January 31, 2017
Timothy Deckman, Ph.D.
More complex markets with direct and indirect competitors. Products with greater upside potential. Increased development risk. Shorter commercial design timelines. Complex, multi-stage, multi-drug regimens.
Cumulatively, these factors point up the increased importance to BioPharmaceutical manufacturers of modeling commercial decisions in complex markets. Traditional forecasting approach using spreadsheet megamodels cannot account for the complex options and developmental uncertainty that exists in our market today. Nor can these large complex models provide the insights necessary to guide the appropriate strategic decisions.
In this workshop, you will learn how to design and build models quickly and efficiently while managing the statistical error inherent in any forward-looking exercise. The workshop itself will combine didactic learning with group exercises to provide a sense of critical success factors in building models under uncertainty and offer a couple of specific tricks you can use in organizing the process.
- Identify the four high level success factors for modeling under uncertainty
- Explore the challenges inherent in achieving each factor in today’s business environment
- Learn at least two specific tricks that will improve your ability to execute short-timeline decision support models for complex markets