Why big tech companies need so many people

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Hi friends,

Today I’d like to discuss the topic of large companies and why they need so many people. With the massive amount of tech layoffs recently, there’s been a common criticism that these large companies are staffed with legions of lazy people who do little to no work. As someone who has seen and been on both sides, I’d like to give my perspective on what’s happening.

So a little bit of background about me. I’m mainly known for my “Indie Hacking” where I work on 1-2 person businesses. I’ve built an online digital marketplace Flurly, a data infrastructure platform GraphJSON and most recently a GDPR compliant google analytics competitor Beam. However, most people don’t know I’ve also had experience climbing up the ladder of these large FANG companies.

Before I begin, I do want to acknowledge that these companies are far from efficient. It’s super easy to look at the tik tok videos of employees doing everything but work, the seeming lack of any product innovation on core product surfaces, etc. That’s all easy. Today I want to shed light on why this company building strategy is so prevalent and why it might actually be a rational one.

Before I begin, I want to set the stage. As ordinary individuals, we often think of money in their absolute terms. Is that carton of eggs worth 6 dollars? Is this new shiny keyboard worth 100 dollars? etc. We typically think about the value we get relative to how much we pay. For businesses, however, there is an additional dimension of how spending affects future cashflows. If you pay a seemingly exorbitant price for something, as long as the long term return of investment is good, it’s actually quite rational.

Let’s go through a few examples:

Infrastructure – Google/FB/Netflix/etc spend billions of dollars on infrastructure. They pay their best engineers tens of millions of dollars per year. Most people would argue these prices are unreasonable for the few thousands of lines of C++ code these engineers write. However, if you look at the externalities of the investment, it becomes quite obvious why. Better infrastructure means instead of paying Akamai X billions to run your CDN, you can run your own CDN for X/2 billions. Better infrastructure means you have undersea cables that enable lower latency video streaming such that users prefer your app over the up and coming app. Better infrastructure means your service is more resilient and reliable, giving you an edge against competitors and mitigating the risk of black swan events wiping out large parts of your future cash flows.

Experiments – If you have billions of users using your product per day, you can split those users into 100 different “universes”. Each of those universes can map to a team of 10-20 people, trying to optimize their own respective universe of people. Maybe 99 of those teams fail, but the gains from the win of the 1 team can be easily rolled out to the rest of the other 99 universes. If your friend or colleague was in one of the unlucky 99 teams, you may get the impression that they do very little or have very impact. But what you don’t see is the larger probabilistic game that is being played. Due to the sheer scale of these companies, having loads and loads of failed experiments is completely fine as long as you find the 1-2 that do work out.

Blockers – In poker there is a concept of a blocker. If I have an Ace, you have a lower probability of having an Ace. If I have 2 hearts, you have a lower probability of having a heart. In tech, where talent plays an outsized role in returns, one very rational strategy is to simply “block” talent from being competitive by paying them a lot of money to not start companies. If the best of the best are grinding away at the next big thing, that’s a huge existential risk to some of these large companies. Yahoo used to be huge and google used to be tiny. But what if before Larry and Sergey started Google, yahoo offered them a huge new grad offer of 5m / year. Perhaps instead of grinding away in their labs on backrub (the thing that became google), these young phd students would go on a vacation or play some video games instead. This alternate reality could have saved Yahoo. Indeed this is the exact “blocker” strategy is what many of today’s companies like Google/FB/etc are employing.

So that’s my 2c on this whole situation. It’s hard to argue with the financial performance of some of these companies that are criticized for having a culture of laziness and coasters. What do you think? Am I giving these companies too much credit? Or perhaps there is a method to the madness after all?

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