CN1555025A - Sale prediction management system, method and recording medium - Google Patents
Sale prediction management system, method and recording medium Download PDFInfo
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- CN1555025A CN1555025A CNA2003101230820A CN200310123082A CN1555025A CN 1555025 A CN1555025 A CN 1555025A CN A2003101230820 A CNA2003101230820 A CN A2003101230820A CN 200310123082 A CN200310123082 A CN 200310123082A CN 1555025 A CN1555025 A CN 1555025A
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Abstract
The sale prediction management system includes one prediction amount input module, one prediction amount data base, one prediction amount analysis module and one output module. The prediction amount input module receives the sale prediction data of several sold products in several period of at least one user; the prediction amount data base records the sale prediction data and stores at least one part of the past sale prediction data; the prediction amount analysis module is for the analysis of the sale prediction data and the past sale prediction data; and the output module outputs the analysis result of the prediction amount analysis module. In addition, the present invention also provides one kind of sale prediction management method and one kind of program record medium for the sale prediction.
Description
Technical field
The present invention is about a kind of sale prediction management system and method, particularly about a kind of can be according to the sale prediction management system and the method for historical data dynamic management sales forecast amount.
Background technology
Generally speaking, an enterprise has many salesmen usually and is responsible for activities such as the sale of various products and customer service, and all relevant informations of these activities are not only important to sales department, and it is also quite important to departments such as product storage, accounting.
Because the manufacturing of product or buying meeting consume the long duration, thus interior each product consumption of following a certain section cycle length of salesman's prediction in advance, so that enough product quantity can be provided in the section in a certain cycle length in future.If the production cycle of a product was 4 weeks, then the salesman usually can be in the demand of this product of the 1st week elder generation's prediction in the 6th week, i.e. sales forecast amount; And for effectively the keyholed back plate product inventory and the actual sales volume of the product, can reappraise the weekly usually sales forecast amount in the 6th week of salesman.In known sales forecasting system; when if sales forecast amount that the salesman reappraises and previous premeasuring are not inconsistent; usually the sales forecast of the last time can be measured the original sales forecast amount of generation renewal; this is that salesman's sales forecast amount can be more near actual value because more near the time period (the 6th week) of effective sale.
Yet, known sales forecasting system, for example general commercially produced product ERP (Enterprise Resources Plan enterprise resource planning), only simple renewal salesman's sales forecast amount, the relevant information of whole enterprise can not be provided effectively, or how the tracking relevant information develops in time, it is numerous and diverse particularly to work as business organization, or the produce market change rapidly, or relevant cooperation department needs the long period to prepare, or there are a plurality of salesmen to be responsible for identical product simultaneously, or when having a plurality of product needed to handle simultaneously, integrate informations and the systematization prediction is provided effectively all.
Therefore, the sale prediction management system and the method that how a kind of integrate information effectively are provided and provide systematization to predict, one of problem that current just urgency is to be solved.
Summary of the invention
In view of above-mentioned problem, the sale prediction management system and the method that the invention provides a kind of integrate information effectively and provide systematization to predict.
Sale prediction management system of the present invention comprises a premeasuring load module, a prediction amount data base, a premeasuring analysis module and an output module.At this, the premeasuring load module receives a collection of sales forecast data that at least one user imports, and it comprises the sales forecast amount of at least one product at least one cycle; Prediction amount data base writes down this sales forecast data, and store a collection of at least historical sales predicted data, it comprises the historical sales premeasuring of at least one product in a plurality of cycles, and the predicted time section of the predicted time section of this historical sales predicted data and these sales forecast data is overlapped; This premeasuring analysis module is analyzed these sales forecast data and this historical sales predicted data; This output module is exported the analysis result of this premeasuring analysis module.
In addition, the present invention also provides a kind of sales forecast management method, and it comprises that reception is by a collection of sales forecast data, analysis sales forecast data and a collection of at least historical sales predicted data that at least one user imported and the analysis result of exporting these sales forecast data and this historical sales predicted data.In the present invention, these sales forecast data comprise the sales forecast amount of at least one product at least one cycle, and this historical sales predicted data comprises the historical sales premeasuring of at least one product in a plurality of cycles, and the predicted time section of the predicted time section of this historical sales predicted data and these sales forecast data is overlapped.
