Accelerate Programme: L4 Improvement Practitioner

4 Level 4 Improvement Practitioner

Who is this course for?

This course is ideal for individuals who are leading an improvement project team whithin a non-manufacturing setting.

What topics are covered?

Knowledge Statements:

Compliance: Legislative and customer compliance requirements including health and safety.
Team formation & leadership: Decision-making techniques e.g. consensus, authority rule, majority rule.
Project management: Business case, risk analysis and management, toll-gate reviews, work breakdown structure, lessons learned, pilot studies, project review, process management and measures, benefits tracking.
Presentation & reporting: Reporting templates, message mapping, case for change.
Change management: Stakeholder identification, analysis and management (RACI). Change curve, resistance characteristics, change sponsorship, compelling point of view.
Principles & methods: Business value of Lean and Six Sigma improvement methods - 8D, practical problem solving, Define Measure Analyse Improve Control, Design for Six Sigma.
Project selection & scope: Y=f(x) equation (outputs are the result of inputs), business scorecard cascade.
Problem definition: Cost of Poor Quality, problem analysis models such as Is/Is Not.
Process mapping & analysis: Swim lane, value stream map, performance metrics – continuous, Parameter diagram, Takt time, Overall Equipment Effectiveness, theory of constraints principles, Kanban.
Data analysis – basic tools: Spreadsheets and pivot table analysis, statistical analysis software.
Measurement systems: Repeatability and Reproducibility principles.
Basic statistics & measures: Control charts - attribute data, principles of normality.
Data analysis - statistical methods: Measures of central tendency and spread.
Process capability & performance: Capability analysis – continuous data for normal distribution.
Root cause analysis: Key principles including symptoms, failure-mode, potential/verified cause, critical inputs, escape point. Graphical representation of data with dot, scatter and box plots.
Experimentation: Active versus passive analytics, design of experiments, experiment plan.
Identification & prioritisation: Selection and prioritisation matrix, Failure Mode and Effects Analysis.

Skill Statements:

Compliance: Work in accordance with organisational controls and statutory regulations.
Communication: Speak and write clearly. Influence others, question effectively. Plan and deliver meetings presenting insight to engage audiences.
Coaching: Observe, listen, use questioning, provide feedback and spot learning opportunities.
Project management: Define, sequence, plan and schedule activities with phases and milestones. Estimate effort and duration. Create and update project charter. Review progress.
Change management: Sponsorship contract, surface and manage resistance, build compelling narratives for change, assess change impact.
Principals and Methods: Select and apply a structured method and appropriate improvement tools engaging with subject matter experts to deliver business benefits.
Project selection and Scoping: Support the identification of improvement opportunity and the scoping of these projects.
Problem definition: Support development of problem/opportunity statements.
Voice of the customer: Support application of techniques to identify and prioritise customers, their requirements and ensure balance against the stated and unstated needs of the business (Voice of the Business).
Process mapping & analysis: Process map to measure and analyse flow and value. Identify interfaces, functional responsibilities and ownership. Use insight to identify potential opportunities and map future state.
Lean tools: Seek in-process waste through understanding of value within the value stream.
Measurements systems: Plan, carry out and assess results of a measurement system study.
Data acquisition for analysis: Develop a sampling strategy.
Basic statistics & measures: Use graphical analysis to understand distribution and stability.
Data analysis-statistical methods: Identify data-types and select analysis methods and tools. Assess time series data stability and analyse making relevant insight.
Process capability & performance: Select methods and metrics for analysis.
Root cause analysis: Select and apply the appropriate graphical tool dependent on the data type to identify patterns, trends and signals to establish hypothesis.
Experimentation & optimisation: Plan designed experiment with clear objectives, and appropriate levels of Measurement Systems Analysis, analyse experiment data and optimise.
Identification & prioritisation: Identify and prioritise factors, ideas and solutions.
Data analysis – SPC: Select and apply appropriate tools for ongoing monitoring and control. Analyse and interpret control charts.
Benchmarking: Conduct structured benchmarking to support target setting.
Sustainability & control: Identify failure modes and embed learning from improvements.

Behaviour Statements:

Drive for results: Continuous drive for change and encourages others to deliver results across functional areas capturing and standardising best practice.
Team-working: Awareness of own and others’ working styles. Creates high performing team.
Professionalism: Promotes a moral, legal and socially appropriate working manner, aligns behaviours to the organisations values. Maintains flexibility to needs of project.
Continuous development: Proactively seeks and acts on feedback. Reflects on performance and has a desire for development. Adapts quickly to working with new situations/stakeholders/challenges.
Safe working: Ensures safety of self and others, speaks out to challenge safety issues.