The Imperfectionists

The Imperfectionists Plot Summary

Introduction

In today's rapidly changing world, uncertainty has become the new normal. Organizations and individuals face unprecedented disruption from technological innovation, geopolitical shifts, and environmental challenges. Traditional approaches to problem solving often falter in this environment, as they typically rely on certainty and historical data that may no longer be relevant. What's needed is a fundamentally different approach to navigating uncertainty. The mindsets framework presented here offers a practical and powerful way to embrace uncertainty rather than fear it. Through six distinct yet interconnected strategic mindsets, problem solvers can develop the mental agility needed to thrive amid change. These mindsets help us move beyond the paralyzing dichotomy of either reckless betting or risk-averse inaction. Instead, they enable us to step thoughtfully into uncertainty, gather valuable information through small experiments, crowd-source expertise beyond our immediate circle, and compel others to action through compelling storytelling. This framework doesn't just help us solve today's problems—it transforms how we view uncertainty itself, turning it from a threat into an opportunity for innovation and growth.

Chapter 1: Ever Curious: Embracing the Mindset of Exploratory Learning

The ever-curious mindset represents our most fundamental orientation toward uncertainty. Rather than viewing the unknown as threatening, the curious problem solver approaches it with genuine wonder and a desire to learn. This mindset helps us navigate ambiguity by encouraging us to ask questions, explore possibilities, and remain open to unexpected discoveries. At its core, curiosity is the desire to close the gap between what we know and what we want to know. When confronted with uncertainty, our natural response might be to retreat to what's familiar, but curiosity pushes us in the opposite direction—toward exploration. Curiosity thrives within a particular sweet spot of uncertainty: too little uncertainty generates boredom, while too much creates anxiety. The curious problem solver recognizes this dynamic and cultivates a state of productive uncertainty where learning can occur. The ever-curious mindset manifests through three key behaviors: flourishing in the flow of ideas, asking audacious questions, and creating space for novelty. Those who flourish in the flow of ideas position themselves in environments where new information, perspectives, and challenges naturally emerge. Albert Einstein, for example, made his revolutionary discoveries while working as a patent clerk, surrounded by innovative ideas about time synchronization and electromagnetic devices. This immersion in the flow of technological development fueled his groundbreaking insights about relativity. Audacious questions represent another powerful aspect of the curious mindset. These questions challenge assumptions and open new pathways for exploration. When SpaceX's Elon Musk asked if it was possible to build a mission-critical computer for $10,000 rather than the traditional $10 million, he wasn't merely seeking cost savings—he was challenging an entire industry's understanding of what was possible. Such questions often lead to breakthrough innovations by forcing us to reconsider established limitations. The curious mindset also requires creating space for novelty, gestation, and psychological safety. Organizations that value curiosity recognize that innovation requires time for ideas to develop naturally. Johann Sebastian Bach created his most enduring masterpieces not when rushed to meet weekly deadlines, but during his retirement when he could explore music with genuine curiosity. Similarly, organizations that foster psychological safety—where people feel comfortable asking questions without fear of appearing ignorant—create fertile ground for curiosity to flourish. In practice, fostering curiosity within organizations requires deliberate effort. Leaders can encourage curious exploration by modeling question-asking behavior, creating dedicated time for experimentation, and celebrating learning rather than just outcomes. Companies like 3M and Google, which have policies allowing employees to spend a percentage of their time on projects of personal interest, demonstrate this commitment to curiosity as a core problem-solving mindset.

