JP2005352588A - Information processing device, method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To calculated expectation effect for each management condition in multistep commercial flow and to establish optimum management condition, that is, an optimum sales condition on a management entity side based on the expectation effect. <P>SOLUTION: A demand prediction model setting part 14 sets a predicted demand of a commodity for one or a plurality of terminal conditions about trade of the commodity by a terminal entity in the multistep commercial flow. A probability distribution calculation part 16 calculates a realization frequency for each terminal condition to the corresponding management condition for one or each of a plurality of management conditions related to the trade of the commodity by the management entity in the multistep commercial flow. Based on the predicted demand and the realization frequency, expectation effect in the multistep commercial flow is calculated for each management condition. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an information processing apparatus, an information processing method, and a program that enable planning of sales conditions that optimize an expected effect in a multistage commercial flow.

  Until now, many of the proposed demand prediction models have been based on the assumption that a seller sells directly to a buyer, that is, demand prediction in a single-stage commercial flow. For example, in the case of a retail business that is the end of a multi-level commercial flow, the business objectives such as sales volume and profits are optimized by using a demand forecast model that takes into account the price / non-price sales promotion effect that is set by itself. It is possible to make a sales plan. By using a demand forecast model that takes into account the price / non-price sales promotion effect, it is possible to formulate a sales plan that optimizes business objectives such as sales volume and profit.

  Profit optimization methods using a demand prediction model that takes into account price / non-price sales promotion effects are disclosed in Patent Documents 1 and 2. Patent Document 1 proposes a method for predicting the sales volume when a product is set at a certain price based on past sales performance data. Patent Document 2 describes these consumer demand models. Methods have been proposed to incorporate psychological effects (non-price promotional effects). As described above, the conventionally proposed method can be used in the case of a single stage, such as an end subject of a commercial flow such as retail business.

  On the other hand, from the viewpoint of the main body (for example, a manufacturer) located upstream of the multi-stage commercial flow, the increase in profits provided downstream of the commercial flow or the influence of increase / decrease in the distribution inventory is desired for the purpose of expanding market share. In order to realize profit optimization at the effective level that has been eliminated, by performing demand forecasts closer to the final consumer, it eliminates inefficiency due to partial optimization by each entity and expansion of forecast error However, there is a need for optimization with a view to the entire multi-stage commercial flow.

JP-A-5-67119 Japanese translation of PCT publication No. 2002-513488

  However, even if a downstream demand forecast model is held, the upstream entity does not have the right to determine downstream sales conditions (price / non-price), so there is a problem with the evaluation method for the plan. I had it.

  Therefore, an object of the present invention is to provide a management entity located upstream of the multi-stage commercial flow as a whole or a part of the commercial flow for each sales condition (hereinafter referred to as management condition) where the decision right can be exercised. It is to be able to calculate the optimal management conditions, that is, the optimal sales conditions on the management subject side based on the expected effects.

  According to a first aspect of the information processing apparatus of the present invention, a predicted demand setting unit that sets the predicted demand of the product for each of one or more terminal conditions related to the sales of the product by the terminal entity in a multi-stage commercial flow; Realization frequency calculation means for calculating the realization frequency of each of the end conditions for the corresponding management condition for each of one or a plurality of management conditions related to the sale of the product by the management entity in the multistage commercial flow, the predicted demand and the It has the 1st expected effect calculation means which calculates the expected effect which concerns on the said predicted demand in the said multistage commercial flow for every said management conditions based on realization frequency, It is characterized by the above-mentioned.

  According to a second aspect of the information processing apparatus of the present invention, the predicted demand setting means for setting the predicted demand of the product for each of one or more end conditions related to the sale of the product by the terminal subject in the multi-stage commercial flow, Realization frequency calculating means for calculating the realization frequency of each of the end conditions for the corresponding management condition for each one or a plurality of management conditions related to the sale of the product by the management entity in the multi-stage commercial flow, the management condition, Profit calculation means for calculating the profit in the multi-stage commercial flow corresponding to each terminal condition for each management condition based on the terminal condition and the predicted demand, or the management condition and the predicted demand, and the realization frequency And an expected effect calculation for calculating the expected effect related to the profit in the multistage commercial flow for each management condition based on the profit in the multistage commercial flow corresponding to each terminal condition. And having a means.

  A first aspect of the information processing method according to the present invention is an information processing method by an information processing apparatus, wherein each of one or a plurality of end conditions related to sales of a product by an end subject in a multistage commercial flow A predicted demand setting step for setting a predicted demand, and for each one or a plurality of management conditions related to the sale of the product by the management entity in the multi-stage commercial flow, the realization frequency of each of the end conditions for the corresponding management conditions is calculated. A realization frequency calculating step, and a first expected effect calculation step of calculating an expected effect related to the predicted demand in the multi-stage commercial flow for each management condition based on the predicted demand and the realization frequency. Features.

  According to a second aspect of the information processing method of the present invention, there is provided an information processing method by an information processing device, wherein each of the one or a plurality of end conditions related to the sale of the product by an end subject in a multistage commercial flow A predicted demand setting step for setting a predicted demand, and for each one or a plurality of management conditions related to the sale of the product by the management entity in the multi-stage commercial flow, the realization frequency of each of the end conditions for the corresponding management conditions is calculated. Based on the realization frequency calculation step, the management condition, the terminal condition and the predicted demand, or the management condition and the predicted demand, the profit in the multistage commercial flow corresponding to each terminal condition is calculated for each management condition. Based on the profit calculation step calculated in step (b), the realization frequency, and the profit in the multi-stage commercial flow corresponding to each end condition. Characterized in that it comprises the expected effect calculation step of calculating an expected effect according to the each of the control conditions.

  According to a first aspect of the program of the present invention, a function of the information processing apparatus is executed by a computer.

  According to a second aspect of the program of the present invention, the information processing method is executed by a computer.

  According to the present invention, since the expected effect related to the predicted demand in the multi-stage commercial flow is calculated for each management condition, it is optimal with reference to the expected effect related to the predicted demand for each management condition in the multi-stage commercial flow. Management conditions, that is, optimal sales conditions on the management subject side can be planned.

  Further, according to another feature of the present invention, since the expected effect related to the profit in the multi-stage commercial flow is calculated for each management condition, the expected effect related to the profit for each management condition in the multi-stage commercial flow is It is possible to devise optimal management conditions with reference, that is, optimal sales conditions on the management subject side.

  DESCRIPTION OF EXEMPLARY EMBODIMENTS Hereinafter, preferred embodiments to which the invention is applied will be described in detail with reference to the accompanying drawings.

First, the multistage commercial flow that is the premise of the present invention will be described.
FIG. 12 is a diagram schematically illustrating an example of a multistage commercial flow (hereinafter abbreviated as a commercial flow). In FIG. 12, S0 is a management entity having the right to determine the management condition p0, for example, an entity that is in a position to use an information processing apparatus to which the present invention is applied. Here, the management condition p0 is a sales condition such as a sales price of a product determined by the management entity S0. S1 is an entity that is located at the same level as or downstream of the management entity S0 in the commercial flow and sells products under the management condition p0 determined by the management entity S0. Hereinafter, a plurality of subjects may exist between S0 and S1. The part from S0 to S1 is referred to as a management main part. S2 is a main body that is located downstream from the main body S1 in the commercial flow and purchases products from the main body S1 under the management condition p0. S3 is a terminal entity having the right to determine the terminal condition p1, and is located at the same level as or downstream from the main entity S2 in the commercial flow, and the main entity S2 sells products purchased under the management condition p0 under the terminal condition p1. is there. Here, the terminal condition p1 is a sales condition such as a sales price of a product determined by the terminal entity S3. Hereinafter, a plurality of subjects may exist between S2 and S3. The part from S2 to S3 is called a distribution part. S4 is the final consumer who purchases the product from the terminal entity S3 under the terminal condition p1.

