IBM SPSS Decision Management

Combine predictive analytics and business rules to optimize and automate the millions of small decisions made every day. Increase the positive outcomes of good decisions, and minimize the negative impact of bad decisions.

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Analytics Goes Mainstream


IBM SPSS Decision Management software gives business users a simple way to inject predictive analytics into the business process to ensure optimal outcomes. It offers a simple, "three-click" automated modeling and scoring Web interface.

It is best suited to "front line" operations (such as a call center, branch office, retail store, Web site, point-of-purchase terminal or ATM) because so many customer contacts occur at these sites every day.

IBM SPSS Decision Management can be configured to meet virtually any organization’s business requirements. Currently, two out-of-the-box applications are available:

Decision Management 6 includes all aspects of automated decision design and deployment that an organization needs. It empowers organizations to:

  • Make advanced modeling techniques more broadly available, in order to predict what is likely to happen based on patterns found in historical data
  • Optimize and automate high-volume decisions and produce improve outcomes in specific business situations
  • Monitor how recommendations based on predictive models affect customer interactions or other processes
  • Collect information about results, and use that information to refine predictive models and future recommended actions

What’s New in Decision Management 6?

Simulation capabilities

  • Run multiple simulations, compare the outcomes of different approaches – modifying variables such as cost and profit margin – and then deploy the best-performing models

Customizable business applications

Modeler Advantage

  • Enhance collaboration between business users and analytic professionals. Through a simple Web-based interface, business users can easily design and build models based on their own business scenarios, with their expert analysts validating and refining those models to improve results. This means that the results of predictive models by be deployed faster but with complete confidence in their reliability.

Read more about how you can put the power of predictive analytics in the hands of business users.



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