🧠 Deep dive — the complete guide to learning from failure
Failure isn't inherently educational. It's our approach to failure that makes it something we can learn from.
On January 17th, I’m co-hosting a 90-minute masterclass on how to design products that get customers to beat down your door.
It’s called The Startup Product Playbook. Grab your seat here!
Failures are like uncut diamonds: their true value is revealed only through a meticulous process of intentional analysis.
This statement challenges an entrepreneurial cliché:
failure ＝ data
Because it's wrong. So, in this issue, I’m going to share how taking a deliberate approach to failure will ensure you always learn from it.
Let’s dive deep 👇
Most people see failure as a setback, but the insightful few view it as a rich, yet untapped, data source.
“Failure is data,” they say.
But that’s only if you know how to use failure.
While it’s valuable to know that you failed, ceasing the analysis at that step misses out on a big opportunity. Because, contrary to popular belief, the failure itself teaches us little.
In other words:
Failure isn’t data by default.
It's a common retort to unpleasant news (I’ve certainly said it before) and it comes from the truth that we can only learn by being wrong before being right. Otherwise, when we were right the whole time, and there was nothing for us to learn.
My honest opinion? Failure is amazing.
It is the foundation of the science upon which this computer was developed, as well as the advances in medicine and healthcare that afford me entering my late thirties with my best years still ahead.
Science is returning us to the Moon and taking us to Mars.
But let’s not romanticise it: failure is uncomfortable, personal, & often public. And, you know what? It should sting, and we should try to avoid it.
Failing sucks!
Yet, it’s the only way we can learn.
Unfortunately, we don’t usually learn much from our failures.
It’s not just due to cognitive dissonance, wishful thinking, and post-hoc rationalisations (thought they certainly play a role in the psychology of decision-making).
Mostly, it’s because data is retrospective:
We get far better data — both in quantity and in quality — if we ask a good question in advance, than we do if we just try to interpret a negative outcome in hindsight.
In other words, you getter data if you think about failure as “failed experiments”, and therefore design your behaviour as experimentation.
Paradoxically, designing for failure also means we fail less!
Bonus: it’s a pretty straightforward process.
Here are three steps you can follow to always learn from negative outcomes, use failure as a ladder of progress, and fail less often.
Step 1: Start with a question.
It’s the simplest thing you can do, but we rarely do it.
When most founders want to try something — a marketing campaign, a social post, a message on a website hero — they do it intending only to “see what happens”.
“I think this value prop will resonate, so let’s run an ad and see what happens,” you say.
The problem with seeing what happens is that you’ll always succeed: in seeing what happens. But you’ll never learn anything, because, unintentionally, you took failure off the table.
You’ll get a number back, but you won’t know what it means, nor how to interpret the result. Is it a good result or a bad result?
“Eh… I’ll just go with my gut.” 💀
The alternative is to start with a question. A good question. And asking a good question requires specificity:
What’s the one thing you’re testing?
What are the details: who, what, where, how, and when?
What does failure look like specifically?
Science calls it an hypothesis: it’s discrete, specific, and falsifiable.
It produces unambiguous results — it’s crystal clear if you were right or wrong. There’s no room for grey.
If you set no bar, you can never miss it, and you never have to face the failure. Before setting out to do anything, write down exactly what success looks like, and allow failure to take place.
Then, once you have a failed hypothesis:
Step 2: Reflect on the failure.
This part’s simple, but hard: ask, “what does this mean?”
In a literal sense, the failure is that whatever our expectation was turned out to be incorrect. But to learn from that miss, we need to dig deeper:
Why did we get the result we did?
How big of a deal is the deviation from expectation?
What does the change in expectation affect?
We often won’t know the answers to these questions, but the next experiment we want to run — the next question we want to ask — often comes from this reflection.
Let’s break it down further using an example.
Any smart founder has a consistently-updated mental model of their startup. Once you get beyond the idea stage, it probably follows the “pirate metrics” — acquisition, activation, revenue, retention, and referral. AARRR.
Aarrr! Like a pirate, you see. 🏴☠️
You have certain metrics for each of those five categories, which tell you:
In the early stages, whether this cockamamie scheme pencils out and is worth our time;
In the growth stages, whether this business is working, and we’re hitting our targets.
When you run an experiment in any of those categories, and then find out your model was wrong, you have new data. You know what the number “actually is”, at least as of the last experiment.
You can then plug the new, validated number into the model and see how it affects things:
Is this still a business worth pursuing?
Is this a pivot moment, or a persevere moment?
Is there an experiment we can run to try to get a better number?
etc.
I’ll pause there, because pirate metrics and the evaluation thereof are the subject of next week’s deep dive, so make sure you’re subscribed:
To recap: it’s not enough to just experiment and fail.
If you don’t understand what the failure means, you can’t do anything about it.
Speaking of doing something about it…
Step 3: Transform the data into a change in behaviour.
This is the most important step!
But it’s also the part too many founders skip: what are you going to do differently?
Do we pivot or persevere?
Do we try something new to achieve the goal?
Do we set a different goal?
Do we change the path we’re on entirely?
If you don’t do anything differently after failing, there’s no upside to failure! You’re jut choosing to fail the same way again in the future. Doh!
Bottom line?
When it comes to trying new things, never just “see what happens”, because you’ll always succeed… in seeing what happens.
But you’ll never learn anything.
Let's bubble back up.
This process might sound familiar: it’s build-measure-learn. But it’s also a process with many AKAs:
ideate, experiment, data;
hypothesise, prototype, test, learn;
empathise, define, ideate, prototype, test;
observe, think, hypothesise, experiment, reflect;
etc.
But don’t overcomplicate it. It’s simple:
Step 1: Ask a question and run an experiment.
Step 2: Ask “what does this mean”?
Step 3: Transform the data into action.
And, honestly? That’s all entrepreneurship is.
And that’ll do it for this deep dive. As always, thanks for reading. Have a fantastic weekend, and I’ll see you next week!
—jdm
PS: If you enjoyed reading this, please take a moment to share it with a friend. I’d be very flattered! It takes you only about 6 seconds to share, and it takes me a lot longer to write it. 😅