JP6829400B2 - Information processing equipment, control methods, and programs - Google Patents

Description

The present invention relates to a technique for forecasting demand for goods and the like.

As for the demand forecast calculated from the past demand record, the accuracy of the demand forecast is higher as the latest, and the accuracy of the forecast is lower as the earlier.

The present invention is an information processing device and information that makes it possible to make an appropriate forecast for a future forecast whose forecast accuracy becomes low by utilizing the latest sales (sales) plan for the demand forecast calculated from the past demand record. Regarding the processing method.

Normally, when forecasting the demand for products, etc., the forecast is made after this month (this week) based on the past demand results up to the previous month (previous week) (see, for example, Patent Document 1).

JP-A-2007-293623

However, the accuracy of the demand forecast is higher in the latest month (week), and the accuracy of the forecast is lower in the earlier months.

This is because if the market environment in the future is different from the current situation, it is not possible to properly grasp the demand trend in the future from the past demand record.

On the other hand, there are cases where a sales (sales) plan is made while utilizing the demand forecast, and this plan is made by performing human purchasing work based on the demand forecast.

Furthermore, the sales (sales) plan is generally fixed for a certain period of time in monthly and weekly operations, for example, the plan for the next month is finalized by the 20th of each month.

The fixed period plan is used as input information for the production plan and ordering plan of subsequent operations, and the sales (sales) plan after the fixed period is used for load adjustment of the manufacturing line, material procurement plan, personnel plan, budget management, etc. There are many cases.

Therefore, in general, the sales plan for the fixed period has high accuracy of the demand forecast as the base, and the planning accuracy is also high because the information such as the latest market trend is taken into consideration by human beings.

However, the accuracy of the base demand forecast for sales plans after the fixed period is low, and the accuracy of the plan is low because it is not possible to accurately grasp the future factors that affect demand, which may affect subsequent related operations. Have sex

As mentioned above, if the market environment in the future is different from the current situation, it may not be possible to make an appropriate forecast because it is difficult to properly grasp future demand trends from past demand results.

Also, in the case of a new product that has no past demand record, for example, there are cases where a sales plan for the next few months is drafted by another system before launch, but future forecast results are required for future material procurement, etc. In some cases,

The present invention has been made in view of such problems, and an object thereof is to provide a mechanism that can accurately forecast the product.

The present invention for solving the above problems is an information processing device for obtaining a demand prediction result of a product by a forecasting means, and is an acquisition means for acquiring information on a sales plan value of the product based on an arbitrary period, and the acquisition. Using the information on the sales plan value based on the arbitrary period acquired by the means and the demand record, the demand forecast result predicted by the forecasting means and the demand record without using the information on the sales plan value are used. It is characterized by including an output means for outputting a demand forecast result predicted by the forecast means.

According to the present invention, by performing demand forecast for product by using the information about the sales plan, it is possible to accurately forecast the product, an effect that.

It is a block diagram which shows the functional structure of the demand forecast calculation apparatus. It is a block diagram which shows the schematic structure of the hardware of the information processing apparatus applicable to a demand forecast calculation apparatus. It is a flowchart which shows the demand forecast processing. It is a block diagram which shows the structure of the product information DB. It is a block diagram which shows the structure of the demand record DB 103. It is a block diagram which shows the structure of the prediction model information DB. It is a block diagram which shows the structure of the prediction result DB. It is a block diagram which shows the structure of the prediction re-execution result DB. It is a block diagram which shows the structure of the sales plan DB. It is a block diagram which shows the structure of the product information setting screen. It is a flowchart which shows the detail of the prediction execution processing. It is a block diagram which shows the structure of the sales plan input screen. It is a flowchart which shows the detail of the prediction re-execution determination processing. It is explanatory drawing for demonstrating an example of cumulative sales plan error (rate). It is explanatory drawing for demonstrating an example of the cumulative demand forecast error (rate). It is explanatory drawing for demonstrating the example that the accuracy of the sales plan in a fixed period is good, but the demand forecast using the sales plan value is invalid. It is a flowchart which shows the detail of the prediction re-execution process. It is explanatory drawing for demonstrating that the demand forecast after a fixed period was performed using the sales plan value. It is a block diagram which shows the structure of the sales plan input screen.

