Learning Strategy and Innovation Training Course

Participants can diagnose whether learning is an appropriate response to a performance issue.

• Performance consulting questions separating knowledge, skill, process and incentive causes
• Root-cause analysis using the Five Whys and fishbone diagrams
• Task analysis identifying critical decisions, errors and performance standards
• Stakeholder interviews structured around observed performance and desired outcomes
• Gap statements written with role, task, standard and business consequence
• Non-learning interventions identified before commissioning development solutions

Participants can create a role-based view of skills demand and development priorities.

• Skills taxonomy structure covering domains, skills, behaviours and proficiency levels
• Role profiles translated into observable tasks and critical skill requirements
• Proficiency scales calibrated using autonomy, complexity and decision impact
• Skills matrices comparing current capability against target role requirements
• Build, buy, borrow and automate responses to priority skill gaps
• Skills data governance covering ownership, validation and refresh cycles

Participants can segment learner populations and use evidence to define experience requirements.

• Learner segments defined by role, context, access and performance need
• Persona evidence gathered through interviews, observation and learning data
• Journey mapping captures moments of need, friction and support
• Accessibility requirements identified using WCAG 2.2 principles and user testing
• Manager expectations incorporated into learner experience and transfer design
• Channel preferences tested without confusing preference with learning effectiveness

Participants can design a coherent learning architecture for priority capability areas.

• Learning architecture connects academies, pathways, resources and performance support
• Portfolio mapping identifies duplicate offers, missing pathways and obsolete content
• Capability academies organised around strategic roles and shared professional standards
• Learning pathways sequence foundation, application, practice and accreditation stages
• Content governance assigns owners, review dates and retirement decisions
• Portfolio principles balance local adaptation with enterprise consistency

Participants can select modalities that fit task risk, audience conditions and transfer needs.

• 70:20:10 model applied to formal learning, social learning and work experience
• Modality decisions based on task criticality, practice requirements and audience access
• Blended journeys combine workshops, digital resources, coaching and field assignments
• Performance support designed as checklists, job aids and searchable guidance
• Cohort learning structures peer accountability, reflection and manager involvement
• Virtual and classroom formats compared through participation, practice and cost

Participants can specify learning experiences that build performance on priority tasks.

• Backward design starts with performance evidence and assessment criteria
• Scenario-based learning mirrors decisions, consequences and workplace constraints
• Deliberate practice sequences repetition, feedback, difficulty and reflection
• Cognitive load managed through chunking, worked examples and progressive disclosure
• Retrieval practice and spaced repetition strengthen long-term skill retention
• Design briefs define audience, task, modality, measures and production constraints

Participants can design social learning structures that support knowledge exchange and practice.

• Communities of practice organised around shared problems and professional identity
• Community charters define purpose, membership, facilitation and contribution norms
• Peer learning formats include case clinics, demonstrations and after-action reviews
• Knowledge capture converts expert practice into reusable guides and decision aids
• Subject-matter experts supported with clear contribution roles and editorial standards
• Community metrics track participation quality, reuse and problem resolution

Participants can assess technology options and define a target learning ecosystem.

• Learning ecosystem maps LMS, LXP, content libraries and collaboration platforms
• Use cases distinguish administration, discovery, practice, coaching and analytics
• Vendor evaluation criteria cover interoperability, accessibility, security and service support
• xAPI data flows connect learning activity with experience-record data
• Integration dependencies mapped across HRIS, identity management and skills systems
• Technology roadmaps sequence quick improvements, migrations and platform rationalisation

Participants can identify suitable artificial intelligence uses and establish proportionate controls.

• Generative AI use cases include content drafting, coaching and practice simulations
• Human review controls address accuracy, bias, confidentiality and intellectual property
• Prompt patterns specify role, task, source constraints and output criteria
• AI-enabled assessment risks examined through validity, transparency and learner disclosure
• Acceptable-use guidance distinguishes approved tools, restricted data and prohibited actions
• Pilot evaluation measures quality, time saved, adoption and unintended effects

Participants can design a measurement approach that links learning activity to performance evidence.

• Kirkpatrick model aligns reaction, learning, behaviour and results measures
• Logic models connect inputs, activities, outputs, outcomes and assumptions
• Measurement questions defined before selecting data sources and dashboard metrics
• Leading indicators track enrolment, practice, manager support and application intent
• Outcome indicators measure quality, productivity, risk reduction and service performance
• Comparison groups and baseline data strengthen claims about contribution

Participants can produce decision-focused learning reports using appropriate data and visualisation.

• Data dictionaries define metric formulas, sources, owners and refresh frequency
• Dashboard design prioritises decisions, exceptions, trends and action owners
• Cohort analysis compares participation, progression and application across learner groups
• Data quality checks identify missing records, duplicates and inconsistent definitions
• Privacy-by-design controls limit access, retention and unnecessary personal data
• Executive narratives explain evidence, limitations, decisions and requested actions

Participants can define the governance, roles and supplier arrangements required to deliver the strategy.

• Target operating model allocates central, local, manager and learner responsibilities
• RACI matrices clarify decision rights for design, funding and quality assurance
• Governance forums review priorities, performance, risks and investment decisions
• Supplier segmentation differentiates strategic partners, specialists and commodity providers
• Statement-of-work specifications define outcomes, acceptance criteria and intellectual property
• Quality assurance standards cover facilitation, content review and learner support

Participants can construct an investment case for priority learning initiatives.

• Cost models include design, delivery, platforms, learner time and maintenance
• Benefit hypotheses quantify avoided errors, productivity gains and reduced external spend
• Prioritisation matrices score strategic value, urgency, feasibility and risk
• Build-versus-buy decisions compare internal capacity, speed, control and total cost
• Business cases state assumptions, sensitivities, dependencies and decision requests
• Resource plans identify programme roles, capacity constraints and critical skills

Participants can plan implementation activities that secure adoption from leaders, managers and learners.

• ADKAR analysis identifies awareness, desire, knowledge, ability and reinforcement needs
• Stakeholder maps assess influence, readiness, concerns and engagement approaches
• Pilot designs establish target groups, success criteria and scale decisions
• Manager enablement provides briefing packs, coaching prompts and accountability routines
• Implementation roadmaps sequence governance, communications, capability and technology milestones
• Risk registers assign mitigations for adoption, data, supplier and capacity risks

Participants can build, review and present a complete learning strategy for a defined organisational capability challenge.

• Strategy narrative states business case, capability priorities and target learner segments
• Skills analysis identifies priority roles, gaps and development pathways
• Target learning architecture specifies modalities, experiences, platforms and support
• Measurement framework links activities to behavioural and business outcome indicators
• Operating model assigns governance, resources, suppliers and decision rights
• Implementation roadmap sequences pilots, scale-up, risks and stakeholder communications
• Peer review tests strategic coherence, feasibility, evidence and presentation clarity