The user should be familiar with legacy system data and terms. The user should have some experience with existing data access software, such as Focus. The team hired a full-time trainer, who informally classified the large user community according to job function, technical competence, and understanding of decision support. As the rollout of the first MkIS application neared, education classes provided real-life case studies closely aligned with user job functions. By linking product-movement data from their nationwide network of stores into a centralized warehouse, it enabled a team of headquarters merchandisers and buyers to perform their own decision support using OLAP tools on the desktop.
Retailers characteristically have a culture of autonomy and self-sufficiency.
For them, data analysis had to be done in a different way. Based on these unique needs, the retailer appointed several technical analysts to a data support desk to bring important sales information to the field quickly. The reports, including revenue forecasts and product purchase analysis, are distributed to the stores and sales offices over the retailer's intranet. The support-desk analysts run standard reports at regular intervals and submit specialized queries at the request of merchandisers and other headquarters staff. Depending on the request backlog and the complexity of the reports, turnaround time can last anywhere from an hour to a few days, but the employees don't seem to mind.