product attribute master, 306 is an evaluation index performance value DB, and 307 is an order. The revision plan DB, 308 is an order system recommended plan evaluation index expected value DB, 309 is a required inventory amount DB, 310 is a required inventory amount change rate DB, 311 is an evaluation index change rate DB, and 312 is an evaluation for the required inventory amount change rate. The index change rate DB 313 is an extraction range parameter table, 314 is an extraction range setting table, 315 is an order plan correction target item DB, and 316 is an order manual correction plan evaluation index estimate value DB. These DBs and tables are stored in the storage device 40.

  FIG. 2 shows a performance display processing unit 60 included in the processing device 30, an evaluation forecast calculation processing unit 70 based on an ordering system recommended plan, a selection support processing unit 80 for an order plan correction target product, and an evaluation index view based on an ordering manual correction plan. It is a figure explaining the relationship between the serial calculation process part 90, each table accommodated in the memory | storage device 40, and each DB.

  In FIG. 2, the demand record system 100 is a system for registering and updating the demand record DB 300. The demand prediction system 110 is a system that registers and updates the demand prediction DB 301. The ordering system 120 is a system for registering and updating the order proposal DB 302. The ordering system registers and updates a database held by itself based on data stored in the order correction proposal DB 307. The inventory system 130 is a system for registering and updating the inventory performance DB 303. The inventory prediction system 140 is a system that registers and updates the inventory prediction DB 304.

  The performance display processing unit 60 inputs data of the demand performance DB 300, the demand prediction DB 301, and the inventory performance DB 303, calculates the evaluation index actual value and the necessary inventory quantity, and stores them in the evaluation index actual value DB 306 and the necessary inventory quantity DB 309, respectively. .

  The evaluation forecast calculation processing unit 70 inputs the data of the inventory prediction DB 304 and the order plan DB 302, calculates the order system recommended plan and the evaluation index forecast value, and orders order revision plan DB 307 and the order system recommended plan evaluation index forecast, respectively. Store in the value DB 308.

  The ordering plan correction target product selection support processing unit 80 inputs the data of the necessary inventory quantity DB 309 and the evaluation index actual value DB 306, refers to the extraction range parameter table 313 and the extraction range setting table 314, The evaluation index change rate is calculated and stored in the necessary inventory change rate DB 310 and the evaluation index change rate DB 311 respectively. Next, the ordering plan correction target product selection support processing unit 80 inputs the necessary inventory change rate DB 310 and the evaluation index change rate DB 311, calculates the evaluation index change rate with respect to the required inventory change rate, and calculates the required inventory change rate. Is stored in the evaluation index change rate DB 312. Next, the ordering plan correction target product selection support processing unit 80 inputs the evaluation index change rate DB 312 with respect to the required stock amount change rate and refers to the extraction range parameter table 313 and the extraction range setting table 314 as the extraction range condition. A matching target product and target month are determined and displayed on the display device 20 to prompt the user to correct the order proposal. When the order plan is modified, the order plan modification target product selection support processing unit 80 stores the data in the order plan modification target item DB 315.

  The evaluation index estimate calculation processing unit 90 based on the orderer manual correction plan inputs the order correction plan DB307, the ordering system recommended plan evaluation index estimate value DB308, and the order plan correction target item DB315, and inputs the orderer manual correction plan and the orderer manual correction plan. Are calculated and stored in the order correction plan DB 307 and the order manual correction plan evaluation index estimate value DB 316, respectively.

  FIG. 3 is a diagram illustrating a data configuration example of the demand performance DB 300. In the demand result DB 300, for each product, a product code column 501 for uniquely identifying the product, a manufacturer name column 502 corresponding to the product code, a quantity column 503 indicating the demand quantity of the product corresponding to the product code, and a product code A money amount column 504 indicating the demand amount of the product to be sold is provided. The quantity column 503 and the amount column 504 are provided in units of one month and are divided in units of one year (12 months). The values stored in the quantity column 503 and the monetary amount column 504 indicate the demand amount as an actual result, and the demand amount up to the previous month of the current month is stored. It is assumed that at least one year of data necessary for the following processing is stored in the demand result DB 300 (the same applies to other DBs). In addition, a part constituting the product may be used instead of the product (hereinafter, the same applies to all “products”).