The present invention also provides a kind of recording medium, and it writes down a computer-readable sales forecast supervisory routine, to carry out above-mentioned sales forecast management method.
As mentioned above, because sale prediction management system of the present invention and method keep the historical sales premeasuring, so that carrying out the analysis of sales forecast data and historical sales predicted data compares, so integrate information and systematized prediction is provided effectively, particularly can grasp the evolution process of predicted value and adjust predicted value according to present existing information, and then can provide the relevant information of whole enterprise effectively, and follow the trail of this relevant information and how to develop in time, and analyze its reason.
The accompanying drawing simple declaration
Fig. 1 is a synoptic diagram, shows the sale prediction management system according to preferred embodiment of the present invention:
Fig. 2 is a synoptic diagram, shows many batches of sales forecast data and effective sale amount, and it is stored in the prediction amount data base;
Fig. 3 A-3C is a synoptic diagram, shows the analysis result according to the premeasuring analysis module of preferred embodiment of the present invention;
Fig. 4 is a synoptic diagram, shows the analysis corrections result according to the premeasuring analysis module and the premeasuring correcting module of preferred embodiment of the present invention; And
Fig. 5 is a process flow diagram, shows the step according to the sales forecast management method of preferred embodiment of the present invention.
The element numbers explanation:
1 sale prediction management system
11 premeasuring load modules
13 prediction amount data base
15 premeasuring analysis modules
17 output modules
19 premeasuring correcting modules
20 users
21 sales forecast data
23 historical sales predicted data
25 effective sale amounts
The step of S01-S04 sales forecast management method
Embodiment
Hereinafter with reference to relevant drawings, sale prediction management system and method according to preferred embodiment of the present invention are described, wherein identical assembly will be illustrated with identical reference marks.
With reference to shown in Figure 1, comprise a premeasuring load module 11, a prediction amount data base 13, a premeasuring analysis module 15 and an output module 17 according to the sale prediction management system 1 of preferred embodiment of the present invention.In the present invention, this premeasuring load module 11 receives a collection of sales forecast data 21 that at least one user 20 is imported, and it comprises the sales forecast amount of at least one product at least one cycle; These prediction amount data base 13 record sales forecast data 21, and store a collection of at least historical sales predicted data 23, it comprises the historical sales premeasuring of at least one product in a plurality of cycles, and the predicted time section of the predicted time section of this historical sales predicted data 23 and these sales forecast data 21 is overlapped; This premeasuring analysis module 15 is analyzed these sales forecast data 21 and this historical sales predicted data 23; The analysis result of these output module 17 these premeasuring analysis modules 15 of output.
Be noted that sale prediction management system 1 can be implemented in an electronic equipment, for example in known computer installation, it comprises a CPU (central processing unit), memory storage, an input media and an output unit.Wherein, CPU (central processing unit) can adopt any known central processing unit framework, for example arithmetical unit (ALU, Arithmetic Logic Unit), buffer and controller etc., with processing and the computing of carrying out various data, and the start of each assembly in the control electronic equipment.Storage device can be any or several mechanized data memory storages such as hard disk drive, CD-ROM drive, dynamic RAM or repeatable read memory write.Input media can be that keyboard or mouse etc. can allow user input data (as these sales forecast data 21) enter user's input interface of electronic equipment.And output unit can be a display etc., to show the analysis result of this premeasuring analysis module 15.
As mentioned above, each module in the present embodiment can be the software module that is stored in the memory storage.And this central processing unit can be by each assembly in the electronic equipment after reading each software module, and for example input media, output unit, memory storage or other software module realize the function of each module.Yet, be noted that, those skilled in the art also can be made into hardware with above-mentioned software module, and as application-specific integrated circuit ASIC (application-specificintegrated circuit) chip etc., this does not violate and exceeds spirit of the present invention and category.In addition, aforesaid prediction amount data base 13 can be any with electronic equipment can access archive database, for example be the electronic databank that is stored in the memory storage.
