Several years ago, I was working in a large dairy manufacturer’s control room, helping implement our product. We were observing the manufacturing process running, when they had an unexpected stoppage on a production critical-asset. While several employees rushed to address the issue on the shop floor, I noticed a shift supervisor copying down some notes in a small notebook. I asked her what she was writing down. She explained that she tried to keep track of a specific in-line quality reading at the point in time when this particular asset failed. She was performing a manual and basic form of data analytics and continuous improvement.
Looking back on this simple interaction, I realized this moment told a compelling story. The shift supervisor was improving and transforming her job skills, creating a mini-database and mental models for analyzing correlations between quality readings and asset failures. This capability is not in the job description of shift supervisors.