Chapter 2: Dragonfly Eye: Viewing Problems Through Multiple Perspectives

The dragonfly eye mindset enables problem solvers to see beyond conventional perspectives by viewing challenges through multiple lenses simultaneously. Named after the compound eyes of dragonflies, which contain up to 30,000 individual lenses providing a nearly 360-degree field of vision, this mindset helps us develop a more comprehensive understanding of complex problems by examining them from various angles. Central to this mindset is the practice of "anchoring outside"—stepping beyond our internal organizational viewpoint to consider how a problem appears from different perspectives. This contrasts with "anchoring inside," where we view issues solely through the lens of our existing organizational structures, processes, and assumptions. When Ford Motor Company separated its electric vehicle operations from its internal combustion engine business while keeping them under the same corporate umbrella, it demonstrated the dragonfly eye mindset by creating space for two different perspectives to coexist productively. The dragonfly eye mindset manifests in three key approaches: changing the lens through which we view problems, widening the aperture to see broader contexts, and employing multiple perspectives simultaneously. Changing lenses involves deliberately adopting unfamiliar viewpoints. When two Stanford MBA students without dental backgrounds examined orthodontics not as a medical procedure but as a consumer experience problem, they revolutionized the industry by creating Invisalign—an approach that traditional dentistry experts couldn't envision because they were constrained by conventional perspectives. Widening the aperture enables us to see broader patterns and relationships that might otherwise remain invisible. Amazon demonstrated this when examining its e-commerce infrastructure not just as an internal resource but as a potential service for external developers. This wider perspective ultimately led to Amazon Web Services (AWS), which transformed cloud computing and became one of Amazon's most profitable businesses. The most powerful application of the dragonfly eye mindset comes from synthesizing multiple perspectives simultaneously. Complex problems like obesity cannot be understood through a single lens. Research teams examining this issue discovered valuable insights by combining geographic, socioeconomic, and intergenerational perspectives, ultimately identifying maternal education as a key causal factor—a finding that no single disciplinary approach could have uncovered. The dragonfly eye mindset serves as a powerful antidote to cognitive biases like confirmation bias (seeking only information that confirms our existing beliefs) and the analogy trap (inappropriately applying patterns from one context to another). When WeWork valued itself as a technology company with network effects rather than as a real estate business, it fell into the analogy trap with disastrous consequences. The dragonfly eye mindset would have encouraged a more nuanced understanding of WeWork's actual business model.

Chapter 3: Occurrent Behavior: Experimenting Relentlessly to Reduce Uncertainty

The occurrent behavior mindset centers on testing hypotheses through experimentation to generate new, real-time data rather than relying solely on historical information or theoretical projections. This approach recognizes that in rapidly changing environments, the most valuable information often comes from what actually happens (what "occurs") rather than what was predicted or assumed. At its foundation, occurrent behavior draws on Bayesian thinking, named after 18th-century statistician Thomas Bayes. This approach begins with prior knowledge, proposes explanations, tests them against new evidence, and then updates beliefs accordingly. In contrast to static approaches that treat uncertainty as a fixed state, Bayesian thinking embraces uncertainty as dynamic and reducible through iterative experimentation and learning. Occurrent behavior manifests in three key practices: creating new data through deliberate experiments, employing novel analytical approaches, and leveraging natural experiments. When the Federal Reserve Bank tested whether weighing money might be more accurate than counting it by hand, they created new data that challenged conventional wisdom and ultimately saved millions of dollars while improving accuracy. Similarly, when Airtasker conducted A/B testing of different booking fee levels, they discovered unexpected customer price sensitivity patterns that substantially increased revenue. Novel analytical approaches represent another dimension of occurrent behavior. When Dr. Fang Chen faced the challenge of predicting underground water pipe failures with extremely sparse data, traditional statistical methods proved inadequate. By developing a new non-parametric Bayesian machine learning model, her team achieved remarkable predictive accuracy, identifying 80% of potential failures by inspecting just 20% of pipes. This innovative approach generated insights that conventional analysis couldn't reveal. Natural experiments provide a third pathway for occurrent behavior when deliberate experimentation isn't feasible. The contrasting COVID-19 responses of neighboring Sweden and Norway created a natural experiment in public health policy. Sweden's less restrictive approach resulted in significantly higher mortality rates than Norway's more precautionary strategy, providing valuable insights for future pandemic preparedness that couldn't have been gained through theoretical modeling alone. In practice, the occurrent behavior mindset requires organizations to balance the costs of experimentation against the benefits of new knowledge. While experiments consume resources and may sometimes fail, they generate real-world evidence that reduces uncertainty and improves decision-making. Space X exemplifies this mindset through its "fly, test, fail, fix" approach, which has enabled rapid learning and innovation, ultimately reducing the cost of putting cargo into space by 95% compared to traditional NASA missions. The occurrent behavior mindset stands in stark contrast to organizational cultures that demand immediate certainty or punish failure. By embracing experimentation as a path to learning rather than as a threat to authority, problem solvers can navigate uncertainty more effectively, turning the unknown into a source of competitive advantage.

