SOURCE: Apollo Data Technologies

November 15, 2005 08:00 ET

Apollo Data Technologies Announces Breakthrough Inventory Forecasting Solution for Retailers; Prevents Out-of-Stock Items to Increase Sales

Using Data Mining to Predict Inventory Levels

CHICAGO, IL -- (MARKET WIRE) -- November 15, 2005 -- Apollo Data Technologies ( announced today its Inventory Forecasting Solution that allows retailers to predict product order levels weeks into the future across their entire store chain. Based on Apollo's advanced predictive models, Inventory Forecasting Solution accurately predicts sales trends and prevents out-of-stock situations for retailers. Apollo's models can also predict the quantities of inventory to stock to keep overstocking costs to a minimum.

Current supply chain management (SCM) software offers logistical breadth but lacks analytical depth and typically uses out-of-date forecasting methods. As a result, retailers are unable to fully capitalize on the massive amounts of sales and product data they collect to optimize inventory levels.

Predictive Analytics applies the science of advanced statistics to data and provides actionable "smart" intelligence ready for businesses to gain competitive advantage. Traditionally used by marketers to increase customer acquisition and retention rates, Predictive Analytics is gaining quick adoption by corporations because of its ability to more accurately optimize operational forecasting like supply chain, sales, and inventory management to increase their bottom line.

Additionally, in a December 2004 report, Aberdeen Group ( found that "A review of advanced technologies in use showed that planned deployments make sense, given results already achieved. Adoption has had positive effects... Applications that use forecasting or optimization to control the levers of merchandise financial and assortment plans, price, promotion, and markdown management had the most dramatic impact on merchandising performance."

Apollo Data Technologies Inventory Forecasting Solution is comprised of four main components which are built on top of SQL Server 2005 technology: First, a modeling database is created which imports a retailer's sales and inventory data from their enterprise data warehouse. Second, predictive models are built from sales and inventory patterns identified in the modeling database. Third, the models are tested with actual sales data to calculate and measure the predictive accuracy and sales opportunity. Finally, the predictive models are then deployed and integrated with the retailer's SCM system to close the loop on their ordering pipeline.

"Recognizing the infrastructure investments retailers have already made, Apollo designed its solution to be platform agnostic and pluggable into their existing SCM systems to immediately generate a higher return on investment," said Jeff Kaplan, principal and co-founder of Apollo Data Technologies. "This allows companies to efficiently predict inventory and the potential to increase sales by hundreds of thousands to millions of dollars."

Microsoft recently selected Apollo to deploy its Inventory Forecasting Solution for Project REAL to predict for the retailer Barnes & Noble which books would be out-of-stock one and two weeks into the future.

Project REAL is a cooperative effort with Apollo, Microsoft and companies including UNISYS, EMC2, ProClarity, Panorama, Scalability Experts, Emulex, and Intellinet, to discover best practices for creating business intelligence applications based on Microsoft SQL Server 2005 (

About Apollo Data Technologies

Apollo Data Technologies ( is the first company delivering true predictive analytic solutions for key vertical markets. Apollo discovers hidden patterns and trends in data to help businesses operate more effectively and efficiently. Its world-renown and award-winning team of Ph.D.s bring decades of distinguished work in analytical CRM, expertise in building and designing data mining applications, and the practical business know-how and experience in applying the results. Apollo provides solutions for all stages of data analysis, including setting data collection strategies, data warehousing, text mining, and predictive analytics and more for customers including Microsoft Corporation, Barnes & Noble, Knight-Ridder and The Seattle Times Company.

Contact Information

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