  The management entity S0 corresponds to, for example, a manufacturer that manufactures a product, and the terminal entity S3 corresponds to, for example, a distributor that is intermediate between the manufacturer and the final consumer S4 and plays an intermediary role. In the example of FIG. 12, there are an entity S1 that sells products under the management condition p0 determined by the management entity S0 and an entity S2 that purchases products from the entity S1 under the management conditions p0. May be the same entity, and the entity S2 and the terminal entity S3 may be the same entity. In the above description, the selling price, which is a price factor, is exemplified as the management condition p0 and the end condition p1, but other price factors such as a discount amount (rate) may be used. Furthermore, it is also possible to apply non-price factors such as advertisements as the management condition p0 and the end condition p1. In the embodiment of the present invention exemplified below, the management entity S0 is a manufacturer, the terminal entity S3 is a distributor, and the management condition p0 and the terminal condition p1 are sales prices (management price, terminal price) as price factors.

FIG. 1 is a block diagram showing a functional configuration of an information processing apparatus according to an embodiment of the present invention.
As illustrated in FIG. 1, the information processing apparatus according to the present embodiment includes a demand prediction management table 11, a cost management table 12, a management price-end price management table 13, a demand prediction model setting unit 14, and a terminal condition probability model setting unit. 15 includes a probability distribution calculation unit 16 and an output control unit 17.

  The demand prediction management table 11 is a table for managing the demand (predicted quantity) predicted for each terminal price for each product, and manages the terminal price and the predicted quantity in association with each product. .

  The cost management table 12 is a table for managing various costs from the manufacture of a product to the sale to the final consumer, such as the manufacturing cost and distribution cost of each product. In the example of FIG. 1, the cost management table 12 manages only the manufacturing cost and the distribution cost of each product, but other costs may be managed.

  The management price-end price management table 13 is a table for managing, for each product, the history of the end price previously realized in the terminal entity for each management price, and the management price and the end price together with the realized date. Is associated with each product.

  The demand forecast model setting unit 14 sets the demand forecast model selected by the demand forecast model selection operation on the menu screen by the user. The demand prediction model is a model for determining the demand predicted for the terminal price, here, the predicted quantity, and the demand prediction model for each product is managed in the demand prediction management table 11. In the selection operation of the demand prediction model by the user, the product is specified, the demand prediction model setting unit 14 selects the demand prediction model corresponding to the specified product, and the probability distribution calculation unit 16 (to be described later) performs the probability distribution calculation process. Set as a demand forecast model to be referenced.

  The terminal condition probability model setting unit 15 sets the terminal condition probability model selected by the terminal price probability model selection operation on the menu screen by the user. The end condition probability model is a model for determining how much each end price is realized with respect to a certain management price. The association is managed in the management price-end price management table 13 for each product. In the selection operation of the end condition probability model by the user, the product is specified, the end condition probability model setting unit 15 selects the end condition probability model corresponding to the specified product, and the probability distribution calculation unit 16 described later performs the probability distribution calculation process. This is set as the end condition probability model to be referred to.

  The probability distribution calculation unit 16 performs a probability distribution calculation process, which will be described later, based on the optimization target index and optimization conditions specified by the user operation on the menu screen. The optimization target index is a statistically derived expected effect such as the sales volume to be optimized, the expected value of contribution profit, x sigma point, etc. The optimization condition is to optimize the expected effect It is a condition. In the following, as the optimization target index, the expected value of the contribution to the merchandise (distribution department) and the whole merchandise to the terminal entity excluding the administration entity, the expected value of the sales volume of the product is specified, A case where a condition for maximizing the value of the optimization target index is designated as an optimization condition will be described as an example.

  For example, when the demand prediction model and the end condition probability model of the product a are set in the demand prediction model setting unit 14 and the end condition probability model setting unit 15, the probability distribution calculation unit 16 includes the demand prediction management table 11 and the management price. The record corresponding to the product a is read from the end price management table 13 and the probability distribution calculation process related to the product a is performed. Further, when a constraint condition is input, only records satisfying the constraint condition are read from the demand prediction management table 11 and the management price-end price management table 13. An example of the constraint condition is the upper and lower limits of the management price and the end price. In this case, the probability distribution calculation unit 16 reads only records whose management price and end price are both within the upper and lower limits.

  When the user designates the optimization target index as “expected value of contribution profit of the entire commercial flow” and the optimization condition as “maximization”, the probability distribution calculation unit 16 obtains the expected value of contribution profit of the entire commercial flow. Therefore, in addition to the demand prediction management table 11 and the management price-end price management table 13, the record corresponding to the product a is read from the cost management table 12, and the expected value of the contribution profit of the entire commercial flow for each management price of the product a And a management price that maximizes the expected value.

  When the “expected value of contribution profit of the entire commercial flow” is specified as the optimization target index and “maximization” is specified as the optimization condition, the output control unit 17 determines the commercial flow obtained by the probability distribution calculation unit 16. The management price that maximizes the expected value of the overall contribution profit is notified to the user on the screen display on the display panel.

FIG. 2 is a diagram schematically illustrating a hardware configuration of a computer system in the information processing apparatus.
As shown in FIG. 2, the computer system 1200 includes a CPU 1201, a ROM 1202, a RAM 1203, a keyboard controller (KBC) 1205 of a keyboard (KB) 1209, and a CRT controller (CRTC) 1206 of a CRT display (CRT) 1210 as a display panel 19. , A hard disk (HD) 1211 and a flexible disk (FD) 1212 disk controller (DKC) 1207 and a network interface card (NIC) 1208 for connection to the network 1220 can communicate with each other via a system bus 1204 Connected configuration.

  The CPU 1201 executes software that reads information from the ROM 1202 or the HD 1211 and the like, thereby comprehensively controlling each component connected to the system bus 1204 and executes processing shown in FIG.

  A RAM 1203 functions as a main memory or work area of the CPU 1201. The KBC 1205 controls instruction input from the KB 1209, a pointing device (not shown), or the like. A CRTC 1206 controls display on the CRT 1210. The DKC 1207 controls access to a boot program, various applications, edit files, user files, and a network management program. The NIC 1208 controls data communication with the information processing apparatus via the network 1220.

  Note that the demand prediction model setting unit 14, end condition probability model setting unit 15, probability distribution calculation unit 16, and output control unit 17 in FIG. 1 are configured by programs in the CPU 1201 and the ROM 1202, for example. Further, the demand prediction management table 11, the cost management table 12, and the management price-end price management table 13 are configured in, for example, a recording medium of the RAM 1203 or the HD 1211.

  Next, the operation of the information processing apparatus in the present embodiment will be described with reference to FIG. FIG. 3 is a flowchart showing a flow of operations of the information processing apparatus.

  First, the demand prediction model setting unit 14 determines whether or not a demand prediction model has been selected by an operation on the menu screen by the user (step S31). If the demand prediction model is not selected (step S31 / no), the process waits until the demand prediction model is selected. When the demand prediction model is selected by the user (step S31 / yes), the demand prediction model setting unit 14 performs setting processing for the selected demand prediction model (step S32). Here, it is assumed that the demand prediction model for the product a is selected.

  Subsequently, the terminal condition probability model setting unit 15 determines whether or not the terminal condition probability model is selected by an operation on the screen by the user (step S33). When the terminal condition probability model is not selected (step S31 / no), the process waits until the terminal condition probability model is selected. When the terminal condition probability model is selected by the user (step S31 / yes), the terminal condition probability model setting unit 15 performs processing for setting the selected terminal condition probability model (step S34). Here, it is assumed that the end condition probability model of the product a is selected.

