Lousy Equations – Change the Game

Have you ever worked inside a lousy equation?

Six Sigma certification is about building the skill set to understand and control processes to achieve substantial, permanent gains. Have you ever found yourself in a project where the team, despite a great deal of effort, is struggling to bring a process to an acceptable level of performance? Sometimes, despite an effective use of the Six Sigma tools, teams cannot “crack the nut,” – they cannot identify and control the key inputs that are driving unwanted variation. The temptation in these situations is to stay on course, applying the DMAIC process within the confines of the existing process, when a faster and more effective approach might be a process or product redesign.

Let’s look at an example that some can relate to – let’s say that John, a recently certified Six Sigma Black Belt , decides to use the DMAIC approach to find a girlfriend. Having spent too much time in front of the television in his early years, John believes that perfecting his “pick-up lines” is the only way to realistically meet a girl. So John sets up a simple experiment where he tries four different pick-up lines at various locations, from bars to bakeries, also varying a few factors like eye contact, the strength of his smile, and the color of his shirt. John is a hard worker, and ultimately introduces himself to 60 women in three months. Here are the results

– 52 of the 60 women had no interest in John whatsoever
– 4 women took John’s phone number but did not call him
– Another 4 took his number and called him, and two of these resulted in dinners out with John
– Of the two women that went to dinner with John, one did not show interest in seeing him again, and the other had a boyfriend who was traveling overseas at the time.

So where did John go wrong? He was working inside a lousy equation, trying to optimize a fundamentally lousy process. How often do we find ourselves in this situation – we work within the confines of our existing process, lured by the fact that we sometimes get good results, believing that we have failed if we do not find the “root cause” and obtain zero-defect performance. This is a common flaw in Six Sigma certification training: too much emphasis is placed on understanding and controlling existing processes, with little focus on building cross-functional teams to generate “out of the box” solutions that may result in faster, more effective fixes.

Let’s look at John’s situation. There were some big factors that John will never be able to control, like the fact that many women are immediately put off by superficial pick-up lines. Also, John has no way of knowing which women are already in relationships. These two factors alone provide with a John a best-case success rate under 50% for a first date, even if he is the best looking guy on the planet! Clearly John’s issues go beyond using the DMAIC approach to optimize his “process” for finding a girlfriend. His process is fundamentally broken, and no amount of optimization will provide meaningful results.

John is persistent and hard working, but also smart enough to know when he is “barking up the wrong tree,” so he meets with a relationship consultant who writes a whole new equation for John, one that has been proven time and time again. Two major changes are in order: (1) use a reputable dating service to find women looking for a relationship with a guy like John, and (2) actually engage in genuine conversations with these women during his introductory discussions with them – no superficial pick-up lines.

John’s life changed. First, his success rate in landing a first date went from 3% to 67% (two out of three) – a rate that the best pick-up line in the world couldn’t have provided. Second, he was able to stop working his equation altogether, because the second of the two women who agreed to go out with John turned out to be the love of his life.

It’s important to recognize when a team is struggling with a lousy equation and needs a game changer – a significant process or product redesign that results in a new equation with tremendous potential for success. This is where having a cross-functional team is crucial, because Six Sigma Black Belts are usually not process and product design experts. So the message is, seek the most productive path to a lasting solution, even if it means abandoning the DMAIC approach within the confines of a current process or product design.

Here are a couple of examples –

Magnet Adhesion Project

A motor manufacturer bonds magnets to motor housings using epoxy glue that is heat-cured. The Cpk for bond strength is 0.4, not good! Despite a number of studies, the Six Sigma Black Belt and her team cannot find and control the variables that are driving poor bond strength. Finally she holds a brainstorming session, seeking “out of the box” solutions. A team member proposes a secondary grit-blasting operation on the magnets to improve adhesion. This additional process ends up solving the problem, and the short term Cpk improves to 2.5! A solid control plan is put in place to monitor the grit blasting operation, and the process produces zero loose-magnet defects in the years that follow. Had the team stayed on the path of finding and controlling root causes within the confines of the existing process, they might still be working on the project.

Cracked Pump Housings

A pool pump manufacturer is receiving field complaints due to cracked pump housings. A Six Sigma team is put on the project, and after an extensive DMAIC study cannot find which factors are causing cracked housings. A number of studies are done, including chemical analysis, melt viscosity on the (plastic) housing material, dimensional analysis on good versus failed housings, and a geographical analysis of the failures to understand possible environmental factors. After several weeks with no root cause identification, a design engineer looks closely some of the field failures and proposes a redesign to the housing, adding more material and more generous radii in the areas where the cracks are forming. The approach ultimately solves the problem completely, and the “fix” is robust, meaning that it does not require extensive monitoring in the manufacturing process.