Making Innovation Repeatable: ODI as Operational Infrastructure
Challenge
Innovation work operated project-by-project — each engagement reinvented its own discovery process, assessment criteria, and validation approach. Without a shared framework, innovation outputs varied in rigor, opportunity prioritization relied on intuition rather than data, and it was impossible to compare opportunities across value streams using consistent criteria. The strategy team needed externally validated customer research to assess which platform opportunities were genuinely high-value versus internal assumptions — but no systematic way to produce or evaluate that research existed.
Solution
Built a complete Outcome-Driven Innovation (ODI) methodology operationalized as executable skills, commands, and templates. The system codifies Tony Ulwick's ODI framework — the principle that customers hire solutions to accomplish jobs, and that jobs are stable even as solutions change — into a repeatable research and assessment pipeline across 9 phases: Frame → Discover → Map → Prioritize → Assess → Validate → Test → Recommend → Learn. Opportunity scoring uses a quantitative formula (Opportunity = Importance + (Importance – Satisfaction)) with outcomes plotted on an importance-vs-satisfaction landscape. A dual-path assessment framework separates optimization (Path A, scores 10–14) from disruption (Path B, scores 15+). Value Labs — 15–30 minute structured customer conversations following an 80/20 listening rule — serve as the primary research instrument. The entire methodology was codified into 11 reusable skills, 9 executable commands, and 6 templates.
Results
Codified a complete innovation methodology eliminating per-project reinvention — deployed across 4+ active projects with ODI scoring replacing intuition-based prioritization. Dual-path assessment (Path A optimization vs. Path B disruption) adopted by the strategy team for platform investment decisions. Skill library structured in reusable layers — 7 generic skills applicable to any project plus domain-specific additions — so new projects inherit the generic layer and build only unique additions. Triangulation model (primary customer research plus secondary SME and provider validation) established as the standard for strategic research, reducing the risk of building products based solely on internal assumptions.