  Subsequently, the probability distribution calculation unit 16 determines whether or not an operation for specifying an optimization target index and an optimization condition has been performed by a user operation on the screen (step S35). When the user performs an operation for specifying the optimization target index and the optimization condition (step S35 / yes), the probability distribution calculation unit 16 proceeds to the probability distribution calculation process of step S36. Here, it is assumed that the selected optimization target index is “expected value of contribution profit of the entire commercial flow” and the optimization condition is “maximization”.

  Subsequently, the process proceeds to a probability distribution calculation process by the probability distribution calculation unit 16 in step S36. The probability distribution calculation process by the probability distribution calculation unit 16 will be described in detail with reference to FIG. FIG. 4 is a flowchart showing in detail step S36 in FIG. 3 when “expected value of contribution profit of the entire commercial flow” is designated as the optimization target index and “maximization” is designated as the optimization condition.

  In the probability distribution calculation process of step S36, since the demand prediction model and end condition probability model of the product a are set in step S32 and step S34, the probability distribution calculation unit 16 uses the demand prediction management table 11 and the management price− A record corresponding to the product a is read from the terminal price management table 13 (step S361a). In addition, when there is a constraint condition input together with an optimization target index and optimization condition designation input, only records satisfying the constraint condition are read from the demand prediction management table 11 and the management price-end price management table 13. Here, the upper and lower limits of management price 4.6 (10,000 yen) to 5.4 (10,000 yen) and the upper and lower limits of end price 5.4 (10,000 yen) to 6.6 (10,000 yen) are entered as constraints. It shall be assumed. Therefore, the probability distribution calculation unit 16 reads only the records satisfying the upper and lower limits 5.4 (10,000 yen) to 6.6 (10,000 yen) from the demand forecast management table 11, and the management price-end price management table. From 13 only records that satisfy both the upper and lower limits of the management price 4.6 (10,000 yen) to 5.4 (10,000 yen) and the upper and lower limits of the end price 5.4 (10,000 yen) to 6.6 (10,000 yen) Is read.

  In the present embodiment, the forecast quantity for each terminal price read from the demand forecast management table 11 takes the following values as shown in FIGS. 5 (a) to 5 (e). FIG. 7 is a diagram showing the relationship of the predicted quantity to the end price in this example.

・ Predicted quantity for end price 5.4 (10,000 yen) = 98 (pieces)
・ Predicted quantity for end price 5.6 (10,000 yen) = 97 (pieces)
・ Predicted quantity for terminal price 5.8 (10,000 yen) = 92 (pieces)
・ Predicted quantity for end price 6.0 (10,000 yen) = 80 (pieces)
・ Predicted quantity for terminal price 6.2 (10,000 yen) = 50 (pieces)
・ Predicted quantity for terminal price 6.4 (10,000 yen) = 30 (pieces)
・ Predicted quantity for terminal price 6.6 (10,000 yen) = 10 (pieces)

  Subsequently, the probability distribution calculation unit 16 takes statistics of the appearance frequency of each terminal price for each management price in the record read from the management price-terminal price management table 13, and uses the statistical value to calculate the probability distribution of the terminal price (occurrence probability). ) Is obtained (step S362a). Taking the case of a management price of 4.6 (10,000 yen) as shown in FIG. 5A, the probability distribution of each terminal price is as follows. Probability distributions at other management prices are as shown in FIGS.

・ For management price 4.6 (10,000 yen), probability of occurrence of end price 5.4 (10,000 yen) = 0.2 (20%)
-Probability of occurrence of end price 5.6 (10,000 yen) against management price 4.6 (10,000 yen) = 0.55 (55%)
-Probability of occurrence of end price 5.8 (10,000 yen) against management price 4.6 (10,000 yen) = 0.2 (20%)
・ Probability of occurrence of terminal price 6.0 (10,000 yen) against management price 4.6 (10,000 yen) = 0.0505 (5%)
-Probability of occurrence of terminal price 6.2 (10,000 yen) against management price 4.6 (10,000 yen) = 0 (0%)
-Probability of occurrence of terminal price 6.4 (10,000 yen) against management price 4.6 (10,000 yen) = 0 (0%)
-Probability of occurrence of terminal price 6.6 (10,000 yen) against management price 4.6 (10,000 yen) = 0 (0%)

  In addition, since the designated optimization target index is an expected value of the contribution profit of the entire commercial flow, the probability distribution calculation unit 16 reads the record (manufacturing cost, distribution cost) corresponding to the product a from the cost management table 12. (Step S363a) For each management price, contribution profits (manufacturer CM, distribution CM) of the management main body and distribution unit for each product a corresponding to each terminal price are calculated (step S364a). The contribution profit of the management main part per product a corresponding to each terminal price for each management price can be obtained by subtracting the manufacturing cost from the management price as follows (see FIGS. 5A to 5E). ).

-In the case of a management price of 4.6 (10,000 yen) Management price 4.6 (10,000 yen)-Production cost 3.5 (10,000 yen) = Contribution profit of management entity per product a 1.1 (10,000 yen)
-In the case of a management price of 4.8 (10,000 yen) Management price 4.8 (10,000 yen)-Manufacturing cost 3.5 (10,000 yen) = Contribution profit of management entity per product a 1.3 (10,000 yen)
-In the case of management price 5.0 (10,000 yen) Management price 5.0 (10,000 yen)-Manufacturing cost 3.5 (10,000 yen) = Contribution profit of management entity per product a 15,000 (10,000 yen)
-In the case of a management price of 5.2 (10,000 yen) Management price 5.2 (10,000 yen)-Manufacturing cost 3.5 (10,000 yen) = Contribution profit of management entity per product a 1.7 (10,000 yen)
-In the case of a management price of 5.4 (10,000 yen) Management price 5.4 (10,000 yen)-Manufacturing cost 3.5 (10,000 yen) = Contribution profit of management entity per product a 1.9 (10,000 yen)

  Further, the contribution profit of the distribution unit per product a corresponding to each terminal price for each management price can be obtained by subtracting the management price and the distribution cost from the terminal price as follows. In the following, only the case of a management price of 4.6 (10,000 yen) will be exemplified (see FIG. 5A), but other management prices are also obtained in the same way (FIGS. 5B to 5E). reference).

・ In the case of management price 4.6 (10,000 yen) and terminal price 5.4 (10,000 yen) Terminal price 5.4 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution department contribution profit per product a 0.3 (10,000 yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 5.6 (10,000 yen) Terminal price 5.6 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution department contribution profit per product a 0.5 (10,000 Yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 5.8 (10,000 yen) Terminal price 5.8 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution department contribution profit per product a 0.7 (10,000 Yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 6.0 (10,000 yen) Terminal price 6.0 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution Department contribution profit per product a 0.9 (10,000 Yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 6.2 (10,000 yen) Terminal price 6.2 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution Department's contribution profit per product a 1.1 (10,000 yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 6.4 (10,000 yen) Terminal price 6.4 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution department contribution profit per product a 1.3 (10,000 yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 6.6 (10,000 yen) Terminal price 6.6 (10,000 yen)-(management price 4.6 (10,000 yen) + distribution cost 0.5 (10,000 yen) Yen)) = Distribution department contribution profit per product a 1.5 (10,000 yen)

  Next, the probability distribution calculation unit 16 multiplies the contribution profit of the management main body unit and the distribution unit for each product a corresponding to each terminal price for each management price by the corresponding predicted quantity, thereby obtaining The total contribution profit (manufacturer total CM, distribution total CM) of the management main body and distribution department corresponding to each terminal price is calculated (step S365a). The following is an example of a management price of 4.6 (10,000 yen) (see Fig. 5 (a)), but the total contribution profit of the management main body and distribution department corresponding to each terminal price at other management prices is also shown. It can be calculated by a similar method (see FIGS. 5B to 5E).

