Lean Six Sigma Fusion and Confusion

The Six Sigma journey of many organizations has morphed into “lean Six Sigma” during the past couple of years.

While the fusion of two methodologies has yielded benefits, it has also spawned a number of urban legends on the context and relevance of combining the two methodologies.

What follows are just some of the common misconceptions surrounding this fusion.

Urban legend No. 1: Lean Six Sigma is a trimmed down version of Six Sigma.

Many practitioners may laugh at that statement, but it is not uncommon to find staff in many organizations (including some who are responsible for driving operational excellence) who assume that lean Six Sigma is a simplified version of Six Sigma: perhaps a Six Sigma Lite. 

This misconception is easy to clear up with the right communication which explains that lean Six Sigma is a hybrid created by integrating some of the best practices from lean with the method developed by W. Edwards Deming—define, measure, analyze, improve, and control (DMAIC)—used to reduce defects by finding the root causes of defects, eliminating them, and sustaining that improvement level. DMAIC has become one of the two key methods on which Six Sigma projects are based.  

Urban legend No. 2: Six Sigma represents the hard side and lean represents the soft side of process improvement.

This is based on a widely held belief (especially by those who consider themselves to be of a more analytical bent) that when we talk of Six Sigma, it means performing hard core statistical data analysis.

Lean, on the other hand, represents the softer side of identifying and eliminating waste in the process and getting continuous flow by creating a value-stream map and performing some light-weight calculations linked to customer demand rate (takt time), work allocation, and head count.

It is not uncommon to hear project reviewers commenting, “We think this project is more lean than Six Sigma since the team has only reviewed the process and eliminated the wasteful steps.”

In some organizations such genre of projects are demoted to a lower level in the Six Sigma hierarchy of belts—Yellow Belt or White Belt instead of Green Belt or Black Belt.

The unstated message for employees is that if your project does not demonstrate use of statistical analysis tools then it does not meet the threshold set for a Green Belt or Black Belt project.

The unintended fallout of the above misinterpretation is that employees go to great lengths to draw some nice-looking probability distribution curves or capability analysis charts to impress management. Some take great pains to hide their efforts of reverse engineering their solutions by sprinkling a few data analysis slides that show how the conclusions were arrived at through data analysis and not through process walk-through alone. The tragic consequence of these actions is that somewhere down the line the essence of process improvement gets subsumed by these misdirected efforts.

It therefore comes as a surprise to many practitioners that Toyota practices lean and not Six Sigma. That does not mean they don’t make use of data analysis tools; far from it.

Toyota follows the plan-do-check-act (PDCA) cycle, a method for learning and improvement; they don't follow DMAIC but use the seven basic quality tools, with the Pareto chart and control chart for data analysis.

One stark difference with respect to Six Sigma programs is that there's no pressure to train everyone on a plethora of statistical tools, which has been the bane for many Six Sigma implementations in the past.

Another difference is the strong preference for observing and understanding the variation in the process in real time rather than collecting data throughout a time frame to consolidate into a Pareto chart, for example. This is akin to a detective preferring to investigate a recent case that rather than a cold-case where the trail and many of the clues no longer exist, making it more difficult to solve.

If we map this mindset to the Six Sigma journey then a process-map analysis of the measure phase is another way of observing a process and collecting data on its performance and variation in real-time. For many process-improvement journeys, this can yield much more insight than days of collecting data where, more often than not, the context has been lost over time (e.g., Donald J. Wheeler’s numerous articles in Quality Digest Daily on the fatality of analyzing data without context).

Urban legend No. 3: Six Sigma is for disruptive improvement (3.4 defects per million opportunities) and lean is for incremental improvement (kaizen).

Stated in another, not-so-polite way, lean allows staff to close a project by showing marginal improvement in the name of kaizen.

This phenomenon is very common in organizations where process improvement is seen as an additional chore to be performed on top of regular work.

For many organizations the business philosophy is “to make good products for the customer.” The implied message for staff is, “Perform normal daily management (to make good products) plus process improvement (in case defects are observed).”

This is very different from how organizations such as Toyota respond to what their business philosophy is, “Improving and evolving how we make good products for the customer.”

The message here for staff is very clear: “Normal daily management equals process improvement.”

Integrating a few tools from lean into the Six Sigma journey will not yield sustainable results unless we also understand the mindset behind the tools.

Urban legend No. 4: Six Sigma and lean are only good for manufacturing jobs or production environments with repetitive transactions.

This is a typical misconception for professionals such as software programmers, underwriters, lawyers, doctors, and staff involved in similar "thinking" jobs.

It's really a matter of understanding the context of the particular industry and adapting lean Six Sigma tools to that context.

For example, there is a lot of emphasis on standardization of work practices in lean. Standardization of work practices can help reduce the variation associated in people-intensive processes, provide a good training aid, as well as help with root cause analysis.

Very few people in the service industry actually understand the manner in which standardization of work has to be performed. Most assume it means agreeing to the workflow steps as laid out on a flowchart. However, this only captures the "what to do" part of the process and misses two other key elements

• How to do it?
• Why to do it in that manner?  (To prevent waste, improve productivity, reduce costs, prevent operator harm, etc.)

 

For service industry environments, standardization of work practices is one key tool that can be leveraged to reduce process variation.

Conclusion

For effective and sustainable business results, process improvement imperatives based on lean Six Sigma must invest the time to appreciate the mindset behind the tool set. Otherwise it will only add to the confusion in the minds of staff who may view it as another management fad.

About The Author