In this series of posts, I am going to show how engineering underpins the world economy more than we think, and how we can improve our engineering performances by changing the way we think about engineering. The last post was bad news for us engineers. The good news is that we can all gain by improving our engineering performances. However, to turn our performance around, we first need to understand what’s not working.
Companies like IPA Global have answers based on statistical analysis, and have provided these answers for several years. They will tell you which factors are statistically correlated with successful projects, as Ed Merrow has written in his book. However, even the projects they interact with are getting worse, and there are many more projects that they don’t assess, such as government engineering projects. Political constraints with these projects usually rule out closing down a failing project: unemployment is often a bigger issue than a failed project for government sponsors.
Clearly there are other factors at work here. The fundamental difficulty with statistical correlations is that they cannot provide causes. Try this example. My hair grows every day and Halley’s comet is moving further from the sun every day. But that does not mean that my hair will get shorter when Halley’s comet comes back towards the sun. Statistical correlations can tell you which factors are correlated with project outcomes, but these associations cannot tell us much about the causes of project failures or how to make improvements.
We have to turn to different kinds of research to find the underlying causes for engineering project failures. The qualitative ethnographic research we do with engineers can help identify potential causes that statistical correlations miss.