To conclude our current discussion of “If you can’t measure it, you can’t manage it” to its end point, let’s consider the consequences of taking this too literally- “I measure, therefore I manage”
There is an industry now for collecting data, massaging it, producing charts or spreadsheets – for others to use. So how much time is spent finding out whether the data is actually used and appreciated? Is there a process for following through the decisions made on the basis of that information to see how the data could be improved?
What can we do to improve our management?
Deming was, of course, a great believer in the value of metrics and statistical analysis, but even he realised that there was more to management than metrics and stated that one of the seven deadly diseases of management is running a company on visible figures alone.
A great example of the dangers of so doing can be drawn from the electricity company that decided to withdraw from service its most recent (and thus most efficient) coal fired plant only two thirds into its life and to build a new power plant using a new and untested coal source – because their model told them to! Questioning revealed that neither the modeller nor anyone else knew what was causing the model to generate its results.
Many a works system is designed to determine when works should be carried out. Inevitably this is based on the designer’s best knowledge and judgement at the time. But what if circumstances change? What alerts us to the fact that there IS a change? Do we know enough to make adjustments? Are we critically analysing the output of the system or do we take the system outputs for granted?
Question: Do you have examples of where measurement has led us astray?