SAS Institute Wants To Predict Your Profitability

SAS Profitability Management uses cost and revenue modeling techniques to provide managers with insights into what drives profitability. They can track the profitability performance of classes of customers or even individual customers, product groups or specific products, and distribution channels. The ability to analyze revenue, costs, and asset categories in such detail allows businesses to manage profit as a performance metric, SAS says.

Traditional activity-based cost-allocation models can't provide the same level of detail that the new software provides. A recent report from AMR Research analyst John Hagerty says that effective profitability management today requires the ability to analyze information at the transaction level.

SAS Service Intelligence software helps businesses monitor, predict, and optimize the performance of their aftermarket customer service operations. The tools provide a means of improving customer satisfaction while at the same time increasing profits through improved forecasting of customer demand, reduced inventories, and better management of warranty claims. The applications can feed product quality information back into a company's design and manufacturing operations. The suite includes SAS Warranty Analysis, SAS Service Operations Optimization, and SAS Service Parts Optimization applications.

Aberdeen Group analyst Mark Vigoroso says improving post-sales service ranks among the top three priorities for CFOs. SAS says Shanghai GM, a joint venture between General Motors and Shanghai Automotive Industry Corp., is using the Warranty Analysis application to gain a better understanding of its warranty expenses and its aftermarket service operation.

SAS Profitability Management will ship in December, while SAS Service Intelligence is available now.

Later in November SAS also will ship SAS Model Manager, a tool for managing the predictive analysis models that an increasing number of businesses use for making strategic and tactical decisions, such as estimating risk exposure or analyzing customer profitability. Some companies, particularly those in the financial services industry, rely on hundreds of business models in their production systems. But models can become outdated and provide erroneous information and that, in turn, can lead to problems such as offering credit to consumers who are credit risks.

SAS Model Manager, which is integrated with SAS Enterprise Miner data mining software, continually checks the accuracy and usefulness of business models. The software also helps enforce the use of best practices during the model development process.