Breakthrough Innovation from Brilliant Mistakes
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Contributor: Paul Schoemaker, author of Brilliant Mistakes (Wharton Digital Press, 2011); Marketing Professor and Research Director of the Mack Center for Technological Innovation at the Wharton School, University of Pennsylvania; Founder and Chairman of Decision Strategies International.
Discover breakthrough innovation, and accelerate organizational learning, by adopting a mindset and a process for deliberate mistake-making.
What if some of your most tried-and-true assumptions about the way you do business were wrong? What if, in fact, they were costing you market share, or preventing you from taking advantage of a new opportunity that could significantly increase your bottom line? Assumptions can be wrong for numerous reasons, ranging from changes in the world in which the assumptions were formed to lack of humility among those at the top. Testing assumptions — in effect, making deliberate mistakes — offers the possibility of more effective business practices, groundbreaking innovation, and even greater profits.
Brilliant mistakes have two prime ingredients. First, they require a significant challenge to the status quo. Second, that challenge allows for deep new insights to emerge whose benefits far exceed the cost of the original mistake. These deep insights, or accelerated learning, can be as important as the discovery of a breakthrough innovation.They can be “portals of discovery” that lead to even greater improvements in your future prospects. By purposefully making and learning from mistakes, you can realize significant benefits.
How Companies Use It
- A strategy consulting firm, Decision Strategies International (DSI, for which Schoemaker serves as Chair), determined that its policy of not responding to certain Requests for Proposals (RFPs) was worth testing. Ordinarily, DSI would not have responded to an RFP without knowing anyone in the organization, under the assumption that the prospective client was price shopping or had already determined its favorite candidate. The next such RFP it received, from a regional electric utility, was assigned to recent hires to create a proposal under senior supervision. To DSI’s pleasant surprise, the unknown client accepted the proposal, and also hired DSI for other projects, amounting to more than $1 million in consulting fees.
- Until 1984, U.S. telephone companies had to provide service to every household in their region, no matter the household’s credit history. The companies collected deposits from customers with the worst credit history, believing that they were most likely to damage equipment and/or not pay their bills. They tested this assumption by not charging the deposit for several months from these “bad” risks, and found that this customer segment had fewer delinquencies than some other customer segments, with less damage to equipment. The counterintuitive insight caused them to recalibrate their risk models and to charge deposits based on different criteria. The improved credit models added an average of $137 million to the bottom line every year for a decade.
- A pet food manufacturer monitored their sales chiefly through their main point of distribution, supermarkets. A newly hired VP argued that sales were in decline, even though recent data gathered through the supermarket channel clearly demonstrated a steady hold on market share. The VP recommended that the company start monitoring non-traditional channels, such as pet superstores and direct sales through veterinarians. Although a cost–benefit analysis suggested otherwise (the monitoring would add considerable cost and reduce profits), the pet food manufacturer invested in the new monitoring, and found that their overall market share was indeed in decline. Adhering to their tried-and-true method of relying on supermarket sales was placing the company at serious risk of obsolescence, missing the growth opportunities in alternative channels. Thanks to a brilliant mistake, expanding the company’s traditional monitoring efforts, senior management was able to get ahead of this unrecognized fall in market share, realign sales and distribution strategies, and monitor trends in customer behavior more carefully.
- See the Additional Resources links below for more examples and research findings.
Making and learning from brilliant mistakes entails a disciplined process of deliberate mistake-making:
- Identify assumptions. What are the key assumptions or accepted norms about the way you do business? They might include the best ways to obtain new business, spend marketing resources, give incentives, or define hiring criteria.
- Select assumptions for testing. From your list, use two metrics to find the assumptions most likely to yield valuable results: first, how significant is the metric to how you run your business, and second, how confident are you in the accuracy or correctness of the assumption. Hone in on those assumptions that score high on importance and less high on certainty in their correctness.
- Rank the assumptions. Ask a group a series of questions about this subset of assumptions to generate an overall score indicating the relative value of putting these assumptions to the test. How true are the following (1 = not true, 7 = very true): 1. The potential benefit of the experiment is significantly higher than its cost, 2. We make this decision repeatedly, 3. This is a complex problem to solve analytically, 4. Our experience base with this assumption is limited, 5. The business conditions surrounding this issue have changed. The assumption with the highest score should be the one you test.
- Create strategies for making mistakes. If you always spend 70% of your marketing dollars on traditional media, consider spending a greater portion on social media. If you use interviews to identify appropriate job candidates, consider using a combination of testing and interviews. Think the way advertising legend David Ogilvy did; he ran a few ads that he thought would not work, just to test his thinking.
- Execute the mistake efficiently. Ogilvy would just run a few of his “loser” ads, not many. The goal is to fail quickly and inexpensively.
- Learn from the outcome using a forensic mindset. Note all unexpected outcomes of your test, even those that seem minor or peripheral. Then think deeply about what these deviations from expectation tell you — generate multiple hypotheses for each and run further tests to understand them. Be persistent the way scientists, journalists, and forensic specialists are.
- Profiting from Uncertainty. Paul J. H. Schoemaker, with Robert E. Gunther (Free Press, 2002). Declares that uncertainty is not the enemy but rather where the greatest opportunities are. Presents a systematic approach that combines concepts such as scenario planning, flexible strategies, options portfolios, and dynamic monitoring to create novel strategies for profiting from ambiguity.
- Peripheral Vision: Detecting the Weak Signals that Will Make or Break Your Company. George Day and Paul J. H. Schoemaker (Harvard Business Press, 2006). Examines the common causes and frequent consequences of a “vigilance gap,” the inability of both individuals and organizations to recognize and then act upon “weak signals from the periphery” before it is too late. Day and Schoemaker recommend a series of seven steps to bridge this gap.
- Paul Schoemaker is the Learning Director of Wharton Executive Education's Critical Thinking: Real-World, Real-Time Decisions program, and also teaches in the Global CEO Program: A Transformational Journey and the Advanced Management Program.
About Nano Tools:
Nano Tools for Leaders® was conceived and developed by Deb Giffen, MCC, Director of Innovative Learning Solutions at Wharton Executive Education. It is jointly sponsored by Wharton Executive Education and Wharton’s Center for Leadership and Change Management, Professor of Management Michael Useem, Director. The Academic Director of Nano Tools is Professor of Management Adam Grant.
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