Laslala

To identify the main problem(s) of the case, using our Case Analysis Guide, we look for important “performance measures” related to some “systems” and/or “goals/objectives” in the case. Using this tip, we find two most interesting and contrasting instances of such systems and performance measures in this case:

ShopKo’s Markdown Optimizer System: From the case, it is clear that ShopKo implemented this IS to be able to meet the challenge of the new shorter product cycles imposed by designer chains. The challenge really involves balancing the conflicting “objectives” of (a) making the store-space available for the next cycle, while (b) pricing the older goods to maximize the revenues! Fortunately, the related performance measures found in the case are all very satisfactory: Leftover gross margin up 25%, Store-staff payroll costs down 24%, Unsold good down from 5% to 2% (that is 60% reduction!), Expected Net Profits up USD15M or 15%. Since all these measures are clearly “good”, there is no need for further analysis of the markdown Optimizer system. In contrast, the story for Pamida’s Distribution Center project is quite different, as summarized below.

Pamida’s Distribution Center Project: Considering ShopKo’s goal of expanding into the small-town market, it seems natural for Pamida’s (with its High In-stock Strategy) to modernize all its warehousing facilities to meet the expected high demand. Accordingly, Pamida embarked on a massive modernization of its warehouses through the Distribution Center Project. The goal of this project was to transform the existing flow-trough type warehouses (where goods arrive and are immediately shipped to the stores) into a latest type of full-service Distribution Centers (DC) where inventory is stored, and shipped to the stores on a more responsive, Just-in-Time, basis.

Despite of its Hi-Tech ambitious goal, the performance measures in terms of the stock availability in the stores, and associated monetary performance for...