Smarter.PFI Pharma Forecasting Intelligence
A Joint venture between Rivershill Consultancy and Differentia Consulting
If we looked at Forecasting Blog-Sphere we might expect
- how do I improve forecast accuracy?
- tell me where should the forecasting function sit ?
- how do I make the S&OP process work?
Important as the above are, more often we see..
- the forecasters role needs to be respected more
- we need to know the difference between forecasts and operational plans
- we need to understand the relationship between uncertainty and risk
Please give me forecasts together with the underlying assumptions. Without the assumptions I cant make sense of the numbers
Working with Differentia Consulting we started to design the Pharma Forecasting Intelligence.
The first task was to define the logic flow of the data captured by the system and we hit on the idea of making the journey similar to a storyboard mapping.
To ensure the storyboard flow design met the needs of decision makers we asked them to tell us the fundamental questions to which they needed answers. The structure shown below:
- Purpose and Scope
- Forecast Logic
Taking each module separately these are the questions it answers:
- Purpose and Scope:
Has the forecast the characteristics to help me with my investment decisions; are the time scales, currency, countries and granularity/fit for purpose?
How is the future described? I need to be told how the competitive environment is evolving, what future market access hurdles we will have to meet and what the reaction of our competitors will be, for example?
- Forecast Logic:
Tell me- in a non-technical-language how you have transformed qualitative assumptions into quantitative outputs. I will need to see how we will gain market share and how quickly we will get it. Also show me how future events have been included in the forecast.
This is all about making comparisons. If I have several assets in development I need to be able to compare the forecasts for each opportunity on a common template. I also need to see how, not only how outputs change over time but how the associated assumptions change as well. I also want to know how each forecasting affiliate sees the opportunity, for example by comparing each level of patient cascade in the model.
Armed with the above logic design we were able to produce a system that…
uniquely links the forecasts with the assumptions. The process was date-stamped to ensure the correct link is maintained over time.
made searching for the answers to specific questions much easier
enables the users to design in any benefits they might need for example a Monte Carlo simulation output can be included to view the most important uncertainties in the forecast and hence manage the main sources of risk.
Smarter Pharma Forecasting Intelligence (Smarter.PFI) brings together numbers and supporting narrative in one system for the first time. This significantly helps decision makers to see the context surrounding the bare numbers it encourages informed discussion around the real issues and provides focus to each stakeholder.