“ShopKo and Pamida: Systems Triumph or Tragedy?”
An Information Systems Case (Laudon & Laudon, 9th Ed. Website)
ShopKo, a regional discount merchandise retail chain headquartered in Green Bay, Wisconsin, has about 140 stores in larger Midwestern cities, and 221 Pamida stores serving rural areas in the Midwest, Mountain, and Pacific Northwest regions. ShopKo focuses on popular higher-margin categories such as casual apparel, health and beauty items, and housewares. Sales totaled $3.18 billion for the fiscal year ending in January 2005, and the company was recently acquired by a private company affiliate of Goldner, Hawn, & Morrison Inc.
ShopKo has been an intensive user of applications to improve decision making about inventory levels, sales performance, store layout, and selection of merchandise. One of its most powerful tools has been a system to determine prices and timing of apparel markdowns. Traditionally companies that sell apparel have four product cycles a year, one for each of the seasons. However such companies now face serious competition from companies like Gap that now operate on rapidly changing product cycles, often bringing in new product lines every two to four weeks. One of the growing problems ShopKo had to address was what to do with the excess (or overstocked) merchandise when a cycle ends.
At the end of a season (or cycle), companies have faced two problems. One is the need to empty its shelves in time for the arrival of the new cycle products (bathing suits do not sell well in the winter while fur coats are not in demand in the summer). The other problem is getting rid of the overstocked items at the highest possible price in an attempt to minimize losses in revenue. Traditionally the method ShopKo (and most other clothing retailers) used to determine clearance prices for overstocked items was to set each product price based upon