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

FIG. 1 is a configuration diagram showing an example of a functional configuration and the like of a demand forecast calculation device 100, which is an example of an information processing device (computer).

As shown in FIG. 1, the demand forecast calculation device 100 according to the present embodiment includes a storage unit 101 for storing data required for processing or the like executed by the demand forecast calculation device 100, and a product information setting unit. It includes 108, a prediction execution unit 109, a sales plan input unit 110, a prediction re-execution determination unit 111, a prediction re-execution unit 112, and a prediction result confirmation unit 113.

The storage unit 101 includes a product information DB 102, a demand record DB 103, a forecast model information DB 104, a forecast result DB 105, a forecast re-execution result DB 106, and a sales plan DB 107.

The product information DB 102 stores product information related to the product. For example, as shown in FIG. 4, the product code, the product name, the confirmation period, the cycle, whether or not the sales plan is used, the prediction re-execution determination flag, and the error evaluation period. , A database with items such as the cumulative period of forecast errors and the threshold of sales planning errors.

These product information are registered in the product information DB 102 by setting the product information in the product information setting unit 108. The setting of product information will be described later.

The demand record DB 103 accumulates past demand record values for each product and each day. For example, as shown in FIG. 5, the demand record DB 103 includes items such as a product code, a date when a product is requested, and a demand record. It is a database.

The prediction model information DB 104 stores various predictable prediction models (for example, moving average, exponential smoothing, etc.). For example, as shown in FIG. 6, the prediction model and the prediction indicating the parameters used in the prediction model are shown. It is a database having items such as model parameter 1, prediction model parameter 2, ...

The forecast result DB 105 stores the result of forecasting the demand of the product. For example, as shown in FIG. 7, the product code, the forecast calculation starting date, the demand forecast value 1, the demand forecast value 2, and the demand forecast value are stored. It is a database with items such as 3, ....

As the result of these forecasts, the result of the demand forecast executed by the forecast execution unit 109 is stored. The details of the demand forecast executed by the forecast execution unit 109 will be described later.

The forecast calculation start date means the cycle start date of the date when the forecast execution unit 109 executes the forecast calculation of the demand.

Further, the cycle means a calculation unit of a demand forecast. For example, when a forecast value in a month (week) unit is required, the cycle start date is the first day of the month (week).

For example, if the forecast calculation execution date is October 4, 2015 and the forecast unit is month, the forecast calculation starting date is October 1, 2015.

In addition, the demand forecast value stores the calculated value for the forecast calculation period for each cycle from the forecast calculation start date.

For example, if the forecast starting date is October 1, 2015 and the cycle is a month, the forecast value 1 is the forecast value for October, the forecast value 2 is November, and the forecast value 3 is December. Stores the forecast value of.

The forecast re-execution result DB 106 stores the result of recalculating the demand forecast using the sales plan value in the finalized sales plan. For example, as shown in FIG. 8, the product code, the finalization period, and the forecast are stored. It is a database having items such as a calculation starting date, a demand forecast value 1, a demand forecast value 2, a demand forecast value 3, ...

As the result of recalculating the demand forecast using these sales plan values, the result of the demand forecast executed by the forecast re-execution unit 112 is stored. The details of the recalculation of the demand forecast executed by the forecast re-execution unit 112 will be described later.

The forecast calculation start date means the cycle start date of the date when the demand forecast recalculation is performed in the forecast re-execution unit 112.

The demand forecast value stores the calculated value for each cycle before the fixed period for the forecast calculation period.

For example, if the forecast start date is October 1, 2015, the forecast value is monthly, and the fixed period is 1 (month), the demand forecast value 1 does not store anything, and the demand forecast value 2 is November. , Demand forecast value 3 stores the demand forecast value for December.

The sales plan DB 107 stores information related to the sales plan of the product. For example, as shown in FIG. 9, the product code, the sales plan starting date, the sales plan value 1, the sales plan value 2, and the sales plan value 3 are stored. It is a database with items such as, ...

As the information related to these sales plans, the information input by the sales plan input unit 110 and the information taken in from the external system are stored. The sales plan input unit 110 will be described later.

The sales plan start date means the cycle start date of the date when the sales plan is taken in from the sales plan input unit 110 or the external system and the sales plan is finalized.

