In the early days of lean it was all about imitation. People looked at Japanese factories and said, “They have quality circles, let’s have quality circles.” Or TQM, or kanban or JIT or kaizen. Lean factories work in production cells, let’s curl up our lines into cells. And so forth. The nature of early scholarship and publishing on what came to be called lean didn’t help this. Value stream maps, A3 templates, kata – the popular tool of the day may change but as long as the approach is a simple, local solution to addressing systemic problems, the results will be limited.
That’s what seems to have happened with the experiment in the United States to reduce class sizes by hiring more teachers, as the Wall Street Journal reports that public schools learned an expensive lesson on class size. Billions were spent hiring more teachers in order to reduce the ratio of students to teachers, based on early but unscientific indications that smaller was better. This seems like a silver-bullet solution to a complex problem of improving results from an education system. Naturally there were unintended consequences such as creating demand for additional teachers that resulted in hiring them away from poorer to wealthier school districts. The initiative was well-intended, but the large-scale implementation was simplistic and not scientific.
We observe nearly the same phenomena when organizations attempt to adopt, or imitate, a lean system. Setting team size and span of control for front line leaders is a perfect example. The traditional companies try to keep indirect labor costs low by having a leader try to manage a large area and many people. The lean approach is to draft the standard work (content, sequence, timing, output) for that leader’s work in order to support the performance for their teams, and measure the time and skills needed for that leader to succeed.
For example, an automotive assembly line paced at a takt time of about a minute may have one leader for 5 to 8 workers. This is based on scientific measurement and testing of a shift’s worth of work for that team leader as they train, fill in, respond to problems and handle admin tasks in a typical day. “That means we need to have team sizes of between 5 and 8 people” would be the wrong conclusion to draw, even if you were an automotive company with that takt. Those who pay the bills hear this sometimes interpret it to mean that they can get away the high end of this range “8 to 10 people”. The correct approach is to take a step back and grasp the system as a whole, understand the inputs and outputs to that team’s success, and define the leader’s work, and therefore span of control, to support it.
When problem solving is done unscientifically, the danger is not that we won’t solve the problem successfully. It is that we will learn the wrong lessons from our failures. If the public schools only learned “an expensive lesson on class size” then the failure is larger than simply the wasted money. The lesson learned should not be “small class sizes don’t work”. That will only result in administrators and policy makers chasing after whatever next solution looks better, wasting more money. Rather, the lesson learned should be that unscientific approaches to problem solving rarely work and do so only by luck. The problem is not that the experiment with class sizes was a failure, it is that public school policy setters likely have not learned and will repeat a mistake. This is a lesson that any organization that has made progress on their lean journey will have learned early on.