- Leading improvement teams: Holding team members/stakeholders to account for delivering agreed actions within an improvement project and building/maintaining appropriate stakeholder relationships inside and outside the organisation to deliver improvement project objectives
- Strategic Deployment of Continuous Improvement: Contribute to deployment of improvement strategy, participating as an active member of the improvement community
- Communication: Prepare and present concise proposals and plans. Capture and share progress through effective formats and channels. Use and handle questions effectively. Build rapport with others.
- Capability Development: Train, facilitate and critique the application of tools used by improvement practitioners including tool-selection, links between tools, how they are used within a structured method, analsysis of results and presentation of recommendations
- Project planning: Plan and manage finances, multi-stakeholder delivery and benefits realisation
- Change planning: Design reinforcement, engagement and communication strategies
- Principles and Methods for Improvement: Guide others on the selection of appropriate methods (eg. Practical Problem Solving, Define-Measure-Analyse-Improve-Control, 8-Disciplines, Identify-Define-Optimise-Verify) to deliver improvements. Conduct gateway assessments to ensure suitability of projects to progress
- Project selection & scope: Guides others on the selection and scoping of improvement projects and the intial response to product/process performance issues. Identify, scope and prioritise improvement opportunities that map to high-level organisation objectives and key value-streams
- Process mapping & analysis: Guide others on the selection of appropriate process mapping and analysis tools. Critique improved state
- Lean tools: Identify and analyse value-streams using appropriate methods and tools to optimise flow to customer. Develop a plan for Lean deployment within the organisation including effective and relevant performance metrics.
- Measurement: Guide others on the planning, analysis and interpretation of data collection & measurement studies including the design of tests to recreate failures & steps to diagnose/reduce short & long-term measurement variation
- Statistics & measures: Confirm data and fit for a range distribution models. Establish predictions. Calculate confidence intervals
- Data analysis-statistical methods: Model random behaviour and make inferences with levels of confidence. Calculate/recommend sample size. Test hypotheses for all data types. Assess input/output correlation. Generate, analyse and interpret simple and multiple predictive relationship models
- Process capability & performance: Identify data stability/distribution issues and apply appropriate strategies to enable robust Capability Analysis. Analyse life data to establish rates and patterns
- Root cause analysis: Make appropriate use of data to assess contribution of critical inputs/root cause(s) to product/process performance using appropriate graphical and statistical tools to draw and coomunicate conclusions
- Experimentation & optimisation: Guide others on the planning, analysis and interpretation of experiments. Plan,conduct, analyse and optimise both full & fractional experiments
- Data analysis – Statistical Process Control: Monitor and asses ongoing process variation and changes through chart-selection, control-limit setting, sample sizing/frequency and control-rules
- Benchmarking: Guide others on benchmarking to support all stages of improvement projects including future-state design
- Failure mode avoidance: Decompose complex systems in order to define main functions. Anaylse system interactions. Cascade knowledge through fault tree analysis. Create and assess design rules, standards & verification methods. Complete robustness studies to select appropriate control strategies and detection methods
- Sustainability & control: Guide others on control and sustainability planning including methods and tools to maintain benefits, extraction of learning, replication, sharing and consolidation of new knowledge into organisational learning
- Leading improvement teams: Personality types, team development stages, motivational techniques, situational leadership, learning styles, mentoring models
- Project planning: Multi-element business case, financial plan, benefits realisation plan, risk management plan, project plan
- Project reviews & coaching: Coaching models, Maslow’s hierarchy of needs
- Change planning: Change management methods, impact/readiness, influencing strategies
- Commercial environment: Business and economic risks including changes in legislation, government regulation or trading condidtions that can impact all aspects of improvement from Project Selection through to selection/implementation of improvements
- Principles & methods for Improvement: How to apply Improvement Methods (eg. Practical Problem Solving, Define-Measure-Analyse-Improve-Control, 8-Disciplines, Identify-Define-Optimise-Verify) across all functions, policy deployment principles, Lean culture
- Voice of the customer: Interviewing and focus groups, Quality Function Deployment principles and how to build a House of Quality
- Process mapping & analysis: Activity network diagrams, design structure matrix, process modelling, key function diagrams and analysis
- Data acquisition planning: Stratification, rational sub-groups, power and sample size
- Statistics & measures: Probability distributions and how to test for fit of probability distributions to data. Confidence intervals, central limit theorem. How to test data for stability and normaility and strategies for dealing with non-stable or non-normal data
- Lean concepts and tools: Principles of Lean Thinking and Lean tools including origins and cultural aspects critical to successful application within an organisation.
- Measurement system analysis: Repeatability & Reproducibility analysis. Long term measurement error
- Process capability: Data transformation, life data analysis and prediction
- Root cause analysis: Matrix plots, multi-vari charts, hypothesis testing principles and methods, correlation and regression principles and methods
- Experimentation: Principles of full and fractitional designed experiments including replicates, repeats, randomisation, blocking and centre points, resolution and confounding. Planning and analysis using residuals, main effects & interaction plots, hierarchy of terms, Response Surface Method, Split plots, Analysis of variance (ANOVA). Approaches for model optimisation
- Identification & prioritisation: Creativity tools e.g. theory of inventive problem solving (TRIZ), Pugh matrix
- Failure mode avoidance: System state flow, boundary diagram, interface analysis tables, fault tree analysis, robustness checklist, tolerance design and analysis. Principles and links between Failure Modes and Effects analysis for concepts, designs, processes.
- Sustainability & control: Control and reaction plans. Prevention controls
- Drive for results: Co-ordinates and delivers sustained improvement across the business by engaging with, and inspiring stakeholders; adopting a can-do attitude
- Team-working: Leads cross functional project teams proactively, regularly supports others and replicates learning
- Professionalism: Exemplifies high standard of professional integrity, ethics and trust within the organisation, whilst maintaining flexibility to the needs of the business
- Process Thinking: Drives process-thinking and customer-focused, data-driven decision making
- Continuous development: Identifies & models opportunities for development of self & others
- Safe working: Adopts a proactive approach to safety, encouraging others and suggesting compliance improvements
Individual employers will set their own entry requirements; typically Improvement qualification level 4, or equivalent.
Typically, 14-18 months.
Apprentices without level 2 English and maths will need to achieve this level prior to taking the end-point assessment. For those with an education, health and care plan or a legacy statement, the apprenticeships English and maths minimum requirement is Entry Level 3. British Sign Language qualification is an alternative to English qualifications for those whom this is their primary language.
Originally published on Gov.uk, this information has been re-used under the terms of the Open Government Licence.";