Data Warehousing: Using the Wal-Mart Model
A real-world look at how Wal-Mart developed and uses its massive data warehouse.
TABLE OF CONTENTS Data Warehousing: Using the Wal-Mart Model
Chapter 11: Merchandising Sample Analyses
This chapter continues the theme of the previous chapter but for a different subject area, merchandising. In this chapter youwill find the basic analyses that most retailers will be building for the merchandising department. As mentioned before, many ofthese analyses build on what has already been defined in other areas, such as store operations analyses. The basic premise of adata warehouse is that detailed data is available to the entire business. As in the previous chapter, each application is given asmall overview, a list of data elements, and a sample report. These analyses build upon themselves and get more complex toward theend of the chapter.
Basic Merchandising Information Needs
From a retail perspective, merchandising is very broad. A data warehouse can quickly provide a retailer with several keyanalyses to improve the business. I have identified many common areas for retailers to focus in order to improve theirmerchandising position. Of course, each retailer has a unique set of merchandising challenges. Below is a list of analyses thatmany merchants perform or want to be able to perform:
- basic article POS analysis
- article selling versus planned selling analysis
- fast-selling article analysis
- slow-selling article analysis
- vendor performance analysis
- category performance analysis
- article selling by geographic locations
- comparative article sales (article vs. article)
- store and article grouping
- basic affinity selling
- out-of-stock analysis
After mastering...Some retailers spend 80% of their time researching to perform these analyses. That time can be reducedto 20% or less for retailers that do not already have a data warehouse.
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