The steps in Six Sigma methodology are grounded in the following principles:
Business success is based to a large extent on the reduction of process variation and thus predictable and stable process results are achieved.
All business processes are quantifiable and can be subject to measurement, analysis, improvement and control.
Significant and sustained improvements in quality are dependent on the buy-in and support of the whole organisation - at all levels - and especially from the active sponsorship and support and from top management.
The Six Sigma methodology requires the support of an infrastructure of "Champions," "Master Black Belts," "Black Belts," "Green Belts", etc to lead and implement.
Maintaining a very clear focus on achieving measurable and quantifiable financial returns from all Six Sigma projects.
A universal commitment that decisions are made on the basis of verifiable data, rather than on "guestimates" and assumptions.
The steps in Six Sigma methodology fall into 3 distinct areas:
The purpose of process improvement is to eliminate the root causes of performance deficiencies in processes that already exist in the organisation. These performance deficiencies may be causing real problems for the organisation, or may be preventing it from working as efficiently and effectively as it could. To eliminate these deficiencies a five-step approach is used and this is known as DMAIC [define, measure, analyse, improve, and control].
Sometimes simply improving existing processes is not enough, and, therefore, new processes will need to be designed, or existing processes will need to be re-designed. As with process improvement, a five-step approach is used to design/re-design a process and this is known as DMADV [define, match, analyse, design & implement, and verify]
Because it requires a fundamental change in the way an organisation is structured and managed, process management is often the most challenging and time-consuming part of Six Sigma.
Process management comprises:
# Defining processes, key customer requirements, and process
# Measuring performance against customer requirements and
key performance indicators
# Analysing data to enhance measures and refine the process
# Controlling process performance by monitoring process inputs, process operation, and process outputs, and responding quickly to problems and process variations