Due to tightening margins in the competitive automotive retail industry, Strauss Discount Auto, a leading after-market retailer of automotive parts, supplies and accessories in the Northeastern United States, implemented a data warehouse to meet the challenges it faced with stocking the company's 110 stores with 14,000 products from 700 vendors. Within the first year of its data warehouse implementation, the company has already begun to reap the benefits of real-time sales and inventory information.
Prior to embarking on the data warehouse initiative in February 1997, Strauss lacked a coherent business intelligence system to organize and analyze information on key areas of corporate and store operations. Strauss had outdated computing resources; the IS department had to gather data from multiple sources, manually load it into a PC database management system and attempt to analyze the data with custom-built front-end tools. Unfortunately, this process could not accurately reflect daily conditions in the fast-moving retail automotive business. The lack of timely business information hampered Strauss' ability to make correct business decisions because it was managing from a summary and historical view rather than from real-time specifics.
Strauss' top management was intensely interested in correctly measuring sales performance and conducting margin analysis. Specifically, inventory control was a major concern where the "shrink" number required more specific analysis. The shrink number is the difference between what is booked as inventory on the company's general ledger and what is actually in inventory at the stores themselves. Spoilage, breakage and shoplifting are all typical reasons for this shrinkage.
Strauss initiated a high-level internal review involving executive management. A data analysis audit led to a formal database design. A conceptual system was then created so that vendors and toolsets could be reviewed against it. The audit resulted in the selection of ShowCase STRATEGY data warehousing solution running on IBM's AS/400 platform.
Strauss' warehouse resides on an IBM AS/400 Model 53S server with 512MB of memory and a 56GB disk. A traditional IBM DASD is used for storage. End users operate thin clients running Windows 95 and access data via a TCP/IP network over a 10MB Ethernet LAN.
The major benefit of selecting the AS/400 platform was that Strauss avoided the introduction of a new hardware architecture resulting in reduced operational and support costs. The AS/400 also provided built-in relational data management capabilities, hardware integrity and reliability, along with an integrated operating system. In addition, the inherent scalability of the AS/400 provided a solution that would allow the warehouse to scale to a size of 30-50GB.
Strauss implemented STRATEGY because it was a single-vendor solution, eliminating the need to integrate tools from multiple vendors. Strauss was also impressed with STRATEGY's built-in relational and multidimensional database capabilities for queries, reporting and data analysis. It provided a broad range of capabilities from traditional query and reporting to OLAP and had a solid strategy for integrating relational and OLAP solutions, providing users with a seamless view of all data available in the warehouse. STRATEGY's thin clients also had a significant impact on reducing client acquisition costs. Strauss currently uses ShowCase STRATEGY's Analyzer, Essbase/400, Query, Report Writer and Server products.
Strauss has three primary departments that are currently benefiting from the implementation of STRATEGY: merchandising, store operations and finance. Examples of the benefits include:
- Merchandising can now analyze the sales figures and inventory levels of products in order to maximize product profitability. STRATEGY has enabled one merchandiser to analyze financial results from a new product introduction after the product had been on the shelves for only one day, which was not previously possible.
- Store operations now has the tool to better analyze performance of each retail outlet. They can more accurately track how products are selling in various store locations, optimizing retail space and product sales for increased overall store productivity and performance.
- A financial analyst can generate a sales report in minutes compared to the previous process which took hours and included the task of calling each store, collecting and collating the data, and then manually entering it into a PC spreadsheet.
There are a few obvious early indicators of the data warehouse's success. Strauss has experienced a significant reduction in end-user requests for reports from IS. Prior to STRATEGY, IS was responsible for all the reports which end users are now generating on their own. This has significantly reduced the IS time and budget spent on developing and generating reports. Also, end-user demands for additional data and reporting capabilities are increasing, indicating that the new system is working. Users would not be demanding more information if they were not using the data warehouse and finding it to be valuable asset.
Advice for those who are embarking on a data warehouse initiative:
- Spend an adequate amount of time to plan for and prepare the data. Despite the fact the Strauss spends a great deal of time insuring the consistency and accuracy of the data prior to putting it into the warehouse, data accuracy is IS' number one problem. There are many consistency issues to be aware of such as when and where data is being filed.
- It is vital to gain executive sponsorship of the project at the beginning of the data warehousing initiative. Building and managing a data warehouse requires a significant time commitment from top executives, and if they are not behind the project, it will be very difficult to get the necessary time allocated to insure success. A data warehouse will ultimately lead to changes in the way that a company does business; and if top management is not willing to embrace those changes, championing them throughout the organization, the project is doomed to fail. Executive buy-off on the project will also ease the approval process for financial expenditures.
- Be prepared for the rapid growth of the data warehouse, requiring additional disks and processors. Both tend to grow at a faster rate than one would anticipate due to increased demands on the system by end users who are empowered by the new information available to them.
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