How Moonshots Are Like Enzymes
Enzymes are catalysts. They take something that’s stuck and make it unstuck, so it can reach a different state.
Many biological pathways need enzymes. For example, if you have Molecule C (let’s call him Clark) and Molecule S (let’s call him Superman), and you want Clark to morph into Superman, how do you make that happen? And why doesn’t Clark spontaneously transform into Superman, if Superman is a more powerful state?
The answer is that the process is thermodynamically unfavorable: it requires energy. Clark is stable and boring. He needs a boost to become Superman. If you graph it out, it might look like this:
See that big hill in the middle, standing between Clark and Superman? That’s a steep energy requirement. In other words, it takes a burst of energy for Clark to become Superman. If we need more Supermans, we’ll have to do something to help more Clarks get over the hill.
So over the hill is a desirable concept here.
In this analogy, yes. And how does Clark get over the hill? Enter enzymes.
Enzymes are keys made to fit a particular molecule. In our example, let’s say there’s an enzyme that’s perfectly adapted to Molecule C, aka Clark. It attaches to him, and the combined Molecule C + E (that’s Clark plus Enzyme) has different properties and therefore faces a much lower hill. (For a more scientific explanation of how this works, this Khan Academy video is fairly accessible.)
With the lower hill, it’s now way easier for Molecule C (Clark) to become Molecule S (Superman). So the population of Clarks gets smaller because more of them transform into Supermans. (Some Supermans also may transform back into Clarks, but let’s stick to the main point of this article.)
Let’s bring this around to risk management.
One step at a time. Let’s talk about moonshots. Moonshots are similar to enzymes in that they take an unlikely state and make it somewhat more likely—sometimes vastly more likely. The Manhattan Project was a moonshot in World War II. Without the project’s massive funding and coordinated action, scientists probably would not have succeeded. The goal was too difficult and expensive for the scientists to achieve on their own (without funding). The graph might look like this:
Similar to our Clark-to-Superman graph, eh? The goal (breakthrough/success) state enabled more efficient energy use (nuclear power is both controversial and efficient), but the path to that state was blocked by a steep hill. With massive government funding, it became feasible.
The Apollo space program was another example of a moonshot. In fact, the missions to launch rockets to the moon were the origin of the word “moonshot”! Any massive injection of funding toward an unlikely outcome—government grants, private R&D spending, venture capital funding—can be thought of as enabling a moonshot. Will it be enough to get over the hill? Maybe. Not all enzymes fit all molecules, and not all hills are the same height.
How about a more complex example?
Sure. Sometimes these graphs aren’t so straightforward. Let’s take Betsy, a high-school graduate. She needs tuition funding to go to college, and in this case Betsy can use loans or grants as her enzymes to get over the hump and onto the next stage of achievement as a college graduate. After that, she works for a while, but Betsy soon finds herself stuck. She’s not getting promoted, and she’s not exactly unhappy but is starting to feel dissatisfied and wonder, “What’s next?” But there’s a really big hill in front of her. Nothing she’s tried is working so far.
Betsy needs an enzyme to help her get over the hump, but until she finds the right enzyme, she’s stuck at a local equilibrium: a valley between two hills, aka the most thermodynamically stable place in her immediate vicinity. Here’s Betsy:
There are better places Betsy could get to, but the energy required is too great unless some catalyst comes along: maybe a mentor, maybe she goes to grad school, maybe she changes careers. But until then, she’s stuck. Local equilibria can feel comfortable or stifling, depending on goals, circumstances, and resources.
And the key to getting out of them and finding something even better? Enzymes. Moonshots. Catalysts. Things that disturb the status quo. Sometimes it can even be a lucky discovery. A moldy petri dish was the key that unlocked antibiotic therapy for billions of people. The penicillin mold—and Alexander Fleming’s recognition of it as something special—was the catalyst for his own scientific breakthrough and for humanity’s defeat of ancient scourges.
Local equilibria are also an interesting model for thinking about our own conceptions of the universe, society, and our place in it. Is capitalism a local equilibrium? Is the theory of gravity? Is democracy as we practice it? Maybe we haven’t found the true optimum state yet in many spheres.
Okaaaaaayyyyy, so the risk management piece.
Right. Risk management comes in because enzyme science is not a perfect analogy for messy human living. In the more ordered world of biology, a particular enzyme fits a particular molecule precisely. But in the messy world of everyday human living, most moonshots fail. We sometimes have to try a lot of different approaches before we find the perfect fit to get us over the next hill. That process can be frustrating, expensive, and time-consuming. And if we don’t figure it out quickly enough, we can get permanently stuck or even backslide to a less optimal state.
Risk management can help narrow down options and prioritize the ones most likely to succeed, increasing our chances of reaching the next local equilibrium. On the flip side, overzealous risk management can lead us to rule out strategies that would have worked, simply because they seem too far-fetched (which usually means “too distant from current practice”).
But allowing ourselves to explore beyond our usual boundaries can be hugely beneficial. The benefits aren’t limited to consciously planned experimentation, either. As John Sterman wrote in his excellent book Business Dynamics, “Random noise can also unfreeze systems that are stuck on local optima, sending them into a new neighborhood where the dynamics are quite different, and can determine which of many equally attractive paths a system takes….”
Organizations that become too hidebound and homogeneous lose the variation and flexibility that can increase the chances for innovative breakthroughs. That’s why, at the societal and organizational levels, a diversity of perspectives can be so important for identifying all reasonable strategies and then applying risk management to select the most promising moonshots.
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Extra, Extra!
Three links from the depths of my bookmark archives; think of these as tangential extras for curious readers:
1. He predicted the dark side of the Internet 30 years ago. Why did no one listen? - by Reed Albergotti in The Washington Post - being Cassandra is hard, because no one wants to hear it when it could make a difference.
2. Changing your diet could add up to 13 years to your life, study says - by Sandee LaMotte in CNN - even starting at age 60 can add 8 or 9 years.
3. This is why physicists suspect the Multiverse very likely exists - by Ethan Siegel in Big Think - why the multiverse is more likely than not.