DMAIC (Define, Measure, Analyze, Improve, Control) is a data-driven, structured, customer-centric problem-solving methodology. Each phase builds on the last to arrive at practical solutions for challenging problems. Define tells you what to measure. Measure tells you what to analyze. Analyze tells you what to improve. And Improve tells you what to control.

Each phase has particular objectives and is supported by a specific set of activities. Let's take a closer look at them.

Donald J. Wheeler, PhD is a world-renowned expert in continuous improvement. He's worked with W. Edwards Deming and wrote the classic book Understanding Variation. 

Wheeler once wrote and said, "Statistical Process Control is, at its heart, about getting the most from your processes. It is about the continual improvement of processes and outcomes. And it is, first and foremost, a way of thinking... with some tools attached." 

I’d like to thank him for providing the perfect quote for a blog about process control charts because measurement, control, and improvement are exactly what they are designed to enable.

Six Sigma is a business methodology focused on improving the quality of goods or services an organization produces by reducing variance in the production process. Six Sigma leaders know that when a production process lacks the stability to create high-quality output consistently, it will continue producing defective products until someone intervenes and improves the process. Reducing variation requires constant monitoring and measurement as systems tend to erode if not kept in check. Over the years, Six Sigma practitioners have developed a set of tools and methods that address control, problem-solving, and improvement to eliminate defects and waste. Here are a few of the most essential.

As you might guess from the name, a Lean Six Sigma methodology combines Lean manufacturing principles and those of Six Sigma. This approach to production management is popular in the automotive manufacturing industry. Although there are a few areas of caution, the methodology has helped Ford, Caterpillar, General Motors, Goodyear, and many more achieve their quality and value goals.

Oil & Gas companies need to be ever more flexible and agile to succeed as the industry continues to face price volatility, technical innovation, and an uncertain regulatory environment. Given these unstable conditions, it’s not surprising that some Oil & Gas companies are reluctant to adopt a standardized continuous improvement method. However, when applied thoughtfully, with an eye on the long-term, the principles of continuous improvement are relevant and can drive results even in the most dynamic environments. That’s why the Lean Six Sigma model is gaining traction in oil & gas.

The world’s most successful organizations are relentless in their quest for flawless processes and perfect execution. The ability to reliably produce quality outcomes with minimal waste is elusive but achievable with the right leadership and attention. That’s why many organizations turn to proven process improvement methodologies and techniques.

Six Sigma is a business management methodology that leverages a scientific approach to quality measurement with the aim of reducing variation and defects. The method was pioneered by Motorola and Allied Signal and then made famous by GE who boasted $10 billion in savings during the first years of implementation.

Lean is another methodology, philosophy, tool set, and management system that also uses a scientific problem solving approach, and more. "Lean" is a generic term that was given to the Toyota Production System, or TPS. The two pillars of TPS are usually described as "just in time flow" and "quality at the source."

Lean and Six Sigma are often used together by organizations in multiple industries, bringing methods and mindsets from each approach.

Many frameworks exist for implementing the methodologies. Many of those tools can be useful to organizations whether or not they fully embrace the Lean or Six Sigma approaches. Here are a few that our customers have found most valuable.

DMAIC is said to be the Six Sigma methodology’s roadmap to improvement. It is one of the core tools of the approach, but organizations also use it as a standalone improvement technique. We have clients in almost every industry from healthcare to construction who have achieved quantifiable impact against core business metrics by using this technique. Here are some of the questions we get asked about it most often.

Statistical control charts are a useful tool for managing and improving all sorts of processes. They’ve been used in manufacturing for decades and are increasingly popular in other industries from healthcare to higher education. Control charts give leaders a clear and consistent way of evaluating and talking about process behavior and performance. They help managers make good decisions about which processes are stable and which require attention.

While at first glance, they may look very simple, just a line graph with data points plotted over time, there are some important concepts that you should understand if you are new to the approach.

This post covers the basic, yet critical principles of control charts.

DMAIC (Deh-May-Ick) is one of the most important tools in the continuous improvement toolbox. It is most closely associated with the Six Sigma methodology, but it is also used by those who practice Lean or don’t subscribe to a methodology at all. The reason that DMAIC is so popular is that it is a problem-solving framework that takes teams from discovering root causes to long-term, stable standard work. It is a repeatable process that employees can learn to apply to any number of process problems.  

DMAIC stands for Define, Measure, Analyze, Improve, and Control.  Motorola is credited with bringing it to prominence, although it was essentially an evolution of the improvement methodology used by Toyota.

A deeper dive reveals why it works so well.