What if the teams that struggle to define their problem early are actually your best innovation bet?
Dr Johnathan Cromwell, Associate Professor of Entrepreneurship and Innovation at the University of San Francisco, shares findings from a study of over 1,100 real innovation teams at a Fortune Global 500 company. The results overturn one of the most deeply held assumptions in innovation management: teams that started with low problem clarity but gained it by the midpoint achieved an implementation rate of over 80% — compared to approximately 50% for teams that defined their problem clearly from the outset.
In this episode, Mark and Johnathan explore:
Why problem and solution co-evolve rather than follow a linear sequence — and what that means for how you run innovation projects
The critical midpoint transition: why the halfway point of any project is the moment that determines success or failure
How to manage a portfolio of front-end innovation projects when ambiguity is a feature, not a bug
Why Jobs to Be Done are not as stable over time as the framework assumes — and where the five whys technique changes the game
How AI is not just solving existing problems faster but revealing entirely new problems companies did not know they had
The three modes of AI adoption: exploiting existing problems (Instacart), expanding the problem (Khan Academy), and exploring new ones entirely
Johnathan also shares practical advice for the VP of Innovation under pressure to show return on investment — and why dismissing projects without a clear problem definition may mean dismissing your best future innovations.
Published research referenced in this episode:
Cromwell & Harvey (2026). The Hidden Power of Messy Teams. MIT Sloan Management Review, Spring 2026.
Cromwell & Harvey (2025). A Problem Half-Solved Is a Problem Well-Stated. Research Policy, 54(3).
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