For example, if a monthly (weekly) sales plan value is required, the cycle start date is the first day of the month (week).

As an example, if the final date of the sales plan is October 5, 2015 and the sales plan unit is a month, the starting date of the sales plan is October 1, 2015.

In addition, the sales plan value stores the sales plan value for the fixed period for each cycle.

For example, if the starting date of the sales plan is October 1, 2015, the fixed period is 2 (months), and the cycle is a month, the sales plan value 1 is the sales plan value for October, and the sales plan value 2 is. Stores the sales plan value for November.

FIG. 2 is a diagram showing an example of the hardware configuration of the demand forecast calculation device 100.

In FIG. 2, 201 is a CPU that comprehensively controls each device and controller connected to the system bus 204.

Further, the ROM 202 or the external memory 211 is necessary to realize a function executed by a BIOS (Basic Input / Output System) or an operating system program (hereinafter, OS) which is a control program of the CPU 201, and each server or each PC. Various programs described later are stored.

Reference numeral 203 denotes a RAM, which functions as a main memory, a work area, and the like of the CPU 201. The CPU 201 realizes various operations by loading a program or the like necessary for executing a process from the ROM 202 or the external memory 211 into the RAM 203 and executing the loaded program.

Reference numeral 205 denotes an input controller, which controls input from a keyboard (KB) 209, a pointing device such as a mouse (not shown), or the like. Reference numeral 206 denotes a video controller, which controls the display on a display such as a CRT display (CRT) 210. Although it is described as CRT210 in FIG. 2, the display may be not only the CRT but also another display such as a liquid crystal display. These are used by the administrator as needed.

Reference numeral 207 is a memory controller, which is connected to a hard disk (HD) for storing boot programs, various applications, font data, user files, edit files, various data, etc., a flexible disk (FD), or a PCMCIA card slot via an adapter. It controls access to an external memory 211 such as a compact flash (registered trademark) memory.

Reference numeral 208 denotes a communication I / F controller, which connects and communicates with an external device via a network (for example, LAN600 shown in FIG. 1), and executes communication control processing on the network. For example, communication using TCP / IP is possible.

The CPU 201 can display the outline font on the CRT 210 by executing the outline font expansion (rasterization) process in the display information area in the RAM 203, for example. Further, the CPU 201 enables a user instruction with a mouse cursor or the like (not shown) on the CRT 210.

Various programs described later for realizing the present invention are recorded in the external memory 211, and are executed by the CPU 201 by being loaded into the RAM 203 as needed.

Further, a definition file and various information tables used when executing the above program are also stored in the external memory 211, and detailed description of these will be described later.

FIG. 3 is a flowchart showing an example of the demand forecast processing executed by the demand forecast calculation device 100.

In this demand forecasting process, each function unit (product information setting unit 108, forecast execution unit 109, sales plan input unit 110, and forecast re-execution determination unit) showing the computer recorded in the external memory 211 or the like as shown in FIG. The CPU 201 performs this according to the control of a program for operating the computer as the prediction re-execution unit 112, the prediction result confirmation unit 113), and the prediction re-execution unit 112.

In step S101, the product information setting unit 108 sets the product information necessary for the demand forecast of the product.

At this time, the product information setting unit 108 displays the product information setting screen 300 as shown in FIG. 10 on the CRT 210 and prompts the user to input.

Then, the product information setting unit 108 receives the information input via the product information setting screen 300.

In addition, regarding the setting of each item of the product information setting screen 300, the user sets the product information for which the demand forecast is to be performed in the product information setting area 301.

In the product information setting area 301, a product code, a product name, a confirmation period, a cycle, whether or not a sales plan is used, a prediction re-execution judgment flag, an error evaluation period, a prediction error cumulative period, a sales plan error threshold, and the like are set.

This fixed period means an arbitrary period in which the sales plan is used, and when the forecast re-execution unit 112 recalculates the demand forecast, the demand forecast is used from the current month (current week) using the sales plan for the fixed period. To recalculate.

The cycle means the calculation unit of the demand forecast. For example, if the cycle is a month, the predicted value is calculated on a monthly basis, and if the cycle is a week, the predicted value is calculated on a weekly basis.

