Sarah DaVanzo is best known as a “super-forecaster” who works at the intersection of innovation, marketing, branding, trends, and culture. She is known internationally, has launched several companies and has presented at TEDx. In her current role within the L’Oréal Group (USA), she has developed agile innovation methods to help brands sync with trends, anticipate change, improve relevance, and design for the future. In this Luminaries interview Sarah describes her work, the importance of curiosity, and the methods she uses to detect trends that have led to a 73% futures prediction accuracy rate.
Kay: What methods do you use in your work as a trend forecaster to capture the zeitgeist?
Sarah: What we’re looking to do is triangulate. If we start to notice a behavior, we want to make sure signals or data points are coming from multiple different sources to corroborate that behavior. To have one’s finger on the pulse of how culture and humans are moving, do call-scanning for signals—looking for online and offline qualitative and quantitative data points through primary research or secondary research.
Typically, we’re not going to spend a lot of time on a behavior where there’s only two or three incidences of that. If we’re looking for the zeitgeist, we’re looking for patterns.
Over time you need to do this regularly—the daily rigor is very critical. It’s impossible to jump in and jump out. You’re scanning news feeds, looking at research reports. It requires being a polymath looking broadly across different data sources. You start to see signals and patterns emerge after a while. Our job as researchers is to then see whether there’s correlation and causation beyond the correlation. We use machines and technology for this, but there’s also a human intuition part.
Kay: How do you convince others to see what you are seeing?
Sarah: Convincing others to see it is a very different proposition. Sometimes it takes two different types of people, depending on your audience. Showing data is important. In my experience, the audience is often at the C-suite level, so they’re very data-driven. They want to see concrete forecasting driven by multiple data sources and even predictive modeling if need be.
One of the most successful ways to show the future trajectory of where culture is going is through what I call “cultural forensics”, showing trend patterns historically that lead us up to this moment. When you unpack multiple historical trend lines, you’ll see the tipping points and the dipping points, the inflection points, and the catalysts. You can infer insights from them, showing a series of historical trends (some people call it “back casting”), to see where the future is headed. I find this approach to be one of the simplest, not requiring as much heavy data analytics, so anyone can do it.
Kay: So, the researcher becomes a tuning fork.
Sarah: Yes, that’s a great way of looking at it, and the music is the insight. We create, but the tuning fork is responding to the vibrations. Right? I want to challenge the whole idea of researcher because on the client side no one is jumping around having a party over the research. It’s the insights and specifically the discovery that come out of the insights, what the implications are on how I can transform those insights to action, that will further the business.
More and more we’re focused in on two kinds of buckets of insights—the obvious insights, which are super-important because you need to validate; and we’re pushing more and more on our discovery and exploration partners, to unearth the unobvious insight that hopefully will give us competitive advantage, a higher order insight that will give us some unique way into an opportunity.
Kay: What should you do at the beginning of a foresight research project?
Sarah: It starts with due diligence of the secondary research, scanning and conducting the desktop research, which might include social listening, like poring through Reddit, which has fabulous unfiltered conversations that are self-moderated, and Giphy.com, which is a search engine for gifs. Like Reddit, it’s user-generated content. People tag with language, so you’re getting a sense of the imagery that humans are ascribing to hashtags. You’re getting an unfiltered view of how people think about topics and conversation topics, so it requires semiotics, but looking at the gifs that are connected to certain hashtags is a fascinating exercise. Hashtag heuristics, I mean, that sounds kind of crazy.
Kay: Hashtag heuristics—that does sound crazy!
Sarah: Yeah, the heuristics of hashtags. On Instagram people are organizing their conversations with hashtags, and sometimes the most insightful threads are to see the slang words and phraseology smushed together in a hashtag, and what people attribute that to, and what they’re tagging the content to. With pop culture having such an influence on perception, behavior, and aspiration it’s so critical that we understand it. Researchers today need to get their handle on what’s happening broadly in pop culture and use the informal tools of communication in pop cultures, like Instagram, like Reddit, and so forth.
Kay: You’ve said that to be good at this type of work you need to cultivate an explorer’s mentality. Would you please talk about this?
