The Upside of Uncertainty: A Guide to Finding Possibility in the Unknown
Nathan Furr & Susannah Harmon Furr
320 pages, Harvard Business Review Press, 2022
Although most people agree that we live in increasingly uncertain times, few of us have been taught the robust skills for navigating uncertainty with courage and resilience. Not surprisingly then, when we run into uncertainty, we end up feeling anxious, afraid, or tripping headlong into any number of behavioral traps, such as threat rigidity or rumination. In these moments we forget a fundamental truth: The best things in our lives—meaningful relationships, education and careers, breakthroughs made by scientists, and change created by social entrepreneurs—only come after first facing uncertainty. To reach new possibilities we envision, we must all first step into the unknown. And even when devastating uncertainty happens to us, the way we meet the challenge can help us navigate that struggle.
The good news is that there are tools for facing the unknown with courage, that we can practice, and thereby increase our courage but also our ability to tap into the possibility hidden on the other side of the uncertainty coin. In The Upside of Uncertainty, we describe more than 30 tools to help navigate uncertainty which we discovered reviewing the empirical research and in interviews with creators, innovators, artists, and entrepreneurs.
We organize these many tools around a “First Aid Cross for Uncertainty.” This first aid cross has four categories of things you can do when facing the unknown: reframing uncertainty from being a source of loss to a potential source of possibility, priming in advance so we are prepared for it, doing in ways which lead to more positive action, and sustaining ourselves through the inevitable challenges. The tools are meant to help you accomplish these four tasks in new and refreshing ways. For example, the do section describes ways to take action that increase the likelihood of positive outcomes. One of the tools we discovered is “Learning Through Fog.” When you do something new, or your world gets rattled by an unexpected event, it is easy to feel lost. People often describe such a feeling like being lost in the fog, unsure where to go. How can you discover your way out of the fog?—Nathan Furr and Susannah Harmon Furr
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Martin van den Brink, who led one of the most challenging breakthroughs in semiconductor manufacturing, says navigating uncertainty is like driving a car in difficult conditions: It is foggy and dark. [There are] a few folks with red lights ahead of you, and you are driving as fast as you can. But as you start to get more successful, you are in front. There are no more lights in front, and you have no clue what to do.” How do you navigate through the fog?
The fields of evolutionary biology, strategy, and innovation sometimes use the analogy of an “opportunity landscape” hidden by fog to describe uncertain situations. Imagine a 3D topographical map full of hills and valleys. With no knowledge of the landscape shrouded in the mist, how could you know whether you are standing next to a cliff—a dangerous area—or next to a bigger hill, an even more interesting opportunity? Research suggests that the best way through the fog is to adopt a set of learning techniques—fast cycles, simple rules, and switching approaches—to learn as quickly as possible so that you don’t spend all your time hesitating on a hilltop or bumbling blindly through the gloom.
Fast Cycles
Startup accelerators are a great environment to get clues about how to learn quickly under uncertainty. Founders face dozens of unknowns, from which market to tackle to how to negotiate a contract, and accelerators are a new type of organization created to support them. Unlike startup incubators, which provide an office for an indeterminate period, accelerators accept a group of startups (a class) for a fixed period (typically three months), give them “ramen money” (enough money to survive on ramen noodles) in exchange for equity, and then coach them until a final demo day, when they pitch to external investors for funding. For example, Y Combinator hosts a dinner each week for participants, where successful entrepreneurs describe their lessons learned as well as introduce accepted entrepreneurs to mentors and customers who challenge their assumptions. Today there are several thousand startup accelerators, and graduated companies include Airbnb, Dropbox, and GitHub.
A recent academic study of the eight leading accelerators asked, What is the best way to design an accelerator to help the founders learn as quickly as possible? Should you standardize or customize the program for each startup, compress or pace interactions with mentors, guard secrets or require founders to share with each other? The researchers found that the greatest challenge founders face is the trap we described in chapter 17 of forcing the machinery (settling for suboptimal certainty) in the face of so many unknowns.