The cycle is determined by whether the sales plan is monthly or weekly, but the cycle is not necessarily monthly or weekly.

If the sales plan is on a daily basis, the cycle can be set as a day, and the sales plan planning unit may be set.

Whether or not to use the sales plan means whether or not to perform the forecast calculation using the sales plan value determined in the sales plan. If there is no sales plan used, only the forecast calculation from the actual demand is performed.

The forecast re-execution determination flag is valid only when the sales plan is used or not, and is a flag indicating whether or not to determine the validity of the forecast calculation using the sales plan value.

If the prediction re-execution determination flag is N, the sales plan is used to perform the prediction re-execution, and if the determination flag is Y, the effectiveness is used to determine whether or not the prediction re-execution is possible using the sales plan.

The error evaluation period, the prediction error accumulation period, and the sales plan error threshold are valid only when the prediction re-execution judgment flag is Y, and are necessary parameters in the error calculation described later. The error evaluation period, the cumulative prediction error period, and the sales planning error threshold will also be described later.

If you want to add product information to the product information setting area 301, press the add button 302 to add a blank record to the product information setting area 301, and set the product information in this record.

If you want to delete the product information displayed in the product information setting area 301, press the delete button 303 with the product information you want to delete selected, and the product information will be deleted and hidden from the product information setting area 301. ..

To save the product information displayed in the product information setting area 301, press the save button 304 to save the product information displayed in the product information setting area 301 in the product information DB 102 and display the product information setting screen 300. To close, press the close button 305.

Returning to the description of FIG. 3 again, in step S302, the forecast execution unit 109 acquires the demand record of the forecast target product in the demand record DB 103 for the product registered in the product information DB 102, and obtains the forecast quantity. calculate.

In step S102, the product registered in the product information DB 102 is processed.

FIG. 11 is a flowchart for explaining the details of the prediction execution process in step S102.

In step S201, the cycle of the forecasted product is acquired from the product information DB 102, the actual demand of the forecasted product up to the previous month (previous week) is acquired from the demand actual DB 103, and the actual demand is totaled according to the cycle.

In step S202, the demand forecast quantity of the forecast product after the current month (current week) is calculated from the demand record aggregated in step S201 and the mathematical forecast model registered in the forecast model information DB 104. The demand forecast quantity calculated at this time is registered in the forecast result DB 105.

In step S203, the process ends when the demand forecast calculation of all the products is completed, and returns to step S201 when the uncalculated products remain.

Returning to the description of FIG. 3 again, in step S103, the demand forecast value of the product calculated in step S102 from the forecast result DB 105 is displayed on the sales plan input screen 400, and the input of the sales plan is prompted.

FIG. 12 shows an example of the configuration of the sales plan input screen 400. On the sales plan input screen 400, in addition to displaying the calculated demand forecast value, the past demand record acquired from the demand record DB 103 is also displayed so that the validity of the demand forecast value can be verified.

Further, in the sales plan input field 401, by displaying the demand forecast value as the default display, it is possible to avoid the omission of the sales plan input.

Note that the sales plan DB 107 is not limited to the registration in this step as long as the information is equivalent to the sales plan, and any method of registration may be used.

When the save button 402 is pressed to save the information input in the input field 401, the input information is registered in the sales plan DB 107, and when the sales plan input screen 400 is closed, the close button 403 is pressed.

For example, if there is unofficial information from a business partner, or if a sales plan is created by another system, it is subject to subsequent processing by registering it in the sales plan DB 107 in advance.

Returning to the description of FIG. 3 again, in step S104, the forecast re-execution determination unit 111 is in the demand record and forecast result DB 105 of the forecast target product in the demand record DB 103 for the product registered in the product information DB 102. Demand forecast value, forecast re-execution result Demand forecast value in DB106 and sales plan value registered in sales plan DB107 are acquired, and forecast re-execution using the sales plan from the error between the demand forecast value and the sales plan value. Is determined whether or not to perform.

In other words, it is judged from the past actual situation whether the market trend inferred from the sales plan for the fixed period can be taken into consideration in the future.

FIG. 13 is a flowchart for explaining the details of the prediction re-execution determination process in step S104.

