Product Strategy and Innovation Training Course

Participants can define innovation domains that connect strategic priorities with addressable opportunities.

• Innovation ambition matrix: core, adjacent and transformational growth horizons
• Opportunity areas derived from strategic goals, market shifts and customer friction
• Three Horizons framework applied to present performance and future growth
• Problem spaces separated from solutions, channels and preselected technologies
• Strategic constraints identified: regulation, capacity, brand, data and operating model
• Innovation thesis written with target domain, rationale, boundaries and success measures

Participants can plan customer research that produces decision-ready evidence.

• Research questions linked directly to decisions, assumptions and uncertainty reduction
• Stakeholder mapping identifies buyers, users, influencers, gatekeepers and beneficiaries
• Interview guides use laddering, critical incidents and non-leading prompts
• Observation plans capture workarounds, context, constraints and unmet needs
• Evidence quality assessed through triangulation, sample relevance and researcher bias
• Insight repositories separate direct evidence, interpretation, assumptions and decisions

Participants can formulate customer problems as prioritised jobs, pains and desired outcomes.

• Jobs to Be Done identifies functional, emotional and social progress sought
• Job stories specify situation, motivation, expected progress and desired outcome
• Forces of Progress maps push, pull, habit and switching anxiety
• Outcome-driven innovation measures importance and satisfaction for desired job outcomes
• Problem statements define user, circumstance, unmet need and consequential impact
• Assumption mapping separates desirability, viability, feasibility and usability uncertainties

Participants can select target segments using evidence of need, value and accessibility.

• Segmentation bases compare needs, behaviours, value, context and firmographic variables
• Segment profiles document jobs, triggers, barriers, willingness and channel preferences
• TAM, SAM and SOM estimates distinguish market potential from reachable demand
• Attractiveness scoring weighs segment value, growth, access, competition and fit
• Beachhead segment selection focuses learning, proposition development and early adoption
• Personas used cautiously as evidence summaries rather than fictional customer substitutes

Participants can identify high-value intervention points across a customer journey.

• Customer journey maps show stages, actions, emotions, channels and pain points
• Moments of truth identified through consequence, frequency and customer sensitivity
• Service blueprints connect customer actions with frontstage and backstage processes
• Failure demand reveals avoidable contacts created by broken products or services
• Journey metrics link experience signals to conversion, retention and service cost
• Opportunity statements prioritise journey interventions with measurable customer outcomes

Participants can create value propositions that address a specific customer job and context.

• Value Proposition Canvas aligns customer jobs, pains, gains and offer elements
• Benefit ladders connect product attributes with functional and emotional value
• Value propositions distinguish category, target customer, promise and proof
• Gain creators and pain relievers tested against evidence rather than intuition
• Switching costs assessed across money, effort, risk, habit and status
• Message hierarchies organise primary promise, supporting claims and substantiation

Participants can assess competitive alternatives and define a defensible product position.

• Competitive alternatives include non-consumption, workarounds, incumbents and internal solutions
• Porter's Five Forces assesses structural pressure on product profitability
• Perceptual maps compare positions using customer-relevant decision criteria
• Differentiation sources tested for relevance, credibility, durability and operational feasibility
• Ecosystem maps identify partners, platforms, regulators, suppliers and complementors
• Positioning statements articulate category, target, difference, reason and competitive frame

Participants can describe how a product creates, delivers and captures value.

• Business Model Canvas links customer segments, channels, resources and revenue
• Revenue models compare subscription, transaction, licensing, usage and cross-subsidy approaches
• Unit economics calculate contribution margin, acquisition cost, retention and payback
• Pricing research explores willingness to pay, reference prices and value metrics
• Cost-to-serve analysis exposes operational implications of proposition and channel choices
• Commercial assumptions recorded with ranges, sources, owners and validation plans

Participants can design experiments that test critical product assumptions efficiently.

• Lean Startup cycle connects hypotheses, minimum tests, evidence and decisions
• Assumption tests match method to uncertainty, stakes, speed and available evidence
• Prototype fidelity selected for concept, workflow, usability or technical-risk learning
• Fake-door tests measure demand before building full product functionality
• A/B tests specify variants, success metric, sample requirements and stopping rules
• Experiment cards document hypothesis, method, threshold, result and next decision

Participants can translate validated learning into a coherent product concept and scope.

