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Reliable analysis of business data produces insights for competitive advantage
SAS leads the forecasting software market with deeper penetration than other software vendors in industries such as consumer packaged goods, manufacturing, banking, pharmaceuticals, retail, utilities and higher education. This finding was based on published reports. SAS currently has more than 6 500 licences with 3 969 unique customers globally for just one of its forecasting products. In a survey of published 2005 Top Ten and industry lists, SAS forecasting solutions were licensed by a large percentage of companies in the following industries:
"Today's competitive landscape has forced organisations to operate more efficiently, not just on a day-to-day basis but also in planning for the future," said Jim Davis, chief marketing officer at SAS. "Decision-makers at these companies use SAS forecasting solutions to give them an accurate picture of the future and the ability to reliably measure the impact of economic and marketplace factors. The result is competitive advantage." SAS solutions for forecasting help organisations across the industry spectrum plan at the most operational level – where day-to-day decisions take place. For example:
With SAS forecasting technologies, decision-makers accurately analyse and forecast processes that take place over time. By identifying previously unseen trends and anticipating fluctuations, executives can more effectively plan for the future. Factors that affect business, including the economy, market conditions, customer demographics and such marketing activities as sales promotions, can be identified, quantified and included in the forecasting processes for improved results. Charlie Chase, market strategy manager at SAS, says: "Forecasting at 75% accuracy versus forecasting at 90% accuracy can mean the difference in hundreds of thousands of dollars to the bottom line. "With SAS, our customers know they can trust the analytics, plus we provide a complete forecasting solution that includes data access, data cleansing, large scale automatic statistical forecasting, and integration with planning and business systems." |
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