How to predict the future of your industry (and why it matters)

No, I'm not really sure what it is either...

This friendly looking contraption was seen as the future of oceanography in 1963.

One of the hard truths about thought leadership is that it requires you to either predict, or create the future.

That doesn’t mean repeating the same ‘bold’ ideas that everyone in your industry already accepts as “the next big thing”.

For example: in technology today you can’t build thought leadership today with the idea that cloud computing is the next big thing. There’s no ‘leadership’ in that opinion, because 99%+ of the market already believes it to be the case.

Industry leadership requires you to generate opinions about the future that are differentiated. Your opinions must go above and beyond what most of your industry believes to be their future.

Takeaway 1: Thought leadership requires predictions about the future

Takeaway 2: Thought leadership requires predictions that aren’t already believed by a majority of your industry

That’s a short introduction into why thought leaders must predict the future. Now let’s talk about how you do it, with five big ideas to help you craft predictions about the future of your industry:

1. Just start (predicting what might happen in 10 years time)

The most important thing about predicting the future is to start doing it. Forget about some of the more detailed methods we’re going to talk about below. Just get into the habit of saying “In ten years time I think…” 

Takeaway 3: Start by predicting at a 10 year horizon.

Start by forcing yourself beyond the traditional 12 month forecasting window, and remember this quote when you think you might be overdoing it:

“We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten. Don’t let yourself be lulled into inaction.”
– Bill Gates

It’s really hard to get started, but there’s definitely a snowball effect. Once you start thinking at this timeframe, it gets much easier. You’ll quickly start connecting the dots around your predictions for the future.

Takeaway 4: The more prediction you do, the easier it becomes. 

Deal with the fact that you will be wrong about some things. That’s ok. Over a ten year window even the most experienced predictors will be wrong about many things.

But being wrong over the long term is less relevant that how well you establish the inevitability of the change. Because the 10 year future is most powerful as a catalyst for shorter term action. If the 10 year future comes with inevitability, the buyer may as well take action now – because they will have to at some stage in any case.

Takeaway 5: Accuracy matters. But inevitability matters more.

2. Extrapolate on patterns you already recognise

I was recently reading the fantastic Moonwalking with Einstein – It’s a NY Times bestseller about competitive memory championships by Joshua Foer.

It’s a great read. The author starts out reporting on the US memory championships, and gets sucked deeper and deeper into the world of competitive memory – eventually winning the US championship.

In the book, there’s a particularly interesting section talking about how experts become experts. Did you know, that in every chess grand master’s development, there’s a point at which memorising the board becomes effortless? It becomes so easy for the budding chess master to memorise the board that they can play multiple games, straight out of their memory.

But an amazing thing happens if you arrange chess pieces on a board in a completely random fashion, in a pattern that could never have happened during normal gameplay. When the pieces are random, chess grandmasters has practically the same memory for the board as anyone else – completely hopeless.

Identifying the patterns of gameplay (each seen thousands of times) that allows such impressive and quick memorisation. In fact, MRIs of expert players show that the main part of the brain accessed during a chess game is long-term memory, not analytical reasoning (which is the case for beginners).



An expert beats you because they’re better at pattern recognition. Not because they’re smarter.

The grandmaster doesn’t beat you because they can think ten moves ahead of you. She beats you because she can immediately identify the analogy to millions of previous games played.

This goes much further. In just about all fields, experts don’t win because they’re smarter. They win because they’re better at recognising patterns.

Takeaway 6: Expertise is pattern recognition

To connect back to thought leadership, I’d argue that every CEO and senior executive satisfies the criteria as an “expert” in their field. So if we buy into the idea that you’ve reached the top – not because you’re smarter – but because you’re better are recognising and acting on patterns, what does this mean?

In this case, building predictions isn’t about reasoning. It’s not about analysis. It’s about connecting the dots between the different patterns that you know to be the case. Once you’ve started there, it’s easy to take the next step and start identifying new patterns.

The first step is consciously realising the patterns that you already recognise. What are the big ‘patterns’ that sit underneath your expertise?

“It is said that the present is pregnant with the future. “


3. Go from first principles

In How Google Works, Larry Page explains: “When I was younger and first started thinking about my future, I decided to either become a professor or start a company. Either option would give me the freedom to work from first principles. This autonomy of thought is behind almost everything we do at Google, behind our greatest successes and some of our impressive failures.”

Peter Thiel says in Zero to One: “The paradox of teaching entrepreneurship is that such a formula necessarily cannot exist; because every innovation is new and unique, no authority can prescribe in concrete terms how to be innovative. Indeed, the single most powerful pattern I have noticed is that successful people find value in unexpected places, and they do this by thinking about business from first principles instead of formulas.”

Takeaway 7: Pull your industry back to first principles. What widely accepted truths does this call into question?

4. Predict from history. Past cycles will repeat

History has a way of repeating itself. As George Santayana famously said:

“Those who cannot learn from history are doomed to repeat it.”

There are many patterns in every industry that have happened over and over again. There are lessons that have been learnt many times. Find the patterns within your industry from the the 60s, 70, 80s, 90s. etc.

Many, but not all of these patterns and cycles will repeat again in the future. The technology may have changed. But human nature has not.

Takeaway 8: Previous cycles within your industry will repeat. The technology may have changed. But human nature has not.

5. Learn from research and start with the outside view.

The latest research on forecasting shows that the best forecasters regualarly use something called the “outside view” when predicting the future.

This is a great quote from the Freakonomics podcast on “How to be less terrible at predicting the future” :

“One of the more distinctive differences between how superforecasters approach a problem and how regular forecasters approach it is that superforecasters are much more likely to use what Danny Kahneman calls the outside view, rather than the inside view. So, if I asked you a question about whether a particular sub-Saharan dictator is likely to survive in power for another year, a regular forecaster might get to the job by looking up facts about that particular dictator in that particular country, whereas the superforecasters might be more likely to sit back and say, “Hmm, well, how likely are sub-Saharan dictators who’ve been in power x years likely to survive another year?” And the answer for that particular question tends to be very high. It’s in the area of 85, 95 percent, depending on the exact numbers at stake. And that means their initial judgment will be based on the base rate of similar occurrences in the world. They’ll start off with that and then they will gradually adjust in response to idiosyncratic inside-view circumstances.”

Takeaway 9: Start with the outside view.

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