In the present embodiment, described historical sales predicted data 23 is the described sales forecast data that the user imported in last cycle and/or preceding several cycles, can be the data of single product or the data of most products (work on the salesman of these data of input is decided); And described premeasuring analysis module 15 can be described sales forecast data 21 and a described historical sales predicted data 23 of analyzing same user, be the sales forecast data that same user imports at different cycles, so that whether effectively analyze specific user's sales forecast amount accurate; Described premeasuring analysis module 15 also can be described sales forecast data 21 and a described historical sales predicted data 23 of analyzing different user, so can effectively integrate the sales forecast amount and the quantity in stock of enterprise.Certainly, because the data of input can be that variable is put in order with user, also can be that variable is put in order with the product, therefore described premeasuring analysis module 15 also can be handled single product or handle most products.
In addition, when the time proceeds to the cycle of previous prediction, can obtain the effective sale amount 25 in this of section effective sale situation, it is transfused to and is stored in the described prediction amount data base 13 cycle length.At this moment, at least since the predicted time section of described historical sales predicted data 23 and the predicted time section of described sales forecast data 21 overlap, described premeasuring analysis module 15 is also analyzed these sales forecast data 21, historical sales predicted data 23 and effective sale amount 25, so that further analyze more same user, different user, identical product or this sales forecast amount of different product and the deviation situation of actual value.As mentioned above, described sale prediction management system 1 also comprises a premeasuring correcting module 19, and it revises the sales forecast amount of these sales forecast data 21 according to these sales forecast data 21, historical sales predicted data 23 and effective sale amount 25.And revised these sales forecast data 21 are by output module 17 outputs.
This can be seen that of the present invention one big feature: gradual (rolling) handles.On the one hand, the data of arbitrary specific period all are to be approached gradually by the data of previous a plurality of cycle institute's gradation records to obtain, and the while also can allow each relevant departments progressively handle and prepare; On the other hand, all can import the predicted data in the cycle of following certain limit, the reference data in future also progressively be revised data for relevant departments provide in any cycle.
For content of the present invention is more readily understood, below will lift an example, with the start flow process of explanation according to the described sale prediction management system 1 of preferred embodiment of the present invention.
At first, utilize described premeasuring load module 11 to receive the described sales forecast data that the user imported, and each these sales forecast data of pen comprises a series of described sales forecast amount, as shown in Figure 2, in the present embodiment, the user imports once this sales forecast data weekly, and the sales volume in every following 12 weeks of this sales forecast data prediction, for example, when initial day of the 1st week (July 1), the sales forecast amount weekly in following 12 weeks of user in predicting (7/1-9/22); When initial day of the 2nd week (July 8), the described sales forecast amount weekly in following 12 weeks of user in predicting (7/8-9/29); When initial day of the 3rd week (July 15), the described sales forecast amount weekly in following 12 weeks of user in predicting (7/15-10/13); When initial day of the 4th week (July 22), the described sales forecast amount weekly in following 12 weeks of user in predicting (7/22-10/20); In the present embodiment, user in predicting one drive IC is in weekly described sales volume, and the unit of described prediction sales volume shown in Figure 2 is " ten thousand ".In addition, if the present date is July 22, then the described sales forecast data imported on the same day of user (the sales forecast amount weekly of prediction 7/22-10/20) are aforesaid described sales forecast data 21, and the described sales forecast data that formerly (comprise 7/1,7/8 and 7/15) and imported are aforesaid historical sales predicted data 23, and these sales forecast data (comprising sales forecast data 21 and historical sales predicted data 23) are stored in the described prediction amount data base 13.
In addition, this prediction amount data base 13 more stores effective sale amount 25 weekly, and as shown in Figure 2, if the present date is July 22, then this prediction amount data base 13 records the amount of effective sale weekly in 1-3 week, and the cycle does not afterwards have the effective sale amount as yet.
Then, described premeasuring analysis module 15 is analyzed this user's prediction accuracy or other required analysis result according to described prediction amount data base 13 stored described sales forecast data (as shown in Figure 2).As shown in Figure 3A, to a certain specific period time period, if the described sales volume of being predicted in this user sales forecast data formerly is soon near described effective sale amount, just very approaching described effective sale amount when importing described sales forecast amount for the 3rd time for example, show that then this user is quite high to the grasp degree of market demand situation, and then be when passing the warehousing department door by described output module 17 when this analysis result, these sales forecast data according to this user that this storage department can be very relieved are prepared the product inventory in following several weeks ahead of time.
