CATEGORY: Data Mining and Visualization
REVIEWERS: Kit Nicholson, senior sales director, and Doug Wendling, senior database analyst, for Maytag International.
BACKGROUND: Maytag International, headquartered in Chicago, Illinois, is responsible for finished goods export sales, licensing of the corporation's appliance and floor care brands, and joint ventures worldwide. Maytag International's presence in markets around the world includes direct sales operations in Australia, Mexico, Puerto Rico and the United Kingdom.
PLATFORMS: Maytag International runs Dimensional Insight DI-Atlantis (the OLAP server engine) on a Windows NT server, and 70 users access the DI-Atlantis data Models using DI-Diver from Windows 98 clients. Models store five years of data.
PROBLEM SOLVED: In the past, we were sending thousands of pages of paper reports per year to each region. It was tedious for us to get detailed information on a customer from those reports and unreasonable to carry them when visiting a customer site. Although our salespeople were as prepared as possible, sometimes questions would arise that they couldn't answer simply because they didn't have the data with them. With DI-Diver, the data is updated monthly and distributed to users over the LAN. For remote users in Lebanon, for example, we send the updated model on a CD. The detailed data is relevant to their region, and they are able to "dive" into the data models to answer questions from their laptops instead of shuffling through thousands of pages of printed reports.
PRODUCT FUNCTIONALITY: DI-Diver is used in Magtag offices around the world to track sales and analyze profitability for refrigeration, laundry, floor care, cooking and dishwasher product categories. DI-Diver reports include sales dollars, unit totals, revenue, cost, warranty and gross margin information for 1,700 SKUs and 1,000 customers. DI-Diver allows Maytag International employees to communicate more effectively with customers and each other, find and capitalize on the most profitable product mixes, and quickly identify and eliminate the least profitable SKUs. Additionally, if a manager questions data within the DI-Diver reporting package, he or she can quickly determine the root of the question. DI-Diver gives a clear and accurate view of the organization as a whole. We share information that allows us to be more intelligent and more responsive to both external customers and our internal production facilities. We pinpoint occasional errors and find out what caused them very quickly with DI-Diver. The first year we used DI-Diver, there was a big question regarding profitability in one of the regions. We investigated the data and found out that the margins were lower because the value-added tax had not been pulled out of the cost. This was done in minutes. Before DI-Diver, it may have taken us days or longer to figure this out. With regard to product planning, we use DI-Diver to determine where we have opportunities to expand sales. As we plan to expand sales, we use DI-Diver to dive into a product category, for example refrigeration, and then dive down further into different types of refrigerators to look at regions where each is most popular. With Di- Diver, we can determine the best product mixes and expand sales by targeting those retailers with the most suitable products.
STRENGTHS: DI- Diver's strengths include ease of use and ease of maintenance. The implementation, building of models, and modifications to models are very straightforward. It is a plug-and-play software package.
WEAKNESSES: We are not satisfied with the way DI-Diver formats reports. We would like them to fit to a page. DI-Diver 4.1 will include this capability.
SELECTION CRITERIA: We looked at other business intelligence products and found that the DI-Diver Model is compact, very easy to use with little training and very beneficial to our people all around the globe. We analyzed the cost of the old way versus the cost of implementing DI- Diver. We have definitely received a return on investment.
DELIVERABLES: One person in the IT department creates and maintains DI-Diver models. Users click through models and create reports to analyze product performance by territory, country, customer, model, category units and sales dollars. Maps give users a geographical view of product distribution, and DI-Diver's timeseries feature allows users to analyze products and customers year-to-date versus last-year-to-date, or by month. Timeseries produces aggregate data for the different periods of time and the absolute and percent difference between them.
VENDOR SUPPORT: Overall, we are satisfied with support from Dimensional Insight.
DOCUMENTATION: The manuals are a good reference.
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