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8 Steps to Proper Operational Process Change

July 9, 2013
Many times, conversation about process improvement neglects the more important topic of how to change a process.

There is much discussion about continuous improvement, kaizen and operational excellence pursuits in operations management. Many times, the topic of process improvement neglects the more important topic of how to change a process. While there is a desire to avoid stifling creativity among the best and brightest within an organization, a process change without process discipline can become the opening of Pandora’s Box and lead to degraded performance. Following are eight steps that, if followed, allow us to properly change a process with discipline while still embracing the insights and excitement of our rank-and-file operators.

1. Know the Current Process

One of the most important questions to ask at this stage is “Why is the process in its current state?” All too often, we see individuals try to drive change without understanding what caused the process to become the way it is. It is a sign of lazy analytics if the change proposer assumes the process is flawed because individuals who designed it were lacking in process design knowledge. Perhaps the changes we seek are only possible because of new technology or change in supplier. Regardless of the reasons, we need to understand the lineage of the process to avoid past mistakes. Additionally, we need a readily communicable model of the current process. If the organization is ISO-certified and fully compliant, a good documentation of the process should be readily available.

2. Know Why We Wish to Change the Process

The typical reason for process change is either cost reduction or variation reduction. For cost-reduction changes, a good cost deployment is essential. For variation reduction, the change agent should know whether random variation or special-cause variation (or both) is to be eliminated. We can typically erase special-cause variation with rifle-shot solutions (turn off the special cause and we turn off the variation). For random variation, typically increased capital expenditure (except in the cases of very sloppy processes) is needed to decrease variation.

3. Clearly Identify the Change to be Made

Once the current process is found to be deficient in some way, the new process should be articulated clearly and concisely. This may be in the form of a text-based document, a flow chart or other organization-appropriate form of documentation. Sample testing of the documentation to ensure clarity is important. Can operators look at the document and explain back to you how the new process will work? Do several operators understand the documentation the same way, or do they interpret it differently? Documentation should lead to clear understanding with little to no operator-to-operator interpretation variation.

4. Obtain Feedback and Buy-in from All Affected Stakeholders

In a forum of your choice (town hall meeting, posting with opportunity for anonymous feedback, etc.), the new process should be expressed to all individuals who are affected by the change. This includes all individuals who provide an input to the process as well as those who receive an output from the process. Will they be affected in a meaningful way? Will the change cause unanticipated results in their portions of the process? Will this process change add value (or eliminate value-destroyers) for the customer?

5. Revalidate Process Discipline, Data and Measuring Systems for the Change

At all times, we should be certain that processes are followed, data are reliable and our measuring systems are capable of providing data we can use to make good managerial decisions. That said, once we “shine the management light” on the process we are working to improve, change can occur that makes it necessary to re-validate our behaviors, methods and measurements.

Before driving the change in our process, we must ensure that the process that’s in place is adhered to properly. This alone can drive significant reduction in random variation. Once we’re certain of strong process discipline, we should measure the process once again and ensure that we are obtaining reliable data from our measuring systems. If necessary, a good gage R&R should be conducted to ensure quality and reliability of data.

6. Train for the Change

After the process changes have been detailed and documented with feedback from all stakeholders, and a method of measurement is implemented, all affected and responsible operators should be trained. This training must be documented and, if possible, operators should have the ability to review the training offline.

7. Declare a Clean Line, and Execute the Change

Using our measuring system, we should be able to determine a clean line. The clean line is a point in time, prior to the change, which will allow us to categorize data as “before the change” or “after the change.” This will be a critical step as we go forward in order to keep track of the changes and analytically validate their effectiveness.

8. Measure, Analyze, Improve and Control

After the change is implemented, results should be measured and analyzed. Was the change effective? Was the source or sources of variation eliminated? If appropriate, use the analyzed data to further improve the process, make adjustments based on reality and, most importantly, control the process. Be certain that the changes that were made are maintained and the process is controlled. Review all process documentation created throughout the process and ensure it accurately reflects the new process.

If a proper change management process is maintained, we can minimize special-cause variation due to individualized process approaches and still embrace improvement recommendations as they occur in our organizations.

Jason Piatt is president of Praestar Technology Corp., a provider of consulting and training services to manufacturers in the Mid-Atlantic region specializing in lean, Six Sigma & strategy formation.

About the Author

Jason Piatt | President

Jason Piatt is cofounder and president of Praestar Technology Corp.  Prior to founding Praestar Technology, Jason held various tactical and executive positions in engineering, sales and marketing, and program management with a leading power transmission component manufacturer.  He has served as a member of the faculty at Penn State University and has taught at Pennsylvania College of Technology in electrical and mechanical engineering technology, mathematics, and physics.

Jason earned a Bachelor of Science in electrical engineering with minors in mathematics and physics from Bucknell University. He also earned a Master of Science in electrical engineering from Bucknell and an MBA with honors from Mount Saint Mary's University.  Jason earned an executive certificate in technology, operations, and value chain management from the Sloan School at The Massachusetts Institute of Technology (MIT).  Jason completed his Six Sigma Black Belt training at the University of Michigan as well as additional graduate education at the Wharton School - University of Pennsylvania.

Jason and the Praestar Consulting team have assisted numerous manufacturers in the areas of lean manufacturing, Six Sigma, sales and marketing management, and strategy formation.

Jason has received numerous awards and recognition including senior membership in the Institute for Electrical and Electronics Engineers (IEEE) and membership in Sigma Xi Research Society.  He is a monthly columnist for IndustryWeek.com and has been referenced as an authority on manufacturing competitiveness by the Wall Street Journal Radio Network and other leading publications.

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