In addition, shown in Fig. 3 B, in a certain specific period time period, if the described sales volume of being predicted in user's sales forecast data formerly is lentamente near described effective sale amount, for example when importing described sales forecast amount for the 8th time just near described effective sale amount, though show that then this user can the prediction markets demand, but the grasp degree of the market demand is still disliked not enough, therefore be when passing described storage department by described output module 17 when this analysis result, this storage department must prepare the product library storage in following several weeks modestly, to avoid remaining too much product, or there is the situation of product inventory deficiency to take place.
Shown in Fig. 3 C, equally in a certain specific period time period, if the sales volume of being predicted in user's described sales forecast data formerly departs from described effective sale amount fully, then represent this user not grasp the market demand fully, therefore be when passing described storage department by described output module 17 when this analysis result, this storage department must give up these sales forecast data of this user, perhaps its these sales forecast data of importing is revised.
As mentioned above, when the described sales volume of being predicted in user's described sales forecast data formerly departs from described effective sale amount fully, the sales forecast amount that described premeasuring correcting module 19 is revised ensuing described sales forecast data according to the previous described sales forecast data and the described effective sale amount in each cycle.For example, if the user is leaked the demand of a certain downstream manufacturers of estimation, then its described sales forecast data of importing may all be lower than described effective sale amount for each issue, at this moment, described premeasuring correcting module 19 is revised these sales forecast data of this user, and the possibility of result can obtain pretty good prediction effect (shown in Fig. 3 C).
Be noted that the described sales forecast data that described sale prediction management system 1 can a plurality of users of confluence analysis be imported in the section in several cycle lengths are so that provide systematized sales forecast result.In the present embodiment, described prediction amount data base 13 records store the described sales forecast data that a plurality of user imports, wherein these sales forecast data of each user as shown in Figure 2, at this moment, described premeasuring analysis module 15 is integrated these all sales forecast data, and export this analysis result by described output module, for example export to storage department.With reference to shown in Figure 4, sales forecast data to 10-13 week are analyzed, and the described sales forecast data point of being imported during 9 weeks before each cycle is represented with " Δ ", the sales forecast data point of being imported during 6 weeks before each cycle is represented with " x ", the described sales forecast data point of being imported during 3 weeks before each cycle is represented with " o ", at last, the described effective sale amount point in each cycle is represented with "--", can judge whole sales forecast data by Fig. 4 error is arranged, but can adopt 3 all mean values preceding and the sales forecast data that 6 weeks are preceding to revise prediction result, this modified value point is represented with " * ".
In addition, if in certain cycle, successively import repeatedly data (referring to that the identical entry destination data is repeated input), present embodiment can also have the historical record function.Also promptly, can use the data of last input to be used as the sales forecast data in this cycle on the one hand; The described data of each time input with other also store on the one hand, as the reference data (for example being used for revising the sales forecast data) of subsequent operation.
Certainly, as previously mentioned, present embodiment also can be that certain single product or some product are predicted.At this, no longer repeat for example.
In addition, the present invention also discloses a kind of sales forecast management method, it is the method that the sale prediction management system 1 of application of aforementioned is come the prediction management sales volume, and it comprises that reception is by sales forecast data (S01) that at least one user imported, the analysis result (S04) analyzing these sales forecast data and a collection of at least historical sales predicted data (S02) and export these sales forecast data and this historical sales predicted data.In addition, this sales forecast management method can also comprise the sales forecast amount (S03) of revising these sales forecast data according to these sales forecast data, historical sales predicted data and effective sale amount.Be noted that, utilize aforesaid sale prediction management system 1 to carry out according to sales forecast management method of the present invention, its step content as previously mentioned, so no longer repeat.
In addition, the present invention also provides a kind of recording medium (for example CD, disk and removable hard drive or the like), and it writes down a computer-readable sales forecast supervisory routine, so that carry out above-mentioned sales forecast management method.At this, be stored in this sales forecast supervisory routine on this recording medium, form by a plurality of code segment basically, and the function of these code segment corresponds to the foregoing description.
