SIX CRITICAL CONSIDERATIONS FOR QUANTITATIVE MARKET MODELING IN THE LIFE SCIENCES
Consideration 4: Where is the Data Coming From?
The life science and clinical diagnostics markets are unique. Compared to high-profile consumer and B2B markets, where data about market size, vendor share, average selling price, unit volumes, and geographic distributions are constantly collected and refined (often in real-time), data about life science customers and vendors is incredibly sparse (and often lagging). Even in highly attractive life science markets, the number of paying customers can be orders of magnitude smaller than in consumer markets, and building a consensus about purchase trends and behaviors is a significant statistical challenge.
So when you read a syndicated market report that appears to break down the served market for some young, emerging technology in amazing detail, segmented by dozens of disease research areas, subdivided by geography, and cross-referenced by vendor, you should really ask: “Where is this data coming from?” You might be surprised how many reports selling for thousands of dollars aren’t really based on any systematic collection of primary data, and are often created by analysts unfamiliar with the topic. Conjecture is cheap.
And if you’re hiring a firm to collect data and build you a market model, investigate the quality of their work. Do the people creating the model have a background in the subject matter? Are they steeped in the applications space? How long have they worked in the field? Have you seen examples of how they think and have put together models? Have other people you trust recommended them? If you look back on past work they did, how accurate was it? Can they explain the variances between what they authored and what really happened? What sources of data did they use as the basis for their model? Was it referenceable and objective? Are they willing to work with others to expose and tighten assumptions? Budget and time aside, did they incorporate primary research where secondary data was lacking?