  FIG. 4 is a diagram illustrating a data configuration example of the demand prediction DB 301. In the demand forecast DB 301, for each product, a product code column 511, a manufacturer name column 512 corresponding to the product code, a quantity column 513 indicating a demand forecast quantity of the product corresponding to the product code, and a demand forecast for the product corresponding to the product code An amount column 514 representing the amount is provided. The quantity column 513 and the amount column 514 are provided in units of one month, and are divided in units of one year (12 months). The values stored in the quantity column 513 and the money amount column 514 indicate the demand forecast amount. This demand forecast amount is estimated from the fluctuation trend of the demand amount in the demand record DB 300 indicating the demand amount as the record.

  FIG. 5 is a diagram illustrating a data configuration example of the order proposal DB 302. The order proposal DB 302 includes, for each product, a product code field 521, a manufacturer name field 522 corresponding to the product code, a quantity field 523 indicating the order quantity of the product corresponding to the product code, and the order amount of the product corresponding to the product code. A money amount column 524 is provided. The quantity column 523 and the amount column 524 are provided in units of one month and are divided in units of one year (12 months). The values stored in the quantity column 523 and the money amount column 524 indicate the order quantity as an order proposal. The order proposal DB 302 is estimated from the fluctuation trend of the demand amount in the demand result DB 300 indicating the demand amount as the result.

  FIG. 6 is a diagram illustrating a data configuration example of the inventory performance DB 303. In the stock record DB 303, for each product, a product code field 531, a manufacturer name field 532 corresponding to the product code, a quantity field 533 indicating the stock quantity of the product corresponding to the product code, and the stock amount of the product corresponding to the product code are displayed. A money amount column 534 is provided. The quantity column 533 and the amount column 534 are provided in units of one month, and are divided in units of one year (12 months). The values stored in the quantity column 533 and the money amount column 534 indicate the end-of-month stock amount as a result, and the stock amount up to the previous month of the current month is stored.

  FIG. 7 is a diagram illustrating a data configuration example of the inventory prediction DB 304. In the inventory prediction DB 304, for each product, a product code column 541, a manufacturer name column 542 corresponding to the product code, a quantity column 543 representing a stock forecast quantity of the product corresponding to the product code, and an inventory prediction of the product corresponding to the product code An amount column 544 representing an amount is provided. The quantity column 543 and the amount column 544 are provided in units of one month, and are divided in units of one year (12 months). The values stored in the quantity column 543 and the money amount column 544 indicate the inventory forecast amount at the end of each month. This predicted stock quantity is estimated from the fluctuation tendency of the stock quantity in the stock record DB 303 indicating the stock quantity as the record.

  FIG. 8 is a diagram illustrating a data configuration example of the product attribute master 305. The product attribute master 305 is provided with a product code column 551, a manufacturer name column 552 corresponding to the product code, and a product group column 553 corresponding to the product code for each product. The product group is the name or identifier of the product group to which the product belongs.

  FIG. 9 is a diagram illustrating a data configuration example and a data example of the evaluation index actual value DB 306. The evaluation index actual value DB 306 includes, for each product, a product code field 561, a manufacturer name field 562 corresponding to the product code, a percentage field 563 indicating an immediate delivery rate of the product corresponding to the product code, and an inventory of the product corresponding to the product code. An amount column 564 representing the amount of money, a month number column 565 representing the number of months of inventory of products corresponding to the product code, and an amount column 566 representing the monthly inventory of products corresponding to the product code are provided. The percentage column 563, the amount column 564, the month number column 565, and the amount column 566 are provided in units of one month, and are divided in units of one year (12 months). This evaluation index result value is a numerical value calculated from the demand result DB 300 indicating the demand amount as the result and the inventory result DB 303 indicating the stock amount as the result.

  The “immediate delivery rate”, “inventory amount”, “number of inventory months”, and “inventory monthly quotient” exemplified here are defined as follows.

  Immediate delivery rate: Indicates the average value of the quantity-based provision rate for each product.

  Inventory amount: A value obtained by multiplying the target product by a value obtained by multiplying the monthly average stock quantity for each product by the unit price. In addition, it is a value including non-moving goods that have no demand for one year.

  Number of months of inventory: A value obtained by averaging the number of months of inventory on a quantity basis by dividing the number of monthly average inventory for each product by the average number of demands for 6 months. The value excludes non-moving goods that have no demand for one year.

Monthly inventory: Indicates the value obtained by dividing the sum of the inventory amount by the sum of the average number of 6-month demand for each product multiplied by the unit price. In addition, it is a value including non-moving goods that have no demand for one year.

  Non-movable product: Indicates a product for which no demand has been recorded for the past 12 months.