・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.4 (10,000 yen), the contribution profit of the management body per product a is 1.1 (10,000 yen) x the predicted quantity is 98 (pieces) = the management body Total contribution profit 107.8 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.6 (10,000 yen) Contribution profit of management entity per product a 1.1 (10,000 yen) x forecast quantity 97 (pieces) = management entity Total contribution profit 106.7 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.8 (10,000 yen) Contribution profit of management entity per product a 1.1 (10,000 yen) x predicted quantity 92 (pieces) = management entity Total contribution profit of 101.2 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.0 (10,000 yen) Contribution profit of management entity per product a 1.1 (10,000 yen) x predicted quantity 80 (pieces) = management entity Total contribution profit of 88.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.2 (10,000 yen) Contribution profit of management entity per product a 1.1 (10,000 yen) x predicted quantity 50 (pieces) = management entity Total contribution profit 55.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.4 (10,000 yen), the contribution profit of the management body per product a is 1.1 (10,000 yen) x the predicted quantity is 30 (pieces) = the management body Total contribution profit 33.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.6 (10,000 yen) Contribution profit of management entity per product a 1.1 (10,000 yen) x forecast quantity 10 (pieces) = management entity Total contribution profit 10.0 (10,000 yen)

-In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.4 (10,000 yen), the contribution profit of the distribution department per product a 0.3 (10,000 yen) x the expected quantity 98 (pieces) = of the distribution department Total contribution profit 29.4 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.6 (10,000 yen), the contribution profit of the distribution department per product a 0.5 (10,000 yen) x the predicted quantity 97 (pieces) = the distribution department Total contribution profit 48.5 (10,000 yen)
-In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.8 (10,000 yen) Contribution award of distribution department per product a 0.7 (10,000 yen) x predicted quantity 92 (pieces) = distribution department Total contribution profit 64.4 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.0 (10,000 yen) Distribution a contribution contribution per product a 0.9 (10,000 yen) x forecast quantity 80 (pieces) = distribution department Total contribution profit 72.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.2 (10,000 yen) Distribution a contribution contribution per product a 1.1 (10,000 yen) x predicted quantity 50 (pieces) = distribution department Total contribution profit 55.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.4 (10,000 yen) Distribution a contribution contribution per product a 1.3 yen (10,000 yen) x predicted quantity 30 (pieces) = distribution department Total contribution profit 39.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.6 (10,000 yen) Distribution a contribution contribution per product a 1 million (10,000 yen) x forecast quantity 10 (pieces) = distribution department Total contribution profit 15.0 (10,000 yen)

  Subsequently, the probability distribution calculation unit 16 calculates the total contribution profit (total CM) of the entire commercial flow corresponding to each terminal price for each management price (step S366a). The total contribution profit of the entire commercial flow corresponding to each terminal price for each management price is obtained as the sum of the total contribution profits of the corresponding management body and distribution department as follows. The following is an example of a management price of 4.6 (10,000 yen) (see Fig. 5 (a)), but for other management prices as well, the total contribution profit of the entire commercial flow corresponding to each terminal price by the same method. Can be calculated (see FIGS. 5B to 5E).

・ In the case of a management price of 4.6 (10,000 yen) and an end price of 5.4 (10,000 yen) Total contribution profit of the management department 107.8 (10,000 yen) + total contribution profit of the distribution department 29.4 (10,000 yen) = 137.2 (10,000 yen)
・ In the case of management price 4.6 (10,000 yen), end price 5.6 (10,000 yen) Total contribution profit 106.7 (10,000 yen) in the management department + total contribution profit 48.5 (10,000 yen) in the distribution department = 155.2 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.8 (10,000 yen) The total contribution profit of the management department 101.2 (10,000 yen) + the total contribution profit of the distribution department 64.4 (10,000 yen) = 165.6 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.0 (10,000 yen) The total contribution profit of the management entity 88.0 (10,000 yen) + the total contribution profit of the distribution department 72.0 (10,000 yen) = 160.0 (10,000 yen)
・ In the case of management price 4.6 (10,000 yen) and terminal price 6.2 (10,000 yen) Total contribution profit 55.0 (10,000 yen) in the management department + total contribution profit 55.0 (10,000 yen) in the distribution department = 110.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.4 (10,000 yen) Total contribution profit of the management department 33.0 (10,000 yen) + total contribution profit of the distribution department 39.0 (10,000 yen) = 72.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.6 (10,000 yen) Total contribution profit of management department 11.0 (10,000 yen) + total contribution profit of distribution department 15.0 (10,000 yen) = 26.0 (10,000 yen)

  From the above, the total contribution profit of the management main part, the distribution department and the whole commercial flow is required. FIG. 8 shows the relationship between the total contribution profits of the management main body, the distribution department, and the entire commercial distribution for each terminal price when the management price is 5.0 (10,000 yen) (corresponding to FIG. 5C). The total contribution profit of the entire commercial flow is calculated by taking the sum of the contribution profit (manufacturer CM) of the management entity per product a and the contribution profit (distribution CM) of the distribution department per product a. It is also possible to obtain the contribution profit of the entire commercial flow per a, and multiply by the predicted quantity corresponding to the contribution profit of the entire commercial flow per product a.

  Subsequently, the probability distribution calculation unit 16 calculates an expected value (expected contribution profit) of the total contribution profit of the management main body part, the distribution part, and the entire commercial flow corresponding to each terminal price for each management price (step S367a). The expected value of the total contribution profit of the management entity is obtained by multiplying the total contribution profit of the corresponding management entity by the corresponding occurrence probability and totaling it. Multiplying the total contribution profit of the relevant distribution department by the corresponding occurrence probability, and obtaining the result, the expected value of the total contribution profit of the entire commercial flow is the same as the total contribution profit of the entire commercial flow. It is obtained by multiplying the corresponding occurrence probabilities and tabulating. In the following, the case of a management price of 4.6 (10,000 yen) will be exemplified (see FIG. 5A), but other management prices are also managed in the same manner, with the management main body and distribution department corresponding to each terminal price. And the expected value of the total contribution profit of the whole commercial flow can be calculated (refer FIG.5 (b)-(e)). The expectation of the total contribution profit of the entire commercial flow can also be obtained by taking the sum of the expected value of the total contribution profit of the corresponding management entity and the expected value of the total contribution profit of the distribution department.

・ In the case of a management price of 4.6 (10,000 yen) and an end price of 5.4 (10,000 yen) Total contribution profit of the management entity 107.8 (10,000 yen) x 0.2 = 21.56 (10,000 yen)
Total contribution profit of the distribution department 29.4 (10,000 yen) x 0.2 = 5.88 (10,000 yen)
Total contribution profit of the entire commercial flow 137.2 (10,000 yen) x 0.2 = 27.44 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.6 (10,000 yen) Total contribution profit of the management entity 106.8 (10,000 yen) x 0.55 = 58.685 (10,000 yen)
Total contribution profit of the distribution department 48.5 (10,000 yen) x 0.55 = 26.675 (10,000 yen)
Total contribution profit of the entire commercial flow 155.2 (10,000 yen) x 0.55 = 85.36 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 5.8 (10,000 yen) Total contribution profit of the management department 101.2 (10,000 yen) x 0.2 = 20.24 (10,000 yen)
Total contribution profit of the distribution department 64.4 (10,000 yen) x 0.2 = 12.88 (10,000 yen)
Total contribution profit of the entire commercial flow 165.6 (10,000 yen) x 0.2 = 33.12 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and an end price of 6.0 (10,000 yen) Total contribution profit of the management entity 88.0 (10,000 yen) × 0.05 = 4.4 (10,000 yen)
Total contribution profit of distribution department 72.0 (10,000 yen) x 0.05 = 3.6 (10,000 yen)
Total contribution profit of the entire commercial flow 160.0 (10,000 yen) × 0.05 = 8.0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.2 (10,000 yen) Total contribution profit of the management entity 55.0 (10,000 yen) x 0 = 0 (10,000 yen)
Total contribution profit of distribution department 55.0 (10,000 yen) x 0 = 0 (10,000 yen)
Total contribution profit of the entire commercial flow 110.0 (10,000 yen) x 0 = 0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.4 (10,000 yen) Total contribution profit of the management entity 33.0 (10,000 yen) x 0 = 0 (10,000 yen)
Total contribution profit of distribution department 39.0 (10,000 yen) x 0 = 0 (10,000 yen)
Total contribution profit of the entire commercial flow 72.0 (10,000 yen) x 0 = 0 (10,000 yen)
・ In the case of a management price of 4.6 (10,000 yen) and a terminal price of 6.6 (10,000 yen) Total contribution profit of the management entity 11.0 (10,000 yen) x 0 = 0 (10,000 yen)
Total contribution profit of distribution department 15.0 (10,000 yen) x 0 = 0 (10,000 yen)
Total contribution profit of the entire commercial flow 26.0 (10,000 yen) x 0 = 0 (10,000 yen)

