Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform Industries
by Safi Bahcall
30 popular highlights from this book
Key Insights & Memorable Quotes
Below are the most popular and impactful highlights and quotes from Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform Industries:
When Jobs finally took over, gone was the dismissive attitude toward soldiers. In March 1998, he hired Tim Cook, known as the “Attila the Hun of inventory,” from Compaq to run operations.
When asked what it takes to win a Nobel Prize, Crick said, ‘Oh it’s very simple. My secret had been I know what to ignore.
As teams and companies grow larger, the stakes in outcome decrease while the perks of rank increase. When the two cross, the system snaps. Incentives begin encouraging behavior no one wants. Those same groups—with the same people—begin rejecting loonshots.
People may think of Endo and Folkman as great inventors, but arguably their greatest skill was investigating failure. They learned to separate False Fails from true fails.
When groups are small, for example, everyone’s stake in the outcome of the group project is high. At a small biotech, if the drug works, everyone will be a hero and a millionaire. If it fails, everyone will be looking for a job. The perks of rank—job titles or the increase in salary from being promoted—are small compared to those high stakes. As teams and companies grow larger, the stakes in outcome decrease while the perks of rank increase. When the two cross, the system snaps. Incentives begin encouraging behavior no one wants. Those same groups—with the same people—begin rejecting loonshots.
While the individual man is an insoluble puzzle, in the aggregate he becomes a mathematical certainty.
That message got through to Jobs. Jobs had a role in the system—he was a brilliant deal-maker and financier. It was Jobs, for example, who insisted on timing the Pixar IPO with the Toy Story release, and Jobs who negotiated the Pixar deals with Disney. But he was asked to stay out of the early feedback loop on films. The gravity of his presence could crush the delicate candor needed to nurture early-stage, fragile projects. On those occasions he was invited to help near-finished films, Jobs would preface his remarks: “I’m not a filmmaker. You can ignore everything I say.” Jobs had learned to mind the system, not manage the project.
Ferocious attention to scientific detail—or artistic vision or engineering design—is one tool, tailored to the phase, that motivates excellence among scientists, artists, or any type of creative.
champion is not the same as relinquishing attention to detail. The chief executive at Genentech for fourteen years, Art Levinson, was famous—and feared—for his insistence on scientific precision.
The collapse, for example, of IBM’s legendary 80-year-old hardware business in the 1990s sounds like a classic P-type story. New technology (personal computers) displaces old (mainframes) and wipes out incumbent (IBM). But it wasn’t. IBM, unlike all its mainframe competitors, mastered the new technology. Within three years of launching its first PC, in 1981, IBM achieved $5 billion in sales and the #1 position, with everyone else either far behind or out of the business entirely (Apple, Tandy, Commodore, DEC, Honeywell, Sperry, etc.). For decades, IBM dominated computers like Pan Am dominated international travel. Its $13 billion in sales in 1981 was more than its next seven competitors combined (the computer industry was referred to as “IBM and the Seven Dwarfs”). IBM jumped on the new PC like Trippe jumped on the new jet engines. IBM owned the computer world, so it outsourced two of the PC components, software and microprocessors, to two tiny companies: Microsoft and Intel. Microsoft had all of 32 employees. Intel desperately needed a cash infusion to survive. IBM soon discovered, however, that individual buyers care more about exchanging files with friends than the brand of their box. And to exchange files easily, what matters is the software and the microprocessor inside that box, not the logo of the company that assembled the box. IBM missed an S-type shift—a change in what customers care about. PC clones using Intel chips and Microsoft software drained IBM’s market share. In 1993, IBM lost $8.1 billion, its largest-ever loss. That year it let go over 100,000 employees, the largest layoff in corporate history. Ten years later, IBM sold what was left of its PC business to Lenovo. Today, the combined market value of Microsoft and Intel, the two tiny vendors IBM hired, is close to $1.5 trillion, more than ten times the value of IBM. IBM correctly anticipated a P-type loonshot and won the battle. But it missed a critical S-type loonshot, a software standard, and lost the war.
Let’s call it the Moses Trap: When ideas advance only at the pleasure of a holy leader—rather than the balanced exchange of ideas and feedback between soldiers in the field and creatives at the bench selecting loonshots on merit—that is exactly when teams and companies get trapped. The leader raises his staff and parts the seas to make way for the chosen loonshot. The dangerous virtuous cycle spins faster and faster: loonshot feeds franchise feeds bigger, faster, more. The all-powerful leader begins acting for love of loonshots rather than strength of strategy. And then the wheel turns one too many times.
Bush and Vail understood that the doomsday cycle is not inevitable, and that the best chance for sustainable, renewable creativity and growth comes from bringing an organization to the top-right quadrant: separate phases connected by a balanced, dynamic equilibrium.
Keeping the forces in balance is so difficult because loonshots and franchises follow such different paths. Surviving those journeys requires passionate, intensely committed people—with very different skills and values. Artists and soldiers.
I’ve always appreciated authors who explain their points simply, right up front. So here’s the argument in brief: 1. The most important breakthroughs come from loonshots, widely dismissed ideas whose champions are often written off as crazy. 2. Large groups of people are needed to translate those breakthroughs into technologies that win wars, products that save lives, or strategies that change industries. 3. Applying the science of phase transitions to the behavior of teams, companies, or any group with a mission provides practical rules for nurturing loonshots faster and better.