  FIG. 10 is a diagram illustrating a data configuration example of the order correction plan DB 307. The order correction proposal DB 307 includes, for each product, a product code field 571, a manufacturer name field 572 corresponding to the product code, a quantity field 573 indicating the recommended ordering system quantity of the product corresponding to the product code, and a product corresponding to the product code. An amount field 574 that represents the recommended order amount for the ordering system, a quantity field 575 that represents the orderer's manual correction plan quantity for the product corresponding to the product code, and an amount field 575 that represents the orderer's manual correction plan amount for the product corresponding to the product code are provided. ing. The quantity column 573, the amount column 574, the quantity column 575, and the amount column 576 are provided in units of one month, and are divided in units of one year (12 months). The order correction proposal numerical value is extracted as a result of processing by the evaluation index prediction processing unit 70 based on the ordering system recommended proposal and as a result of processing by the evaluation index prediction calculation processing unit 80 based on the manual order correction plan. It is a numerical value. The database held by the ordering system is updated with the order correction proposal numerical value.

  FIG. 11 is a diagram illustrating a data configuration example of the ordering system recommended plan evaluation index estimated value DB 308. In the order system recommended plan evaluation index estimated value DB 308, for each product, a product code column 581, a manufacturer name column 582 corresponding to the product code, a percentage column 583 representing an immediate delivery rate of the product corresponding to the product code, and a product code An amount field 584 that represents the stock price of the corresponding product, a month field 585 that represents the number of months in stock of the product corresponding to the product code, and an amount field 586 that represents the monthly stock of products corresponding to the product code are provided. The percentage column 583, the amount column 584, the month number column 585, and the amount column 586 are provided in units of one month, and are divided in units of one year (12 months). The order system recommended plan evaluation index expected value is a numerical value calculated from the stock forecast DB 304 indicating the stock forecast amount and the order plan DB 302 indicating the order amount as the order plan.

  FIG. 12 is a diagram illustrating a data configuration example of the necessary inventory DB 309. As illustrated in FIG. The necessary inventory DB 309 is provided with a product code field 591, a manufacturer name field 592 corresponding to the product code, and a quantity field 593 representing an appropriate stock quantity of the product corresponding to the product code for each product. The quantity column 593 is provided in units of one month and is divided in units of one year (12 months). This necessary stock quantity is a numerical value calculated from the demand result DB 300 indicating the demand amount as the result.

  FIG. 13 is a diagram illustrating a data configuration example of the necessary inventory amount change rate DB 310. The required inventory amount change rate DB 310 includes, for each product, a product code column 601, a manufacturer name column 602 corresponding to the product code, and a percentage column 603 representing a required inventory amount change rate corresponding to the product code. The value stored in the percent column 603 indicates a necessary inventory amount change rate as a result. This required inventory quantity change rate is calculated from the required inventory quantity in the past and the order proposal target month.

  FIG. 14 is a diagram illustrating a data configuration example of the evaluation index change rate DB 311. In the evaluation index change rate DB 311, for each product, a product code column 611, a manufacturer name column 612 corresponding to the product code, a percentage column 613 representing an immediate delivery rate change rate of the product corresponding to the product code, and a product corresponding to the product code The percentage column 614 representing the inventory amount change rate of the product and the percent column 615 representing the rate of change in the number of months of the product corresponding to the product code are provided. This evaluation index change rate is a numerical value calculated from the evaluation indexes of the past and the order plan target month.

  FIG. 15 is a diagram illustrating a data configuration example of the evaluation index change rate DB 312 with respect to the required inventory amount change rate. The evaluation index change rate DB 312 for the required inventory change rate includes, for each product, a product code column 621, a manufacturer name column 622 corresponding to the product code, a percent column 623 indicating a rate of change in the immediate delivery rate of the product corresponding to the product code, A percentage column 624 representing the rate of change in the inventory amount of the product corresponding to the product code and a percentage column 625 representing the rate of change in the number of inventory months of the product corresponding to the product code are provided. The evaluation index change rate with respect to the required inventory change rate is a numerical value calculated from the required inventory change rate DB 310 and the evaluation index change rate DB 311.

  FIG. 16 is a diagram illustrating a data configuration example of the extraction range parameter table 313. The extraction range parameter table 313 is provided with a parameter definition column 631 and a parameter value column 632 defined as “a”, “b”, and “c”. The value stored in the parameter numerical value column 632 is an arbitrary numerical value corresponding to the parameter definition, and is a value that is changed while operating the system. This value is used as an extraction range for each product in the extraction range setting table 314 described later.

