Driver-Based Planning is a hot topic in the world of forecasting, planning and budgeting. What distinguishes “driver-based” from “not driver-based” is the use of mathematics to create budgeting, forecasting, and planning models.
Driver-based planning is used to predict future values based on trends and relationships between different measures such as costs, revenues and kPis. By entering a number into certain accounts known as ‘drivers’, the model will then calculate related information.
Drivers are set by taking a target measure (e.g. revenue or some other ‘outcome’) and establishing what directly impacts its value. For those items, we then establish what impacts them – and so on. measures at the end of the chain are known as ‘drivers’. Where possible, ‘drivers’ need to be validated against past behaviour.
Figure 5: Simple example of a driver-based model.
In the example shown in figure 5, the drivers of net profit include price per unit, unit cost, no. of visits and conversion rate. By entering data into these measures, the model is able to calculate net profit.
These models also recognise constraints such as production volume and that at certain levels cost and revenue profiles may change e.g. the impact of discounts, late delivery penalties, or that more staff will be needed which will cause a step change in values. they also recognise that there is nearly always a time-lag between the driver and the result it supports.
Driver-based models are good for modelling the relationships between activities and can be used to quickly generate future outcomes, but without the time, effort and politics involved in setting these values.
However, these models only work for certain measure such as costs/revenues that can be directly related to drivers. other measures such as overheads will be required to get the full picture. also they do not take into account unpredictable external influences such as the weather and they can only model what has happened in the past, which may not be a reliable indicator of the future in a volatile market or where product life cycles are relatively short.
The concept of driver-based planning was used to great effect in the movie MoneyBall. The film, which was based on a book by Michael Lewis, illustrated how a Major League Baseball team's assistant general manager used statistical analysis to identify the organization's key drivers for success. The analysis, which clearly showed that on-base percentage should be a key driver for player selection, changed the way the team's general manager approached planning and allowed his team to successfully compete against other teams with more financial resources.