Day One

• Clarification of definitions for metrics, measurements, targets and goals and what their proper place is in R&D

• Contrast results versus predictive metrics – how they work together to deliver success

Successful metrics systems at leading companies go beyond just counting. They get right to the heart of what needs to be focused on to improve effectiveness and efficiency. We review case studies of how an aligned, predictive, well governed metrics system propels R&D to new levels of performance.

Metrics don’t have to be difficult to be successful. The powerful, but simple “three step” methodology lies at the core of doing metrics right. This session will review each step and its associated tools and how they contribute to metrics success.

Day Two

Introduction to the “metrics tree” – a tool to determine cause-effect relationships. Specifically, by leveraging the experience of the organization’s professionals to understand what really causes each goal to occur, the resulting “causal actions” can define R&D’s contribution to goals and build the foundation for R&D metrics.

Taking into account learning curves, partnering opportunities and existing skill sets, interim targets must be set for each metric defining performance expectations throughout the near and mid-term.

• Key steps for establishing governance - both predictive and results metrics must be reviewed and acted upon regularly. A governance system is the lynchpin of successful metrics implementation.

• Applying a straight forward, but effective approach to monitor your new R&D metrics.

With a solid knowledge base in place to set up R&D metrics, the next course of action is to develop a realistic implementation plan. The final exercise of this workshop outlines the steps necessary to deploy your new R&D metrics.