  Subsequently, as shown in FIG. 6, the probability distribution calculation unit 16 calculates an expected value of the total contribution profit of the management main body unit, the distribution unit, and the entire commercial flow for each management price (step S368a). In the following, the example of a management price of 4.6 (10,000 yen) is illustrated, but the expected value of the total contribution profit of the management main part, the distribution department and the entire commercial flow is calculated for other management prices by the same processing. Can do. FIG. 9 shows the relationship of the expected value (expected contribution profit) of the total contribution profit of the management main part, the distribution department and the entire commercial distribution with respect to each management price.

-Expected value of the total contribution profit of the management entity corresponding to the total contribution profit of 21.56 (10,000 yen) + end price of 5.6 (10,000 yen) corresponding to the end price of 5.4 (10,000 yen) Total contribution profit of management entity corresponding to total contribution profit of 58.685 (10,000 yen) + end price 5.8 (10,000 yen) of management body section 20.24 (10,000 yen) + end price 6.0 (10,000 yen) ) Management entity's total contribution profit 4.4 (10,000 yen) + terminal price 6.2 (10,000 yen) Management entity's total contribution profit 0 (10,000 yen) + terminal price 6.4 ( Management entity's total contribution profit corresponding to 0 (10,000 yen) + management entity's total contribution profit corresponding to end price 6.6 (10,000 yen) = 10,000 (10,000 yen) = total contribution of management entity Expected value of profit 104.885 (10,000 yen)

-Expected value of total contribution profit of distribution department Distribution department corresponding to total contribution profit of 5.88 (10,000 yen) + end price 5.6 (10,000 yen) corresponding to end price 5.4 (10,000 yen) Corresponding to total contribution profit of 12.88 (10,000 yen) + end price of 6.0 (10,000 yen) in the distribution department corresponding to total contribution profit of 26.675 (10,000 yen) + end price of 5.8 (10,000 yen) Corresponding to the total contribution profit of the distribution department corresponding to the total contribution profit 3.6 (10,000 yen) + end price 6.2 (10,000 yen) of the distribution department 0 (10,000 yen) + end price 6.4 (10,000 yen) Distribution Department Total Contribution Profit 0 (10,000 Yen) + Distribution Department Total Contribution Profit 0 (10,000 Yen) corresponding to terminal price 6.6 (10,000 Yen) = Expected Distribution Department Total Contribution Profit 49.035 (10,000 Yen) Circle)

・ Expected value of the total contribution profit of the entire commercial flow Corresponds to the total contribution profit of 27.44 (10,000 yen) + end price 5.6 (10,000 yen) corresponding to the end price 5.4 (10,000 yen) Total contribution profit of the entire commercial flow corresponding to total contribution profit of 85.36 (10,000 yen) + end price 5.8 (10,000 yen) of the entire commercial flow 33.12 (10,000 yen) + end price 6.0 (10,000 yen) ) The total contribution profit of the entire merchandise corresponding to) is 8.0 (10,000 yen) + end price 6.2 (10,000 yen) The total contribution profit of the entire merchandise corresponding to 0 (10,000 yen) + the end price 6.4 ( The total contribution profit of the entire commercial flow corresponding to 10,000 yen) The total contribution profit of the entire commercial flow corresponding to the end price 6.6 (10,000 yen) 0 (10,000 yen) = the total contribution of the entire commercial flow Expected value of profit 153.92 (10,000 yen)

  Here, since the optimization condition designated by the user is “maximization”, as shown in FIG. 6, the management price with the largest expected value of the total contribution profit of the entire commercial flow is the management price 4. 8 (10,000 yen). Therefore, the probability distribution calculation unit 16 selects the management price 4.8 (10,000 yen) corresponding to the expected value of the total contribution profit of the entire commercial flow having the highest value as a solution that satisfies the optimization condition. The output control unit 17 controls the management price 4.8 (10,000 yen) selected as a solution satisfying the optimization condition by the probability distribution calculation unit 16 and the entire commercial flow corresponding to the management price 4.8 (10,000 yen). Display the total contribution profit on the display panel.

  The display items on the display panel are not limited to the management price that is the solution that satisfies the optimization condition and the total contribution profit of the entire commercial flow corresponding to the management price, but each item (terminal price, Manufacturer CM, Distribution CM, Predicted Quantity, Manufacturer Total CM, Distribution Total CM, Total CM, Distribution Probability, Manufacturer (Manufacturer Total CMx Probability), Distribution (Distribution Total CMx Occurrence Probability) Derived statistical information such as variance value of total contribution profit, x sigma point, etc. may be displayed on the display panel.

  As described above, according to the present embodiment, the expected effect for each management price in the multistage commercial flow (in the above example, the expected value of the total contribution profit of the entire commercial flow) is calculated, and among these expected effects Since the management price that satisfies the specified optimization condition is selected and displayed as a solution, the user should plan the sales conditions (management conditions) of the management entity in the multi-stage commercial flow with reference to the displayed management price. Is possible.

  Next, another operation example of the information processing apparatus according to the present embodiment will be described. This operation example is different from the above-described operation example in step S36 in FIG. 3, and FIG. 13 shows details of step S36 in FIG. 3 in this operation example. In step S32 and step S34 in FIG. 3 in this operation example, it is assumed that the demand prediction model for the product a and the end condition probability model for the product a are selected as in the above-described operation example.

  Since the demand forecast model and end condition probability model of the product a are set in step S32 and step S34, the probability distribution calculation unit 15 changes the demand a from the demand prediction management table 11 and the management price-end price management table 13 to the product a. The corresponding record is read (step S361b). In addition, when there is a constraint condition input together with an optimization target index and optimization condition designation input, only records satisfying the constraint condition are read from the demand prediction management table 11 and the management price-end price management table 13. Here, similarly to the above-described operation example, the upper and lower limits of the management price are 4.6 (10,000 yen) to 5.4 (10,000 yen), and the upper and lower limits of the end price are 5.4 (10,000 yen) to 6. It is assumed that 6 (10,000 yen) has been input. Therefore, the probability distribution calculation unit 16 reads only the records satisfying the upper and lower limits 5.4 (10,000 yen) to 6.6 (10,000 yen) from the demand forecast management table 11, and the management price-end price management table. From 13 only records that satisfy both the upper and lower limits of the management price 4.6 (10,000 yen) to 5.4 (10,000 yen) and the upper and lower limits of the end price 5.4 (10,000 yen) to 6.6 (10,000 yen) Is read.

  Also in this operation example, as shown in FIGS. 14-1 (a) to (e), the forecast quantity for each terminal price read from the demand forecast management table 11 takes the same value as the value shown in FIG. Subsequently, the probability distribution calculation unit 16 takes statistics of the appearance frequency of each terminal price for each management price in the record read from the management price-terminal price management table 13, and obtains the probability distribution of the terminal price from the statistical value ( Step S362b). Also in this operation example, as shown in FIGS. 14A to 14E, the probability distribution of each terminal price takes the same value as the value shown in FIG.

