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Knowing how to spot trends as a leader before they hit everyone else's radar is not about having better information. It's about looking in different places.

Most leaders who feel caught off guard are not inattentive. They're focused on the center of their industry, which means they're getting the same information at the same time as everyone else. By the time something shows up in your core industry news, it's not a signal. It's a headline. You've already missed the early window.

In this episode, I walk you through three specific shifts that help leaders see what's coming before it becomes obvious. I use real examples, including AI signals that were hiding in plain sight for decades: bank fraud detection, Netflix recommendations, autocomplete in search. And I share one of my favorite examples of an energy company that sent its research and development team to a cardiology conference to solve a problem with valves. None of these signals were obscure. Leaders who spotted them early just knew where to look, and they were asking different questions.

The three shifts I break down: from confirmation to curiosity, from the center to the periphery, and from certainty to early action. Each shift comes with a question to carry with you and a practical way to build the habit. I also give you a 20-minute weekly assignment to start developing real strategic foresight, no matter where you sit on the org chart.

Listen and catch the full episode here or wherever you listen to podcasts. You can also watch it and replay it on my YouTube channel, JanelAndersonPhD.

Why do some leaders always seem to be able to see what's coming before everyone else. Is that a personality thing? Is it something that you're born with, or is it actually something you can develop? This question comes up more and more frequently these days because things are changing so fast all the time, and anyone, whether you have a position of formal authority or not knows that getting caught off guard feels terrible, and in hindsight, you can almost always catch the signs that were there all along.

And it's not that you weren't paying attention. Most often, it's that you were paying attention, but just not to the things that were changing. You were either too busy with everything else that was going on to notice, or you were focused on like putting out some fire, some big problem that had just cropped up, and so you were looking, but you were looking in the wrong places. Now we're talking today about how to spot trends more easily, how to catch on to the hidden signals that seem hidden, but really they're not, as you'll come to see.

And this will help you spot trends earlier. It will help you be more strategic in your role, no matter if you are a person who leads people or just a leader from the side in your organization. And you will be far less likely to say, I keep getting blindsided by things I should have seen coming, or how come I didn't know about this? I feel like I'm always catching up.

Okay, you're going to be much less likely to be saying those things to yourself if you put into play the things that we talk about in this episode. Now, most people assume that great leaders are better predictors of the future, they are not. They are better observers. They are paying attention to the things in the periphery, the things that are adjacent to the things that they need to be working on, and that adjacency can come up a number of different ways.

It can be in adjacent markets. It can be in adjacent product lines. It could be in oh an adjacency that seems like like it came out of left field. We'll talk about some of these as we as we go along.

But the more you're able to pay attention and cast a wide net, the better you are at spotting those signals, drawing drawing the lines between the dots and connecting those dots, and then being ready for what comes next. Because as we know, it's all always changing. So the popular image of leadership is someone standing in the front of the room with a grand vision for the future, but the reality is, leaders who navigate uncertainty well do something much less glamorous. They notice small things better and earlier than everyone else.

They make a concerted effort as to what they pay attention to. Could be odd customer behaviors, seemingly unrelated headlines, tensions on their team, technology shifts, or things that don't work. Changes in what people value. Good leaders, excellent leaders, spot these patterns before those patterns become obvious to everybody else, and that early noticing is what looks like being able to predict the future from the outside.

The problem is there's never a lack of signals. In fact, we've got so much information coming at us so fast, all the time, every day. It's hard to know what to pay attention to. So the signals are always there.

The problem is taking a step back, taking a beat, slowing down a second, and looking more widely, casting a wider net in where you're looking. Now I talk about this in a couple of my keynotes, but more most specifically in the keynote called "Expect the Unexpected. If you're spotting the signals early, you are much more inclined to be able to connect the dots, put things together, and figure out what comes next or what might come next. You might not exactly know, but you'd be in a much better position to have a few theories, one of which might be right, or a combination of some of them might be right.

So again, the problem is never a lack of signals. The problem is where most leaders are looking. Now, let's take AI as an example. Some people feel that with the advent of the large language models like ChatGPT, Perplexity, Gemini, and so on, that all of that just came out of nowhere.

But the signals were there all along. Let me just give you a handful of ideas of signals that were there all along. Remember autocomplete? You probably use it all the time, almost every day.

