Predictive Analytics Project Design: A Nine-Step Guide to Realizing Business Value

July 16, 2012 No Comments

Predictive analytics continues to develop as a key decision technology across virtually every type of business because of its promise to enhance business performance and derive significant competitive advantage.

The business performance enhancements achieved are generally based on more effective allocation of the organization’s resources, especially in functional areas such as marketing, attrition/retention, fraud, risk management, and other areas where relatively low-incidence behaviors have a significant impact on business performance.

Technology is also critical. Yet a project’s success is primarily determined by strategic technology implementation—not by the technologies themselves. No piece of software, and no algorithm, understands the domain of the decision process or the project team’s unique performance metrics.

Ultimately, predictive analytics projects are evaluated based on their return on investment and by the contribution they make to the business objectives of the sponsoring organization. That contribution is always based on each organization’s unique project performance metrics. This TDWI Checklist Report examines the strategic steps that predictive analytics project teams must take in order to define, design, and implement successful projects.

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