Martin Raymond is a co-founder of The Future Laboratory and a journalist, and he is considered one of the world’s leading futurists. We talked recently about the critical role of the human researcher in foresight research as we enter an age that will be dominated by artificial intelligence.
Kay: Do you feel it’s possible to predict the future?
Martin: I don’t think it is possible to predict anything. What you do is to look at the existing landscape and identify those people, products, or services that are either a minority perspective or they’re innovating in a category or sector, or they’re early adopters. So, people who, in themselves, are a tiny, tiny minority. We’re talking about 2.5 percent of any group or any population. You look at them and you look at the echoes and indicators coming from the general landscape. Then you ask yourself questions: What are people considering about tomorrow? How are they wanting tomorrow to be? Are there people already on the playing field who are potentially taking us in that direction?
What you try to do is to identify signs, signifiers, and clues as to how the future may look. You can then start looking at statistics which suggest increases in how we use Product X, or how consumers are thinking about Product Y in a different manner, or how a new idea has started spreading across the landscape, which more and more people are buying into. What you’re doing initially is building up a thesis, and then using existing facts, stats, and expert insights to add a framework to that thesis. When you’ve done that, you start looking at early-to-market case studies or start speaking to the innovator, the adopter, or the expert who will potentially confirm your thesis and indicate that the journey has started.
When you start putting these things together, it begins to give you what I call the “arch of the bridge.” If I say an arch is taking place and there’s enough facts, statistics, insights, and early adopter consumers suggesting that this is the direction we will take, then I would suggest to my clients that this is an area that warrants further investigation. While you’re not predicting, you are using your intuition on top of certain existing things based on fact. You are then using your ability to extrapolate forward, or using existing facts to create a third opportunity or another part of the bridge.
Kay: What questions do you ask to help you understand the signals you’re detecting?
Martin: If you think about it, if you work in the area of research and you have the natural curiosities and instincts of the researcher to ask questions about the new and the next and the anomalous, and the oddities that you see in a general or mainstream landscape, you then ask yourself: Why these things are happening? How are these changes coming about? What are the factors potentially motivating those changes? And then you start talking to the early adopters, the innovators, to the small groups, tribes, or influencers who are either kickstarting a change or reporting on those changes.
At the Future Laboratory Network, we have a core team in London who are monitoring what’s happening on Facebook, Instagram, WeChat, Snapchat, etc., and speaking to editors who sit in what I call “cultured outposts.” So, for the beauty industry quite a lot of cultural references are coming from Southern Korea at the moment. If I’m thinking about food in terms of health foods and whole foods, and how we are responding to foods generally, I’m looking at California, L.A. specifically; Phoenix, Arizona; and Portland, Maine, in America. Then I switch to Europe; I start looking at Lisbon, at East London, and Paris.
So, all the time, I’m building up a picture of what I call the edge or the extremes where these innovators and early adopters and change-makers either live or are experimenting or instigating those changes. What I have is the core hub of the research, my spokes going out, and then at the end of those spokes, an anomalous network of people who are influencers, early adopters, or innovators who are feeding into a network or speaking to other people who are doing similar or different things in parallel networks or communities.
What you’re plugging into is an ecosystem of anomalies; an ecosystem that is about differences and about being contrary and deviant. Where most businesses and mainstream research organizations are looking out for what we would call early mainstream or the general majority of people, by nature and I guess by sense of requirement, we spend the time looking in the underbrush of culture. In those parts of the Internet or society generally where big businesses are just not interested, there isn’t profit. There isn’t a natural sense of commerciality, and worse still, there isn’t a requirement to produce something for a relevant or existing market. My thought always is: while every business is asking why, the deviant is asking why not. When I encounter a group of individuals or a tribe who is asking why not, they get plugged into the network and they become part of our “why not” on how the world will change. Why not change it this way rather than the way we’re thinking about. They are people
I want to have sitting in the network
all the time.
Kay: How do you find these people?
Martin: The techniques are fairly basic. Scanning, or cultural brailling, is one of the processes that all forecasters or trend analysts will look to. So, whether you’re doing that online, whether you’re using AI scrapes to do it, whether you are doing it through a network of like-minded analysts or editors, what we would call “cultural navigators,” all of them are asking what’s new and what’s next. Within those questions, they’re asking: What is the oddity in the pattern that is suggesting that we are about to take a different turn in the pathway of history? Or rather, in the pathway of the future? How you identify them is slightly more complex.