Great accelerators counteract this tendency by forcing entrepreneurs to do things they wouldn’t do on their own. They force founders to meet with a torrent of mentors and customers as many as two hundred in the first month, so they get exposed to more of the opportunity landscape before locking into their initial hunch. Initially, many founders are anxious to describe their idea for fear it will be stolen. Great accelerators force them to talk to people because they recognize, as Debbie Sterling, founder of GoldieBlox, a company created to foster engineering skills for girls, explains: “I don’t think it’s ever really too early to start sharing even just a rough idea or a sketch on paper. I really don’t. I have not yet had an experience where a half-baked idea of mine got stolen by somebody else or executed any better than I would’ve.” Sharing her idea with a waiter at a restaurant led to an introduction to the waiter’s aunt, an editor at the Atlantic, who wrote an important article about GoldieBlox that helped launch the business.
The best startup accelerators also force their entrepreneurs to present to each other, sharing their progress. Once again, many founders are reluctant to share with other founders for fear that their ideas will be stolen, but they consistently discover that the benefits of discovering how to solve a shared problem or seeing new ways to approach a challenge outweigh any imagined risks.
Lastly, great startup accelerators force their startups to meet with a broad array of people, rather than customizing the conversations to a narrow group of “relevant” ones. For example, one founder creating software for social causes balked when the accelerator arranged a meeting with Playboy’s VP of marketing. To his surprise, the Playboy VP was also an active churchgoer and had fabulous ideas. Afterward, the founder gushed, “That was the best meeting I had all summer.” Sometimes the best insights come from far afield. As entrepreneur David Hieatt explains, “If we go looking for answers where everyone else does, we soon think as everyone else does. ... Originality requires some element of oddness.”
Simple Rules
Research suggests that simple rules—fast and flexible heuristics based on past experience—can also help you learn your way through the fog. Rather than relying on overcomplicated plans or just shooting from the hip, you can use simple rules to improve your decision-making by combining lessons from past experience with the flexibility to adapt. If we look closely, we can see simple rules at work everywhere in the world. Although ant brains are forty thousand times smaller than human brains, a simple rule of “look for work” allows millions of ants to develop complex divisions of labor, create intricate supply chains, and independently change jobs. A simple rule at Intel—allocate fabrication space based on profit per wafer—led middle managers to transform the company from making memory to making microprocessors without guidance from senior leaders. Likewise, after Amazon presold over a million DVDs of Mamma Mia for $30, when a competitor announced it would sell the same DVD for $10, the simple rule of “customers first” helped executives make the decision to price match (a $20 million loss of revenue) in “less than 60 seconds,” without guidance from Jeff Bezos.
Researchers at Stanford, Nathan among them, have done extensive research on how entrepreneurs develop simple rules in uncertain environments. They found that more successful entrepreneurs use past experience to develop rules about what to focus on (for example, develop low-cost semiconductors for video game makers rather than attracting new customers) and how to do it (for example, hold weekly meetings with marketing and engineering to integrate new customer insights). As teams learn how to work together, the most effective ones develop more sophisticated heuristics about the timing, order, and priority of different opportunities, such as how to prioritize which geographies to enter. By contrast, less effective entrepreneurs don’t take the time to think about and communicate simple rules, and instead repeat past mistakes again and again.
Startup investor David Hornik says that when it comes to uncertainty, “people who rely upon heuristics to make decisions, as opposed to exhaustive information, will be much better at dealing with uncertainty, because you didn’t have to worry about the fact that information is shifting, because heuristics shift with new information.” Hornik uses a simple rule he calls “human-driven decision making” to make startup investments. “I’m not investing because you are an expert. I’m not investing because I have a theory. I am investing because you have demonstrated you are the sort of person I would like to invest in: you are motivated by passion, not money, and you are creative when facing uncertainty.”
Switching Approaches
Finally, it helps to recognize that there are different learning strategies and that you may need to change yours to match the problem you face. Consider the race to create consumer drones, those flying machines piloted by amateurs buzzing overhead. The entrepreneurs who created this new industry faced three major challenges: what the best architecture is, what drones can be used for, and how to create drones ready to fly out of the box. Stanford researchers studying the industry compared 3DR, founded by former Wired editor Chris Anderson, and DJI, founded by Frank Wang when he was a graduate student. To solve the comparatively simple problem of the best architecture, 3DR’s reliance on crowdsourcing, or turning a problem over to a large group of people, proved most effective. A user in an obscure part of the crowd proposed a quadrotor design from the 1950s that rapidly outpaced Wang’s iterative approach based on his original helicopter design.
