Experience Curve

@RogerBohn complains that The Economist praises a dangerous and obsolete management concept - namely the experience curve or learning curve.

The theory of learning-by-doing was introduced by economists to explain the macroeconomic observation that productivity typically increased during an extended period in which the production processes and technologies remained the same. The theory suggests that these productivity improvements can be related to cumulative production volumes. Economists use the theory to predict that aggregate productivity levels will increase under certain circumstances. However, management consultants have generally used the theory at a microeconomic level, apparently believing that it predicts productivity improvements in specific production units, and that (as Bohn complains) "improvement is inevitable and the same for everyone in an industry".

Bohn points out how productivity in the car manufacturing appears to run entirely counter to the microeconomic interpretation of learning-by-doing. Productivity at Toyota improved far faster than at General Motors, even at a time when it produced (and had cumulatively produced) far fewer cars than GM.

Now here's the twist that may save the theory. Toyota's competitive advantage was in JIT and “The Toyota Production Process,” which Bohn describes as "a system for making more rapid improvement". So Toyota core process wasn't manufacturing-cars, it was improving-manufacturing-cars. Toyota was making improvements at a staggering rate, which left its competitors standing. It's more difficult to count improvements than to count cars (because improvements can be understood in different ways), but it is not hard to believe that Toyota's cumulative number of improvements has been higher than that of GM for a long time now. If we reframe the production system in this way, perhaps the theory of learning-by-doing could apply to this example after all.

But this interpretation of the theory of learning-by-doing is quite different from the conventional interpretation, and would make its use as a predictive tool or as a consultancy tool much more problematic.

The Perfect Question

In the story of Parsifal, the hero ("the consultant") meets someone with a problem ("the client"). The inexperienced Parsifal is reluctant to ask too many questions, and so fails to ask the one critical question. Afterwards, he learns that merely asking this question would have solved the problem.

Actually that's not so far-fetched. As a consultant, I have sometimes happened upon the perfect question. Once I was investigating disappointing productivity figures in a large German firm. The project managers told me it was the fault of the tools and methods group. The tools and methods group blamed the project managers. I sought out the boss of the division and asked an innocent question: Who is actually responsible for productivity? My question triggered a management decision that addressed the problem.

Two things to note here. Sometimes the consultant needs to answer questions, not just ask them. And sometimes the consultant needs to get on with the job, rather than fantasize about finding the perfect question. Parsifal couldn't ask the right question until the time was right.

Towards the end of the tale, Parsifal gets a second chance. In some versions of the story, even though he now knows the proper question to ask, he chooses to ask a different question, a more personal one. It turns out that the authentic question is just as good, if not better, than the perfect question.

Quite so.



Related Post: Asking Stupid Questions (Feb 2013)

Updated 9 Feb 2016