Reduce avoidable variation in how statistical variance analysis is carried out across teams.
Building Statistical Variance Analysis Models for Industrial Processes
Develop the judgement and the documentation needed to run statistical variance analysis properly.
📍 Tunis🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
Improvement in statistical variance analysis that is not measured tends to be reversed quietly. Inspection catches problems in this aspect of quality and productivity management; it does not prevent them. It concentrates on the parts of the practice within quality and productivity management that determine outcomes and treats the rest proportionately. They acquire practical criteria for judging when statistical variance analysis is working and when it is only appearing to. The programme uses small-group work so that each participant's treatment of this part of quality and productivity management is examined, not just described. Mature organisations treat this strand of quality and productivity management as a standing capability rather than a project that finishes. The difficulty is not agreeing that statistical variance analysis matters — it is deciding what to stop doing to make room for it. It is appropriate for those preparing to take on wider responsibility for the quality and productivity management discipline. Participants finish with a short, specific brief on this aspect of quality and productivity management ready to put in front of a decision maker.
Expected Learning Outcomes
Standardise work in statistical variance analysis without removing necessary judgement.
Reduce waste and non-value-adding steps in statistical variance analysis.
Calculate the cost of poor quality attributable to statistical variance analysis.
Align statistical variance analysis with the wider objectives of the operating process rather than optimising it in isolation.
Benchmark statistical variance analysis against comparable operations honestly.
Handle the trade-offs in statistical variance analysis between speed, cost and assurance explicitly rather than implicitly.
Who Should Attend
Quality managers and coordinators responsible for statistical variance analysis.
Department managers accountable for productivity of statistical variance analysis.
Certification and accreditation coordinators preparing evidence on statistical variance analysis.
Experienced practitioners formalising an approach to statistical variance analysis that has grown up informally.
Continuous improvement specialists working on statistical variance analysis.
Training and development staff building internal capability in statistical variance analysis.
Course Modules
Statistical variance analysis: standard work and sustaining gains
2 sessions · 8 pointsSession 1Benchmarking statistical variance analysis without flattering yourself
- Measure current variation in statistical variance analysis before attempting improvement.
- Establish what evidence demonstrates statistical variance analysis is under control.
- Train the team handling statistical variance analysis in the problem-solving method being used.
- Set out the decisions in statistical variance analysis that require sign-off and by whom.
Session 2Control plans for statistical variance analysis that catch problems early
- Define quality for statistical variance analysis in terms the customer would recognise.
- Remove steps in statistical variance analysis that add effort without adding assurance.
- Establish the boundary of statistical variance analysis and record what sits outside it.
- Map the process behind statistical variance analysis by walking it, not by describing it.
Statistical variance analysis: mapping the process as actually performed
2 sessions · 8 pointsSession 1Who answers for statistical variance analysis, and to whom
- Record what was tried on statistical variance analysis and did not work, and why.
- Prepare the summary of statistical variance analysis that senior management will read.
- Set sampling for statistical variance analysis on statistical grounds, not on habit.
- Set the review cadence that sustains gains in statistical variance analysis.
Session 2Mapping statistical variance analysis as it is done, not as it is written
- Choose productivity measures for statistical variance analysis that do not reward shortcuts.
- Identify non-value-adding steps in statistical variance analysis and remove them.
- Define acceptance criteria for statistical variance analysis in advance.
- Benchmark statistical variance analysis against a comparable operation and record the gap.
Statistical variance analysis: control plans, sampling and acceptance
2 sessions · 8 pointsSession 1What to measure in statistical variance analysis and what to ignore
- Test the procedure for statistical variance analysis against a realistic scenario.
- Write standard work for statistical variance analysis with the people who perform it.
- Define supplier quality requirements affecting inputs to statistical variance analysis.
- Agree the smallest change to statistical variance analysis that would be visibly useful.
Session 2Costing poor quality in statistical variance analysis
- Apply structured root cause analysis to the top defect in statistical variance analysis.
- Build a control plan for statistical variance analysis identifying what is checked, when and by whom.
- Confirm that reporting on statistical variance analysis reaches the people who can act.
- Verify that improvements to statistical variance analysis held six months later.
Statistical variance analysis: benchmarking and continual improvement
2 sessions · 8 pointsSession 1Auditing statistical variance analysis to improve it, not to pass
- Prepare the response for the most likely failure in statistical variance analysis.
- Build the internal briefing that explains statistical variance analysis to those affected.
- Write down the assumptions underpinning the approach to statistical variance analysis.
- Close out actions on statistical variance analysis rather than leaving them open indefinitely.
Session 2The decisions in statistical variance analysis that cannot be delegated
- Benchmark the organisation's statistical variance analysis against comparable operations.
- Assign responsibility for keeping documentation of statistical variance analysis current.
- Set out how exceptions to statistical variance analysis are requested and approved.
- Calculate the cost of poor quality attributable to statistical variance analysis.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
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