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NCR Offers New Cashier Productivity Tools

Monday 12 January 2004 11:17 CET | News

NCR has launched the NCR point-of-sale (POS)-based Cashier Management System, a solution that enables retailers to simultaneously boost cashier productivity and reduce inventory shrinkage.

The solution also includes human factors engineering and data mining consulting to optimize the design of the solution in a retail setting, as well as Teradata professional services to customize the application. Retailers have long faced the challenge of improving cashier productivity at the store checkout while increasing customer service. While most POS software contains some performance measurement analytics, the applications have not delivered the improvement in the front-end process retailers now demand. The NCR POS-based Cashier Management System and Teradatas POS productivity analytics include the following standard component technologies: -Teradata data warehouse and associated data loading utilities, which provide the basis for all data collection, storage, retrieval and analysis. -Teradata Warehouse Miner and Data Mining Lab, which provide automatic mining of the data, distilling results down to a series of scoring models to support reports, alerts, and recommendations. - Front-End Productivity Analysis, delivered by NCRs Human Factors Engineering practice, which conducts video analysis prior to and after rollout of POS Productivity reports to tune up front-end processes, recommend techniques that improve productivity and validate that productivity improvements are accurately reflected in the reports. -Teradata and NCR Store Performance Consulting, which provide consultative services to assist retailers in developing the right metrics, business rules, and reports to support the practices and procedures to which they want their enterprise and stores managed. -Teradata professional services, which provides data modeling, ETL and implementation services. The Teradata Retail Logical Data Model and POS productivity templates are also typically included in the package and can be implemented on most standard OLAP tools.


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Categories: Payments & Commerce
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