  FIG. 17 is a diagram illustrating a data configuration example of the extraction range setting table 314. In the extraction range setting table 314, the immediate delivery rate change rate with respect to the required stock amount change rate is set to X, and the range of the X value is set by an arbitrary numerical value of the parameter a, and the stock amount change rate with respect to the required stock amount change rate Y is a range in which the value of Y is set with an arbitrary numerical value of parameter b, and Z is the rate of change in the number of months of inventory with respect to the rate of change in required inventory, and the range of Z is set with an arbitrary numerical value of parameter c This is a table for determining “selected” or “not selected = ×” as the extraction range for each product.

  The illustrated extraction range setting table 314 includes an “X> a” column 641, an “X ≦ a” column 642, a “Y> b” column 643, a “Y ≦ b” column 644, and “Z> c”. Column 645 and “Z ≦ c” column 646.

  FIG. 18 is a diagram illustrating a data configuration example of the order plan correction target item DB 315. In the order plan amendment target item DB 315, for each product, a product code column 651, a manufacturer name column 652 corresponding to the product code, a quantity column 653 indicating an estimated order quantity of the product corresponding to the product code, and a product code are supported. An amount column 654 representing the estimated order amount of the product is provided. The quantity column 653 and the amount column 654 are provided in units of one month, and are divided in units of one year (12 months). The estimated order value stored in the order plan correction target item DB 315 is a numerical value extracted from the order correction plan DB 307. The product to be corrected in the order plan correction target item DB 315 is extracted as a result of the processing of the ordering plan correction target product selection support processing unit 80 described later in detail. Further, the target order month for order plan revision is indicated by a thick frame in the quantity column 653 and the amount column 654.

  When the product and the target month subject to order plan modification are picked up, the system performs a simulation to change the order plan before and after the original order plan and see the change in the evaluation index, and the result is displayed on the display device 20. Display on the screen. As will be described later, the user can modify the order proposal to achieve the target evaluation index.

  FIG. 19 is a diagram illustrating a data configuration example of the orderer manual correction plan evaluation index estimated value DB 316. In the orderer draft evaluation index estimated value DB 316, for each product, a product code column 661, a manufacturer name column 662 corresponding to the product code, a percentage column 663 indicating an immediate delivery rate of the product corresponding to the product code, and the product code are supported. There are provided an amount column 664 that represents the stock amount of the product to be sold, a month number column 665 that represents the number of months of stock of the product corresponding to the product code, and an amount column 666 that represents the monthly stock of the product corresponding to the product code. The percentage column 663, the amount column 664, the month number column 665, and the amount column 666 are provided in units of one month, and are divided in units of one year (12 months). The order manual revision plan evaluation index estimated value is a numerical value obtained by manually correcting the estimated value in the order system recommended plan evaluation index estimated value DB 308.

  FIG. 20 is a flowchart showing a processing procedure of evaluation index forecast calculation based on an order manual correction plan according to an embodiment of the present invention, which will be described next. The portions surrounded by the dotted lines in FIG. 20 are the processing by the performance display processing unit 60, the processing by the evaluation index prediction calculation processing unit 70 based on the system recommendation, and the selection support processing unit 80 for the order plan correction target product, respectively. The process by the evaluation index forecast calculation process part 90 by a process and an ordering person manual correction plan is shown. FIG. 21 is a flowchart for explaining the detailed procedure of the processing by the selection support processing unit 80 for the order plan correction target product.

  (1) First, the performance display processing unit 60 reads the demand performance DB 300, the demand prediction DB 301, and the inventory performance DB 303 (step 401).

  Information in the product code column 501, manufacturer name column 502, quantity column 503, and amount column 504 of the demand record DB 300 is updated when information is registered or changed by the demand information system 100. ing. In addition, each information in the product code column 511, the manufacturer name column 512, the quantity column 513, and the amount column 514 of the demand prediction DB 301 is updated when information is registered and information is changed by the demand prediction system 110. It has been broken. The demand forecast data is used in the calculation in step 404. In addition, each information in the product code column 531, the manufacturer name column 532, the quantity column 533, and the amount column 534 of the inventory record DB 303 is updated when information is registered or changed by the inventory system 130. ing.

  (2) Next, the result display processing unit 60 uses the data read in (1) to calculate and display the evaluation index actual value and the necessary inventory amount (step 402).

  The evaluation index actual value is obtained by Equation 1 to Equation 4.

