last updated: July 12, 2020
Defining human value, introducing the SCARF framework, and the inevitable direction of “progress”
Since I watched my first Rory Sutherland video in middle school, I’ve been fascinated by human irrationality. There are brilliant ideas everywhere, but Sutherland is one of the few people that can consistently provide stories of counter-intuitive solutions that created human value.
One of his famous examples is that of the EuroStar, linking London to Paris. Authorities asked a group of engineers to improve the journey. Six billion pounds and several years later, the train-ride was shortened by 40 minutes, and riders weren’t that much happier. Rory’s suggestion? For 0.01% of the cost, install free Wi-Fi. Maybe even, with some of the remaining budget, hire all the world’s top supermodels to hand out free Chateau Petrus during the ride.
Another example is the London Tube (read, subway), which was struggling with mediocre customer satisfaction. Faster trains? No effect. Prettier stations? No effect. But one thing sky-rocketed customer ratings: small panels at every platform, that showed how many minutes away the next train was.
Sutherland’s point is simple - there are so many ways to unlock human value, and most are cheaper and faster than solving engineering problems.
Defining Human Value
But how to delineate something so broad? Economic value is defined as the difference between how much people are willing to pay for something and how much that something costs to make. But that’s hard to figure out, because people aren’t always honest (or sure) about how much they would pay, until faced with the choice. And sometimes, if enough people are willing to pay for something, companies will do an incredible job of figuring out how to make it cost less. And the key question remains: what will people pay for?
I think that, to understand human value, a simpler definition needs to start with the first word, not the second. And humans, though exactly unpredictable, still follow a pretty straightforward archetype. At a very simple level, we try to recreate positive emotion, and avoid negative emotion. So, I’ll define human value as anything that increases human ‘joy’ and decreases human ‘misery.’ Obviously, I use both of these things loosely, but it puts a firm foundation for our understanding of value - a foundation of emotion. Let me rephrase: the single greatest driver of human value is human emotion.
What does this mean?
Well, among other things, it means the landscape of value is entirely found within the human experience, instead of in different industries. It also means that the direction of progress isn’t defined by technological innovation, but by better emotion (which isn’t always a positive-sum game - but more on this later). Scientific discovery may be exponential, but human value is cyclical.
The SCARF model
It also means that value creation might be a lot simpler than we think. Human joy usually operates along similar vectors. For example, at an individual level, we are subject to powerful instincts that evolved to keep us alive (e.g. loving fatty foods, which is especially dangerous now that we’re no longer fighting to survive in the plains). But we are inherently social creatures, so I’ll use that to narrow my scope. Here, one (admittedly incomplete) framework is SCARF: status, certainty, autonomy, relatedness, and fairness. Status, certainty, and fairness were pretty straightforward for me. Autonomy is the feeling that we have a choice in a given decision (apparently we hate feeling forced to do things). And relatedness is the choice of deciding whether someone is ‘in’ or ‘out’ of a social group (essentially our tribal instincts, mapped to modern behavior).
Each one of these creates a spectrum, where one side is threat, and the other is reward. And put simply, we are always trying to move away from the thread side, and toward the reward side.
Back to the positive sum conversation, we see that some of these vectors are infinite quantities, like certainty. Others, however, are competitive, like status. This means we will never quite reach an equilibrium, so we will be creating (and destroying) value for as long as our species survives.
But the SCARF framework is incredibly useful. If you want to build anything consumer-facing, just pick a random subject area and figure out how to increase one or more of those qualities. It’s a simple equation, with the potential to beat the thousands of bright engineering minds at FAANG. Don’t believe me? Check this out:
The Pizza Miracle
Who would have guessed that Domino’s would beat every tech stock over a decade! Well, except for Netflix, but they’re a great SCARF company, too (more on them a minute), and pizza and Netflix may also be linked. But why Domino’s? Sure, everyone loves pizza, but there are lots of other pizza companies out there - Pizza Hut, Papa John’s, Little Caesar’s… And none of them have returned anything near good ‘ole Domino’s.
Of course, there are many explanations for this outsized success, but the most convincing (and most popular) one started in 1973 when they made a seemingly innocuous promise: if a pizza wasn’t delivered in 30 minutes or less, it was free. Why did this matter? Because it addresses the C of scarf: no one used to know exactly how long a pizza order would take, but the 30 minute ceiling provided at least some certainty. Then, after a low point in the late 2000s (which perfectly set the context for a comeback story), Domino’s started letting customers order in the most convenient way possible (Twitter, Amazon’s Alexa, and even Apple Watch) - increasing autonomy.
Their victory was only assured in 2017, when they released their app. Most importantly, the app would show you what stage your order was at: awaiting processing, in the oven, or on the way. Remember Rory Sutherland’s example of the London Tube? Turns out, waiting is incredibly painful when you don’t know how long you’ll be waiting, aka high uncertainty. Someone had the key insight that people don’t actually mind waiting, as long as they know how long the wait is. And just like the London Tube, customer satisfaction sky-rocketed, and everyone started ordering pizza.
Once you see it in Domino’s, you see it everywhere. Uber is convenient, sure. But it also lets you know exactly how long your driver will need to reach you (of course, they alway end up taking a wrong turn, so the time is never accurate, but that’s not what we care about). Why do people enjoy coding? Because your feedback loop is immediate - as soon as it compiles, you get a pretty good idea if what you made works or not. And while it compiles, you have the holy grail of digital uncertainty - the progress bar.
We haven’t even tried the other parts of SCARF. Let’s start with status. What platforms make it easier for you to advertise your status? Facebook is one, LinkedIn is another. Also the entire luxury goods industry (a $1.3T global market). What about autonomy? Uber lets you decide if you want to pay a little, a moderate amount, or a lot for your ride (UberShare, Uber X, and Uber Black). For another uncertainty example: Netflix, which lowers the DVD delivery-time to nothing. Relatedness? Again, look at pretty much any social media platform, from the upvote button to seeing common friends. Fairness? The entire auction system, old as it is, is set up so that neither the seller nor the buyer feels cheated after a purchase.
It’s an interrelated, multi-dimensional space. Consider that we also want certainty in our perception of fairness, and autonomy in how we reach this certainty, and relatedness in how we go about this. But let’s not take it too deep.
I am using tech companies as examples to demonstrate a simple point: their main value proposition is not actually found in the tech, but in how they use tech to target human emotion. And most tech companies are especially good at the certainty bit. Through this lens, the Information Age should really be renamed the Age of Uncertainty Reduction, especially because information theory defines information as the reduction in uncertainty. (This is such an important idea that I’ll probably write up a separate post to go through its implications).
But this is really good news, because it means there is still so much value to be unlocked. Starting a company doesn’t need to start with a massive technological breakthrough - most of the tools are already available to make some headway in other industries. And any industry that involves people at some point (read, any industry) will keep gravitating towards more SCARF. In a way, this helps you answer the question of what problems are worth solving, by trying to predict which solutions will be chosen by the people (read, given permission to exist through the channel of profit).
So, if it’s time to build, I won’t answer what we should be building. But I will answer what we will be building - or at least, of what we build, what will survive.