Pick a Number! Drug Peak Year Sales Forecasting | Ep. 578

Forecasting Accuracy, Time to Peak Sales, How to Do Better

Hello Avatar! Welcome back for another week of biotech analysis. Today is Sunday, which means this is our Building Biotech newsletter that is focused on discussing biopharma strategy topics. Today, we’ll dive into the fascinating but often frustrating world of pharmaceutical sales forecasting—a cornerstone of decision-making in drug development that is riddled with challenges. Forecasting errors can have profound consequences, from underestimating the market opportunity for a blockbuster drug to shelving promising assets that could have transformed therapeutic landscapes. In today’s analysis, we’ll explore just how accurate these projections tend to be, backed by data and examples, and examine the opportunity costs of getting it wrong. Then, we’ll pivot to a practical framework for improving forecasting accuracy, highlighting strategies that can help avoid these pitfalls and ensure better alignment between innovation and commercial success. Let’s unpack why better forecasts aren’t just numbers—they’re the foundation for smarter, more impactful drug development.

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The High Stakes of Sales Forecasting in Pharma

Forecasting in pharma is no small task.

Decisions about drug development and commercialization hinge on predictions of market opportunity. But these projections are often wrong—and the consequences are significant.

Underestimating market potential? That’s a double loss. Promising therapies might never make it past development. Patients miss out on innovation. Companies miss out on revenue.

So, how accurate are these forecasts? Not very. Studies show forecasting errors can exceed 40% in some cases, with blockbuster drugs often underpredicted by significant margins. On the flip side, overestimation isn’t uncommon either, leading to wasted resources on therapies that fail to deliver expected returns.

This is more than just bad math. It’s a systemic issue tied to complex variables: regulatory timelines, competitive dynamics, patient adoption rates, and even unforeseen market disruptions.

The good news? Better tools and strategies exist.

Modern frameworks integrate real-world evidence, advanced analytics, and scenario planning. They help teams anticipate challenges and refine predictions. By identifying the root causes of forecasting errors, companies can align their decisions with both scientific and commercial realities.

Improved forecasting isn’t just about accuracy. It’s about maximizing opportunities—ensuring patients get innovative treatments and portfolios achieve their full potential.

Pharmaceutical Forecasting: A Game of Chance?