Consideration 5: Is the model output realistic? 

Even with the best of intentions, utilizing carefully curated data and statistically intricate forecasting tools, sometimes the outcome of the model just doesn’t pass the smell test. The hypothesis just isn’t realistic.

It’s easy to get carried away by the promise of a new revenue stream. The fervent demand for a new product/technology, captured in interviews and quantified in a survey that reveals huge unmet needs even for inferior solutions, can get an entrepreneur pretty excited. But in the wake of this excitement, revenue forecasters often forget the time and commercial investment needed to change customer buying behavior. In the clinic, early adopters often need to rewrite medical SOPs, to generate clinical evidence, and to convince payers to code and fund a new approach. Visionary entrepreneurs often think their product represents a transformational technical improvement, when in reality, its benefit to the patient is incremental. And in the time required for these medical and commercial transformations to happen, competitors and other market forces can quickly erode an opportunity that seems to be immediate and obvious today.

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