Prompt delivery rate results = Average for each month (AVE) For each product
{(Demand Actual-B / O (Back Order) Actual) / Demand Actual} (Equation 1)
Inventory amount actual = Σ for each product for each product (monthly average of monthly inventory at the end of each month x unit price) (Equation 2)
Monthly inventory results = AVE each product for each month
{Σ (Monthly average value of each month's inventory) ÷ 6-month average demand} (Equation 3)
Monthly inventory sales results = Monthly {Σ Each product (Monthly average of the end-of-month inventory quantity x Unit price)}
÷ Σ for each product (6 month average demand × unit price) (Equation 4)
The necessary inventory amount is obtained by Equation 5.

Necessary inventory = Monthly average demand for the past year x (Lead time + Planning cycle)
+ Safety stock factor x √ (Lead time + Planning cycle)
× Monthly demand standard deviation for the past year (Formula 5)
In addition, B / O (back order) described in the formula of the actual delivery rate results indicates a case where the ordered product is out of stock. Data such as B / O results and unit prices are stored in a database (not shown).

  The safety stock coefficient is obtained from the following Table 1 on the assumption that “demand follows a normal distribution”.

  Further, the lead time and the planning cycle are arbitrary numerical values that differ depending on the product.

  The actual result display processing unit 60 updates the evaluation index actual value DB 306 and the necessary inventory amount DB 309 with the calculated evaluation index actual value and required inventory amount value, respectively.

  In the processing procedure of FIG. 20, calculation and processing are performed for each product, but processing may be performed for each manufacturer or each product group with reference to the product attribute master 305.

  (3) Next, the evaluation index forecast calculation processing unit 70 based on the ordering system recommended plan evaluates the actual value of the evaluation index calculated in Step 402 (immediate delivery rate result, inventory price result, inventory month result, inventory monthly business result). Then, the inventory forecast DB 304 and the order plan DB 302 are read (step 403), and an order system recommendation plan and an evaluation index (immediate delivery rate, inventory amount, number of months in stock, inventory quotient) are calculated (step 404). Order system recommendation proposals and estimated evaluation indicators are calculated monthly.

  Information in the product code column 521, the manufacturer name column 522, the quantity column 523, and the amount column 524 in the order plan DB 302 is updated when information is registered or changed by the ordering system 120. Yes. Information in the product code column 541, manufacturer name column 542, quantity column 543, and price column 544 of the inventory prediction DB 304 is updated when information is registered and information is changed by the inventory prediction system 140. ing.

  The ordering system recommended plan is obtained by Equations 6 to 8.

Monthly demand forecast value = Σ for each product (demand forecast value) (Equation 6)
Monthly arrival quantity = Σ for each product (proposed quantity) (Equation 7)
Monthly arrival amount = every month Σ each product (quantity plan x unit price) (Equation 8)
The estimated value of the evaluation index is obtained by Equation 9 to Equation 12.

Monthly immediate delivery rate forecast = Each AVE product for each month (estimated immediate delivery rate calculated at the time of ordering) (Equation 9)
Monthly inventory value forecast = Monthly {Σ Each product (Estimated inventory value calculated at the time of ordering)
+ Σ (Fundamentals latest stock at end of month x Unit price)} (10)
Monthly inventory month forecast = AVE for each month (Estimated number of inventory months calculated at the time of ordering) (Equation 11)
Monthly inventory monthly forecast = [{Σ for each product (estimated stock value calculated at the time of order)} for each month}
+ Σ (Fundamental latest inventory at the end of the month x Unit price)] ÷ Σ Each product (6 months average order received x Unit price) (12)
The evaluation index estimate calculation processing unit 70 based on the ordering system recommended plan stores the ordering system recommended plan created on the memory in the quantity column 573 and the amount column 574 of the order correction plan DB 307, and the evaluation index estimated value is stored in the ordering system. The recommended plan evaluation index expected value DB 308 is stored (step 405).

  (4) Next, the selection support processing unit 80 for the order plan correction target product will be described. Here, the order plan revision target product is selected in consideration of the necessary inventory change rate and the evaluation index change rate (step 406). The detailed flow of the ordering plan correction target product selection support processing unit 80 will be described with reference to FIG.

  (5) Next, the evaluation index forecast calculation processing unit 90 based on the orderer manual correction plan reads the order correction plan DB 307 and the orderer manual correction plan calculated in step 406 from the order plan correction target item DB 315 (step 407), The evaluation index expected value of the ordering system recommended plan is read from the ordering system recommended plan evaluation index estimated value DB 308, and the evaluation index estimated value based on the orderer manual correction plan is calculated (step 408).

