Merchandise Planning - Data Sources and Complexity – Where do we start?

Merchandise planners tend to like at least two years worth of history by week, by store and by sub-category of product. Some examples by market: -

• Large department store, 2000 stores by 3500 sub-categories.
• Large fashion store, 2000 stores by 2500 sub-categories.
• Medium department store, 300 stores by 2000 sub-categories.
• Medium fashion store, 200 stores by 1250 sub-categories.

In the interests of Keeping It Simple, most retailers will not plan all their lines down to the sub-category level. Expect to find the most detailed planning going on in apparel and footwear, where ranges change seasonally, though certain electrical stores appear to be getting almost anal in their planning requirements.

US retailers have many more stores to plan for than in other countries, and this tends to make the ranges produced much more homogenous than in Europe or Australia. In the UK for example, a fashion store can present different styles in each city (fashion-forward Manchester versus conservative Leeds, for example), which imposes demands on the people planning the ranges and themes in each category. On the other hand, retailers in the US and across Europe do have to cope with wildly differing climates, where a Florida store may never stock winter wear, while one in Colorado may stock little else, and this imposes demands on the store planners. This is not an issue in Australia.

Most retailers run a Retail Management System, which is like a retail ERP, and all historic data will be available here. There is very little need for sophisticated data integration, mapping, matching or reference to other sources. Most Retail Management Systems run in Oracle or DB2 with the occasional SQL Server database in the smaller retailers.

Please contact us to find out more about our retail analytics and merchandise planning solution.