Performance drives success, but when performance can’t be measured, networks drive success
A few years ago, around 2018 or 2019, I walked into a bookstore and found a book called The Formula: The Universal Laws of Success by Albert-László Barabási. What caught my attention wasn’t just the title, but the tagline: “The Science Behind Why People Succeed or Fail.”
I believe in science (and Islam as well), even though I’m not a scientist, and I believe that the universe runs on patterns. So I found myself wondering: if success feels abstract and vague, can it still be studied, mapped, and distilled into principles we can apply across different areas of life?
Back then, I only took a photo of the cover and told myself I’d read the preview on Kindle.
I didn’t buy it.
Fast forward to today: I reinstalled Kindle to browse the catalog, and I noticed the book was still bookmarked. I reread the preview, and this time I finally bought it.
It’s fascinating. Barabási and his team analyzed massive datasets and distilled recurring patterns into five laws. The value, at least for me, is simple: we get frameworks without having to do the heavy lifting ourselves.
These five laws are:
1. Performance drives success, but when performance can’t be measured, networks drive success.
2. Performance is bounded, but success is unbounded.
3. Previous success x fitness = future success.
4. While team success requires diversity and balance, a single individual will receive credit for the group’s performance.
5. With persistence, success can come anytime.
In this article, I’ll focus only on the First Law. We’ll cover the rest in future articles.
The First Law
Performance drives success, but when performance can’t be measured, networks drive success.
Here’s the idea in plain language: when performance is measurable, success tends to follow performance. But when performance is hard to measure, people rely on other signals, and networks become the engine of success.
When performance is measurable, performance tends to drive success
In fields with clear metrics, it’s easier for others to agree on what “good” looks like. Think of competitive sports, exams, or sales targets. The system may still be imperfect, but the scoreboard makes performance visible.
Barabási and his team examined enormous data from the Association of Tennis Professionals (ATP). A player’s performance can be measured through match outcomes, rankings, and points. For “success,” they used Wikipedia page views as a proxy for public attention and visibility, not as a perfect definition of success itself.
The pattern was striking: when a player wins a major tournament, their Wikipedia traffic spikes. When a player’s performance drops due to injury or poor results, attention tends to decline. In measurable fields, visibility often follows the results.
When performance is subjective, networks drive success
But what about fields where quality is difficult to measure?
Art is a good example. People can disagree strongly about which artwork is “better,” and there’s no universal metric to settle it. In these contexts, Barabási argues that networks take over. Reputation, endorsements, gatekeepers, and institutional context become the signals people use to decide what is valuable.
He references research and data from Magnus Resch, an art-market analyst who built an app called Magnus to help art lovers recognize and price artworks in galleries and museums. One key insight is that galleries and museums form connected circles, almost like an ecosystem.
If an artist starts by exhibiting in a certain “tier” of galleries, their work often circulates within that same network. That can be limiting: the work keeps rotating in the same circle and struggles to break into higher-tier spaces. But once the artist manages to enter a better-connected or higher-status gallery, the network itself can accelerate recognition. The work may be similar, but its placement changes how it is perceived and valued.
This also helps explain why some artworks receive mind-blowing price tags. Often, it’s not only the object that drives the price, but the network and context around it: the artist’s reputation, who collects it, which institutions endorse it, and how the story is framed. The artwork becomes a social signal, not just an object.
Most careers sit in between
Most professions aren’t purely performance-based like tennis, or purely network-driven like the art market. They sit somewhere in between.
Performance exists, but it’s not always visible from the outside. A teacher can be excellent, a public servant can be effective, or a designer can be world-class, yet outsiders may not have a clear way to measure their work. When performance is partly hidden, networks become the bridge between real work and recognition.
This is why someone with strong results can remain unnoticed, while someone else rises quickly. It’s not always because one is better, but because one person’s performance is easier to see, easier to explain, and easier to circulate through the right circles.
What should we do with this?
The takeaway isn’t “performance doesn’t matter,” and it isn’t “connections are everything.” The point is to harness both drivers, because life is rarely played on a single board.
A simple way to apply the First Law:
- Build performance that can be shown. Create visible proof: outcomes, metrics, a portfolio, a record of results.
- Build networks that can carry your performance. Place yourself in circles that understand quality and can vouch for it.
- Make your value easy to repeat. If people can’t describe what you do well in one sentence, they can’t spread it.
- Protect trust by delivering consistently. Networks amplify, but reliability compounds.
In other words, it helps if your network knows how excellent you are, because they will be the ones who spread the word. And if you already have a network, you still need to back it up with real delivery.
Performance gives you substance. Networks give you reach.
In the real world, you often need both.
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