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Transforming forecasting for greater precision and agility
1
The Challenge
A $30+ billion pharmaceutical company specializing in diabetes care faced significant challenges with their forecasting processes. Their data management and business rules were inconsistent across multiple brand forecast workbooks, leading to poor alignment in their Gross to Net (GTN) analysis. The lack of visibility into assumptions made during planning and the inability to model what-if scenarios effectively hindered their ability to respond to changes like Wholesale Acquisition Cost (WAC) adjustments and significant contract changes.
2
The Solution
To address these challenges, Argano designed targeted Anaplan models for Demand Forecasting and GTN Channel Forecasting. These models accommodated separate cycle cadences while streamlining dependencies, providing process consistency and complete visibility across therapeutic types and brands. The solution included full automation of data interfaces to eliminate manual data gathering and introduced landing pages for upstream teams to input data consistently.
3
The Results
The implementation yielded significant improvements: the company decreased time spent on data gathering and forecast setup, achieved greater precision in forecasting pricing and liabilities, and gained visibility into variance drivers at a more granular level. The solution also enabled higher capacity and faster turnaround for what-if scenario modeling, leading to better understanding and collaboration between upstream and downstream departments. These changes collectively enhanced the company's forecasting accuracy and agility, building a foundation for continued growth.