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Sub-Zero Implements New Warranty System
Aug 4, 2005
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Sub-Zero Freezer Company of Madison, WI, U.S. and its corporate companion, Wolf Appliance Company, have implemented a new warranty analysis and text miner system to help improve product quality and reduce overall warranty costs.

According to SAS, supplier of the new system, the tools will allow the appliance manufacturer to create a consistent categorization system for warranty claims and reduce the time it takes to identify and address product defects.

"We're already seeing benefits from the SAS system," confirms David Bien, Sub-Zero reliability director. "We believe the system will pay for itself in 14 months or less. With SAS, we feel that we can be more proactive, reduce warranty expenses, and most importantly, keep our customers satisfied."

The new SAS system reportedly produces a proactive emerging-issues report to highlight new patterns in the previous month's warranty claims. Potential issues are assigned to product engineers for immediate investigation. Sub-Zero engineers from other departments can sign up for e-mail alerts on any of the company's hundreds of product components.

"SAS Warranty Analysis is built on a solid analytic foundation to allow a company like Sub-Zero to avoid catastrophic warranty payouts by finding the problems before they become pervasive," said Thomas Roehm, senior director of SAS supply chain intelligence solutions. "Rather than the typical online analytical processing (OLAP) or rules-based text analysis offered by most other solutions, SAS offers customers a comprehensive business intelligence platform for data-driven, in-depth analysis on text and other data to identify and resolve issues faster than ever."

The new warranty analysis system is said to integrate warranty data with key customer, production, and geographic information in a manner that allows organizations to create useful knowledge. It allows users to identify questionable warranty claims to detect fraudulent activity; to automatically detect emerging issues earlier; to determine the root cause of problems so that company resources are focused on the right areas; and to forecast warranty costs.

The premium refrigeration manufacturer is also using text mining tools to uncover the underlying themes or concepts that are contained in large collections of documents. With this solution, documents are automatically clustered into groups and classified into predefined categories so that they deliver insight into the business issues at hand. Predictive models can be built with this data to forecast the outcome of a response variable based on the contents of the text.

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