It has become trendy for product managers to think of ourselves as capital allocators, our product plans as a product portfolio, to refer to our crazy ideas as ‘high beta’ to garner more support for it.
While the analogy with the investing world can serve as a useful mental model to some extent, it can get overdone as a thought-leadership gimmick. Let me pick my favorite one to dissect in this post:
Product plans should be anti portfolio theory.
All product teams should have ONE bet they are making, and put all their effort into making that successful. The fact of the matter is that a product team is not an entire company. A product team does not need to “survive” against all odds and hedge their risk. A product team needs to build a successful product. Even if that means failing after a while and having to start anew or go into maintenance mode or join other product teams that need to scale (that dreaded phrase ‘get reorg-ed’).
There are two reasons behind this assertion that are two sides of the same coin:
A lack of focus is the biggest killer of success. Most breakthroughs come from the extra 20% time, thinking about the problem in the shower, checking every edge case and then double-checking them all again, chasing down a hunch sparked by the 100th customer conversation. If there is a second project, a second priority marked as P0, there is no slack in the system that allows you to venture into the proverbial no man’s land where breakthroughs lie.
If increased focus is the ‘carrot’ side of the coin, looming failure is the ‘stick’ side. It is a crude metaphor, but nothing motivates like the fear of failure. As much as tech and the Silicon Valley mindset have accepted failure, risen above it even, the aftermath of failure is always painful and we are programmed to avoid pain.
The reason it is on the same coin as Focus is that the fear of failure intensifies focus.
Perhaps these two sides of the coin can be simply referred to as “Ability to focus” and “Need to focus”.
The Tyranny of Two
When a team has two projects, it feels like a hedge — if even one succeeds, we’ll hit our OKRs, make the customer happy, get a decent performance review. The probability of either one succeeding seems much greater than if there were only one project. In actuality however, the overall probability of success goes lower. “Wait, what?” you might exclaim now, “the math does not work like this.” Here is how it plays out:
By divorcing your own odds of success from the odds of success of the project, the project’s odds of success drop dramatically. This happens for both projects without you realizing it. When one project is seeming hard, likely to fail, it is easy and natural to shift focus to the other project. This is deadly, because it prevents you from venturing into no man’s land of “doing what it takes” to look for breakthroughs.
This is true for product pursuits that are charting new territory, which is often the nature of venture-backed products. And this is why “product bets” are different from “investment bets” —the success of two product bets stop being disjointed events the moment the same team becomes responsible for both.
Learning from great investors
I’ve found investing to be one of the most rigorous disciplines. The best investors have the best mental models for anything, really. The start of this post might have sounded like a jab at mental models from the investment world, but it was only a jab at the boundaries of extending an analogy! Two investors I respect greatly also make a case for honing in:
1. Stanley Druckenmiller
Stanley Druckenmiller is the founder of a hedge fund with $12B AUM. He learned the ropes under George Soros. He was recently interviewed by John Collison (founder of Stripe) at the Sohn Conference. Here’s a relevant snippet of their conversation, jump to 30:35 to listen (emphasis mine):
[John Collison]: Going back to your style, the thing I found very interesting in how you work is this … you know … your philosophy of put all your eggs in one basket and then watch this basket very carefully. And you’ve described how you just develop conviction three to four times a year and act based on that. And I’m curious if you could talk a little bit more about that like the spidey sense going off…
[Stanley Druckenmiller]: Yeah it’s completely contrary to what they teach in business school which is if you’re highly diversified you have less risk than if you’re highly concentrated. I don’t believe that at all. As an investor when I think most people get in the most trouble is when they have stale longs or stale shorts. When you’ve got 15-20 percent of your asset base or sometimes in macro positions I’ll have two or three hundred percent. Believe me they’re not getting stale and you have to have ruthless discipline and you’re coming in every day just to quote Andy Grove “you could not be more paranoid” and you’re constantly reevaluating. And I think it leads to an open mind. So, yeah, I would also say people ask me what I learned from George Soros. I thought when I went there I was going to learn what made the Yen and the Deutsche Mark go up and down and that kind of thing. No. What I learned was sizing is probably 70 or 80 percent of the equation. It’s not whether you’re right or wrong it’s how much you make when you’re right and how much you lose when you’re wrong.
2. Antonio Gracias
Antonio Gracias is the founder of Valor Equity Partners, and an early investor in Tesla and SpaceX. In his conversation with Patrick O’Shaughnessy (jump to 6:00 here) he talked about closing down options for execution (emphasis mine):
And then when we find a company where the strategy is pro-entropic, we think about, are the managers pro-entropic? The people running this company, are they really good at understanding chaos in the world? And the way we think about this, and I’ll differentiate again for resilience, is that a great pro-entropic thinker is someone who is able to keep their probability state, their Bayesian probability state, open on options. So you’re running a company. You always want to have optionality in what’s going to happen and how you’re going to build the company. They will be able to keep that probability state open to the appropriate moment and then close it for execution. Because great managers, great CEOs, great executives are great at strategy, and they’re great at keeping options open. But then when you watch what happens, moments will be like, “Nope, we’re going to close that probability set. We’re going to do that thing. We’re choosing one of those paths or maybe two of those paths. We can’t have 20 of them all the time.” If you have somebody who’s always open state, they don’t get anything done, and you’ve probably seen that too. We have too many ideas and we don’t go anywhere.
Executives that are really good at doing both of those things, opening the probability tree and then knowing when to close it and execute really hard and then reopen it; we define that as pro-entropic thinkers. And they rarely get knocked out of homeostasis. They’re resilient too. They’re usually really good at recovering, but they get knocked out of, I’d say their regular homeostasis by events less than someone who’s resilient because they’re already predicting it. They’ve got a probability tree they’re running already about what the world’s going to look like. And their inference is running against what the world’s going to look like. They’re making decisions about that, and they’re deciding when to toggle down and close off and when to reopen. It’s been really valuable to us.
The best investors value being able to find the one prize, and going after that with a singular effort.
Being “anti-portfolio” has three corollaries that create great product discipline for these teams.
1. Building conviction:
To pick a single path to follow from a slew of options requires a high degree of conviction. Conviction here doesn’t mean blind faith — it is an evidence-based confidence grounded in rigor of logic. This implies any necessary research and analysis upfront.
2. Sizing the upside:
As Druckenmiller says above, more important than being right or wrong is how much you make when you’re right and how much you lose when you’re wrong. With tech products, the downside is often capped, whereas the upside can range enormously. Picking a single bet demands upfront sizing — you want to make sure you’re taking the biggest swing.
3. Knowing the landscape:
Gracias says that great executives have an always-on probability tree of what the world is going to look like. This informs their singular bet, but equally importantly it informs (and improves) all other decisions they take, including anticipating failure and being resilient to it.
If you could solve only one problem, build only one feature, pick only one goal, what would it be?
(Thanks to Zach Perret who greatly influenced my thinking about this and came up with the ‘anti portfolio’ term)