How to Improve Weak Signal Judgment

Everyone collects weak signals now, but most of what they collect predicts nothing. A weak signal isn't a thing to spot. It's a prediction you make. And the edge goes to whoever bets on it while being wrong is still cheap.

So how do you become the one placing the bet, not the one still collecting all those reports? Let's get into it. A weak signal is a faint piece of evidence that points to something a customer will want before they can even name it. And before the market has priced it in.

It's faint because if it were loud, everyone would already be acting on it. It still needs to be deniable because you can always explain it away as noise. And most people do. It's that deniability is the whole point.

The moment it becomes undeniable that that is obvious evidence that's going to happen, the advantage is gone and the price has moved. Ten years ago, noticing was hard. You needed sources, a network, time to read widely, a feel for the edges of your industry. That was the moat.

I remember I would read literally 100 plus magazines a month. I've written about this and I've done a podcast episode on it. probably 15 years ago, if you want to go search back through the archive. And that was the moat of the time.

It isn't anymore. Every team has trend reports and three newsletters and an AI tool that services emerging behaviors on a regular schedule. The noticing got automated. What didn't get automated is the judgment about which signal is predicting structural change and which signals point to nothing real.

and the nerve to act early. Let me tell you a little background. I sat on Roche's, Roche the big medical company, on their innovation board for what's called Roche Diagnostics. This is all the test meters and et cetera.

I was the only outsider in the room, helping decide which ideas got funded. At one point, we took on diabetes care. Now, I'm not a diabetic. So I had Roche ship me every meter and every test strip combination they made.

I had literally hundreds of meters. And I picked my finger up to a dozen times a day to feel what their customers felt. Because my belief is you cannot innovate for a customer whose day you have not lived in. Skip that and everything you're trying to do is a guess.

Roche was a leader in blood glucose testing with its AccuCheck meters. And the math for their business looked obvious. Someone with type 1 diabetes tests around eight times a day, every day, for the rest of their life. A big stable business Type 2 diabetes was the smaller story per patient Those patient tested once maybe twice a day So each one looked worth less to Roche and we filed the category under less interesting.

We could already see type 2 climbing. We waited against the per patient math and explained it away. Now, then type 2 diabetes exploded into one of the fastest growing chronic conditions in the world. And the category stopped being about counting tests per day at all because the monitoring went continuous.

The always-on sensors that you see people wearing on their arms today. We had seen the early edge of both shifts. We even predicted them. We just couldn't move fast enough.

And the reason the one that kills most weak signals inside of the big company, and that is project approval and annual budgets are built to fund what's already proven not to chase something faint. Roast now did get there. AccuCheck, SmartGuide, it's real-time continuous monitor is on the market. But I just wish we had moved the moment we saw it instead of waiting for the next budget cycle to make it safe.

So how do you read a weak signal? We didn't miss the type 2 signal for lack of noticing. We noticed. We missed it on the three things that come after.

And these are the three you can train. The move starts once you got the signal you can't quite dismiss. And the skill is what to do with it. First up, you got to be able to tell the canary from the costume.

Now, the canary in the coal mine was used by coal miners to predict air quality. And it matters because the air would change. And if you saw the canary change, it told the coal miners, get out of that space. It signals something structural, a shift in the environment that affects everyone in it, whether they've noticed it yet or not.

A costume is the opposite. A few people put it on, it's striking, it spreads for a season, then they take it off and the room is exactly as it was. On day one, the two looked identical. A behavior appears.

It's unusual. It's spreading. The only question that matters is whether it predicts a change in the customers cannot reverse. Once they start down that change, they will not come back.

Or is this a moment that will just pass? It's a fad. Now, back in 2018, I wrote about telling a trend from a fad, and the test still holds. Ask what need the behavior reveals.

Type 2 was a canary and we read it as a costume because we counted testing frequency instead of the need underneath it That need millions of people learning to manage a lifestyle disease only grew The discipline is refusing to let the size of the spike tell you which one you looking at. Costumes spike too, sometimes even higher because everybody hops on the bandwagon, and follow the leader, you're reading for the need, not the noise. The next is read the window. A signal's window is short.

Too early and you can't tell from the noise and you waste resources chasing ghosts. Too late, it's obvious, everyone sees it, and the advantage is already priced in. The value lives in that narrow gap in between. Waiting for more evidence feels like better judgment.

But the evidence that finally convinces you has already reached your competitors. Certainty and advantage move in opposite directions. So by the time you're sure, sure is just another word for you're too late. The question isn't whether the signal is real or yet.

It's how much longer you can be the only one taking it seriously. Waiting is not your advantage. But then that gets you into the third step. Act while being wrong is still cheap.

This is the move that separates the people who read signals from those who collect them. And almost nobody is willing to make it. A signal you predict but never act on is still watching. One of my quotes that I say all the time, and you're probably tired of hearing it, ideas without execution as a hobby.

And I don't know about you, but I'm not in the hobby business. The whole value of an early signal is that you move before it's confirmed. Wait for proof and you're waiting too long. So you have to act on thin evidence and you got to get comfortable with this.

And let's face it, thin evidence is wrong a lot, which means you will be wrong a lot and that's fine. But people hear that and they freeze because they picture the cost of being wrong as that big failed product launch or that wasted year or the budget burned on a gas. People call that caution. It isn't.

The skill is structuring the bet so that being wrong is cheap. You don't commit a product line to a deniable signal. You commit a prototype, a landing page, one conversation with 10 customers, a two-week test that costs you a sprint and buys you information you cannot get any other way. Being early and wrong should cost you about a week.

Being early and right should put you a year ahead of your competitors. You're not betting on being right. You're buying the option to be right. cheap enough that being wrong doesn hurt and you scale up only as the signal firms up That why the noticing crowd never gets here Noticing carries no risk so it never builds the muscle for cheap commitment.

They watch, they report, they wait for certainty, and they call that foresight. It's the safe choice and its value is zero. So let's talk about how do you practice this? How do you do something with this to actually exercise it?

So pick one behavior you've been dismissing as noise in your customers, in your product idea that you're working on, on a blank idea, come up with something. But what's that one behavior you've been dismissing as noise? something you've seen more than once. Maybe it's your customers, your kids, your own habits that you've waved off because it looked too small or too strange to matter.

Then run it through the three moves. Is it a canary or a costume? What need is the behavior revealing? A need the person can't go back from or a novelty they'll sit down next season?

Write the answer in one sentence. If you can't, you don't understand the signal yet. Step two, find the window. How much longer does this stay deniable?

Who else is likely seeing it? If the honest answer is it already feels obvious, pick a different signal. You're late on that one. Step three, design the cheap bet.

What's the smallest thing you could do this month to test whether you're right? Where being wrong costs you a week, being right puts you ahead. Name the bet. Name the cost.

Name what you're going to learn from this. Then do this one real signal and you'll feel the difference between collecting signals and using them. Collecting is comfortable. Using one costs you a decision.

If you want a sparring partner for that, I've built one for you. From Signal to Bet is a digital download. It's a set of AI prompts that run a signal through these same three moves and argues with you for you to read at each one. It's free over at innovation.

tools or down in the link below. The exercise teaches you the moves. The prompts makes you defend them. This is your partner to argue against.

The signal was always there for you and for everyone reading the same reports you read. The edge was never in seeing it. It was in what you were willing to do before it was safe to do anything at all. Get good at that and you stop reacting to the future and you start arriving early.

We'll see you next week. Bye bye.