West Chester, PA — August 28, 2008 — Prescient Applied Intelligence, Inc. this week announced the release of the Visibility & Analytics (V&A) Inventory Module. V&A Inventory expands upon the existing V&A application modules and provides suppliers and retailers visibility into information needed to manage the flow of product and to ensure the desired inventory is available on the shelf for the consumer at all times.
V&A is a Web-based business intelligence solution, powered by Prescient's Demand Signal Repository. The Demand Signal Repository (DSR) is a data warehouse that manages point-of-sale and other transactional data from retailers and suppliers and enables customers to apply the data using collaborative solutions.
V&A Inventory keeps track of in-store stock positions as well as identifies the quantity of product on the shelf at any given time. The application comes with a set of standard reports but is also customizable, allowing users to configure their own reports based on data attributes that effect their decision-making process. Additionally, with delivery information matched against point-of-sale (POS) data, suppliers can identify gaps in flow ratio and make proactive changes to ordering and delivery practices.
One consumer products company, who has been a long-time Prescient customer, was experiencing in-store shrink approaching 17 percent. The company said it saw the opportunity to become one of the first adopters of the V&A Inventory and Shrink modules as a way to combat this growing problem. V&A provided them visibility and information from the item data spanning 7,500 stores and multiple retail partners. The company said the insight was invaluable as it focused on shrink reduction and improved service levels at the store shelf.
The results that the company gained from the V&A modules include a reduction of over $500,000 in inventory discrepancies and a 12 percent reduction in shrink. They have also reported a significant time savings in daily analysis and reporting through use of the V&A application.
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