"Grow or die, that's what I believed, no matter the situation." — Phil Knight

In the startup world, you’ll often hear that companies are either growing or slowly dying. There’s no in between. The metric varies — sales, monthly active users, whatever is core to the business. But the same principle applies to the capability of the group itself, and this is just as true in modern MLB front offices.

There are three meaningful ways an analytics department can grow:

• adding people, and thus more output

• expanding the scope of problems it owns

• leveraging new technology and tools to produce more or better output
  

These aren’t mutually exclusive — the best departments are doing all three. But they’re worth examining separately, because they each carry different risks and rewards.

Hiring

New people bring new ideas — new ways of thinking about old problems, and new problems worth thinking about. This effect compounds when the hire is either coming from another organization or operating at a senior level. There is real, underrated value in someone who has simply been there and done that — who can say with confidence, “when I was at XYZ, we solved it like this.” Maybe that method is outdated or doesn’t translate perfectly. But the knowledge is valuable, and the pattern-matching is faster than building from scratch.

The problem space an analytics department owns is also just enormous. Everything from pitcher injuries to Korean player projections to when to bunt to optimizing third base coach decisions on tag-up plays. Some of these are large efforts; some are niche. Not every problem warrants a dedicated person. But there is a baseline headcount below which you simply cannot cover the surface area.

And that surface area is only expanding. Biomechanics exploded. Teams now have pitching and hitting motion capture labs. Torpedo bats became a thing. Teams ship their own internal mobile apps. Other internal departments — player development, medical, strength and conditioning — are rightly asking for more analytical support, and the nature of that support has become significantly more sophisticated.

In the good ol’ Moneyball days, you could mostly ignore the S&C coach and they’d be frustrated, but not dangerous. Today it’s different. Because one thing that is assuredly worse than a frustrated S&C coach is a frustrated S&C coach with just enough programming knowledge and access to Claude.

Expanding Scope

Growing the scope of what the department owns is distinct from simply hiring more people to do existing work. This is about deliberately moving into adjacent problem spaces — building new capabilities rather than deepening existing ones.

Player development is a clear recent example. The analytics departments that stayed in their lane — draft models, game strategy, roster construction — ceded enormous ground to organizations that pushed into development earlier and more aggressively. Medical and strength and conditioning could be next. The teams treating those as purely human-judgment domains are leaving data on the table. There are many frontiers beyond this that are partially or barely explored.

The discipline here is prioritization. You can’t own everything, and trying to spreads the department too thin. The question isn’t should we expand but where should we expand next, and in what order.

New Tools & Technology

Computer vision models are genuinely useful — but not trivial to implement. Compute is now effectively free — but leveraging it well requires deliberate investment. Trajekt, new bat designs, mental skills platforms, vision training, sports nutrition, bone density testing for projecting young Latin players’ development — all of it is becoming more powerful, generating more signal, and creating more opportunity for the teams willing to engage with it seriously.

The risk is insularity. The tools that will matter most in five years may not be coming from inside baseball. They’re being built in other domains — medicine, defense, consumer tech — and the organizations that are scanning broadly and adapting quickly will have a structural edge over those that are only watching what other teams are doing.

The Cost of Standing Still

Sam Altman put it plainly: “Either you’re growing, or you’re slowly dying. Perfect equilibrium is rare.”

McKinsey’s research on high-growth companies makes a related point — that all companies need a second act. The ones that survive and thrive aren’t the ones that perfected their first act; they’re the ones that built the next thing before the first one peaked. The MLB landscape is littered with examples of this: organizations that were ahead of the curve on one wave and behind on the next, and others that have sustained relevance by continuing to reinvent what the analytics function looks like.

Being static isn’t neutral. If your competitors are growing their capabilities and you aren’t, your relative position is declining even if your absolute capability is flat. That’s the real teeth of “grow or die” — it’s not just about internal improvement, it’s about a competitive arms race with no finish line, even if the commissioner thinks otherwise.

The teams that commit to growth across these facets will be the ones continuing to succeed. Sadly, for many of the others, you won’t realize you’re dying until it’s too late.

I’m not bitter

I loved my time in the org. I met great people - players, coaches, data scientists, scouts, lunch ladies - more people than I can name. Many of the people are still my best friends. My experience was a great one - I’d do it all again.

The “bitter” actually is a nod to the great Richard Sutton’s Bitter Lesson. While there will inevitably be longer posts on this topic, it states briefly that instilling human knowledge into computational systems to help solve problems may help in the short term, but will inevitably be far surpassed by systems that effectively leverage search and learning. The bitterness is in what it takes away: the clever human insight, the hard-won intuition, displaced by scale. Yet for me, there’s something magical in that. The bitter lesson is the ingenuity in the system.

So what’s next?

If I were running an analytics department in an MLB front office today, this is how I’d try to do it. Some posts will be technical. Some will be about structure, culture, and organizations. Some will just be whatever I’m thinking about. My only goal is to get through 162 of these — and maybe earn a shot at some special nights in October, just like the rest of us.