A lot of the innovators, until quite recently, weren’t visible. Now that the language of innovation has changed, innovators understand that visibility doesn’t just gain recognition, it gains investment and funding. Ten years ago, it was very difficult for us to plug into the innovator without getting out and getting into the field and visiting not just New York, but Brooklyn, and not just visiting a street in Brooklyn, but knowing which door to knock on. And that came about through having quite a complex personal network.
When I set the business up in 2001, I was doing a lot of traveling. Probably about 150 days per year traveling, doing talks, meeting people, and visiting places that had been mentioned. My background is in journalism, so I was using the journalist instinct for research through personal introduction, serendipitous encounter, research, checking people’s online profiles, doing introductions through third parties, etc. It was more about us reaching out, where now a lot of the innovators, and early adopters particularly, are not just reaching out, but reaching in. They see a benefit to joining the network and they see a value in volume. Previously, innovators weren’t necessarily interested in being seen in volume-based circles or circles which were above commerciality or profitability. But now they see that there is a mutual benefit for being visible. Increasingly, when you look at crowdsourced funding sites, you can go directly to them and look at the Top 500 trending or early-to-market products, ideas, or services and start using them as a way to put together a sense of how the world is changing.
Kay: In The Trend Forecaster’s Handbook, you devote an entire chapter to
strategies for developing and leveraging online networks in the forecasting process. This has become an important skill set for researchers. What other skills do great researchers have?
Martin: The great researchers have three skills: one is the ability to research; the second is the ability to bring intuition into that research; and the third is to take intuition and research and drain from it deep and meaningful insight. Once you have insight, then it’s possible through imagination, storytelling, scenario planning, and future mapping to create a foresight strategy. My view about research is it’s a bit like the rich compost or mulch that sits around the roots of the trees. When it’s applied properly, it can grow the most beautiful and strange, but also the most unexpected product or the unexpected service. The role of the researcher increasingly would be to automate quite a lot of the processes that we now have to do—the seeking out, the finding, the synthesis, and freeing of our time to be able to analyze better, to story-tell better, to develop better scenarios, and to create better roadmaps for the future.
Qualitative research is not just about adding value to the quantitative, which is always seen somehow as more important. But qualitative research is about developing the great maps, stories, and frameworks for our future lives. It’s a difference between, as somebody says, “Taking an alphabet,” which is the fact, and rearranging those things to create the book, novel, poem, or great piece of music. That’s the adjective. And the adjective, as we know historically, has turned out to be more useful than the fact.
Kay: What can humans do that a machine cannot?
Martin: It’s the human’s ability to forward-extrapolate, to imagine, to theorize, and also to dream.
However, when the field researcher, the anthropologist, the ethnographer, or researchers like yourself walking along a street notice something anomalous, they bump into a certain thing serendipitously and start making connections. And by creating a framework with a map, you start building a story. And by building the story, you start seeing the future, and therefore, you see what’s missing from that future. You begin to see gaps and opportunities, and suddenly you see the beauty of research. That’s when research really comes alive and where AI will fail for the next decade because it is focused on the wrong things. It’s focused on what’s existing. History is inevitable;
the future isn’t.
The Stone Age didn’t come to an end because we ran out of stone. The Stone Age came to an end because we are matching better ways to create a new age, and that has been the case throughout history. The setter-outers, the researchers, the voyagers, and the adventurers; men, women, and all genders went out to look at the world and came back with different views of the world. And they seeded that knowledge in a way that changes the world. That’s what good research does…what I call boundary-breaking or boundary-crossing research.
Qualitative research measures an emotion. It has to capture an adjective, an odd activity. The way people place food in a cupboards at home are all indicators and hints. They’re not facts; they’re not recording things the way the machine would want them. Because of that, there’s an opportunity to create or reinterpret the role of the researcher in the future, the human interpretive role.
So, the human intersection will become the big thing that Silicon Valley 4.0 will want to plug in to the computer because they realize that, in the end, without the brain of serendipity, the love of accident, or the skepticism of human understanding, we would all end up like we’re living in Switzerland. This might be great on paper, but not many people want to live in Switzerland long-term.
Kay: Yeah, where you get arrested for mowing your lawn on a Saturday afternoon.
Martin: Exactly. It’s all ecumenical. Yeah, it’s all nice. The problem is: nice isn’t great. And nice becomes the thing that we hate because it lacks the jaggedness, edginess, and the awkwardness that particular people bring to the world, and those awkward angles and edginess that we get are sometimes the places where change happens.
Kay: Well, Martin this has been an amazing conversation. Thank you!
Martin: Thank you!