  Here, it is assumed that the optimization target index specified in this operation example is “expected value (expected quantity) of predicted demand (predicted quantity) in commercial flow” or “expected value of total contribution profit of the entire commercial flow”. . The probability distribution calculation unit 16 calculates the expected quantity corresponding to each terminal condition for each management condition by multiplying the corresponding predicted quantity and the occurrence probability for each terminal condition (step S363b).

  Subsequently, the probability distribution calculation unit 16 calculates the expected quantity of each management price by totaling the expected quantities corresponding to each terminal condition (step S364b).

  Subsequently, the probability distribution calculation unit 16 reads (manufacturing cost, distribution cost) corresponding to the product a from the cost management table 12 (step S365b). For each management price, the contribution profit (manufacturer CM, distribution CM) of the management main body part and the distribution part per product a corresponding to each terminal price is calculated (step S366b). The contribution profit of the management main body part per product a corresponding to each terminal price for each management price is obtained by subtracting the manufacturing cost from the management price (see FIGS. 14-2 (a) to (e)), The contribution profit of the distribution department per product a corresponding to each terminal price for each management price is obtained by subtracting the management price and the distribution cost from the terminal price (see FIGS. 14-2 (a) to (e)). ).

  Subsequently, the probability distribution calculation unit 16 adds the contribution profit of the management main part per product a and the contribution profit of the distribution department per product a, thereby obtaining the per product a corresponding to each terminal price. The contribution profit (commercial flow CM) of the entire commercial flow is obtained (step S367b).

  Subsequently, the probability distribution calculation unit 16 calculates an expected value (manufacturer total CM, total distribution CM, total CM) of the total contribution profit of the management main unit, the distribution unit, and the entire commercial flow corresponding to each terminal price (step) S368b). That is, the probability distribution calculation unit 16 multiplies the contribution profit of the management main body part per product a by the expected quantity, thereby calculating the expected value of the total contribution profit of the management main body corresponding to each terminal price for each management price. , And multiplying the distribution department contribution profit per product a by the expected quantity, the expected value of the distribution department total contribution profit corresponding to each end condition is calculated for each management price, and one product a The expected value of the total contribution profit of the entire commercial flow corresponding to each end condition is calculated for each management price by multiplying the contribution profit of the entire commercial flow and the expected quantity.

  Subsequently, the probability distribution calculation unit 16 calculates the expected value of the total contribution profit of the management main body unit, the distribution unit, and the entire commercial flow for each management price (step S369b). That is, the probability distribution calculation unit 16 aggregates the expected value of the total contribution profit of the management entity for each management price by aggregating a value obtained by multiplying the total contribution profit of the management entity corresponding to each terminal price by each occurrence probability. To calculate the expected value of the total contribution profit of the distribution department for each management price, by summing up the total contribution profit of the distribution department corresponding to each end price and the probability of each occurrence. By summing up the total contribution profit of the entire commercial flow corresponding to the occurrence probability, the expected value of the total contribution profit of the entire commercial flow is calculated for each management price.

  Here, the optimization target index specified by the user was “expected value of predicted demand in commercial flow” or “expected value of total contribution profit of the entire commercial flow”, and the optimization condition was “maximization”. As shown in 14-2, the management price at which the expected value (expected quantity) of the predicted demand in the commercial flow is the maximum is the management price 4.6 (10,000 yen), and the expected value of the total contribution profit of the entire commercial flow The management price with the largest is the management price of 4.8 (10,000 yen). Accordingly, the probability distribution calculation unit 16 corresponds to the management price 4.6 (10,000 yen) corresponding to the maximum expected value of the predicted demand in the commercial flow and the maximum expected value of the total contribution profit of the entire commercial flow. A management price of 4.8 (10,000 yen) is selected as a solution that satisfies the optimization condition.

  The output control unit 17 has a management price of 4.6 (10,000 yen), an expected value of predicted demand in the commercial flow corresponding to the management price of 4.6 (10,000 yen), 95.35 (pieces), a management price of 4.8 (10,000 yen). Yen) and the expected value 160.14 (10,000 Yen) of the total contribution profit of the entire commercial flow corresponding to the management price 4.8 (10,000 Yen) are displayed on the display panel in association with each other. In this operation example, as in the above-described operation example, information corresponding to an arbitrary item among the items illustrated in FIG. 14B may be displayed on the display panel.

  According to the above operation example, the expected effect for each management price (in the above example, the entire commercial flow corresponding to a plurality of specified optimization targets (expected value and sales volume of the total contribution profit of the entire commercial flow) The expected value of the total contribution profit) is calculated, and a management price that satisfies the optimization condition corresponding to each of the plurality of optimization target indexes is selected and displayed as a solution. Therefore, the user can plan the sales conditions (management conditions) of the management entity in the multi-stage commercial flow with reference to both solutions.

  Another example of the optimization target index applicable to this information processing apparatus is the cumulative distribution probability of the total contribution profit of the entire commercial flow. In this case, the information processing apparatus obtains the total contribution profit of the entire commercial flow corresponding to each terminal price for each management price by the same process as described above, and arranges the obtained total contribution profit of the entire commercial flow in ascending order for each management price. In this order, the corresponding distribution probabilities are cumulatively added. FIG. 10 shows the results (cumulative distribution probability) of the total contribution profits of the entire commercial flow arranged in ascending order and the distribution probabilities accumulated for every 5 (10,000 yen) in the arranged order for each management price. FIG. 11 shows the relationship of the cumulative distribution probability of each management price with respect to the total contribution profit of the entire commercial flow. The optimization condition in this case includes maximization of the cumulative distribution probability corresponding to the total contribution profit designated by the user. In this case, the probability distribution calculation unit 16 selects the management price that maximizes the cumulative distribution probability corresponding to the designated total contribution profit as a solution that satisfies the optimization condition.

  In the above description, as the optimization target index, the expected value of the total contribution profit of the entire commercial flow, the sales quantity in the commercial flow, and the cumulative distribution probability of the total contribution profit of the entire commercial flow are exemplified. It is possible to specify the optimization target index. In the optimization target index, an objective variable and an optimization target can be designated broadly. The objective variables that can be specified are the sales volume and the contribution profit in the above example, and in addition, the operating profit and the sales ratio of the sales promotion expenses can be specified. The optimization target that can be specified is the expected value and cumulative distribution probability in the above example. In addition, the mode value of the objective variable and the probability that the objective function satisfies a certain condition can be specified. is there. In this information processing apparatus, it is possible to specify a combination of these objective variables and optimization targets as optimization target indexes. Furthermore, in the above description, a discrete model is used as the demand prediction model and a discrete probability model is used as the terminal price probability model. However, a continuous model based on a specific function type can be used.

  Furthermore, in this embodiment, as shown in FIGS. 5 and 14-2, in addition to the expected value of the total contribution profit of the entire commercial flow, it is possible to calculate the expected value of the total contribution profit of the management main body and the distribution department. is there. In the above, since the “expected value of the total contribution profit of the entire commercial flow” is specified as the optimization target index, the operation of optimizing the expected value of the total contribution profit of the entire commercial flow has been described. The expected value of the total contribution profit may be specified by the optimization target index. In this case, the information processing apparatus obtains the expected value of the total contribution profit of the designated management entity or distribution department for each management price, and selects an optimal solution among them. As described above, according to the present embodiment, it is possible to optimize the expected effect not only in the entire commercial flow but also in a part of the commercial flow (management main body, distribution unit).

  Another object of the present invention is to supply a storage medium storing software program codes for realizing the functions of the above-described embodiments to a system or apparatus, and the computer (or CPU or MPU) of the system or apparatus stores the storage medium. Needless to say, this can also be achieved by reading and executing the program code stored in.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the program code itself and the storage medium storing the program code constitute the present invention.