Chapter 4: Collective Intelligence: Harnessing Wisdom Beyond Expertise

The collective intelligence mindset recognizes that in uncertain environments, the best solutions often emerge not from individual experts but from diverse groups working together. This approach acknowledges Bill Joy's observation that "no matter who you are, most of the smart people work for someone else," and seeks to harness that distributed intelligence to solve complex problems. Traditional expertise, while valuable in stable conditions, often proves insufficient in rapidly changing environments. Studies by Philip Tetlock demonstrate that diverse groups of thoughtful non-experts frequently outperform domain specialists in forecasting complex outcomes. Similarly, in medical diagnostics, collective approaches combining artificial intelligence with human judgment now outperform individual specialists in areas like melanoma detection and cardiac prediction. The collective intelligence mindset responds to this reality by seeking wisdom beyond conventional expertise. This mindset manifests through three distinct approaches: crowdsourced expertise, collective wisdom, and AI-enabled collective intelligence. Crowdsourced expertise can be competitive, as with prize competitions like the Longitude Prize of 1714, which offered £20,000 to anyone who could solve the problem of determining a ship's longitude at sea. The solution came not from established astronomers but from clockmaker John Harrison, demonstrating how competitions can draw solutions from unexpected sources. Modern platforms like Kaggle apply this approach to contemporary challenges, including The Nature Conservancy's FishFace project, which crowdsourced algorithms to identify fish species from camera footage. Collective wisdom represents another dimension of this mindset, particularly when it incorporates ancestral or community knowledge. In Northern Australia, the reintroduction of traditional Indigenous fire management practices—combined with modern satellite mapping and carbon credit systems—has dramatically reduced destructive wildfires while generating environmental and economic benefits. This blend of ancestral wisdom with contemporary science exemplifies how collective intelligence can transcend temporal boundaries. AI-enabled collective intelligence represents the frontier of this mindset, combining human judgment with machine learning capabilities. While AI alone cannot replace human creativity, and humans alone cannot process the vast quantities of data now available, their combination creates powerful problem-solving systems. Platforms that organize "AI swarms," where groups think together in algorithm-guided interactions, now outperform both individual humans and standalone AI in many predictive tasks. The failure of Quibi, a short-form video streaming service backed by industry experts and $1.75 billion in funding, illustrates the limitations of traditional expertise compared to collective intelligence approaches. While Quibi relied on Hollywood experts to curate content, competitor TikTok flourished by employing AI algorithms to analyze user preferences and behavior at scale, creating a self-reinforcing system of collective content curation that quickly surpassed Quibi's expert-driven model. Implementing collective intelligence requires organizations to overcome barriers like intellectual property concerns, resource limitations, and cultural resistance to external ideas. Companies that successfully adopt this mindset map their ecosystems to identify potential collaborators, create incentives for external contributions, and develop processes for integrating diverse perspectives into their problem-solving approaches.

Chapter 5: Imperfectionism: Stepping Into Risk Through Measured Action

The imperfectionist mindset provides a strategic approach to uncertainty that avoids both reckless risk-taking and paralytic risk aversion. Rather than waiting for perfect information or making all-or-nothing bets, imperfectionists step deliberately into uncertainty through measured actions that build knowledge, capabilities, and strategic position over time. At its core, imperfectionism acknowledges that perfect certainty is unattainable and often comes at too high a cost in rapidly changing environments. Instead of seeking perfection before acting, imperfectionists take calculated steps that allow them to gather information, test assumptions, and refine strategies through experience. This approach is exemplified by companies like Amazon, which entered consumer financial services not through a massive acquisition but through a series of small moves—investments, partnerships, and team hires—that built knowledge and capabilities while limiting downside risk. The imperfectionist mindset operates through two primary strategic approaches: stepping into risk and passing off risk to others. Stepping into risk involves making incremental moves that improve strategic position while generating new information about market dynamics. Each move builds on previous learning, creating what might be called a "growth staircase" that balances three elements: stretch (acquiring new capabilities), momentum (building confidence through early successes), and flexibility (maintaining optionality in uncertain environments). Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO) demonstrated this approach in defending its valuable Wi-Fi patent. Rather than immediately launching an expensive legal battle against multiple tech giants, CSIRO first brought a test case against a single smaller company in a favorable jurisdiction. This initial move established legal precedent that strengthened CSIRO's position for subsequent, larger actions, ultimately generating hundreds of millions in licensing revenue through a carefully sequenced strategy that responded to evolving conditions. The second dimension of imperfectionism involves passing risk to others who can better bear it. The All England Lawn Tennis Club, which organizes Wimbledon, exemplified this approach by paying insurance premiums for 17 years to cover the remote possibility of tournament cancellation. When COVID-19 forced the first cancellation since World War II, the club received a $219 million payout, demonstrating how transferring certain risks can create strategic resilience. Pharmaceutical companies employ sophisticated imperfectionist strategies by monitoring promising drug candidates in academia and biotech startups, then acquiring them at optimal points in their development. Rather than bearing all the discovery risk internally, these companies let others take early-stage risks, then apply their expertise and resources to later development stages where their capabilities add greatest value. Novartis followed this approach with its groundbreaking cancer therapy Kymriah, licensing technology developed at the University of Pennsylvania after university researchers had already demonstrated promising results. Implementing imperfectionism requires organizations to distinguish between reversible and irreversible decisions, tailor processes to different types of risk, and learn systematically from both successes and failures. Pre-mortems (imagining potential failures before they occur) and post-mortems (analyzing actual outcomes after decisions) help build organizational learning capabilities that improve future decision-making under uncertainty. The imperfectionist mindset represents a fundamental shift from traditional strategic planning based on illusory certainty toward a more dynamic, responsive approach that acknowledges uncertainty as a permanent condition requiring continuous adaptation and learning.