  The estimated value of the evaluation index based on the manual order revision plan is obtained by Equations (13) to (16).

Monthly immediate delivery rate correction value = AVE for each product for each month {Average expected immediate delivery rate on simulation set when registering immediate delivery coefficient k (parameter value)}
× [1- (Ordering system recommendation proposal-Ordering manual correction proposal)
÷ {Order Monthly Demand Forecast Value x (Stage + 1) x (1 + Safety Stock Coefficient)}] (Equation 13)
Monthly inventory value correction value = (Monthly inventory month correction value x 6-month average demand x unit price)
+ Σ (Fundamentals latest end of month inventory x unit price)} (14)
Monthly inventory month correction value = AVE each product for each month {average expected inventory months in simulation set when registering immediate delivery coefficient k (parameter value)}
× [{(Ordering system recommended plan-Ordered manual correction plan) ÷ Monthly actual delivery count} ÷ 6-month demand average]
(Equation 15)
Monthly inventory monthly quotient correction value = [(Σ each product monthly inventory value correction value)
+ Σ (Fundamentals latest stock at the end of the month x Unit price)] ÷ Σ Each product (6 months demand average x Unit price) (16)
Forecast values are calculated monthly.

  The evaluation index estimate calculation processing unit 90 based on the order manual correction plan stores the evaluation index estimate value based on the order manual correction plan created in the memory in the order manual correction plan evaluation index estimate value DB 316 (step 409). Further, the evaluation index forecast calculation processing unit 90 based on the ordering manual correction plan updates the input ordering system recommended plan with the corrected ordering plan data, and stores the ordering manual correction plan in the ordering correction plan DB 307.

  (6) Next, the system determines whether there is unprocessed data in the demand record DB 300 and the inventory record DB 303 (step 410). If all the data has been processed, the process ends. If there is unprocessed data, the process returns to step 401 and the above process is repeated.

FIG. 21 is a flowchart showing the processing procedure of the ordering plan correction target product selection support processing unit 80, which will be described next. The part surrounded by the solid line in FIG. 21 shows the processing by the selection support processing unit 80 for the order plan correction target product.
(1) The ordering plan correction target product selection support processing unit 80 sets an extraction condition based on the monthly order amount (actual result) for each product, and extracts the corresponding product (step 501). For example, "Extract the product code of monthly order amount> 1,000,000 yen (this part is an arbitrary number)"
Etc. The larger the monetary scale, the greater the impact on the evaluation index, so the range is first set according to the monetary amount.

  (2) Next, the ordering plan correction target product selection support processing unit 80 reads the necessary stock amount DB 309 storing the necessary stock amount calculated in step 402 for the extracted product code, and places an order for each product. A necessary inventory amount change rate is calculated for the past one year (= 12 months) from the proposed month (step 502). The formula for calculating the required inventory change rate is as follows.

Necessary inventory change rate = (Monthly average required inventory for the past year from the order proposal target month / Required inventory quantity for the order proposal target month)
× 100 (Equation 17)
The ordering plan correction target product selection support processing unit 80 stores the calculated required inventory quantity change rate in the required inventory quantity change rate DB 310.

  (3) Next, the ordering plan correction target product selection support processing unit 80 reads the data of the evaluation index actual value DB 306 for the extracted product code, and targets the past one year (= 12 months) from the ordering plan target month. Then, the rate of change of the evaluation index (immediate delivery rate, inventory amount, number of months of inventory) in inventory management is calculated (step 503). The calculation formula for the rate of change of the evaluation index (immediate delivery rate, inventory value, inventory months) is as follows.

Instant delivery rate change rate = (Monthly average instant delivery rate over the past year from the order proposal target month / Instant delivery ratio in the order proposal target month) x 100 (Equation 18)
Stock price change rate = (Monthly average stock price for the past one year from the order proposal target month / inventory amount for the order proposal month)
× 100 (Equation 19)
Rate of change in number of months in stock = (monthly average number of months in the past year from the order proposal target month / number of months in the order proposal target month)
× 100 (Equation 20)
The ordering plan correction target product selection support processing unit 80 stores the calculated evaluation index change rate in the evaluation index change rate DB 311.

  (4) Next, the ordering plan correction target product selection support processing unit 80 reads the respective data of the necessary inventory amount change rate DB 310 and the evaluation index change rate DB 311, and stores the stock corresponding to the extracted required inventory amount change rate for each product. The change rate of the evaluation index (immediate delivery rate, inventory amount, inventory months) in management is calculated (step 504). The rate of change of the evaluation index with respect to the rate of change in required inventory for each product is as follows.