  As a storage medium for supplying the program code, for example, a flexible disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (basic system or operating system) running on the computer based on the instruction of the program code. Needless to say, a case where the functions of the above-described embodiment are realized by performing part or all of the actual processing and the processing is included.

  Further, after the program code read from the storage medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function is determined based on the instruction of the program code. It goes without saying that the CPU or the like provided in the expansion board or function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing.

It is a block diagram which shows the function structure of the information processing apparatus which concerns on one Embodiment of this invention. It is a figure which shows roughly the hardware constitutions of the computer system in information processing apparatus. It is a flowchart which shows the flow of operation | movement of information processing apparatus. It is a flowchart which shows in detail step S36 of FIG. 3 when the expected value of the contribution profit of the whole commercial flow is specified as the optimization target index and maximization is specified as the optimization condition. It is a figure which shows the various calculation results with respect to each terminal price for every management price. It is a figure which shows the calculation result of the expected value of the total contribution profit of the management main part for every management price, a distribution part, and the whole commercial flow. It is a figure which shows the relationship of the predicted quantity with respect to a terminal price. It is a figure which shows the relationship of the management main part, the distribution part, and the total contribution profit of the whole commercial flow with respect to each terminal price in one management price. It is a figure which shows the relationship of the expected value of the total contribution profit of the management main part, a distribution part, and the whole commercial flow with respect to each management price. It is a figure which shows the result (cumulative distribution probability) for every management price which arranged the total contribution profit of the whole commercial flow in ascending order, and accumulated distribution probability every 5 (10,000 yen) in the arranged order. It is a figure which shows the relationship of the cumulative distribution probability in each management price with respect to the total contribution profit of the whole commercial flow. It is a figure which shows an example of a multistage commercial flow typically. It is a flowchart which shows the other operation example of step S36 in FIG. It is a figure which shows the various calculation results with respect to each terminal price for every management price. It is a figure which shows the various calculation results with respect to each terminal price for every management price.

Explanation of symbols

11: Demand prediction management table 12: Cost management table 13: Management price-end price management table 14: Demand prediction model setting unit 15: End condition probability model setting unit 16: Probability distribution calculation unit 17: Output control unit

Claims (28)

