Patent Grant
6922706
1. Field of the Invention
This invention relates to methodology for utilizing data mining techniques in the area of shelf-space management.
2. Introduction to the Invention
Data mining techniques are known and include disparate technologies, like neural networks, which can work to an end of efficiently discovering valuable, non-obvious information from a large collection of data. The data, in turn, may arise in fields ranging from e.g., marketing, finance, manufacturing, or retail.
We have now discovered novel methodology for exploiting the advantages inherent generally in data mining technologies, in the particular field of shelf-space management applications.
Our work proceeds in the following way.
We have recognized that a typical and important “three-part” paradigm for presently effecting shelf-space management, is a largely subjective, human paradigm, and therefore exposed to all the vagaries and deficiencies otherwise attendant on human procedures. In particular, the three-part paradigm we have in mind works in the following way. First, a shelf-space manager develops a shelf-space database comprising a compendium of individual shelf-space-requirements—e.g., specific shelf-space-requirements which took place in its past. Secondly, and independently, the shelf-space manager develops in his mind a shelving availability database comprising the shelf-space manager's personal, partial, and subjective knowledge of (otherwise objective) retail facts culled from e.g., the marketing literature, the business literature, or input from colleagues or salespersons. Thirdly, the shelf-space manager subjectively correlates in his mind the necessarily incomplete and partial shelving-availability database, with the shelf-space-requirements' database, in order to promulgate an individual's shelf-space-requirements prescribed shelf-space management and ultimate solution.
This three-part paradigm is part science and part art, and captures one aspect of the problems associated with shelf-space management. However, as suggested above, it is manifestly a subjective paradigm, and therefore open to human vagaries.
We now disclose a novel computer method which can preserve the advantages inherent in this three-part paradigm, while minimizing the incompleteness and attendant subjectivities that otherwise inure in a technique heretofore entirely reserved for human realization.
To this end, in a first aspect of the present invention, we disclose a novel computer method comprising the steps of:
The novel method preferably comprises a further step of updating the step i) shelf-space-requirements database, so that it can cumulatively track the shelf-space-requirements history as it develops over time. For example, this step i) of updating the shelf-space-requirements database may include the results of employing the step iii) data mining technique. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of shelf-space-solutions results and updating the shelf-space-requirements database.
The novel method preferably comprises a further step of updating the step ii) shelf-space-availability database, so that it can cumulatively track an ever increasing and developing technical shelf-space management literature. For example, this step ii) of updating the shelf-space-availability database may include the effects of employing a data mining technique on the shelf-space-requirements database. Also, the method may comprise a step of refining an employed data mining technique in cognizance of pattern changes embedded in each database as a consequence of shelf-space-solutions results and updating the shelf-space-solutions database.
The novel method may employ advantageously a wide array of step iii) data mining techniques for interrogating the shelf-space-requirementss and shelf-space-solutions database for generating an output data stream, which output data stream correlates shelf-space-requirementss problem with shelf-space availabilty solution. For example, the data mining technique may comprise inter alia employment of the following functions for producing output data: classification-neural, classification-tree, clustering-geoographic, clustering-factor analysis, or principal component analysis, or expert systems.
In a second aspect of the present invention, we disclose a program storage device readable by machine to perform method steps for providing an interactive shelf-space management database, the method comprising the steps of:
In a third aspect of the present invention, we disclose a computer comprising:
We have now summarized the invention in several of its aspects or manifestations. It may be observed, in sharp contrast with the prior art discussed above comprising the three part subjective paradigm approach to the problem of shelf-space management, that the summarized invention utilizes inter alia, the technique of data mining. We now point out, firstly, that the technique of data mining is of such complexity and utility, that as a technique, in and of itself, it cannot be used in any way as an available candidate solution for shelf-space management, to the extent that the problem of shelf-space management is only approached within the realm of the human-subjective solution to shelf-space management. Moreover, to the extent that the present invention uses computer techniques including e.g., data mining techniques, to an end of solving a problem of shelf-space management, it is not in general obvious within the nominal context of the problem and the technique of data mining, how they are in fact to be brought into relationship in order to provide a pragmatic solution to the problem of shelf-space management. It is rather an aspect of the novelty and unobviousness of the present invention that it discloses, on the one hand, the possibility for using the technique of data mining within the context of shelf-space management, and, moreover, on the other hand, discloses illustrative methodology that is required to in fact pragmatically bring the technique of data mining to bear on the actuality of solving the problem of shelf-space management.
The invention is illustrated in the accompanying drawing, in which
The detailed description of the present invention proceeds by tracing through three quintessential method steps, summarized above, that fairly capture the invention in all its sundry aspects. To this end, attention is directed to the flowcharts and neural networks of
Attention is now directed to
It is well understood that the computer system and method of the present invention can be implemented using a plurality of separate dedicated or prigrammable integrated or other electronic circuits or devices (e.g., hardwired or logic circuits such as discrete element circuits, or programmable logic devices such as PLDs, PLAs, PALs, or the like). A suitably programmed general purpose computer, e.g., a microprocessor, microcontroller or other processor devices (CPU or MPU), either alone or in conjuction with one or more peripheral (e.g., integrated circuit) data and signal processing devices can be used to implement the invention. In general, any device or assembly of devices on which a finite state machine capable of implementing the flow charts shown in the figures can be used as a controller with the invention.
This application is related to application Ser. No. 09/604,535 to Levanoni, et al. filed Jun. 27, 2000; to application Ser. No. 09/612,683 to Levanoni, et al. filed Jul. 10, 2000; to application Ser. No. 09/633,830 to Levanoni, et al. filed Aug. 7, 2000; and to application Ser. No. 09/696,552 to Levanoni, et al. filed Oct. 25, 2000. Each of these applications is co-pending and commonly assigned.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4947322 | Tenma et al. | Aug 1990 | A |
| 5212765 | Skeirik | May 1993 | A |
| 5224203 | Skeirik | Jun 1993 | A |
| 5241467 | Failing et al. | Aug 1993 | A |
| 5282261 | Skeirik | Jan 1994 | A |
| 5307260 | Watanabe et al. | Apr 1994 | A |
| 5313392 | Temma et al. | May 1994 | A |
| 5408586 | Skeirik | Apr 1995 | A |
| 5640493 | Skeirik | Jun 1997 | A |
| 5680305 | Apgar, IV | Oct 1997 | A |
| 5712989 | Johnson et al. | Jan 1998 | A |
| 5748188 | Hu et al. | May 1998 | A |
| 5774868 | Cragun et al. | Jun 1998 | A |
| 5826249 | Skeirik | Oct 1998 | A |
| 5832496 | Anand et al. | Nov 1998 | A |
| 5893076 | Hafner et al. | Apr 1999 | A |
| 5966704 | Furegati et al. | Oct 1999 | A |
| 5970476 | Fahey | Oct 1999 | A |
| 6078922 | Johnson et al. | Jun 2000 | A |
| Number | Date | Country |
|---|---|---|
| WO-0043934 | Jul 2000 | WO |