S-type loonshots are so difficult to spot and understand, even in hindsight, because they are so often masked by the complex behaviors of buyers, sellers, and markets. In science, complexities often mask deep truths: mountains of noise conceal a pebble of signal.
On the creative side, inventors (artists) often believe that their work should speak for itself. Most find any kind of promotion distasteful. On the business side, line managers (soldiers) don’t see the need for someone who doesn’t make or sell stuff—for someone whose job is simply to promote an idea internally. But great project champions are much more than promoters. They are bilingual specialists, fluent in both artist-speak and soldier-speak, who can bring the two sides together.
Peter Thiel and Ken Howery at Founders Fund, however, reached out to their friends behind the scenes at Friendster. They dug into why users were leaving the site. Like other users, Thiel and Howery knew that Friendster crashed often. They also knew that the team behind Friendster had received, and ignored, crucial advice on how to scale their site—how to transform a system built for a few thousand users into one that could support millions of users. They asked for and received a copy of Friendster’s data on user retention. They were stunned by how long users stayed with the site, despite the irritating crashes. They concluded that users weren’t leaving because social networks were weak business models, like clothing brands. They were leaving because of a software glitch. It was a False Fail. Thiel wrote Zuckerberg a check for $500,000. Eight years later, he sold most of his stake in Facebook for roughly a billion dollars.
Bush wrote, he learned “how not to fight a war.” In the high-stakes competition between weapons and counterweapons, the weak link was not the supply of new ideas. It was the transfer of those ideas to the field. Transfer requires trust and respect on both sides.
A failed outcome, for example, does not necessarily mean the decision or decision process behind it was bad. There are good decisions with bad outcomes. Those are intelligent risks, well taken, that didn’t play out. For example, if a lottery is paying out at 100 to 1, but only three tickets are sold, one of which will win, then yes, purchasing one of those three tickets is a good decision.
We can think of analyzing why a move is bad—why pawn-takes-bishop, for example, lost the game—as level 1 strategy, or outcome mindset. After a bad move costs him a game, however, Kasparov analyzes not just why the move was bad, but how he should change the decision process behind the move. In other words, how he decided on that move, in that moment, in the context of that opponent, and what that means for how he should change his decision-making and game-preparation routine in the future. Analyzing the decision process behind a move I’ll call level 2 strategy, or system mindset.
Evaluating decisions and outcomes separately is equally important in the opposite case: bad decisions may occasionally result in good outcomes.
At Pixar, Catmull probed both systems and processes, after both wins and stumbles.
Like Vannevar Bush, who insisted, as described in chapter 1, that he “made no technical contribution whatever to the war effort,” Catmull saw his job as minding the system rather than managing the projects.
In April 2000, three years after Steve Jobs returned to Apple, he invited Art Levinson to join his new board of directors. After Jobs passed away in 2011, Levinson replaced him as chairman of Apple.
Apple’s P-type loonshots, of course, transformed their industries: the iPod, the iPhone, and the iPad. But what ultimately made them so successful, aside from excellence in design and marketing (most, although not all, of the technologies inside had been invented by others), was an underlying S-type loonshot. It was a strategy that had been rejected by nearly all others in the industry: a closed ecosystem.
Apple’s P-type loonshots, of course, transformed their industries: the iPod, the iPhone, and the iPad. But what ultimately made them so successful, aside from excellence in design and marketing (most, although not all, of the technologies inside had been invented by others), was an underlying S-type loonshot. It was a strategy that had been rejected by nearly all others in the industry: a closed ecosystem. Many companies had tried, and failed, to impose a closed ecosystem on customers. IBM built a personal computer with a proprietary operating system called OS/2. Both the computer and the operating system disappeared. Analysts, observers, and industry experts concluded that a closed ecosystem could never work: customers wanted choice. Apple, while Jobs was exiled to NeXT, followed the advice of the analysts and experts. It opened its system, licensing out Macintosh software and architecture. Clones proliferated, just like Windows-based PCs. When Jobs returned to Apple, he insisted that the board agree to shut down the clones. It cost Apple over $100 million to cancel existing contracts at a time when it was desperately fighting bankruptcy. But that S-type loonshot, closing the ecosystem, drove the phenomenal rise of Apple’s products. The sex appeal of the new products lured customers in; the fence made it difficult to leave.
To understand what phase transitions tell us about nurturing loonshots more effectively, we need to know just two things about them: 1. At the heart of every phase transition is a tug-of-war between two competing forces. 2. Phase transitions are triggered when small shifts in system properties—for example, density or temperature—cause the balance between those two forces to change. That’s it.
Although all people are different, and all teams are different, what makes emergent properties and the phase transitions between them so interesting is that they are so predictable. We will see why organizations will always transform above a certain size, just like water will always freeze below a certain temperature,
In the early 1990s, a pair of physicists showed that below a critical density of cars on the highway, traffic flow is stable. Small disruptions—drivers tapping their brakes when squirrels run by—have no effect. Traffic engineers call that a smooth flow state. But above that threshold, traffic flow suddenly becomes unstable. Small disruptions grow exponentially. That’s a jammed flow state. The sudden change between smooth and jammed flow is a phase transition.
The terrific thing about the science of emergence is that once we understand a phase transition, we can begin to manage it. We can design stronger materials, build better highways, create safer forests—and engineer more innovative teams and companies.
