The Context
Here at J+D we create 100’s of strategic forecasting and operational planning models for many of the largest pharmaceutical companies year on year. These figures have increased consistently, certainly in the last 3-5 years; as scrutiny from pharmaceutical investors puts increasing pressure on revenue generation and growth.
Forecasting is a business-critical activity as it drives Investment Planning, Production, Marketing, Sales, R+D and essentially serves to mitigate investment risk.
Despite the importance of forecasting, many of our clients openly admit that they lack time, resource, understanding and general capability to optimise their approach to forecasting. Thus, a less than optimal forecast is created. Often the forecast is based on several numbers without the context/evidence to support the prediction and those in senior positions are left to make less than confident decisions about the future of their brands.
The Challenge
Forecasting is becoming more challenging as revenues are becoming increasingly difficult to generate and individual markets are more complex.
Complexity maybe derived from a diversification in indications, patent changes on products and opportunities in later lines of therapy/ or further combinations; all with a view to squeezing the last drop of profit from every potential brand investment opportunity.
Herein lies the problem, forecasting teams (more so outside the US and EU) are limited by resources and therefore, in some cases there are fundamental forecasting capability gaps, for example:
- The ability to engage with a variety of teams to obtain cross functional buy-in
- The capability to manage change when implementing alterations to the forecasting process (which can be met with much resistance)
- The technical understanding of the basic fundamentals of forecasting
- The basic understanding of the core business objective behind the forecast itself
The Solution
Improving the forecasting processes within an organisation isn’t an overnight task it takes time, energy and motivation to overcome resistance and to improve capabilities.
In order, for the forecasting process to work effectively we believe there are several pillars that support the overall optimum forecasting framework:
- The forecast must develop transparency around opportunity and risk and be supported by strong evidence to underpin the numbers
- The process must align all forecasting activities to generate one truth
- Complexity really is the enemy when developing decentralised forecasts. The challenge is to provide the required level of understanding around KPI’s without driving down compliance to the process
- Investment in training is key, and needs to be accessible, relevant and appropriate to requirements of users.
Forecasting is a complex multi-faceted discipline that needs to be managed and continually improved and adapted.
Best practice is attainable and overall confidence in robust decision making can be achieved.
Author: Maiko Midena
Maiko has been delivering forecasting and analytical solutions for more than 25 years. From his background in econometrics, he is now leading the technical development of specialist forecasting software at J+D Forecasting to address the challenges faced within pharmaceutical forecasting.
