Disruptive Innovation Training Course

Participants can identify customer and market conditions that support disruptive opportunities.

• Non-consumption analysis identifies customers excluded by price, access or complexity
• Mapping underserved segments against current offerings, channels and service requirements
• Jobs-to-be-Done distinguishes functional, emotional and social customer progress
• Outcome-driven innovation identifies underserved outcomes and satisfaction gaps
• Customer journey mapping reveals friction, workarounds, delays and abandonment points
• Opportunity scoring compares market accessibility, unmet demand and incumbent vulnerability

Participants can gather and assess evidence for a customer problem before proposing solutions.

• Problem interviews separate observed behaviour from stated preferences and solution requests
• Interview guides use context, trigger, struggle and workaround questioning sequences
• Recruiting participants beyond current customers avoids incumbent channel and loyalty bias
• Assumption mapping ranks desirability, feasibility, viability and compliance uncertainties
• Evidence logs record quotes, behaviours, counterexamples and confidence levels
• Triangulating interviews, operational data and market signals strengthens problem assessment

Participants can design a business model suited to a disruptive market entry.

• Business Model Canvas connects customer segments, value propositions and revenue logic
• Value proposition design matches customer jobs, pains and gains
• Revenue architecture compares subscription, transaction, usage-based and cross-subsidy models
• Cost-to-serve analysis tests whether lower performance supports profitable access
• Channel design balances self-service, partners, mobile access and assisted delivery
• Business model assumptions expose dependencies on scale, trust and unit economics

Participants can design experiments that test the highest-risk venture assumptions.

• Lean Startup builds, measures and learns through controlled assumption testing
• Minimum viable products test behaviour without building full operational capability
• Hypothesis statements specify target users, expected behaviour and measurable thresholds
• Experiment cards define methods, samples, metrics, duration and decision rules
• Smoke tests, concierge tests and landing pages test demand efficiently
• Cohort metrics distinguish acquisition, activation, retention, referral and revenue signals

Participants can plan market entry and adoption for a disruptive offering.

• Diffusion of Innovations explains adopter categories, communication channels and observability
• Crossing the Chasm identifies the transition from early adopters to mainstream users
• Whole product analysis identifies complementary services required for buyer adoption
• Switching costs include habits, contracts, data, risk and workflow disruption
• Beachhead market selection concentrates resources on a reachable initial segment
• Reference customers and proof points reduce perceived adoption risk

Participants can assess disruptive threats and select proportionate strategic responses.

• Competitor signal analysis separates credible traction from publicity and isolated pilots
• Disruption threat maps compare customer overlap, performance trajectory and business model
• Scenario planning tests incumbent responses under alternative adoption and pricing paths
• Response choices include ignore, partner, acquire, imitate or create separately
• Cannibalisation analysis compares protected revenue against delayed strategic adaptation
• War-gaming exposes competitor reactions, channel conflict and customer migration patterns

Participants can recommend structures and governance for disruptive innovation work.

• Resource dependence explains why core units reject low-margin emerging opportunities
• Dedicated teams protect exploratory work from established process and performance demands
• Ambidextrous organisation design separates exploration activities from exploitation operations
• Governance charters define decision rights, funding authority and escalation routes
• Innovation accounting tracks learning milestones before conventional profit measures
• Risk, legal and compliance engagement begins during experiment design

Participants can prioritise disruptive initiatives using staged investment and evidence criteria.

• Three Horizons categorises core, emerging and future growth investments
• Portfolio matrices compare strategic fit, uncertainty, upside and resource requirements
• Stage-gate decisions use evidence thresholds rather than presentation quality alone
• Real options logic preserves flexibility under high market and technology uncertainty
• Venture funding tranches link capital release to validated learning milestones
• Kill criteria prevent prolonged investment in weak or unsupported assumptions

Participants can create an action plan for advancing a disruptive innovation opportunity.

• Opportunity briefs summarise target users, unmet jobs and disruptive foothold
• Stakeholder maps identify sponsors, blockers, influencers and affected operating teams
• Experiment backlogs sequence critical assumptions by risk and learning value
• Ninety-day plans assign actions, owners, decision dates and evidence outputs
• Leadership narratives explain uncertainty without overstating market certainty or returns
• Review cadences connect experiment findings to portfolio and governance decisions