In fact, Microsoft Word now does autocomplete sometimes with entire phrases as you're typing a document. Your email is also auto completing, but just let's go back before auto complete was in our documents. It was in search, and so a machine was finishing your sentences. A machine was finishing your thought as you first started to type something like, "What's the diagnosis for? and then it fills in the blank of like the top searches that somebody has been looking for a diagnosis for, and sometimes these are really really funny too because you can just type the first few words and then up come 10 different examples of what other people have been searching for.

Oftentimes they're not what you're searching for, but still, that autocomplete, which has been around since the early days of Google, that long, that is a machine finishing your sentence, trained on patterned data for millions of users conducting searches. That is AI. That is artificial intelligence, just baked right into a product you've been using forever. Another example: banking fraud detection.

How many of you have had an opportunity to experience your bank calls you, and they've detected fraud on your account, or maybe you have a credit card that doesn't work, and you're like, why doesn't this work? Maybe you're in a different state. Maybe you're in a different country. Maybe you purchased something in a pattern that was different from what you usually purchase or where you purchase.

Again, it could be the zip code, it could be the type of purchase that you made. Now, most of us deeply appreciate when our bank is trying to detect fraud on our behalf. Now, I know it does get a little bit irritating when you're trying to use that credit card. Maybe it's the only one you've got with you, and it's got a freeze on it because the fraud has been detected on it.

But again, there is no human mining your data, looking at every transaction. That is all done algorithmically, and that is done because your bank has analyzed millions upon millions, perhaps billions upon billions of transactions, and compared them with your typical behavior, and it detects an anomaly. Again, that's AI, and that's been around since the 1990 s. All right, here let's take one more that maybe hits a little closer to home: Netflix's recommendations.

Okay, and this could be any streaming service, but Netflix is, of course, of course, the most popular and the first one who was doing this. So a system, Netflix's algorithm, and Netflix's system rather is watching what you watched all the way to the end, or if it was a series, what you watched the next and the next and the next of, and if you made it to the end of that movie or the end of that series or the end of that season, Netflix knows that you like that, and so Netflix is going to serve up. If you liked this, you'll probably like this. And what's behind all of that?

An algorithm that is mining the data of you as the user, you as the watcher, and benchmarking that against all of the other user data that it has. So those examples of AI have been around for literally decades. None of these were hidden. They were in everyone's hands.

They were on everyone's screens. We were all using them, and most people experienced them as a convenience. Now, a small number of leaders look at them and they ask, "What does this tell me about where things are going? If my bank has this much intelligence about me, what if we put that information?

What if we put that intelligence into the hands of individuals instead of just banking institutions monitoring our banking behavior, or entertainment institutions monitoring our entertainment experiences. Okay, so when we start to notice the patterns, and then think about, well, if that's possible, what else might be possible? And that's the difference. That's the difference between a leader who can spot those trends, a leader who is future ready, a leader who can lead through uncertainty more effectively?

They're not smarter. They're not better connected. They're not more intelligent. They're just asking different questions, and they're paying closer attention to what might matter.

Okay, now there are three shifts that I want you to make so that you can be more like that. You can be more equipped to spot trends early. You can be more equipped to be a strategic leader with foresight. Again, whether you are leading from the side or leading from a higher place on the organizational chart.

So we're going to go through those three shifts in the rest of the episode, and then I'm going to give you an assignment because you know I always do. There is some work for you to do based on this episode. All right, shift number one is to move from confirmation to curiosity. So most leaders tend to confirm what they already think and what they already know, they're looking for, and sometimes you've heard it called confirmation bias.

We're looking for all the things that support what we already believe to be true, but great leaders are ready to be surprised. Same news cycle, completely different intake. Okay, so we're all looking at the same things, but great leaders are looking at it, going like, hmm, where is this matching this, or where do I see some similarities even across vastly different domains, and starting to plug those things together. Now, looking for confirmation feels productive, and it makes you feel confident in what you know.

Curiosity, on the other hand, feels insufficient. Curiosity feels a little unnerving because when you start to get curious, then you start to spot some of these early patterns, and sometimes you can be, you know, surprised, but in a different way-not like caught off guard, surprised-but you start to see like, oh, that happened and that happened. What if we plug those together? Ooh, interesting.