Predicted demand setting means for setting the predicted demand of the product for each of one or more terminal conditions related to the sale of the product by the terminal subject in a multi-stage commercial flow;
Realization frequency calculation means for calculating the realization frequency of each of the end conditions for the corresponding management condition for each of one or more management conditions related to the sale of the product by the management entity in the multi-stage commercial flow;
An information processing apparatus comprising: a first expected effect calculation unit that calculates an expected effect related to the predicted demand in the multistage commercial flow for each management condition based on the predicted demand and the realization frequency. . Based on the management condition and the terminal condition, profit calculating means for calculating the profit per product of the entire multi-stage commercial flow corresponding to the terminal condition for each management condition;
Based on the predicted demand and the realization frequency, an expected effect related to the predicted demand of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition, and the multiple corresponding to each terminal condition is calculated. Based on the profit per product of the entire stage commercial flow and the expected effect on the predicted demand of the entire multi-stage commercial flow corresponding to each end condition, it relates to the profit of the entire multi-stage commercial flow The information processing apparatus according to claim 1, further comprising: a second expected effect calculation unit that calculates an expected effect for each management condition.   The profit calculation means is based on the management condition, and per product of the management main body part, which is a part including the management main body corresponding to each end condition to the main body in which the management main body sets the management condition. And the merchandise of the distribution section which is a part excluding the management main body from the multi-stage commercial flow corresponding to each terminal condition based on the management condition and the terminal condition. Profit per one is calculated for each management condition, the profit per product of the management main body corresponding to each terminal condition, and the one commodity of the distribution section corresponding to each terminal condition 3. The information processing according to claim 2, wherein the profit per product of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition based on the profit per hit. Dress .   The second expected effect calculation means calculates the profit per product of the management main body corresponding to each terminal condition and the predicted demand of the entire multi-stage commercial flow corresponding to each terminal condition. Based on the expected effect, the expected effect related to the profit of the management main body part is calculated for each management condition, the profit per product of the distribution unit corresponding to each end condition, and the respective The expected effect related to the profit of the distribution department is calculated for each management condition based on the expected effect related to the predicted demand of the entire multi-stage commercial flow corresponding to the end condition. Information processing device. As the calculation target of the expected effect related to the profit by the second expected effect calculation means, the expected effect related to the profit of the multistage commercial flow, the expected effect related to the profit of the management entity, and the profit of the distribution department A calculation target specifying means for specifying at least one of the expected effects;
5. The information processing apparatus according to claim 4, wherein the second expected effect calculation unit calculates an expected effect related to a profit corresponding to a content specified by the calculation target specifying unit for each management condition. Predicted demand setting means for setting the predicted demand of the product for each of one or more end conditions related to the sale of the product by the terminal subject in a multi-stage commercial flow;
Realization frequency calculation means for calculating the realization frequency of each of the end conditions for the corresponding management condition for each of one or more management conditions related to the sale of the product by the management entity in the multi-stage commercial flow;
Profit calculation means for calculating the profit in the multistage commercial flow corresponding to each terminal condition for each management condition based on the management condition, the terminal condition and the predicted demand, or the management condition and the predicted demand When,
Based on the realization frequency and the profit in the multi-stage commercial flow corresponding to each terminal condition, an expected effect calculating means for calculating the expected effect related to the profit in the multi-stage commercial flow for each management condition An information processing apparatus characterized by that.   The profit calculation means calculates, for each management condition, the profit per product of the entire multi-stage commercial flow corresponding to each terminal condition based on the management condition and the terminal condition, and the predicted demand And, based on the profit per product of the entire multi-stage commercial flow corresponding to each terminal condition, the profit of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition The information processing apparatus according to claim 6.   The profit calculation means is based on the management condition, and per product of the management main body part, which is a part including the management main body corresponding to each end condition to the main body in which the management main body sets the management condition. And the merchandise of the distribution section which is a part excluding the management main body from the multi-stage commercial flow corresponding to each terminal condition based on the management condition and the terminal condition. Profit per one is calculated for each management condition, the profit per product of the management main body corresponding to each terminal condition, and the one commodity of the distribution section corresponding to each terminal condition 8. The information processing according to claim 7, wherein the profit per product for the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition based on the profit per hit. Dress .   The profit calculating means, based on the profit per product of the management main body corresponding to each end condition, and the profit of the management main body corresponding to each end condition based on the predicted demand While calculating for each management condition, the profit per product of the distribution unit corresponding to each terminal condition, and the profit of the distribution unit corresponding to each terminal condition based on the predicted demand The expected effect calculation means calculates the expected effect related to the profit of the management main body for each management condition based on the profit of the management main body corresponding to each end condition and the realization frequency. And calculating an expected effect related to the profit of the distribution unit for each management condition based on the profit of the distribution unit corresponding to each terminal condition and the realization frequency. The information processing apparatus according to.   The profit calculating means manages the profit of the management main body corresponding to each terminal condition and the profit of the distribution section corresponding to each terminal condition based on the management condition, the terminal condition and the predicted demand. Calculated for each condition, and based on the profit of the management main body corresponding to each end condition and the profit of the distribution section corresponding to each end condition, the entire multi-stage commercial flow corresponding to each end condition The information processing apparatus according to claim 6, wherein a profit is calculated for each management condition.   The profit calculation means calculates the profit per product of the management main body corresponding to each terminal condition based on the management condition for each management condition, and sets the management condition and the terminal condition. Based on the management conditions, the profit per product of the distribution unit corresponding to the terminal conditions, the profit per product of the management main unit corresponding to the terminal conditions, And, based on the predicted demand, the profit of the management main body corresponding to each terminal condition is calculated for each management condition, and the profit per product of the distribution section corresponding to each terminal condition The information processing apparatus according to claim 10, wherein, based on the predicted demand, the profit of the distribution unit corresponding to each terminal condition is calculated for each management condition.   The expected effect calculation means calculates, for each management condition, an expected effect related to the profit of the management main body based on the profit of the management main body corresponding to each end condition and the realization frequency, The expected effect related to the profit of the distribution unit is calculated for each management condition based on the profit of the distribution unit corresponding to each terminal condition and the realization frequency. The information processing apparatus described. As the calculation target of the expected effect related to the profit by the expected effect calculating means, the expected effect related to the profit of the entire multistage commercial flow, the expected effect related to the profit of the management main body, and the expectation related to the profit of the distribution department A calculation target specifying means for specifying at least one of the effects;
The information processing apparatus according to claim 9, wherein the expected effect calculation unit calculates an expected effect related to a profit corresponding to the content specified by the calculation target specifying unit for each management condition. An information processing method by an information processing apparatus,
A predicted demand setting step for setting a predicted demand of the product for each of one or a plurality of end conditions related to the sale of the product by the terminal subject in a multi-stage commercial flow;
A realization frequency calculating step for calculating a realization frequency of each of the terminal conditions for the corresponding management condition for each one or a plurality of management conditions related to the sale of the product by the management entity in the multistage commercial flow;
A first expected effect calculation step of calculating, for each management condition, an expected effect related to the predicted demand in the multistage commercial flow based on the predicted demand and the realization frequency. . Based on the management condition and the terminal condition, a profit calculating step for calculating profit per product for the entire multi-stage commercial flow corresponding to the terminal condition for each management condition;
Based on the predicted demand and the realization frequency, an expected effect related to the predicted demand of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition, and the multiple corresponding to each terminal condition is calculated. Based on the profit per product of the entire stage commercial flow and the expected effect on the predicted demand of the entire multi-stage commercial flow corresponding to each end condition, it relates to the profit of the entire multi-stage commercial flow The information processing method according to claim 14, further comprising a second expected effect calculation step of calculating an expected effect for each management condition.   In the profit calculating step, based on the management condition, per product in the management main body part that is a part including the management main body corresponding to each end condition to the main body in which the management main body sets the management condition And the merchandise of the distribution section which is a part excluding the management main body from the multi-stage commercial flow corresponding to each terminal condition based on the management condition and the terminal condition. Profit per one is calculated for each management condition, the profit per product of the management main body corresponding to each terminal condition, and the one commodity of the distribution section corresponding to each terminal condition 16. The information according to claim 15, wherein the profit per product of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition based on the profit per hit. Processing method.   In the second expected effect calculation step, the profit per product of the management main body corresponding to each terminal condition and the predicted demand of the entire multi-stage commercial flow corresponding to each terminal condition Based on the expected effect, the expected effect related to the profit of the management main body is calculated for each management condition, the profit per product of the distribution unit corresponding to each end condition, and each The expected effect related to the profit of the distribution unit is calculated for each management condition based on the expected effect related to the predicted demand of the entire multi-stage commercial flow corresponding to the end condition. Information processing method. As the calculation target of the expected effect related to the profit in the second expected effect calculation step, the expected effect related to the profit of the multistage commercial flow, the expected effect related to the profit of the management entity, and the profit of the distribution department A calculation target designating step for designating at least one of the expected effects.
The information processing method according to claim 17, wherein, in the second expected effect calculation step, an expected effect related to a profit corresponding to the content specified by the calculation target specifying step is calculated for each management condition. An information processing method by an information processing apparatus,
A predicted demand setting step for setting a predicted demand of the product for each of one or a plurality of end conditions related to the sale of the product by the terminal subject in a multi-stage commercial flow;
A realization frequency calculating step for calculating a realization frequency of each of the terminal conditions for the corresponding management condition for each one or a plurality of management conditions related to the sale of the product by the management entity in the multistage commercial flow;
Profit calculation step for calculating profits in the multi-stage commercial flow corresponding to the terminal conditions for each of the management conditions based on the management conditions, the terminal conditions and the predicted demand, or the management conditions and the predicted demand When,
An expected effect calculation step of calculating an expected effect related to profit in the multistage commercial flow for each management condition based on the realization frequency and the profit in the multistage commercial flow corresponding to each terminal condition. An information processing method characterized by the above.   In the profit calculation step, based on the management condition and the terminal condition, the profit per product of the entire multistage commercial flow corresponding to each terminal condition is calculated for each management condition, and the predicted demand And, based on the profit per product of the entire multi-stage commercial flow corresponding to each terminal condition, the profit of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition The information processing method according to claim 19.   In the profit calculating step, based on the management condition, per product in the management main body part that is a part including the management main body corresponding to each end condition to the main body in which the management main body sets the management condition And the merchandise of the distribution section which is a part excluding the management main body from the multi-stage commercial flow corresponding to each terminal condition based on the management condition and the terminal condition. Profit per one is calculated for each management condition, the profit per product of the management main body corresponding to each terminal condition, and the one commodity of the distribution section corresponding to each terminal condition 21. The information according to claim 20, wherein the profit per product of the entire multi-stage commercial flow corresponding to each terminal condition is calculated for each management condition based on the profit per hit. Processing method.   In the profit calculation step, the profit per product of the management entity corresponding to each terminal condition, and the profit of the management entity corresponding to each terminal condition based on the predicted demand While calculating for each management condition, the profit per product of the distribution unit corresponding to each terminal condition, and the profit of the distribution unit corresponding to each terminal condition based on the predicted demand Calculated for each management condition, and in the expected effect calculation step, the expected effect related to the profit of the management main body is calculated for each management condition based on the profit of the management main body corresponding to each end condition and the realization frequency. And the expected effect related to the profit of the distribution section is calculated for each management condition based on the profit of the distribution section corresponding to each end condition and the realization frequency. The information processing method according to claim 21.   In the profit calculation step, based on the management condition, the terminal condition and the predicted demand, the management main body corresponding to each terminal condition and the profit of the distribution section corresponding to each terminal condition are managed. Calculated for each condition, and based on the profit of the management main body corresponding to each end condition and the profit of the distribution section corresponding to each end condition, the entire multi-stage commercial flow corresponding to each end condition The information processing method according to claim 19, wherein a profit is calculated for each management condition.   In the profit calculation step, based on the management condition, the profit per product of the management main body corresponding to each terminal condition is calculated for each management condition, and the management condition and the terminal condition are calculated. Based on the management conditions, the profit per product of the distribution unit corresponding to the terminal conditions, the profit per product of the management main unit corresponding to the terminal conditions, And, based on the predicted demand, the profit of the management main body corresponding to each terminal condition is calculated for each management condition, and the profit per product of the distribution section corresponding to each terminal condition 24. The information processing method according to claim 23, wherein the profit of the distribution unit corresponding to each terminal condition is calculated for each management condition based on the predicted demand.   In the expected effect calculation step, based on the profit of the management main body corresponding to each end condition and the realization frequency, the expected effect related to the profit of the management main body is calculated for each management condition, 25. The expected effect related to the profit of the distribution unit is calculated for each management condition based on the profit of the distribution unit corresponding to each terminal condition and the realization frequency. The information processing method described. As the calculation target of the expected effect related to the profit in the expected effect calculation step, the expected effect related to the profit of the entire multi-stage commercial flow, the expected effect related to the profit of the management entity, and the expectation related to the profit of the distribution department A calculation target specifying step for specifying at least one of the effects;
26. The information processing method according to claim 22 or 25, wherein, in the expected effect calculation step, an expected effect related to a profit corresponding to the content specified in the calculation target specifying step is calculated for each management condition.   The program for making a computer perform the function of the information processing apparatus of any one of Claims 1 thru | or 13. A program for causing a computer to execute the information processing method according to any one of claims 14 to 26.

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