The case for forecast accuracy

People always say that you get what you measure. And it is true. When I want to loose weight and I am serious about it, I do have to step on the scale frequently. The same thing is true for business. What gets measured gets done.


Forecasting has become a critical business process. Pretty much every company that I talk to is either improving or looking to improve this process. One of the measures that can be used to manage the forecast process is forecast accuracy. Forecast accuracy measures the percentage difference between Actuals and Forecast. Let’s say we forecast 100 units sold for next month and it turns out that we actually sold 95, the forecast accuracy value -5%. We can measure accuracy at different levels of an organization, let’s say at the Profit Center level or at the BU level.


A few weeks ago, I had an interesting discussion with a group of consultants. They argued that forecast accuracy is not worth measuring. Their main arguments were:

  • Forecast accuracy cannot be influenced. The markets follow a random path and it can therefore not be expected to achieve accurate forecasts.
  • Forecast accuracy is a dangerous thing to measure and manage. People can start influencing the accuracy by managing their numbers according to expectations (for example sales managers can hold back deals for sake of influencing accuracy)
  • The quality of forecast accuracy is hard to define. Let’s say we beat our own forecast by performing really well. Forecast accuracy is off. Is that good or bad?


Here is my personal view on this topic.

  • No single measure is perfect when looked at in isolation. Let’s say profits. What does the profit number for a certain quarter tell us? Nothing! We need to look at a mix of measures. Forecast accuracy is one measure that we can/ should look at.
  • Forecast accuracy provides us with the ability to identify potential bias. One of my clients, for example, found that their models were flawed. Forecast accuracy revealed this by highlighting a certain consistency.
  • Markets movements are difficult to anticipate. But it is the job of the forecaster to identify potential actions to make sure that targets are achieved. I should have a general clue about what is happening in my business. Once in a while, we encounter some surprises. Does that mean we should not measure forecast accuracy? I beg to differ. At the very least, a detailed analysis of the accuracy measurements can help us learn a lot about our organization and our environment.
  • Forecast accuracy is easy to measure. It can be automated. Cost are almost zero. Why not measure it and potentially learn something?

I could go on and on. The bottom-line is that forecast accuracy is easy to measure and that it allows us to get a good sense for our ability to forecast and manage our business. But we need to be careful about how we utilize the metric. A singular focus on managing just accuracy won’t do anybody any good. But that’s true for anything. If I want to loose weight, I should also look at muscle mass and water content – not just weight as measured in lbs or kg. But to start bashing a single metric is not a good way. I am all for looking at forecast accuracy – often.