The Strategy of Experimentation
Overview:
Research resources are too scarce to be squandered going down blind alleys and coming up empty handed at project end. We can no longer afford to play hunches or to rely on so called experts, whose opinions all differ, to guide research. Nor can we rely on the gross inefficiencies of old-fashioned one-factor-at-a-time experimentation to guide decisions. Instead, R&D must proceed systematically and with a goal of using unbiased data to guide decisions, following an overall strategy guided by statistical thinking and the scientific method.
We will also discuss Details of screening designs for determining the most influential among many, many factors, characterizing designs for the identification of interactions and optimizing designs are discussed, with examples given. We also touch on mixture designs for formulations and other commonly employed designs.
Why should you Attend:The Strategy of Experimentation offers a clear path to accelerated launch of successful products and to process improvement. It is a data driven approach to R&D that avoids dead ends, disappointment and wasted precious R&D resources. The basic principles are simple and can be easily understood without knowledge of statistics.
Areas Covered in the Session:
- Motivation for the Strategy of Experimentation
- The Hidden Laboratory
- Statistical Thinking
- The Iterative Nature of Experimentation
- Data Driven Decisions
- Simple Factorial Designs
- Characterizing Designs
- Optimizing Designs
- Mixture Design
Who Will Benefit:
- R&D VPs, Directors, Managers and Technologists
- Engineering professionals
- Marketing VPs, Directors and Managers
- Market Research Directors