What Manufacturers Can Do When Hitting The Continuous Improvement Wall

By Gregg Gordon, Senior Director, Manufacturing Practice

Ask manufacturing engineers or production supervisors how long they have been under pressure to reduce costs and improve productivity and they’ll most likely say since they started working.

Improvement methodologies such as Total Quality Management and Design for Manufacturability come on strong, and manufacturers rally around them as a new approach to wringing incremental performance out of operations. And yet decades later on the production floor, some weeks everything performs flawlessly and other weeks it seems that Murphy’s extended family has come to visit.

Fatigue with the improvement projects can set in over the years because the big issues of a production line have been managed. The machines are rarely down for more than an hour. Kanbans to manage and reduce WIP have been implemented. As the teams move down the Pareto chart, the big gains have been achieved and each new effort seems to
return less gain. Eventually people move on to other issues and performance of the production line flattens out.

Exploring the Issues of Variability
Chasing down the biggest issues first is so ingrained in our minds that it seems almost like a law of nature. Invoking a justification of Pareto analysis, commonly known as the 80/20 rule, brings nods of agreement in justifying the order of how issues should be addressed.

But there is a follow-up question that should be asked that almost never is: “Even though we’ll solve our biggest issue, how much variability will be left in our system based on the remaining issues?” This is an important question because the process will suffer from the cumulative effects of the remaining variability. The workforce can be a significant cause of variability. So as the number of employees who participate in the process increases, there is going to be a cumulative effect of variability from each employee within the overall process.

Disruption Happens
As each employee is an independent variable, employees’ effect in terms of delay on production is cumulative. Bringing a process into control requires the management of all the independent variables affecting the process, including the workforce.

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