In step S301, it is determined whether or not the product information of the forecast product is used in the sales plan, the forecast re-execution determination flag is Y, and the confirmation period is greater than 0. That is, it is determined whether or not the forecast using the sales plan value is possible.

If the above conditions are satisfied, the process proceeds to step S302, and if the conditions are not satisfied, the process proceeds to step S307. The presence / absence of the sales plan of the forecast product, the forecast re-execution determination flag, and the confirmation period are registered in the product information DB 102.

In step S302, the actual demand of the forecasted product for a certain period in the past is acquired from the actual demand DB 103, and the past sales plan value of the forecasted product is acquired from the sales plan DB 107, and the cumulative sales plan error for the fixed period is calculated.

There are various methods for calculating the error, but the error calculation method is not particularly specified as long as it represents the discrepancy between the sales plan value and the actual demand. As an example, the calculation is performed using the following formula such as [Formula 1].
[Formula 1]

FIG. 14 shows an example of the cumulative sales planning error (rate). The past fixed period is registered in the product information DB 102 as an error evaluation period.

In step S303, if the sales plan error calculated in step S302 is equal to or less than the threshold value, the accuracy of the sales plan is judged to be good, and the process proceeds to S303. If the sales plan error is larger than the threshold value, the sales plan value is regarded as the actual demand. It is determined that the predicted re-execution process performed is impossible, and the process proceeds to step S307. The threshold value is registered in the product information DB 102 as a sales planning error threshold value.

In step S304, the demand forecast value of the forecast product for the past fixed period is acquired from the demand forecast DB 103, and the past demand forecast value of the forecast product is acquired from the forecast result DB 105, and the cumulative demand forecast error of each of the fixed period destinations is calculated. ..

Similar to step S302, there are various error calculation methods, but the error calculation method is not particularly specified as long as it represents the discrepancy between the demand forecast value and the actual demand.

As an example, with respect to the parameters used in [Formula 1], there is a method of substituting the sales plan value at the k time point ahead at the time point i with the actual demand value at the k time point ahead at the time point i.

FIG. 15 shows an example of the cumulative demand forecast error (rate). The past fixed period is registered as an error evaluation period, and the cumulative period is registered as a prediction error cumulative period in the product information DB 102.

In FIG. 15, the demand forecast value (k = 2) as of January, which is the forecast start date, means the demand forecast value for February calculated in January (January (k = 1) is the fixed period). Similarly, the forecasted demand value (k = 3) as of January, the forecast starting date, means the forecasted demand value for March calculated in January (January (k = 1) is the fixed period).

In step S305, the demand forecast errors calculated in step S304 are compared.

If the demand forecast error based on the demand forecast made using the past sales plan value calculated in step S302 is smaller than the demand forecast error made using the past demand actual value calculated in step S304, the sales plan value is set. Judging that the demand forecast used is valid, the process proceeds to S306.

On the other hand, if the demand forecast error based on the demand forecast made using the past sales plan value calculated in step S302 is greater than or equal to the demand forecast error made using the past demand record calculated in step S304, the sales plan It is determined that the demand forecast using the value is invalid, and the process proceeds to step S307.

The accuracy of the sales plan in the fixed period is good, but the demand forecast using the sales plan value is invalid. As an example, the sales plan in the past fixed period shows only a temporary demand trend and is not continuous. Cases and the like can be mentioned.

For example, as shown in the upper part of FIG. 16, as of August, the sales plan value is set in consideration of the increase in the demand level after August, and the demand forecast after the fixed period of August and September is also possible. It is assumed that it matches the market trend.

Then, as shown in the lower part of FIG. 16, there are cases where the demand level drops to the original level after October at the time of October.

In step S306, the forecast re-execution flag is stored as Y for the product for which the demand forecast using the sales plan value is determined to be valid in step S305. The predictive re-execution flag is an internally held flag with an initial value of N, and is cleared when the processing of the subsequent step S305 is completed.

In step S307, the process ends when the prediction re-executability determination of all the target products is completed, and returns to step S301 when the undetermined products remain.

Returning to the description of FIG. 3 again, in step S105, in the forecast re-execution unit 112, the product registered in the product information DB 102 is registered in the demand record of the forecast target product in the demand record DB 103 and further in the sales plan DB 107. Acquire the sales plan to be made and recalculate the forecast quantity.

