How do you know your process is "IN Control"?

How do you know the process is  “In Control”?

This is a question frequently asked by managers, auditors and engineers.  After all, there are huge implications to the bottom line not to mention customer satisfaction when a process has a probability of producing defects. And yes, all processes have a probability of producing defects.

Unfortunately in many organizations, there are two common answers to this question: “We know the process is in control because we do not have any customer complaints” or “The process is doing the same as it always has and it passed quality control tests”.

Not receiving a corrective action request from a customer is helpful secondary evidence. However, it does not ensure that the process is in control, it simple means that the customer has not complained. Perhaps they have already moved on to your competitor and the issue is not worth the hassle. Maybe they don’t value your relationship enough to waste their resources to call and try to determine the root cause. Or perhaps their process is not robust enough to catch the error. Therefore they are propagating the error out to their customers, further exacerbating the issue. All of these scenarios put the company’s continued revenue stream at risk as well as erode the brand reputation.

The second common response, “The process is doing the same as it always has”, again is helpful secondary information but does not conclude that the process is in control. It also provides no insight to ensure the QC processes are in control or even appropriate. It simple means that a defect was not detected by the current measurement system. Further it provides no mechanism as how to make improvements.

There is an old Mark Twain quote:

“If you always do, what you always did,

You’ll always get, what you always got.”

Anybody that knows me will tell you this is my favorite quote. Organizations with this mentality, never adapt, never improve, and never innovate. Organizations that practice this philosophy shrivel and die.

In order to understand if your process is in control, you must first measure it. This comment goes beyond the obvious, but in my experience most companies don’t truly understand if their measurement systems generate data that is statistically equivalent or not.  In order to make a determination of control, an understanding of the sources and amount of variance that the system produces are necessary. This concept of understanding and then reducing process variance is at the heart of the Six Sigma philosophy.

Six Sigma often suffers from the perception that it is used only by large companies, on expensive projects or by engineers that need to perform higher-level math functions.  This is simply not the case; Six Sigma is just a set of tools and techniques employed to measure process variance therefore providing a roadmap as to where to best implement improvements. Similar to Batman’s Utility belt, the Six Sigma methodology has several different “tools” at it disposal to measure and reduce process variance. This trick is to use the right tool for the job.

To answer the question, “How do you know the process is “In Control”, the easiest solution is to implement a Six Sigma philosophy. Like every other methodology, Six Sigma tools vary in complexity from the very simple, like control charts and standard deviation calculations, to the slightly more sophisticated mathematical tools like ANOVA or  T-Test. However, no matter the tool, you first have to put aside perceptions and bias and measure the process to determine how repeatable and reproducible your system is. Using a Six Sigma approach will allow an organization to focus on the right opportunities to achieve maximum benefit.  GE realized $12billion in savings in their first 5 years of use, imaging what it could do for your company.