The single most important factor influencing pharmaceutical and biopharmaceutical decisions is demand forecasting. Forecasts impact decisions regarding capital cost, outsourcing for product commercialization, and many other critical aspects of production. It’s no secret that drug forecasts are notoriously incorrect, and often by large margins. John LaMattina, former president of Pfizer Global R&D, foresees no improvement in forecasting accuracy.1 How then, do companies minimize risk?
Two-Thirds of Forecasts Are Incorrect
Achieving accurate forecasts remains extremely challenging, with numerous factors causing product demand variability. Demand forecasts are made during the initial phase of drug development with little information on which to base sales projections. Companies must build capacity and inform manufacturing commitments as early as four to five years before launch, while the label may arrive only six to nine months prelaunch.2 In that time span, variables and market conditions change, and competing products may enter the market. As a result, two-thirds of forecasts are incorrect, with high rates of significant over- or underestimation. One study found that greater than 60 percent of drug forecasts over- or underestimated peak revenues by more than 40 percent of the actual.3