• Concept statements combine target user, job, proposition, proof and boundaries
• Minimum viable product defined by learning objective, not minimal feature count
• User story mapping orders activities, tasks, releases and learning priorities
• Service requirements include process, policy, support, data and partner dependencies
• Non-functional requirements cover security, accessibility, reliability, privacy and performance
• Product scope decisions distinguish essential capabilities from later enhancement candidates

Participants can rank product opportunities using transparent strategic and economic criteria.

• RICE scoring compares reach, impact, confidence and estimated effort
• Weighted scoring models reflect strategic fit, customer value, risk and return
• Cost of delay combines user value, time criticality and risk reduction
• Opportunity solution trees connect desired outcomes, opportunities, solutions and experiments
• Portfolio matrices balance core improvement, exploration, risk and investment horizons
• Kill criteria define evidence thresholds for stopping, pausing or redesigning initiatives

Participants can communicate a product direction that aligns stakeholders around choices and outcomes.

• Product vision states intended future customer and business value
• Vision narratives explain current problem, future state, choices and evidence
• Strategic themes organise investments around customer outcomes rather than departments
• Working backwards begins with customer value, adoption evidence and operating implications
• Narrative structure anticipates sponsor questions about value, risk and trade-offs
• Product principles guide recurring decisions when detailed requirements remain uncertain

Participants can build outcome-led roadmaps that make sequencing and dependencies visible.

• Outcome-based roadmaps connect strategic themes, initiatives, measures and time horizons
• Now-next-later roadmaps communicate direction without false date precision
• Release planning considers learning, customer value, readiness and technical dependencies
• Dependency maps expose critical paths across teams, suppliers, data and governance
• Capacity scenarios compare delivery options under resource and funding constraints
• Roadmap assumptions reviewed at fixed intervals using new evidence and performance data

Participants can define a product measurement system that supports decisions and learning.

• North Star Metric links recurring customer value with sustainable product growth
• Metric trees connect strategic outcomes with behavioural and operational drivers
• AARRR funnel measures acquisition, activation, retention, revenue and referral
• Cohort analysis separates retention patterns from aggregate customer activity
• Leading and lagging indicators prevent delayed recognition of product problems
• Metric definitions specify formula, source, cadence, owner and decision use

Participants can establish governance that supports rapid learning while managing material risks.

• Innovation governance distinguishes discovery funding from scale-up investment decisions
• Stage-gate reviews assess evidence, risk, readiness and next funding requirement
• Risk registers address customer harm, regulation, security, reputation and delivery
• Ethical product review examines fairness, transparency, consent and unintended consequences
• Data protection impact assessment triggers identified for customer data initiatives
• Decision logs record choices, evidence, dissent, owners and review dates

Participants can plan market entry and adoption activities linked to target customer behaviour.

• Go-to-market plans align target segment, proposition, channel, price and launch sequence
• Adoption barriers mapped across awareness, trial, onboarding, trust and habit formation
• Crossing the Chasm distinguishes early adopters from mainstream customer requirements
• Launch readiness checklists cover support, operations, training, communications and monitoring
• Sales enablement materials translate product value into customer-specific conversations
• Post-launch learning plans combine feedback, usage data, incidents and commercial results

Participants can lead product decisions across functions with clear evidence and accountability.

• Stakeholder analysis identifies influence, interests, objections and engagement approaches
• RACI matrices clarify accountability for discovery, delivery, launch and measurement
• Product review cadences separate strategic decisions from delivery status reporting
• Constructive challenge tests assumptions, evidence quality and alternative interpretations
• Conflict resolution focuses on decision criteria, trade-offs and shared outcomes
• Product communication adapts detail for executives, teams, customers and delivery partners

Participants can plan product scaling, improvement, renewal or retirement using performance evidence.

• Product lifecycle reviews assess adoption, profitability, service load and strategic relevance
• Scaling readiness covers repeatable demand, delivery capacity, controls and unit economics
• Platform strategy evaluates reusable capabilities, interfaces, governance and network effects
• Cannibalisation analysis compares portfolio value, customer migration and competitive response
• Product sunset plans manage customer transition, data retention, contracts and communications
• Continuous discovery routines maintain customer evidence beyond initial product launch

Participants can build, review and present a complete product strategy dossier for a defined opportunity.

• Product strategy dossier integrates evidence, choices, economics, roadmap and governance
• Executive summary states recommendation, investment request, rationale and critical risks
• Customer evidence supports target segment, job, proposition and adoption assumptions
• Portfolio rationale demonstrates strategic fit, prioritisation logic and resource implications
• Roadmap presentation links staged investment to learning milestones and outcome metrics
• Peer review challenges assumptions, decision criteria, evidence gaps and implementation feasibility