The Reverse Engineering Strategy Test
Test strategy by imagining what must be true for it to succeed
Martin and Lafley's Reverse Engineering approach flips traditional strategy analysis on its head. Instead of asking 'What should we do?' and then building a case for the answer, you ask 'What would have to be true for this option to be the best choice?' This reframing transforms strategy debates from arguments about conclusions into collaborative exploration of assumptions.
The method works for any strategic decision. Present each option and list the conditions that would need to be true for it to succeed—assumptions about customers, competitors, capabilities, and economics. Then identify which assumptions you are least confident about and design tests to validate them before making a full commitment.
This approach reduces the ego and politics that poison most strategy processes. Instead of defending positions, leaders examine assumptions together. When someone says 'I don't think Strategy A will work,' you reframe it as 'Which of Strategy A's assumptions do you find least credible?' This shifts the conversation from subjective judgment to testable hypotheses.
- Strategy testing should examine underlying assumptions, not just conclusions
- Asking 'What would have to be true?' transforms adversarial debates into collaborative assumption-testing
- The assumptions you are least confident about should be tested before committing resources
- Every strategy is a bet on a set of assumptions—making those bets explicit reduces risk
- Generate Multiple Strategic OptionsBefore testing, ensure you have at least two to three genuinely different strategic options on the table. Each option should represent a distinct where-to-play and how-to-win combination, not minor variations of the same approach. The quality of your strategy depends on the quality and diversity of options you consider—testing a single option against itself produces false confidence.Pro tipInclude at least one option that challenges conventional wisdom—the option that makes people uncomfortable often reveals the most interesting assumptionsWarningIf all your options look similar, you have not generated genuine strategic alternatives
- List 'What Would Have to Be True' for Each OptionFor each strategic option, collaboratively list every condition that would need to be true for it to succeed. Include assumptions about customer behavior, competitor responses, capability development timelines, economic conditions, and regulatory environment. Be comprehensive—unstated assumptions are the ones most likely to prove false.Pro tipAsk each team member individually before the group discussion—this prevents groupthink from filtering out important assumptions
- Identify the Least Confident AssumptionsFor each option, vote on which assumptions the team is least confident about. These are the 'killer assumptions'—the ones that, if wrong, would cause the strategy to fail regardless of how well everything else goes. Rank assumptions by both their importance (impact if wrong) and your confidence level (probability of being right).Pro tipThe assumptions with high importance and low confidence are where you should focus your testing resources—everything else is noise
- Design Tests Before Committing ResourcesFor each killer assumption, design a quick, cheap test that can increase your confidence before you commit major resources. This might be a market test, customer survey, competitive analysis, prototype, or pilot program. The goal is not perfect certainty but sufficient confidence that the critical assumptions hold. Only proceed with full commitment when killer assumptions pass their tests.Pro tipSet clear 'go/no-go' criteria for each test before running it—define in advance what result would increase your confidence versus what would trigger a strategy revision
When P&G was considering a major investment in Bounty paper towels, the team used the reverse engineering approach to identify critical assumptions. They found that the strategy depended on the assumption that consumers would pay a significant premium for absorbency. Rather than debating this assumption in a conference room, they designed in-market tests to validate consumer willingness to pay before committing to the full investment.
Martin developed this approach through his strategy consulting work and his frustration with traditional strategic planning processes where leaders argued past each other defending preferred conclusions. He noticed that most strategy disagreements were actually disagreements about underlying assumptions—one leader believed the market would grow while another did not, one believed a capability could be built while another thought it impossible. By making assumptions explicit and testable, he created a process that depoliticized strategy and produced better decisions.