Managing uncertainty and probability in BD&L Marketing Research
Healthcare products companies of all sizes flourish or fade based on their ability to build robust portfolios by acquiring high-value assets and culling low-level ones. In 2015, there were 468 announced deals involving therapeutic drug assets, devices, diagnostics and insurance companies, according to data from Thomson Reuters, representing a 10% increase over 2014 and a 90% increase over 2012. This extends a trend of an increasing number of deals, beginning in 2013 after a sustained decrease during the economic downturn around 2008.[1]
In most cases, the money invested in these deals would have earned greater return if the manufacturer had simply invested it in a stable stock portfolio. The challenge is that every asset, strong or weak, has at least one senior executive who considers the opportunity “amazing” or “exciting.” Senior executives possess powerful, well-earned faith in their own intuition, and expect analysis to confirm the benefits deal.
The challenge for the consultant is to develop a case that executives can evaluate against their own intuition. This makes the BD&L consultant part strategist, part data scientist, part psychologist and part seer.
No other research discipline presents such a broad, diverse set of issues or requires the same level of consultant confidence to support or oppose the client’s vision and goal. In four assignments with one BD&L client, the results, respectively, a) supported one major acquisition, b) halted another one, c) responded to a restructuring request by recommending divestiture of the target division, and d) backed significant investment in a clinical trial.
The BD&L research must focus on three critical elements:
1. Probability of success. Approval of most deals is contingent on the forecast producing greater return than a specific value (frequently called a hurdle criterion). Even when the hurdle may be a fixed number, it is more helpful to frame the question as “How likely is the deal to clear the hurdle?” Given that the final outcome is likely to be derived from small samples and interpretive data, the methodology must include key analytical tools such as probabilistic statistics like Monte Carlo modeling and bootstrapping in order to answer the “how likely” question accurately.
2. Key sensitivities. When you tell a confident senior executive that s/he is wrong, a savvy consultant must support recommendations with data points that both make sense intuitively and determine what really matters. In this regard, sensitivity analysis enables the consultant to say, “You can increase the chances of success from 50-50 to 70-30 if you can achieve one goal.” If the goal makes sense, the intuitive executive becomes more likely to change his/her mind and see a path to success.
3. Appreciation of commercial considerations. In most BD&L projects, both time and money are at a premium. Qualitative interviews are relatively inexpensive and can be completed quickly. The moderator must be comfortable with key commercial issues, know when and how to probe deeply, bring a skeptical but not negative approach, and ask questions that produce the results necessary to populate models.
Proper analysis involves converting data sets from diverse origins and with different confidence intervals into a model predicting the outcome of the acquisition. For the analyst, this requires an expertise in probability-based statistics, an appreciation of what one can learn from qualitative interviews or surveys with small samples, and a sense of when and when not to believe what appears counter-intuitive.
Finally, know that researcher recommendations matter. Researchers who master the implications of probability and sensitivity while acquiring a keen appreciation of commercial issues can provide real value in a challenging, critical environment.
[1] BioPharma Dealmakers, Deal Trends, December 8, 2016, Laura J. Vitez & Richard K. Harrison