When the demand forecast quantity is recalculated in the same manner as in step S102, the mathematical forecast model registered in the forecast model information DB 104 is used. The demand forecast quantity calculated at this time is registered in the forecast re-execution result DB 106.

FIG. 17 is a flowchart for explaining the details of the predictive re-execution process of step S105.

In step S401, it is determined whether or not the sales plan of the forecast product is used, the forecast re-execution flag stored in step S306 is Y, the forecast re-execution determination flag is N, and the product confirmation period is greater than 0. .. That is, it is determined whether or not to carry out the demand forecast using the sales plan value.

If it is determined that the above determination condition is satisfied, the process proceeds to step S402, and if it is determined that the condition is not satisfied, the process proceeds to step S404. The finalization period of the predicted product is registered in the product information DB 102.

In step S402, the cycle of the predicted product is acquired from the product information DB 102. Further, the demand record of the forecast product is acquired from the demand record DB 103, and the sales plan value for the fixed period of the forecast product is acquired from the sales plan DB 107, and the demand record and the sales plan value are aggregated and merged according to the cycle. In other words, the aggregated sales plan values are regarded as future demand results and used as input information for demand forecast calculation.

FIG. 18 is a processing example of step S402 after totaling the actual demand and the sales plan value when the fixed period is 2 and the cycle is a month.

As shown in the upper part of FIG. 18, when the current month is July and the sales plan values are fixed as 150 for July and 200 for August, this sales plan is as shown in the lower part of FIG. The value is set as the actual demand value (July, August), and the demand forecast after the fixed period (July, August) is performed using the actual demand up to August.

In step S403, the demand forecast quantity after the finalization period of the forecast product is calculated from the demand actual and sales plan values aggregated in step S402 and the mathematical forecast model registered in the forecast model information DB 104. The demand forecast quantity calculated at this time is registered in the forecast re-execution result DB 106.

In step S404, the process ends when the prediction calculation of all the products is completed, and the prediction re-execution flag stored in step S306 is cleared. If uncalculated products remain, the process returns to step S401.

Returning to the description of FIG. 3 again, in step S106, the forecast result confirmation unit 113 calculates the demand forecast value of the product calculated in step S102 from the forecast result DB 105, and the demand forecast of the product calculated from the forecast re-execution result DB 106 in step S105. The value is displayed on the sales plan input screen 400, the validity of the demand forecast value is confirmed, and the sales plan value is corrected as necessary.

FIG. 19 shows an example of the sales plan input screen 400 displayed in step S305 when the current month is November 2015, the fixed period is 2, and the cycle is a month.

The sales plan values for November and December 2015 are human purchases, and the latest demand trends are taken into consideration.

The demand forecast values after January 2016 show the results of considering the latest demand trends using the actual demand up to October 2015 and the sales plan values for November and December 2015.

As for the demand forecast value after January 2016, if the accuracy of the demand forecast using the past sales plan value is better than the accuracy of the demand forecast using the past demand record, Calculated using the sales plan values for November and December 2015.

On the other hand, in the demand forecast value after January 2016, if the accuracy of the demand forecast using the past sales plan value is not better than the accuracy of the demand forecast using the past demand record. , Calculated using the past demand record before November 2016.

As described above, according to the present invention, it is possible to accurately forecast the demand for a product or the like by forecasting the demand for the product or the like by using the determined sales plan.

Further, the present invention can be implemented as, for example, a system, a method, a program, a storage medium, or the like.

As described above, the recording medium on which the program that realizes the functions of the above-described embodiment is recorded is supplied to the system or the device, and the computer (or CPU or MPU) of the system or the device stores the program in the recording medium. It goes without saying that the object of the present invention can be achieved by reading and executing.

In this case, the program itself read from the recording medium realizes the novel function of the present invention, and the recording medium storing the program constitutes the present invention. Recording media for supplying programs include, for example, flexible disks, hard disks, optical disks, magneto-optical disks, CD-ROMs, CD-Rs, DVD-ROMs, magnetic tapes, non-volatile memory cards, ROMs, EEPROMs, and silicon. A disc or the like can be used.