Instant delivery rate change rate relative to required inventory rate change rate = Instant delivery rate change rate / Necessary inventory amount change rate (Expression 21)
Inventory price change rate relative to required inventory quantity change rate = Inventory price change rate / Necessary inventory quantity change rate (Equation 22)
Monthly inventory change rate relative to required inventory change rate = Monthly inventory change rate / Necessary inventory rate change rate (Equation 23)
The ordering plan correction target product selection support processing unit 80 stores the calculated evaluation index change rate for the necessary inventory amount change rate in the evaluation index change rate DB 312 for the required inventory amount change rate.

  (5) Next, the ordering plan correction target product selection support processing unit 80 reads the evaluation index change rate DB 312 with respect to the required stock amount change rate, and refers to the extraction range setting table 314 for the change rate of the required stock amount. Select products with a high rate of change in the evaluation index. An example of the range setting method is as follows.

i. Immediate delivery rate change rate for required inventory change rate> a
ii. Inventory amount change rate relative to required inventory change rate> b
iii. Monthly inventory change rate relative to required inventory change rate> c
(A, b and c are all arbitrary numbers)
Further, the ordering plan correction target product selection support processing unit 80 displays these three range setting methods on the display device 20 and allows the user to select one of the following three conditions (step 505).

i. Instant delivery rate change rate relative to required stock rate change rate> a,
Inventory amount change rate with respect to required inventory amount change rate> b,
Monthly inventory change rate relative to required inventory change rate> c
Conditions that satisfy the above three range settings
ii. Instant delivery rate change rate relative to required stock rate change rate> a,
Inventory amount change rate with respect to required inventory amount change rate> b,
Monthly inventory change rate relative to required inventory change rate> c
Conditions that satisfy two range settings from the above
iii. Instant delivery rate change rate relative to required stock rate change rate> a,
Inventory amount change rate with respect to required inventory amount change rate> b,
Monthly inventory change rate relative to required inventory change rate> c
Conditions satisfying one range setting from among the above The ordering plan correction target product selection support processing unit 80 determines a target product and a target month under the selected conditions (step 506). The ordering plan correction target product selection support processing unit 80 stores the determined data in the ordering plan correction target item DB 315 and displays it on the display device 20.

  (6) Next, the ordering plan correction target product selection support processing unit 80 accepts data input of the ordering plan for the target ordering product by the user via the input device 10 (step 507). The ordering plan correction target product selection support processing unit 80 updates the ordering plan correction target item DB 315 with the correction data. Details of step 507 will be described later with reference to FIG.

  FIG. 22 is a diagram illustrating a simulation result display executed by the ordering plan correction target product selection support processing unit 80 to assist the user in correcting the ordering plan for the extracted ordering plan correction target product. . The target immediate delivery rate, the target inventory amount, and the target inventory month number given as evaluation indexes in the figure are numerical data input by the user via the input device 10. The ordering plan correction target product selection support processing unit 80 uses the formulas 9 to 11 to calculate the immediate delivery rate forecast, the stock price forecast and the stock month forecast when the order quantity is 100, 200,... Each is calculated and plotted on the display device 20 as a graph indicating the simulation result. In this example, the order proposal is changed in steps of 100 around 300 recommended order system proposals. In FIG. 22, the diagram showing ● is a point indicating that the target evaluation index is achieved for the order proposal, and the diagram showing x indicates that the target evaluation index is achieved for the order proposal. It is a point indicating that there is no.

  FIG. 22 shows the August order quantity proposal for the correction target product. The recommended ordering system shows 300 pieces. However, if there are 300 ordering system recommended proposals, the target immediate delivery rate is achieved, but the target stock amount and target stock months are not achieved. Therefore, it can be seen that the order proposal for achieving all of the target immediate delivery rate, the target inventory amount, and the target inventory months is achieved when the number is 200. As a result, it is preferable to employ 200 pieces that have exceeded all target evaluation indexes as manual correction order proposals. The order plan whose data has been manually corrected is stored in the order correction plan DB 307.

  The processing units 60 to 90 can be configured as a processing program, and the processing program is stored in a recording medium such as HD, DAT, FD, USB memory, MO, DVD-RAM, CD-ROM, and provided. Can do.

  The present invention can be used in a wide range of industries such as distribution industry and manufacturing industry.

