A large biotech firm was faced with unpredictable sales and profits due to similar pharmaceutical drugs (biosimilars) being introduced by competitors. Competitive product entry in Big Pharma creates forecast uncertainty in ways that are unique to the healthcare industry, making forecasting exceptionally challenging. The organization needed a sales forecasting model to accurately predict the impact of competitive entrants. The client had dedicated two separate initiatives to addressing this need, and both initiatives failed to achieve their goals.
Unify provided a team of data science experts to investigate existing sources of inaccuracy and design a comprehensive forecasting model to better predict sales. The team met with key stakeholders to better understand the structural components incorporated in their existing economic and product models. A minimally-viable product (MVP) forecasting model was created and evaluated by comparing monthly forecasts to actual product sales. In less than two months, the organization validated the prototype model’s exceptional performance on test data. Unify expanded this model to develop production forecasts for additional product lines and markets.
The Unify team designed a robust model that accurately forecasted sales for three very different products in over 170 countries, under a variety of competitive scenarios. The model outperformed all existing forecasts and was quickly promoted to production use for global planning by the company’s CFO. Unify met the challenge so rapidly that in under three months the final forecasts were incorporated into the organization’s strategic planning cycle for the following fiscal year. The production model Unify created enabled the organization to adapt to the predicted demand, reducing overhead and improving profitability.