Forecasting complex and dynamic markets
“We don’t know enough at this stage.” “We are too far from market launch to forecast sensibly.” These are common concerns, and no one believes early forecasts based on current approaches. There is no data about the future, but that does not seem to stop some people spending (and wasting) large sums to gather it.
The problem is that most forecasting ignores, or significantly underplays, uncertainty.
Dynamic market modelling (DMM) is a scientifically rigorous way to understand and quantify the uncertainty and competitive dynamics that plague product demand and revenue forecasts. DMM produces strategically useful market predictions that inform such business decisions as segmentation, pricing, positioning, candidate selection, R&D prioritisation or franchise strategy.
A recent example
...was a dynamic market model developed for a pharmaceutical company, where the client’s product in a disease area was encountering new competition and many new products (including the client’s) were preparing for launch. The model and the process of building it:
- Informed decisions with cost-effective, relevant data and actionable insights
- Yielded a credible, scientific basis for decision making
- Treated uncertainty explicitly and consistently
- Avoided cognitive biases and single-point forecasts
- Accurately reflected dynamics and complexity
- Captured valuable knowledge capital and developed precise terminology.