Presentation Abstract

The standard approaches to predicting how a new product will be adopted assume that we are completely rational when we decide to use or not use a product. The logic of the approach is that we trade off benefits and flaws across a set of products to pick the best alternative. In mathematical terms, we are supposed to be maximizing the utility of each feature in the products. It might be particularly reasonable to assume that this is how healthcare providers make treatment decisions. In healthcare, more than in any other context, don’t all decisions have to be purely rational?

There’s actually a lot of evidence that suggest this is not what we do when we make decisions, even if you’re a physician. There are elements of decision making that are done either instinctually or impulsively or both. So what’s going on? Why are our instincts so good? It seems likely that underneath our instinctual decision making is an elaborate array of decision rules or heuristics. Recent developments in software algorithms now allow us to build rule based simulations of future market scenarios using just heuristics.

This session will be a didactic presentation where I will illustrate how use a rule based approach to predicting product adoption. It will be based on a blinded case study and will include, Clarifying how to structure initial IDIs to solicit useful decision rules, outlining how decision rules can be used to create a market simulation tool similar to what is typically developed for a discrete choice study, discussing how a set of decision rules from a small sample can be used to reliably predict product adoption, exploring the prospect of this approach being the solution to small scale quantitative research needed in our industry, clarify the implication and application for global research, and emphasizing the value of having explicitly defined decision rules for adopting new products. 

Speaker Biography

Tim is Chief Research Officer at Healogix, a global marketing research and consulting firm. Tim has a Ph.D. in cognitive neuroscience from Tufts University and more than 20 years of experience in basic and applied research. He has more than a decade of industry experience, delivering accessible and actionable information across every major pharmaceutical category. He is responsible for driving research methodology and analysis at Healogix and developing leading-edge research and analytical tools for the company.