The fundamental objective of the Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction. Six Sigma includes data driven tools and techniques to help practitioners to objectively understand and quantify how their processes perform. Six Sigma is about letting the data tell the true story and leading the practitioner to the “root cause” to solve complex problems that have multiple “factors” that have varying degrees of impact on performance.
The objective of the Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction.
Six Sigma Methodology (DMAIC, DMADV, DFSS)
Six Sigma is a rigorous problem solving methodology that uses well-defined progression phases of Define, Measure, Analyze, Improve and Control, popularly known by the acronym, DMAIC. Define is problem definition, making sure you are solving the correct problem. Measure is gathering data that help explain the problem. Analyze is reviewing the data to find patterns that lead to the root cause. Improve is making changes in the process based on the analysis. Control is putting in place to ensure improvements are sustained. For the design and development of new systems or processes, there is a similarly defined progression of phases known as Define, Measure, Analyze, Design and Verify (DMADV) or also referred to as Design For Six Sigma (DFSS).
Six Sigma Principles (reduction in variation)
The Six Sigma methodology was originally implemented in the semi-conductor and electronics industry to reduce variation in manufacturing processes. While the tools have been applied well beyond manufacturing, the principles have held; that improvement in quality comes from the reduction in variation of your process.
Six Sigma Problem Solving Tools
Six Sigma uses a variety of statistical and graphical tools in the DMAIC process. These include visualization tools such as fishbone (cause & effect) diagrams, scatter plots, bar charts, pareto charts and more. In addition, rigorous statistical tools are used to make comparisons of data that go beyond intuition. These tools include hypothesis testing, experimental design and regression.
Lean and Six Sigma
Lean, a set of tools for identifying and eliminating non-value-added steps in a process, and Six Sigma, a set of tools for reducing variation in a process, are often used together. Lean is very good at evaluating the entire Value Stream, and Six Sigma is good at understanding the root cause of problems within the Value Stream. These combined methods are often called the Lean Six Sigma Methodology.
Six Sigma Manufacturing
Six Sigma was initially used to reduce variation and improve quality in manufacturing and often you will hear the term Six Sigma Manufacturing, 6 Sigma Manufacturing and Six Sigma Lean Manufacturing. Within the manufacturing process, each step is analyzed using statistical and graphical tools to understand its process capability and if it can meet customer expectations. The term Six Sigma stands for a process that can “fit” 6 standard deviations between the average value of the process and customers’ specification limits. This process would produce only 3 – 4 defects per million opportunity (DPMO).
However, Lean Six Sigma can be used in many industries including financial services (back office order processing), healthcare (health outcomes from procedures) and distribution (order fill rate, mis-ships). In fact, these industries, with very high transaction volume, can actually be a better fit for DMAIC process.