Reflections on Eleven “Laws” Driving Success in High Tech—A Blog Series

I downloaded a recent white paper from CB Insights that made the following claim in its headline:

What separates success from failure? These 11 laws contain some of the most influential ideas that the biggest tech companies use to run their operations, design business models, and build products.

I am irresistibly attracted to commenting on any list of the most influential ideas. Here is the list of the laws involved here:

1. Moore’s Law
2. Metcalfe’s Law
3. Law of Mobility
4. Gall’s Law
5. Law of Modularity
6. The 2-Pizza Rule
7. Conway’s Law
8. Yule’s Law of Complementarity
9. The Law of Shitty Clickthroughs
10. Zimmerman’s Law
11. Pareto Principle

As you can see, some are more familiar than others, but CB-Insights’ write-ups are quite clarifying, and there is plenty to learn and discuss under each of them. It’s too much, though, for one blog, so I am going to break things up into five separate postings, organized around the following topics:

1. Scalability (Moore’s Law, Metcalfe’s Law, Law of Mobility)
2. Complexity (Gall’s Law, Law of Modularity)
3. Organization (The 2-Pizza Rule, Conway’s Law)
4. Second-Order Effects (Yule’s Law of Complementarity, The Law of Shitty Clickthroughs, Zimmerman’s Law)
5. Prioritization (Pareto’s Law)

We’ll start with scalability.

Scalability in Tech: The Emergence of Exponential Growth

What has made high tech remarkable from its very inception is the early emergence of exponential growth. The initial driver behind this was Moore’s Law, based on an observation made by Gordon Moore in 1965 that the number of transistors on a chip would double every two years, while power consumption and cost to produce would remain relatively flat—a prediction that held true for over fifty years!

This combination of an exponential benefit tied to a linear investment (a log-linear relationship) meant that any semiconductor-enabled function that was scarce and expensive today would over time asymptotically approach becoming ubiquitous and free. Memory, compute, I/O bandwidth—at various points in high tech’s early days, each one was a gating item, and people created design rules to accommodate it as a bottleneck. But a few years later, those innovations would be leapfrogged because a later generation of chips had blown away the bottleneck, calling for a whole new, and radically different, set of design rules. It played hell with traditional ideas of sustainable competitive advantage, but it was a boon to anyone using computer systems for any purpose.

In sum, Moore’s Law drove exponential growth on the supply side, the ability for systems to deliver better and better performance for less and less cost. That’s one-half of the scaling equation. The other half is on the demand side. That’s where Metcalfe’s Law enters the picture. 

Metcalfe’s Law speaks to network effects. It says that the value of any network increases exponentially when its nodes increase linearly—at least, up to a saturation point. At the outset, this is a loss-leader proposition, because the value of a few nodes is less than the trouble it takes to connect them all up. That’s why most networked propositions never make it to scale. But if you can hang in there and get to critical mass, that becomes a game-changer.  Ubiquity creates exponential growth in demand for effectively identical transactions. That’s why early on in the days of the dot.com boom, the joke was that URL should stand for Ubiquity now, Revenue Later. Facebook, Uber, even Airbnb all used this playbook to extraordinary effect. Finally, once a network established critical mass, not only did its value economics attract new users, it also helped retain existing ones, because switching to a new network means having to build up those value economics all over again. 

So early on in the history of tech, Moore’s Law was driving exponential growth on the supply side while Metcalfe’s Law was doing the same on the demand side, and yet growth, while amazing, was not exponential. That is where the third and final leg of the scalability stool comes into play—mobility.

Now, let’s be clear, there is no Law of Mobility—but hey, sometimes you just have to cut us writers some slack! Because there is an underlying economic concept that explains the exponential impact of mobility on growth—transaction costs. Transaction costs represent an unavoidable tax on any transaction, meaning they create a value hurdle that must be cleared before the transaction is worth completing. This is why we no longer call for a taxi but instead summon Uber or Lyft. This is why we think twice about going to a store when we could buy the same product on Amazon. 

Most importantly, for our discussion, this is why exponential growth did not really take off as long as we had to be at a PC to access digital systems. Apple put the kibosh on that problem. Working in concert with cloud computing, WiFi, the Internet, and the Worldwide Web, the iPhone, along with its Android cousins, has made it possible for enterprises of any kind of size to transact with over two billion people worldwide, essentially for free. At the same time, it has empowered the end-user to access anything, anytime, anywhere. Your smartphone is an on-demand portal that transports you instantly anywhere in your world, connecting you to your colleagues, your family, and even to yourself. It is arguably the most indispensable device on the planet.

The net of all this is that the tech sector has been blessed with three exponential accelerators—Moore’s Law to scale the supply side, Metcalfe’s Law to scale the demand side, and the Law of Mobility to demolish transaction costs. This is what is driving the tornado of digital transformation, and it doesn’t look like it will subside anytime soon.

That’s what I think. What do you think?

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