3. Rigorous Learning
This begins with problem recognition and problem resolution using some version of scientific logic, like PDCA. It includes asking 5 whys or 500 whys, going to the gemba (which may be with a customer, etc., not just a factory), and learning how to think critically. That’s a start; there’s more.
Common issues using such frameworks are not probing deeply or widely enough to frame a problem in context, whether it is important or symptomatic when deciding where to invest learning power. A second is not retaining what we learn so that we rework the same problem time and again. That is, collectively absorbing what individuals learn so that it is shared and becomes standard practice is not as easy as it sounds.
A learning system is incomplete without a way to capture what is learned so that it is easily accessible when new situations are faced. The filing system need not be complex; it’s better if it is simple. A3 paper files are a form of such a system, but files are useless repositories if unused. And use of a record system is two-way; as input to it as well as output from it, expected as a regular part of work. Human psychology factors in because we do not like to report negative findings or failures in detail, but that is some of our most important learning.
To explain why design and development of this system is important, consider a description of a university library, used to explain to graduate students why they should know the history of their field. “The library is our past speaking to our present so that you can make our future better than today.”