Friday, April 8, 2011

Lean Six Sigma: Key Concepts and Benefits

Lean Six Sigma implementation is driven by top management, using data analysis and cross-functional teams to:

o Improve processes
o Lower defects
o Reduce process variability
o Reduce costs
o Increase customer satisfaction
o Eliminate waste.

The basic theme in Lean Six Sigma is that if you can measure how many "defects" you have in a process, you can systematically figure out how to eliminate them and get as close to "zero defects" as possible. Specifically it means a failure rate of 3.4 parts per million or 99.9997% accuracy.

Key Concepts of Six Sigma: 

At its core, Six Sigma revolves around a few key concepts.

Critical to Quality       : Attributes most important to the customer.
Defect                          : Failing to deliver what the customer wants.
Process Capability     : What your process can deliver.
Critical to Process      : Parameters that have major impact on achievement of the 
                                          CTQs.
Variation                      : What the customer sees and feels. Six Sigma focuses first 
                                          on reducing process variation
Stable Operations      : Ensuring consistent, predictable processes to improve what 
                                          the customer sees and feels.
Design for Six Sigma : Designing to meet customer needs and process capability.

Myths about Lean Six Sigma:

There are several myths and misunderstandings about Lean Six Sigma, like:
• It is only concerned with reducing defects.
• It is only for manufacturing organizations.
• It uses difficult-to-understand statistics.
• It ends with training and certification.

The Benefits of Six Sigma:

Six major benefits of Lean Six Sigma that attract companies.

• Generates sustained success.
• Sets a performance goal for everyone.
• Enhances value to customers.
• Accelerates the rate of improvement.
• Promotes learning and cross-pollination.
• Executes strategic change.


13 comments:

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  3. Great post! I see this problem all the time as well. Leaders expect answer to pop out of the tools and processes without them having to provide any insight.

    Your example of multivariate regression is a good one. You can super crunch giant data sets to find relationships, but someone with business knowledge needs to figure out if those relationships make sense and if they are actionable.

    I often tell leaders that the data itself is not the story. The story is what is happening in the business, the data simply supports it.

    Thanks for the post!

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