CATEGORY: Data Quality
REVIEWER: Bipin Parmar, vice president of engineering for PartsRiver Inc.
BACKGROUND: PartsRiver is the leading provider of data quality services and analytics for purchasing and inventory in the industrial parts industry. PartsRiver provides an automated solution to maintain the integrity of customers' data that is cost effective, accurate and timely providing visibility into purchasing and inventory inefficiencies, and fuel for other business intelligence decisions.
PLATFORM: Windows 2000.
PROBLEM SOLVED: Our customers are companies who purchase significant quantities of parts for ongoing vehicle and equipment maintenance, including companies such as Ryder which maintains a large fleet of trucks. These companies buy parts from many different suppliers and manufacturers, and our job is to make sure they have accurate parts data so that they can make better purchasing and inventory decisions. However, equipment parts databases cannot be "cleaned up" without significant industry expertise integrated into the solution, which has traditionally required costly and cumbersome manual efforts. We needed a way to more fully automate the parts-matching process, which is why we turned to Centrus, a division of Sagent, to give us these data quality capabilities.
PRODUCT FUNCTIONALITY: We use Centrus Merge/Purge to match part and procurement records across multiple data sources. This enables our customers to avoid costly inventory management mistakes, such as purchasing commodities under different part numbers at varying prices or not complying with warranty and equipment maintenance requirements. Centrus Merge/Purge allows us to use multiple matching algorithms, configure our match logic and allows comparisons using many different views of the underlying data. Enhancing our process with Centrus Merge/Purge provides a significant cost savings to PartsRiver and helps us deliver more accurate and timely information to our customers. Centrus has picked out 20 percent of the parts we were not previously catching with our own tools, and the process which formerly took up to a week to complete now takes just five to six hours.
STRENGTHS: Centrus Merge/Purge has excellent matching algorithms and is easy to use, but the most critical strength is its powerful configuration capabilities. While many organizations only need to maintain the quality of their own data, we must adapt the tool to deal with multiple customer data projects. Centrus Merge/Purge is easy to configure and enables us to tackle each new project quickly and easily.
WEAKNESSES: PartsRiver's indexing requirements were more substantial than the current release of Merge/Purge could accommodate. However, Centrus is addressing this issue in its next release.
SELECTION CRITERIA: We selected the Centrus Merge/Purge product for several reasons. First, Centrus Merge/Purge returned the most accurate results during our vendor evaluation. This was critical because we deal with millions of part numbers every day. Secondly, Centrus Merge/Purge has the capability to match on fields other than name and address, which differentiated it from many other data quality vendors and made it a great fit for our application. Most importantly, Centrus Merge/Purge had the flexibility to meet our configuration needs.
DELIVERABLES: Merge/Purge generates duplicate parts records that we use to normalize the duplicate to the right part.
VENDOR SUPPORT: Centrus Professional Services provided outstanding support from day one. The Centrus sales team allowed us to test drive the product before we signed on for a proof of concept. Once we were ready, they came in and did a proof of concept to help us understand the product better. The primary consultant on the account was responsive and knowledgeable. They were very willing to work within our requirements and never pressured us.
DOCUMENTATION: The documentation was excellent. When Centrus provided me with the product, I was able to use the documentation to immediately begin working with the software. The product itself was also easy to use.
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