But when it came to the more complex problem of finding a use for drones, after falling behind with his helicopter design, Wang decided to switch his approach to learning how to solve the challenge. Wang engaged in parallel experimentation, talking to many users at once, such as firefighters, sports enthusiasts, and farmers, until he met a pilot who described how much money film studios pay for bad aerial footage. Drones could serve this market but doing so depended on creating a high-quality gimbal, a sophisticated device to shoot steady video. To solve this problem, Wang changed strategies again, assembling a multidisciplinary team with software, mechanical, and electrical engineers, then engaging in rapid cycles of experimentation to create a gimbal that ended up increasing revenues to over $100 million. By contrast, 3DR stuck with the community-based approach that had worked for discovering the quadrotor. But while the community members spotted the need for a gimbal, they could never adequately coordinate to make one.
When entrepreneurs tackled the final big challenge, designing a ready-to-fly drone, once again the 3DR community struggled to coordinate, whereas Wang’s team adopted a strategy of switching between big-picture architecture and individual components. “We duct-tape and zip-tie the thing together to show it kind of works, and then just make literally twenty prototypes on a weekly basis, constantly building a new prototype, constantly replacing the zip ties with better parts,” explained an engineer. After hundreds of rapid cycles, DJI created a ready-to-fly drone that captured 77 percent of the drone market, making Wang a billionaire and leaving 3DR in the dust. The Stanford researchers concluded that simple problems can be tackled by people working independently, complex problems require cooperation, and integrated problems require both. More generally, their findings show the importance of being able to switch your approach to learning by asking, “What challenge do I face, and what learning strategy could help me figure it out faster?”
Reflection and Practice
Learning in fog requires adopting fast learning cycles, developing simple rules, and changing your learning strategy as the situation demands. Here’s how you can get started.
1. Create your own accelerator. What would it be like to create your own accelerator experience, such as by forcing yourself to talk to as many people as possible, as quickly as possible, about your idea? When Robin Chase was searching for the right way to describe Zipcar, the vehicle-sharing startup she cofounded, she wrote ideas down on index cards and tested them with everyone she met. She soon discovered the secret to convincing people to try the service was in the words she used to describe it: wheels when you want them!
2. Develop simple rules—fast and frugal heuristics—based on your past experience. You can have simple rules for almost any area of life. Create or adjust simple rules based on what you want to do. Thoughtfully develop your own rules but keep them flexible. They can also turn out to be uncertainty balancers, as they free up mental energy. For example, a benevolent humanitarian’s simple rule might be to give fifteen minutes to everyone asking for it, or a shrewd art collector’s simple rule might be to follow head, heart, and price tag.
Here are a few examples of simple rules to get your imagination started. For staffing: hire slow, fire fast. For eating: have desserts on weekends but not weekdays. For your budget: make coffee at home instead of buying a cup every day. For your social life: spend time with people who make you feel alive. For vacations: visit new places balanced with returning to old favorites. For your relationship with your partner: always (or never, depending on what works for you) resolve a disagreement before bed.
Most importantly, adopt the rules that work for you. In one of the more hilarious illustrations, when Gertrude Stein—novelist and mentor to Ernest Hemingway, F. Scott Fitzgerald, Henri Matisse, and others—discovered her beloved dog, Basket, had passed away, a friend suggested getting a dog of the exact same breed and calling it Basket. Pablo Picasso took the opposite view, arguing that getting the same dog would only remind them of the one they’d lost. Two conflicting simple rules. What did Stein do? For a while she tried to combine them, to have the same and not to have the same.” But in the end, Stein decided she wanted the same dog, and she did call him Basket. “I cannot say that the confusion between the old and the new has yet taken place,” she said.
3. Match the learning technique to the problem. If you face a technical problem, seek out the advice of experts. If you face a customer demand problem, talk to users. If you want to challenge your thinking, talk to contrarians. If you want to broaden your thinking, talk to those outside your discipline. If you tend to read books rather than engage in conversation, then do the uncomfortable thing and get out and talk to people. Change up your style depending on the problem.
4. Prioritize taking action over finding the best way. Many times, our projects depend less on figuring out the best way to do them and more on just getting started. Each step we take reveals more of the opportunity landscape. Although we can see the success of DJI in monetary terms, it’s worthwhile to remember that 3DR is not a failure—it continues to serve other market needs, including the community of drone enthusiasts.