Chapter 6: Show and Tell: Compelling Others to Action Through Storytelling

The show and tell mindset recognizes that even the most brilliant problem solving remains ineffective if it fails to motivate action. This mindset focuses on communicating solutions in ways that engage emotions, challenge assumptions, and compel others to change their behavior or perspective. Traditional approaches to persuasion rely heavily on facts, data, and logical arguments. While these elements remain important, the show and tell mindset acknowledges that humans are visual learners whose decisions are influenced by values, emotions, and narratives as much as by rational analysis. In an era of information overload and widespread skepticism, merely presenting logical arguments—what might be called an "anxious parade of knowledge"—often fails to drive meaningful change. The show and tell mindset manifests through four key approaches: using visual representations to tell stories, employing props to spark curiosity, conducting demonstrations when words fail, and speaking to underlying values rather than just facts. Florence Nightingale exemplified the power of visual storytelling when she created innovative "rose diagrams" showing how preventable diseases killed far more soldiers in the Crimean War than battlefield wounds. These visualizations communicated complex data with emotional impact, ultimately contributing to major reforms in military healthcare. Props serve as powerful attention-grabbing tools that make abstract concepts concrete. When The Nature Conservancy wanted to illustrate how oysters filter water in ecosystems, they placed 17 buckets in a boardroom to physically represent the 170 liters of water each oyster filters daily. This visual prop made an abstract ecological process tangible and memorable, helping secure funding for reef restoration projects. Demonstrations provide compelling evidence when words alone cannot persuade. When physicist Richard Feynman investigated the Space Shuttle Challenger disaster, he conducted a simple but dramatic experiment during a televised hearing, placing O-ring material in ice water to demonstrate how it lost resilience at low temperatures. This live demonstration conveyed the cause of the disaster more powerfully than any technical report could have done. Speaking to values represents the fourth dimension of show and tell, recognizing that people often process information through existing mental frames. Climate scientist Katherine Hayhoe exemplifies this approach by connecting climate solutions to widely shared values like parental concern for children's futures, rather than relying solely on scientific data that might be rejected if it conflicts with existing worldviews. The case of Barry Marshall, who discovered the bacterial cause of stomach ulcers, illustrates the necessity of the show and tell mindset when conventional communication fails. After struggling to convince the medical establishment that the bacterium H. pylori caused ulcers, Marshall took the dramatic step of drinking a bacterial culture himself, developing symptoms, and documenting the results. This extreme demonstration ultimately led to acceptance of his findings and a Nobel Prize, demonstrating how show and tell can overcome even deeply entrenched resistance to new ideas. Implementing the show and tell mindset requires organizations to invest in storytelling capabilities, practice reframing issues to connect with different audiences' values, and design communications that incorporate surprise, novelty, and emotional engagement. By treating persuasion as a creative act rather than merely a transmission of information, problem solvers can bridge the gap between insight and action, transforming solutions into real-world change.

Summary

Strategic mindsets for uncertain times provide a comprehensive framework for navigating a world where change is accelerating and traditional problem-solving approaches often fall short. The six mindsets—ever curious, dragonfly eye, occurrent behavior, collective intelligence, imperfectionism, and show and tell—work together as an integrated system that enables us to approach uncertainty not as a threat but as an opportunity for creative problem solving. The true power of these mindsets lies in their collective application to uncertainty. They begin with curiosity that opens us to new possibilities, continue through multiple perspectives that reveal hidden patterns, gather new data through experimentation, tap into wisdom beyond our immediate circle, step thoughtfully into risk, and ultimately compel others to action through powerful storytelling. In a world increasingly characterized by disruption, volatility, and ambiguity, these mindsets offer not just a way to survive uncertainty, but to thrive within it—transforming the very nature of how we approach problems and discover opportunities where others see only chaos.

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Charles Conn

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