Classroom based Six-Sigma Green Belt Programme

Our Six Sigma Green Belt programme is designed for those wishing to lead
successful Six Sigma project teams within their current role at all levels within the
organisation. It explores the DMAIC methodology and a wide range of Six Sigma
problem-solving tools including descriptive and inferential statistical methods in order
to achieve sustainable improvements. The curriculum also includes a selection of
relevant lean tools as well as key factors for successful change management.

Please not that this is Six Sigma and not Lean Six Sigma which we offer via a different programme

Why study this course?

Our Six Sigma Green Belt is a practical, hands-on course
focused on eliminating waste and increasing effi ciency across
the whole operation and along the supply chain.
Qualifi ed Six Sigma Green Belt practitioners have the skills
and expertise to apply sophisticated improvement tools,
change behaviours and transform business performance.
Practitioners typically generate cost savings of £25,000 –
£250,000 through the Six Sigma projects they implement.
The course is delivered by our team of experienced Master Black Belt
practitioners who also offer mentoring, support and advice

What will I learn?

During this course you can expect to learn a number of key
competencies, including:
• How to increase efficiency to drive up profi tability or offset
cost increases in other areas e.g. raw materials
• How to achieve a more efficient operation, creating
competitive advantage
• The culture and practices to sustain improvement activity
and long term financial benefits
• Recognised Green Belt certification adds credibility to
your team and business within the industry
• Develop strong leadership, problem solving and change
management skills


Part 1 (3 days)
• Six Sigma overview
• How Six Sigma links with lean
• Introduction to the Six Sigma DMAIC process
• Basic statistics and principles of variation
• Introduction to Minitab
• Project charters
• Cause and effect analysis
• Process mapping
• Data collection
Part 2 (3 days)
• Project progress reviews
• Gauge repeatability and reproducibility
• Process capability analysis
• Analysis of Variance
• Graphical analysis of input/ output variables
• Stratification techniques
• Confidence Intervals
• Using the data to change behaviours
Part 3 (4 days)
• Project progress reviews
• Introduction to hypothesis testing (Anova,
Regression, Chi Squared, T-Tests)
• Generating and selecting solutions
• Optimisation of critical x’s
• Mistake proofing
• Process control
• How to make Six Sigma sustainable