Lean Six Sigma Principles - Green Belt

Lean Six Sigma is a proven business process improvement methodology that builds on the best practices and experiences of earlier approaches. It combines best practices around customer focus, empowered teams, process definition, and data analysis.

Lean and Six Sigma are easily blended. They have many similarities in methodology – process focused, team based, and project management. The differences, analyzing quality data versus flow data, are complementary and together provide a balanced view of the process.

The IASSC Green Belt certification is appropriate for a Lean Six Sigma project leader. The Green Belt Body of Knowledge is the list of topics and tools that a Green Belt practitioner should know.

The Lean Six Sigma methodology relies on a five-phased project management methodology. The phases Define, Measure, Analyze, Improve, and Control provide structure to the project.

The Lean Six Sigma methodology encourages the use of a project charter and the creation of a business case to set boundaries on the project and to manage stakeholder expectations.

The Lean Six Sigma methodology involves stakeholders through a set of project reviews. Each type of review has a goal and purpose.

Waste can take many forms including high costs, delayed timing, rework, redundant work and idle processes. One of the primary goals of a Lean Six Sigma project is to identify areas of process waste and eliminating or reducing those sources of waste.

One of the decisions that must be made during the Define Phase is the selection of the project and its boundaries. Lean Six Sigma projects are often part of a portfolio of projects that may be selected and approved as a bundle.

The Pareto principle is a widely accepted technique for prioritizing effort and activity. The Pareto principle will typically be applied in every phase of a Lean Six Sigma project, including this initial Define phase where it is used to prioritize the areas of focus for the project.

Lean Six Sigma methodology is grounded on the voice of the customer. The Define phase collects and assesses information concerning the customer perspective and uses it to focus the project activities.

In order to improve process performance, the Lean Six Sigma project team must understand the current state of the process. Process Mapping is the technique for describing the process and providing a framework for collecting process data.

Lean Six Sigma projects apply the Lean principle of value-added effort in the definition of the project and when identifying the opportunity for improvement.

The problem statement clarifies the goals and activities of the Lean Six Sigma project by specifying the issue to be resolved. It's an excellent communication tool for the team to use with stakeholders.

There are two types of data: variable and attribute. Both types are useful in measuring process performance by analyzing process problems, but they need to be treated differently.

The X/Y matrix is a tool that maps the Voice of Customer needs and concerns onto the process steps and inputs. This tool can take on several different formats, but any of them will provide the Lean Six Sigma team with insight as to the contributing factors of customer value.

The Failure Mode Effects Analysis (FMEA) tool highlights areas of high product design or process execution risk. This tool provides insight into possible causes for observed failures.

The Value Stream Map Data Box is the technique used to capture and analyze data at each step of the Value Stream Map.

The As-is metrics are the measured current state of the process or problem. It is not the best-case, the worst-case, or the “as-designed” case; it is the current average performance of the process or problem.

The purpose of the Measure phase of a Lean Six Sigma project is to collect complete, accurate and meaningful data. There is a simple data collection approach that can be used by the team to ensure this is accomplished.

The normal distribution charts the type of variability in a process parameter that is being measured when the only cause for variation is natural random physical effects. It's the desired distribution when improving a process since it delivers a predictable level of process performance.

When the process or problem data set has multiple characteristics, there are a set of graphing techniques that can show these effects. Although more complex than the basic techniques, they are easy to use and create a picture of the data set.

Z scores are a method of normalizing data from different data sets for comparison or prediction. Z scores normalize the data using the process standard deviation. The Z transformation table will convert Z scores into percentages.

The Central Limit Theorem is a principle that is used to transform non-normal raw data into a data set that is normal.

Problem analysis is the methodical approach to analyzing a problem and finding the root cause or causes. It normally includes creating and testing an hypothesis or an experiment to determine the cause.

Statistical tests are often used to aid the problem analysis. The statistical analysis of a small sample of data can point to root causes of problems in the full data set.

Graphical analysis techniques are particularly good for illustrating significance, similarities or differences, and correlation between parameters within a data set.

The Lean process analysis will reveal flow process flow problems. Lean techniques can be used to analyze flow at both a total process (macro) level or at a process step (micro) level.

The process analysis of the value stream map will reveal quality issues that are occurring within process steps. These are identified by analyzing step data and process flow data.

Analysis of the Lean value stream map and the related data can reveal wasted resources; both people and product or service items that are being processed.

Problem solving often requires an interim solution while a permanent solution is being developed and validated. When multiple possible solutions are available, the team should recommend a solution approach.

Special cause problems should be resolved first in order to achieve process stability. Then common cause problems are addressed to reduce process variation.

Design of Experiments (DOE) is an experimental technique for identifying the primary factors within a system that determine system performance. DOE is particularly useful in complex systems where there are interactions between factors and relationships are not obvious.

Lean process improvements are designed using a “should be” value stream map that shows the new flow. The data box on this map estimates the impact of the elimination and redesign of process steps and the removal of system constraints.

The benefits of Lean improvements rely on changing the process schedule management approach in addition to process redesign. Pull scheduling and visual management are used to maintain smooth flow in the process.

Many problems can be solved using mistake proofing approaches that are embodied in the five Poka Yoke principles that both detect and prevent errors from occurring.

The Five S principles can be used to organize the work place and support and sustain the problem solutions by reducing the likelihood of confusion and rapidly exposing process degradation.

A key element of the control plan is the response plan. It tells the process operators what to do when the process begins to deviate from the parameters laid out in the control plan.

Lean process control focuses on maintaining the process flow of the Should-Be process. It relies on principles of visual control, empowerment, and continuous improvement.

Statistical process control uses real-time process data to determine whether a process is maintaining the improvements that were implemented. Control charts will indicate special cause and common cause variation, empowering process operators to maintain process quality.

Implementing the technical changes of the solution are often easy, the difficulty is usually the emotional and cultural resistance to change. The implementation should be planned and managed as a project. The project should include the actions taken to change the business systems and structures in addition to the specific problem solution.