Uh huh. And so your state of cognitive arousal goes up, and you're much more engaged in the world around you because when you start to spot a couple of things that might be connected, you're much more likely to keep that curiosity alive and start looking for other anomalies that also start to fit that pattern, and that's how you know you're doing it right, when you start to get a little uncomfortable because you're starting to see weird similarities, and you know we may think of it as an intuitive hit. I'll get more to that in a minute, but we may think of it as more of an intuitive hit. And when that is the case, then again we know we're onto something, and we know we're doing it right.

So what this looks like in practice, it looks like actively seeking sources that are going to challenge your assumptions, not just validate them. It means following people who disagree with you. Okay, so that could be watching news sources that are different from the prevailing attitudes that you have. It could mean taking in social media that's different from what you would typically take up, or what the algorithm will naturally serve to you.

So that means you have to take a more active stance and seek out things. But also, when you are bringing things in that cover a wide variety of sources, don't just gravitate towards the ones that you know you're going to agree with. Look more broadly. So, like, let's just say, you know, and here, here's where I think the the very curated media sources that come at us that already know our likes and dislikes are actually doing us a disservice.

Remember the days of the good old fashioned newspaper. Now, I know some people still read a newspaper. I read a weekly newspaper. I read a weekly business paper.

But what I love about reading a newspaper is that there are all kinds of articles there that I would never seek out on my own. There are all kinds of articles there that an algorithm would never serve up to me because they don't fit my profile, and that's where we're going to spot some of these interesting things that start to map together to show us some of those early trends, some of that strategic foresight that we wish we had. So again, we have to be looking in different places, and that means we have to have our curiosity leading the way. So this would mean reading outside your domain on purpose, looking at new sources outside the ones that you would naturally gravitate to on purpose, and looking for some of those connections.

So the question to carry with you at this point is: What would have to be true for this to mean something different than I think it means? What would have to be true for this to mean something different than what I think it means? Okay, so that was your first shift. Now your second shift is to move from the center to the periphery in terms of what you're looking at and what you're looking for.

So the clearest signal of what's coming next is rarely right in the center of your core industry news. By the time it's in the center of your core industry news, well, everyone knows about it. Okay, so you're not early if it's in the core of your industry news. Those sources are already behind the curve by the time something shows up there.

The signals, the real signals to pay attention to if you want to stop being reactive and start being more proactive and start being more strategic and being able to lead through uncertainty better, the real signals to pay attention to live at the edges. These are in adjacent industries. These could be unusual voices. These could be people who are five years ahead or five years outside of your world.

One of my favorite examples of this is a group who was in the energy industry. So imagine gas and oil flowing from where it's being drilled to where it's being refined to where it's ultimately going to the consumer. Well, one of the things that was plaguing them was valves, leaky valves, and also the need to shut off valves very quickly at a moment's notice when something bad upstream or downstream because this is a volatile. I mean, volatile industry, not just a price wise, but a volatile industry.

And so sometimes they need to be able to shut the system down just on a moment's notice. And they were having some trouble with their valves, and they wanted to just make better valves. So you know what they did? They sent a team of their research and development staff to a cardiology conference.

Yes, you heard that right-a cardiology conference because cardiology, of course, is the system of pipes in our you know in our bodies that are moving the blood around, filled with all kinds of different valves, shutting things off, turning things back on again at a second's notice, so that's what I'm talking about when I'm talking about like looking at the periphery, learning from adjacent industries, and of course, yes, they learned tremendous number of things. Some which were completely irrelevant to the way the valves in the energy industry work, but some where they were able to extrapolate those ideas and apply them to the actual pipes and actual valves that were moving gas and oil around, fascinating. Okay, but that's the kind of thing that you need to do if you want to have that level of pattern recognition that is going to make you future ready and that is going to teach you how to anticipate change better as a leader. Okay, so again, in terms of if we want to look back at that AI example.

The AI signals weren't in tech white papers. They were in banking. They were in streaming entertainment services. They were in a keyboard or on your phone, predicting what you were going to type next.

Okay. So leaders who see early are almost always leaders who are looking wider. They're looking wider at the periphery. They may be looking deeper in their industry too.

But again, by the time it gets deep into their industry, they miss the boat and they weren't first to you know first to the table with a new idea. Now, the question to carry around for you with this second shift is who is five years ahead of my industry, and what are they talking about right now? Who is five years ahead of my industry, and what are they talking about right now? Okay, so take that one with you.

