Managing inventory, promotional expenditures and personnel deployment poses significant challenges for retailers of consumer products. Rapidly changing consumer demands, shorter product life cycles, discounts by competitors and uncertainties in manufacturing are among the many factors that complicate these tasks. Managers and executives need to know as much as possible about each of these issues; to gain that knowledge, they have to analyze data from various sources that keep expanding in volume and type. For example, retailers have to combine data from point-of-sale (POS) and radio frequency identification (RFID) systems, pricing data with promotions data, and supply chain data with merchandising data. The ever more complex process of analyzing data requires significantly more work, as well as software and hardware that can manage the flood of data and the relationships among it. [[And while the need for data analysis increases, so do the costs of doing it. WHY?]] But with the fierce competition in today’s markets, companies must find ways to keep up and forge ahead.

Under these competitive pressures and changing business conditions, product, sales, and marketing managers have to make on-the-spot business decisions, and they can’t wait for access to the information they need. Companies have spent many thousands or even millions of dollars on relational databases licenses, massive multiprocessing hardware, and experts who can tune them, but these investments alone can’t keep up with multiplying volumes of data and innovations in business strategies and processes by competitors. And merely adding to those systems will provide only incremental scalability to improve performance and data access temporarily. Competing in the consumer market requires data analysis that scales upward 10 or even 100 times – and conventional technology and yesterday’s information architectures cannot supply these advances. Most retail data analysis systems use relational database management system (RDBMS) architectures that haven’t changed fundamentally since they were introduced in the 1970s.

The only way for IT managers to help their organizations meet the challenges in data growth and analysis is to change the architecture by which they manage data for analysis. Systems must cross-reference data from multiple sources, provide instant access to it and maintain high levels of performance so the data remains current and pertinent to the user’s task at hand.

HyperRoll’s Data Performance Management Suite™ delivers information to users on demand with zero latency, giving them access to information as it becomes available, so they can immediately see the impacts of pricing, promotions and merchandising on sales, review supply chain data and product availability to better serve their customers, and ultimately improve margins and prevail against competitors. Successful companies in retail and consumer products manufacturing already use Data Performance Management Suite to gain the edge they need.

To find out more about HyperRoll products, click here. To discover how these customers have benefited from the enormous value HyperRoll delivers, please contact our sales team at sales@hyperroll.com.