Businesses that are good at forecasting have always enjoyed an important advantage over their competitors. The market trader who stocks up before an influx of out-of-town visitors; the drinks vendor who takes on extra help before a heat wave: both are in the forecasting business. Both are making assumptions about the future based on past experience.

Today, forecasting provides the foundation for planning processes across large organisations: demand and inventory planning, budgeting, sales quota, marketing campaigns and procurement. The more accurate the forecasts, the better the decisions, the more money the organisations can make or save. However, it is surprising how many organisations rely on manual effort and spreadsheets to carry out this important task.

In the case of a large organisation, however, accuracy in forecasting depends on the ability to manage and analyse huge amounts of data. Frequently the numbers are just too big for meaningful human interaction. If your organisation needs to produce forecasts for thousands of items based on trend analysis of millions of transactions, you need the industrial-strength statistical software that only SAS provides.

SASŪ Forecast Server
The latest forecasting solution from SAS features new capabilities such as time series data mining that put SAS far in advance of any other vendor. Built on the SASŪ9 Intelligence Platform, the SASŪ Forecast Server offers exceptional speed and scalability for automatic (batch) and interactive forecasting.

It enables companies to increase the accuracy of their forecasting, driving extra revenue and cost savings to the bottom line. For example:

• Retailers use floor space more effectively, stocking the right number of goods
• Manufacturers forecast demand fluctuations well in advance, knowing what to produce and when
• Banks ensure ATMs are optimally stocked with cash - meeting customer needs without sacrificing potential interest revenue

"In the past, only skilled statisticians could create accurate forecasts through data analysis. By contrast, SAS Forecast Server is built around the needs of different types of user," he adds.

An advanced graphical interface makes it easy for any user to point-and-click his way through the forecasting set-up process, quickly exploiting SAS' superior capabilities. And, as you would expect from SAS, forecasting models can be quickly applied to millions of data series. Once set up, the model can support forecasting as a repeated and ongoing process.

It's great for advanced users too: for example the code can be easily viewed and exported and the program is highly customisable.

"The true test of any system of forecasting is, of course, confidence in the results," says Leigh Bates. "Increasingly, SAS is seen as the standard for predictive software because nobody else can match us for accuracy."

SAS Forecast Studio includes features that add to the confidence of specialist analysts and general business users alike. For example, you can:

• Set up automated forecasting processes through the graphical interface - eliminating human error
• Use SAS analytics to reconcile up and down the hierarchy
• Generate exception reports based on statistical logic and business rules
• Automatically fix exceptions
• Publish results to applications such as the SAS Business Intelligence Portal for further analysis

Jody Porrazzo, Director of Econometric Risk Strategy at APEX Management Group was impressed by the capabilities of SAS Forecast Server. She told SAS, "Our actuaries can do true forecasting of time series data using auto regression models without knowing SAS.

"Before using SAS, they were somewhat overwhelmed by the overabundance of data. Now, they're performing process flows and forecasts, modelling data, and sharing their results throughout the organisation.

"And they're floored at how easy it is!

"Plus, the results are richer and more accurate than ever before. While other analytic packages ignore the fluctuations in data caused by seasonality, SAS allows business users to dig into those patterns and gain a true understanding of the data."

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For further information, please visit: www.sas.com/technologies/analytics/forecasting/index.html