All right, and then let's go on to shift number three. This is moving from certainty. Again, going back to all that confirmation bias and so on that we were talking about before, to early action, to testing things out. So most leaders will wait until the picture is perfectly clear, and by then it isn't a signal on the periphery; it's the headline.

When we're acting on some of this weak, these weak signals, incomplete data, and early information, and thinking about that as a learnable skill, and taking tentative actions to see what happens. We are going to lead well, and we are going to lead fairly conservatively instead of recklessly. Now, I don't want you to take little signals that you see on the periphery, glom them together, and you know, run with that like it's exactly what's going to happen next. We don't.

None of us actually know what's going to happen next, but we can be better predictors of what's going to happen next if we start to spot those early signals, especially when we start to see a pattern happening in the periphery, and then we start to use some low-risk iteration, small tests, quick experiments, rapid prototyping, cheap ways to check whether a signal is meaningful before making a big commitment to it. Whether that's in time, in money, in staffing, whatever. So again, we want to be spotting those early signals and then putting them into action, and waiting for certainty is not patience in a fast-moving world. It's avoidance.

So we just can't wait anymore. Not anyway. If we want to be future-ready leaders, if we want to be able to lead rapidly through uncertainty and lead effectively through uncertainty. So here, the question to carry around in your mind is what's the smallest thing I could do right now to test whether this signal matters?

What is the smallest thing I could do right now to test whether this signal matters? Okay, my friends, I'm going to recap these really quickly for you because if you haven't been thinking this way. This is a total flip on its head of how you go about the world in leading yourself and leading others. So the first shift is from confirmation to curiosity.

You're not looking for what confirms your beliefs. You're engaging in a curious mindset to look to see what's there. Then shift two. Instead of focusing on the center, you're looking at the periphery.

You're looking to spot early signals and looking for patterns. You're looking to see if there's a pattern. And then shift number three. You're moving from certainty to early action.

So when you do start to spot patterns, when you do start to spot things that anomalies that are interesting, where there might be a there there, you're putting it into a low cost, rapid iteration prototype type example type experiment, if you will. Yeah, okay. So here's how you're going to put it to work this week, my friends. Pick one source outside your industry or your usual reading.

It could be in a different discipline. Again, think about those folks in the energy industry going to a cardiology conference. Now, you don't have to do something that broad, but if you are in the energy industry, maybe you read an article that comes from cardiology about valves or about whatever it is that you're interested in in a different discipline. Okay, so pick one thing, one source outside your industry in your usual reading.

It could be a different discipline. It could be a different sector. It could be a different kind of thinker that somebody that you're not following, and just spend 20 minutes with it. So that's one article, one YouTube video.

Ask yourself, what patterns do I see here? What might this tell me about what's going on in my world, in my industry, in the people I'm leading, in the functions I'm leading, and the projects I'm working on, that's the practice. 20 minutes this week. Start there. All right.

Again, my throwdown challenge to you: 20 minutes, looking for signals in the periphery, looking for things that surprise you that maybe don't necessarily make sense, and they and and don't expect it to just land right away. It might be you read this article and like three days later you're taking a shower and you're like, oh, now I see the applicability, okay? Or now I see something I could test with that. Now I see how maybe that fits.

So don't necessarily expect that one article in 20 minutes, or one YouTube video in 20 minutes, is going to completely change your mind or show you something new. Let it percolate, let it sit, let it integrate with the other things you know, and keep up that practice. Start with 20 minutes this week, and then I want you to work yourself up to 20 minutes a day, even if that just means five minutes a day at first, and then 10 minutes a day, but 20 minutes a day is really going to move the dial in terms of you spotting things that you know spotting those early signals that are going to lead to future trends. You don't need a crystal ball, my friends.

You just need a wider view, and you need your curiosity and play to spot the signals that make a meaningful difference. All right, my friends, if this information resonated with you, I highly encourage you to check out my keynote presentation called "Expect the Unexpected. If you are involved in planning a conference, if you are involved in bringing external speakers into your organization, whether that be your professional organization or association, or whether that be into your organization, this is exactly the kind of thing that I talk about in that keynote. Expect the unexpected, and I would love if you pass my name along to somebody who might be in a position to bring me in to share that bigger message with you and your team, or your professional or industry association.

All right, my friends, be well, and I will catch you next time right here on the Working Conversations podcast.

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