It is a block diagram of the evaluation parameter | index forecast visualization system of an Example. It is a figure explaining the relationship between each process part of an Example, each table, and each DB. It is a figure which shows the example of a data structure of demand performance DB. It is a figure which shows the data structural example of demand forecast DB. It is a figure which shows the example of a data structure of order plan DB. It is a figure which shows the data structural example of inventory performance DB. It is a figure which shows the data structural example of inventory prediction DB. It is a figure which shows the data structural example of a goods attribute master. It is a figure which shows the data structural example of evaluation index performance value DB. It is a figure which shows the example of a data structure of order correction plan DB. It is a figure which shows the example of a data structure of ordering system recommendation proposal evaluation index estimated value DB. It is a figure which shows the data structural example of required inventory amount DB. It is a figure which shows the data structural example of required inventory amount change rate DB. It is a figure which shows the example of a data structure of evaluation index change rate DB. It is a figure which shows the example of a data structure of evaluation index change rate DB with respect to required inventory amount change rate. It is a figure which shows the data structural example of an extraction range parameter table. It is a figure which shows the data structural example of an extraction range setting table. It is a figure which shows the example of a data structure of order plan correction object item DB. It is a figure which shows the data structural example of ordering person manual correction plan evaluation index estimate value DB. It is a flowchart which shows the process sequence of evaluation parameter | index forecast calculation by the orderer's manual correction plan of an Example. It is a flowchart which shows the detailed procedure of the process by the selection assistance process part of the order plan correction object product. It is a figure which shows the relationship between the order quantity of correction object goods, and an evaluation index.

Explanation of symbols

  70: Evaluation index foreseeable calculation processing unit based on ordering system recommended plan, 80: Selection support processing unit for product to be revised for ordering plan, 90: Evaluation index foreseeable calculation processing unit for manual order correction plan, 302: Order plan DB, 304 : Inventory forecast DB, 314: Extraction range setting table, 315: Order plan amendment target item DB, 316: Order manual revision plan evaluation index forecast DB

Claims (5)

Referring to the storage means for storing an order proposal for each period of each target inventory and the storage means for storing inventory forecast data, the estimated values of a plurality of evaluation indexes for the period of each target inventory are calculated. And
Calculate the rate of change of the evaluation index with respect to the past average value of the forecast value for the period of each target inventory item,
Extract the target inventory that satisfies the evaluation index change rate extraction condition, and display the order proposal corresponding to the identifier,
Calculate and display an estimated value of the evaluation index for a plurality of ordering proposals when the ordering proposals are fluctuated back and forth for the extracted target inventory items,
An evaluation index prospect visualization method characterized in that an original ordering plan can be modified by an ordering plan that satisfies a plurality of target evaluation indexes. Further, the storage means for storing the necessary inventory quantity for each period of each target inventory item is referred to calculate the change rate of the necessary inventory quantity for the period with respect to the past average value of the required inventory quantity of each target inventory item. ,
The evaluation index prospect according to claim 1, wherein the evaluation index change rate with respect to the required inventory amount change rate is calculated, and the evaluation index change rate with respect to the required inventory amount change rate is used instead of the evaluation index change rate. Visualization method.   2. The evaluation index prospect visualization method according to claim 1, wherein the plurality of evaluation indices are an immediate delivery rate, an inventory amount, and a number of months of inventory. In the calculator,
Referring to the storage means for storing an order proposal for each period of each target inventory and the storage means for storing inventory forecast data, the estimated values of a plurality of evaluation indexes for the period of each target inventory are calculated. Function to
A function of calculating an evaluation index change rate with respect to a past average value of the forecast value for the period of each target inventory item;
A function of extracting a target inventory that satisfies the extraction condition of the evaluation index change rate and displaying an order proposal corresponding to the identifier;
A program for realizing a function of calculating and displaying an estimated value of the evaluation index for a plurality of order proposals when the order proposal is changed back and forth with respect to the extracted target inventory,
A program characterized in that, by causing the computer to execute the program, the original order proposal can be modified by an order proposal that satisfies a plurality of target evaluation indexes. In addition,
A function of calculating a rate of change of the required inventory quantity for the period with respect to a past average value of the required inventory quantity of each target inventory with reference to a storage unit that stores the required inventory quantity for each period of each target inventory When,
A program for realizing the function of calculating the evaluation index change rate with respect to the required inventory change rate,
5. The program according to claim 4, wherein an evaluation index change rate with respect to the required inventory amount change rate is used instead of the evaluation index change rate.

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