Lean Six Sigma

Six Sigma is a disciplined approach to improvement and problem solving designed to achieve near perfection in product and service quality through variation, error and defect reduction. In Six Sigma, near perfection is defined as less than 3.2 errors per million opportunities.

Achieving this target requires reliable quantitative methods to identify and solve performance problems. Originally developed by Motorola, Six Sigma has evolved, finding applications in technology, financial services, manufacturing and other industries with high production or transaction volumes.

Six Sigma is most commonly associated with the DMAIC problem solving model, a variation of the PDSA model developed by Walter Shewart and Edwards Deming. The PDSA Cycle is in fact, at the core of the DMAIC model.

DMAIC is usually placed within an organization context through the addition of Recognize and Sustain.

The Recognize phase represents the efforts of the organization to recognize the problems that exist within the organization and assign priority to them so as to set an agenda for change. DMAIC is then applied to address the problem assigned through the Recognize phase. Once the problem has been solved, Sustain embeds the solution to other areas of the organization — in essence providing the explicit organizational learning arising from the problem solving efforts.

In between the Recognize and Sustain components of the model of course, is DMAIC itself. It defines a problem solving approach of:

Define: the performance problem to be solved. Generally the approach is to boil the improvement effort down to a single customer driven performance metric.

Measure: gather hard data relating to the problem. Focus is palced on potential causal factors driving performance.

Analyze: the data gathered through the measurement phase.The emphasis here is on analytic methods that attempt to confirm causal effects.

Improve: implementing evidenced-based solutions that have a hig probability of effectively addressing the performance problem.

Control: adjusting and finally standardizing the solution so that we don’t loose the gains made. Essentially hard wiring the solution into the way things are done.

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