Consideration 2: How good is good enough? 

Market modeling is expensive! And that expense scales directly with the amount of precision and breadth you try to achieve with your model. So it’s critical to take a step back and think about what kind of modeling exercise is going to meet your needs.  At Chrysalis, we often break market sizing exercises into one of three classes. And each (or at least two of them) has their place.

THE SWAG: 

Sometimes there’s no need for a scalpel when a pocket knife will do.  For companies exploring markets for a new technology or considering expansion markets for existing technologies, Chrysalis often performs a Technology Market Fit, where we consider the needs of customer segments that span dozens of potentially diverse industries. In down-selecting opportunities, it can be critical to make broad distinctions in the size of the potential opportunity.  Is this a $10M market or a $4B market?  The data for the SWAG can come from industry analyst reports, from looking at the revenues of the major vendors in the space, or by quickly estimating the spend per global customer/patient and multiplying by a simple ASP.

THE TOP-DOWN MODEL:  

Danger lies ahead! The top down market-sizing activity is what underpins the models contained in many of the purchasable, 3rd party market research reports. A typical top-down market sizing strategy is to start with a macroscopic estimate of the size of an entire industry, and then to break that industry into smaller market segments using publicly available data sources (e.g., NLP-based publication/citation frequency, revenue splits from earnings reports, population and demographic data). It’s not difficult to produce a report that contains dizzying levels of segmentation, all presented in tidy tables and charts that imply a level of confidence and precision that may or may not be justifiable given the input data. At best, the output of these reports represents a directional view of a market, its major sub-segments, and its possible growth trajectory.

While there is a place for using these reports, many business leaders falsely assume that they can apply the general market trends captured in these reports to the specific subsegment that their business can address. If these leaders can agree amongst their peers and their investors that a directional view of the scale (and potentially the trajectory) of a market is good enough, then this is often the right approach. But all too often, leaders invest in a TOP-DOWN model hoping that they will be able to use it to build a robust framework for a business plan.  What they really need is something more rigorous.

THE QUANTITATIVE OPPORTUNITY ASSESSMENT: 

If it’s critical to understand the dynamics of an opportunity, if you need to understand the upper and lower boundaries of potential revenue for your product over time, if you are trying to build a commercial plan that focuses on the right customers, or if you are trying to compare the risk profiles of different business plans, neither the SWAG nor the TOP-DOWN model is likely to serve you well.  What you really need is something we call a Quantitative Opportunity Assessment, which usually contains the following:

1. Data collected from interviewing and surveying primary sources (e.g., potential customers who might buy your product)

2. Data from secondary sources (e.g., reputable analysis reports, medical incidence and prevalence data) that can be used to triangulate and reconcile the implications of the primary data

3. Precisely constructed segments (see consideration 3)

4. Multiple scenarios that take into account alternative starting assumptions to build  “bull, bear, and base” cases.

5. Quantitative comparisons with similar historical technologies/products and the rate of their commercial evolution.

6. An honest assessment of competitive threats (especially if you are building a revenue model)

7. Consumer willingness to switch from one technology or product to the other (especially in validated, clinical environments)

8. Transparency: understanding where the model is precise and admitting where the model is based on one or more low-confidence assumptions

9. A plan and a process to revise and evolve your model as the dynamics your industry changes or as new information becomes available

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