In sum, owing to keep described historical sales predicted data according to sale prediction management system of the present invention and method, and more described sales forecast data of analysis and historical sales predicted data, so integrate information and systematized sales forecast is provided effectively, and then the relevant information of whole enterprise can be provided effectively, and follow the trail of this relevant information and how to develop in time.What particularly point out is that described sale prediction management system of the present invention and method can dynamically be revised prediction result, so more effectively managerial marketing prediction.
The above for for example, has been not restricted effect only.Anyly do not break away from spirit of the present invention and category, and, all should be included in the claim protection domain of the present invention equivalent modifications or change that the present invention carries out.
Claims (12)
1, a kind of sale prediction management system comprises:
One premeasuring load module, it receives a collection of at least sales forecast data that at least one user imports, and these sales forecast data comprise a sales forecast amount of at least one product at least one cycle;
One prediction amount data base, it writes down this sales forecast data, and a collection of at least historical sales predicted data of storage, this historical sales predicted data comprises a historical sales premeasuring of at least one product in a plurality of cycles, and the predicted time section of this historical sales predicted data and the predicted time section of these sales forecast data are overlapped, wherein a collection of at least these sales forecast data of being imported in the cycle formerly for this user of this historical sales predicted data;
One premeasuring analysis module, it analyzes these sales forecast data and this historical sales predicted data; And
One output module, it exports the analysis result of this premeasuring analysis module.
2, sale prediction management system as claimed in claim 1, wherein this premeasuring analysis module is analyzed same user's sales forecast data and historical sales predicted data, the sales forecast data of analyzing a plurality of users and historical sales predicted data at least, analyzes the sales forecast data and the historical sales predicted data of identical product and/or is analyzed the sales forecast data and the historical sales predicted data of a plurality of products.
3, sale prediction management system as claimed in claim 1, when in certain cycle, having certain data item successively repeatedly to be imported, this prediction amount data base is used the sales forecast data of the data of last input as this certain one-period, and store the data of other each time input, as the reference data of subsequent operation.
4, sale prediction management system as claimed in claim 1, wherein when this prediction amount data base also stores at least one effective sale amount, this premeasuring analysis module is also analyzed these sales forecast data, this historical sales predicted data and this effective sale amount, and this sale prediction management system also comprises:
One premeasuring correcting module, it revises the sales forecast amount of these sales forecast data according to these sales forecast data, this historical sales predicted data and this effective sale amount, and this output module will be exported these sales forecast data of revising.
5, a kind of sales forecast management method comprises:
Reception is by a collection of at least sales forecast data that at least one user imported, and these sales forecast data comprise a sales forecast amount of at least one product at least one cycle;
Analyze these sales forecast data and a collection of at least historical sales predicted data, this historical sales predicted data comprises this historical sales premeasuring of at least one product in a plurality of cycles, and the predicted time section of this historical sales predicted data and the predicted time section of these sales forecast data are overlapped, and wherein this historical sales predicted data is the sales forecast data of importing in the last cycle; And
Export the analysis result of these sales forecast data and this historical sales predicted data.
6, sales forecast management method as claimed in claim 5, the step of wherein analyzing these sales forecast data and this historical sales predicted data comprises one of following at least operation:
Analyze same user's these sales forecast data and this historical sales predicted data;
Analyze a plurality of users' these sales forecast data and this historical sales predicted data;
Analyze these sales forecast data and this historical sales predicted data of identical product; And
Analyze these sales forecast data and this historical sales predicted data of a plurality of products.
7, sales forecast management method as claimed in claim 5, it analyzes these sales forecast data, this historical sales predicted data and at least one effective sale amount, revises and export the sales forecast amount of these sales forecast data whereby.
8, sales forecast management method as claimed in claim 5, when having certain data item successively repeatedly to be imported in certain cycle, this sales forecast management method also comprises:
Utilize the sales forecast data of the data of last input as this certain one-period; And
Store the reference data of the data of other each time input as subsequent operation.