Further, by executing the program read by the computer, not only the function of the above-described embodiment is realized, but also the OS or the like running on the computer is a part of the actual processing or based on the instruction of the program. Needless to say, there are cases where the functions of the above-described embodiment are realized by performing all of the processes.

Further, the program read from the recording medium is written to the memory provided in the function expansion board inserted in the computer or the function expansion unit connected to the computer, and then the function expansion board is based on the instruction of the program code. It goes without saying that there are cases where the CPU or the like provided in the function expansion unit performs a part or all of the actual processing, and the processing realizes the functions of the above-described embodiment.

It goes without saying that the present invention can also be applied when it is achieved by supplying a program to a system or device.

In this case, by reading the recording medium in which the program for achieving the present invention is stored into the system or device, the system or device can enjoy the effect of the present invention.

Further, by downloading and reading a program for achieving the present invention from a server, database, or the like on the network by a communication program, the system or device can enjoy the effect of the present invention. It should be noted that all the configurations in which the above-described embodiments and modifications thereof are combined are also included in the present invention.

100 Demand forecast calculation device 201 CPU
202 RAM
203 ROM
204 System Bus 205 Input Controller 206 Video Controller 207 Memory Controller 208 Communication I / F (Interface) Controller 209 Keyboard (KB)
210 Display device (CRT)
211 External memory

Claims (10)

It is an information processing device for obtaining the demand forecast result of a product by a forecasting means.
An acquisition method for acquiring information on sales plan values of products based on an arbitrary period,
Using the information about the sales plan value based on the arbitrary period acquired by the acquisition means and the demand record, the demand forecast result predicted by the forecast means and the demand record without using the information about the sales plan value are used. , An output means that outputs the demand forecast result predicted by the forecast means, and
An information processing device characterized by being equipped with. And the output means, according to claim 1, characterized in that outputs information on the arbitrary period before the sales plan value forecast predicted using the actual demand without using the information about the result and the sales plan value The information processing device described in. The information processing apparatus according to claim 1 or 2 , wherein the output means also outputs a demand record before the arbitrary period. The information processing apparatus according to any one of claims 1 to 3 , wherein the output means outputs a demand forecast result including the arbitrary period. The information processing apparatus according to any one of claims 1 to 4 , wherein the output means outputs a demand forecast result after the arbitrary period. Whether or not to make a demand forecast using the information on the sales plan value based on the arbitrary period due to the difference between the information on the sales plan value based on the arbitrary period in the past and the demand actual corresponding to the information on the sales plan value. The information processing apparatus according to any one of claims 1 to 5 , further comprising a determination means for determining. The determination means includes an error between a past demand forecast value and a demand record corresponding to the demand forecast value, information on a sales plan value based on the past arbitrary period, and a demand record corresponding to information on the sales plan value. The information processing apparatus according to claim 6 , wherein it is determined whether or not to perform a demand forecast by using the error of the above. An information processing device that forecasts product demand.
Forecasting means for forecasting the demand of the product using the actual demand of the product,
An acquisition method for acquiring information on sales plan values of products based on an arbitrary period,
Using the information on the sales plan value based on the arbitrary period acquired by the acquisition means and the demand record, the demand forecast result obtained by the forecast means and the demand record without using the information on the sales plan value are used. An output means that outputs the demand forecast result predicted by the forecast means, and
An information processing device characterized by being equipped with. It is a control method of an information processing device for obtaining a demand forecast result of a product by a forecasting means.
The information processing device
The acquisition step to acquire information about the sales plan value of the product based on the arbitrary period,
Using the information about the sales plan value based on the arbitrary period acquired by the acquisition step and the demand record, the demand forecast result predicted by the forecasting means and the demand record without using the information about the sales plan value are used. , An output step that outputs the demand forecast result predicted by the forecasting means,
A control method for an information processing device, which comprises executing. A computer that obtains product demand forecast results by forecasting means,
An acquisition method for acquiring information on sales plan values of products based on an arbitrary period,
Using the information about the sales plan value based on the arbitrary period acquired by the acquisition means and the demand record, the demand forecast result predicted by the forecast means and the demand record without using the information about the sales plan value are used. , An output means that outputs the demand forecast result predicted by the forecast means, and
A program to make it work.

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