Data-Driven Decision Making

They say that there are three types of people, those who make things happen, those who watch things happen, and those who wonder what happened.

If you’re a business owner or leader, it probably pays to be in that first group.

The relevance of this for business leaders was made clear by the American quality expert W. Edwards Deming: “It is not necessary to change. Survival is not mandatory”.

If your organisation isn’t measuring activity and using data with a view to sustain or improve itself, then how confident can you be that there will be a tomorrow?

In reverse order, these three “types of people” can give a useful structure for data-driven business improvement.

What just happened? How many units did we use? How many people walked through our door? How often did our process “work” or “fail”? How many visitors became customers? Which reports does the organisation create in order to track performance?

What are we watching happen? Which are the troublesome parts of our process? Which actions cause errors? Why did some visitors fail to become customers?

The leap from these two questions to “How can we make things happen” (successfully) relies on an understanding of numerical and statistical analysis. At least it does if you want the comfort of making evidence-based decisions. Whilst human insight is valuable, evidence-based decisions are superior to constantly “winging it” using gut-feel!

Why is a problem occurring? What if that trend continues? What is likely to happen next? What might happen if we try this solution? What could be the best outcome from trying a new solution? What can we learn from collecting different types of data?

We might be familiar with a construction business measuring the time since the last accident. A digital marketing manager tracking how many visitors have clicked through to a website. A logistics manager analysing real-time traffic reports in order to save fuel during each day’s deliveries.