9, a kind of recording medium, it writes down a computer-readable sales forecast supervisory routine, and this sales forecast supervisory routine comprises:
One premeasuring loading routine code snippet, it receives by a collection of sales forecast data that at least one user imported with computing machine, and these sales forecast data comprise the sales forecast amount of at least one product at least one cycle;
One premeasuring routine analyzer code snippet, it reaches a collection of at least historical sales predicted data with these sales forecast data of this Computer Analysis, this historical sales predicted data comprises the historical sales premeasuring of at least one product in a plurality of cycles, and the predicted time section of this historical sales predicted data and the predicted time section of these sales forecast data are overlapped, wherein the sales forecast data imported in the last cycle for this user of this historical sales predicted data; And
One written-out program code snippet, it exports the analysis result of these sales forecast data and this historical sales predicted data with this computing machine.
10, recording medium as claimed in claim 9, wherein this premeasuring routine analyzer code snippet comprises one of following operation at least:
These sales forecast data and this historical sales predicted data with the same user of this Computer Analysis;
These sales forecast data and this historical sales predicted data with a plurality of users of this Computer Analysis;
These sales forecast data and this historical sales predicted data with this Computer Analysis identical product; And
These sales forecast data and this historical sales predicted data with a plurality of products of this Computer Analysis.
11, recording medium as claimed in claim 9, wherein this premeasuring routine analyzer code snippet is with these sales forecast data of this Computer Analysis, this historical sales predicted data and at least one effective sale amount, and this sales forecast supervisory routine also comprises:
One premeasuring revision program code snippet, it revises and exports the sales forecast amount of these sales forecast data according to these sales forecast data, this historical sales predicted data and at least one effective sale amount with computing machine.
12, recording medium as claimed in claim 9, wherein when having certain data item successively repeatedly to be imported in certain cycle, this premeasuring loading routine code snippet carries out following operation with this computing machine:
Use the sales forecast data of the data of last input as this certain one-period; And
The data storing of each time input is got up with other, as the reference data of subsequent operation.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763586A (en) * | 2009-12-22 | 2010-06-30 | 金蝶软件（中国）有限公司 | ERP system and method and device for monitoring material consumption |
| CN105940418A (en) * | 2014-11-17 | 2016-09-14 | 甲骨文国际公司 | System and method for managing extra calendar periods in retail |
| CN109472623A (en) * | 2018-11-05 | 2019-03-15 | 海尔电器国际股份有限公司 | Measure of managing contract |
| CN109509030A (en) * | 2018-11-15 | 2019-03-22 | 北京旷视科技有限公司 | Method for Sales Forecast method and its training method of model, device and electronic system |
| CN109961306A (en) * | 2017-12-25 | 2019-07-02 | 北京京东尚科信息技术有限公司 | A kind of inventory allocation method and apparatus of article |
| US10474950B2 (en) | 2015-06-29 | 2019-11-12 | Microsoft Technology Licensing, Llc | Training and operation of computational models |
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2003
- 2003-12-24 CN CNA2003101230820A patent/CN1555025A/en active Pending
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101763586A (en) * | 2009-12-22 | 2010-06-30 | 金蝶软件（中国）有限公司 | ERP system and method and device for monitoring material consumption |
| CN105940418A (en) * | 2014-11-17 | 2016-09-14 | 甲骨文国际公司 | System and method for managing extra calendar periods in retail |
| CN105940418B (en) * | 2014-11-17 | 2020-12-08 | 甲骨文国际公司 | System and method for managing additional calendar periods in retail |
| US10474950B2 (en) | 2015-06-29 | 2019-11-12 | Microsoft Technology Licensing, Llc | Training and operation of computational models |
| CN109961306A (en) * | 2017-12-25 | 2019-07-02 | 北京京东尚科信息技术有限公司 | A kind of inventory allocation method and apparatus of article |
| CN109961306B (en) * | 2017-12-25 | 2022-04-12 | 北京京东尚科信息技术有限公司 | Method and device for distributing inventory of articles |
| CN109472623A (en) * | 2018-11-05 | 2019-03-15 | 海尔电器国际股份有限公司 | Measure of managing contract |
| CN109509030A (en) * | 2018-11-15 | 2019-03-22 | 北京旷视科技有限公司 | Method for Sales Forecast method and its training method of model, device and electronic system |
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