Sarah: I like to use the astronaut as a symbol for the nature of the work we do. There’s the astronaut manifesto, which is about being collaborative and toggling between expertise and falling in line. Use what you have rather than what you want or need, and as we conduct research we need to be resourceful. That’s part of their job, and as researchers we also need to prioritize insights and methodologies. Astronauts figure out how much runway they have. They need to test and learn and pilot and have situational awareness, which is what we were just discussing. Like astronauts, modern day researchers take uncomfortable routes and make moonshots. They have to be positive, and prepared, and hack. Look at the way astronauts go about their work, from strategic preparedness to scanning the environment to working with technology. In the space station, the astronaut is completely surrounded by technology.
As insights, exploration, and discovery researchers, we are also surrounded by technology. The human is at the core. I really believe we need to go heart to heart with the increasing reliance on AI and technology to do automated commoditized surveying and data collection and gathering. The art of conversation is the skill of the future. To truly connect with another human, look them in the eyes. If you’re conducting a group or conducting an IDI, you need to be able to really get them to trust you. To be genuinely interested and curious in that other person, and they see that and feel that, and they open up to you—there’s no machine that can do that. Even the best machines and robots have life-like capabilities. I don’t think we’re going to be seeing that between now and the singularity.
Kay: How would you recommend qualitative researchers integrate their work with artificial intelligence?
Sarah: We need to demystify AI. I like to say AI is artificial ignorance—it’s not that smart. It’s basically taking in huge amounts of data links or data oceans and looking for patterns and trying to learn from those patterns. But humans have to train it still, so it’s years, hours, and so much human interaction to train AI into what to look for and what to see. It’s like nurturing a baby, so the human is still playing an important role. A way to tiptoe into this space is through voice. Some pundits believe voice recognition will be the most leapfrogging important technology in the next decade. Fool around with Alexa. Fool around with Siri. Fool around with telephonic research methods, which are forcing one to think about the processes of dealing with it. Think of how you would conduct your research if it was just telephonic. How does it change if there are no eyeballs to eyeballs looking at each other? We need to master those skills and think of the processes for doing it. That’s a simple way of doing it.
Here is another kind of shortcut, but it requires a digital background that not everyone has. Imagine you are conducting a piece of qualitative research and you were like, “I’d like to look at humans in North America and they’re in the South.” And then you say, “Oh, wait. They were kind of in the Sun Belt.” Okay, interesting. “I would like to overlay the CDC data on that, so I’d like to overlay CDC information maybe by zip code and overlay this with census data and behaviors online to see if I can extrapolate something.” As a qualitative researcher we might want to augment this with interviews and so forth. You can go to sources like Fiver.com or Mechanical Turk where you can post to say, “Hey, I’ve got five datasets and I need someone to layer this data and pull out any indices—anything that pops. Surprisingly there are people who can do that at a rather economical price. Without being a software programmer, I can rely on people who can do that very quickly.
Some of the most interesting, profound, useful, and competitively differentiating insights have come from experimenting with a technology platform. In New York City, I go to science fairs at NYU’s Information Technology Program, which showcases technologies developed by the graduate students, and oftentimes they’re startup ventures. Going to those meetings in the winter and spring, getting a firsthand impression, giving a business card—you’d be surprised how often this turns into a success. Every city has its own universities and technology communities. You can also work with research partners who are doing this kind of work, experimenting and exploring, because they’re usually more versed on developments and technology that can be used for research.
One of the ways to spot the zeitgeist is to look for potential partners to experiment with and to say, “What’s the pattern here?” About 10 years ago, I noticed these university programs were all focused on mood. It was all about reading mood and conveying mood… and today we’re all focused on mood-stage marketing, reading mood and the neuroscience of mood—you can call that “mood-geisting.” These are some of the most connected people who are already starting to experiment.
Kay: As a final question, would you please tell us about your work in curiosity?
Sarah: Absolutely. I’ve been studying animal and primarily human curiosity, exploration, and discovery now for close to twelve years. I truly believe that to be prepared for an increasingly VUCA world—volatile, uncertain, complex, and ambiguous—is to be innately exploratory and curious with a specific type of curiosity. People are becoming much more indifferent or lack curiosity, or they have a very deep passion about…whatever—computer programming, or knitting, or some topic. We’ve lost the polymathy, the broad curiosity about the world around us. I’m going to be contentious and blame that on the focus on STEM and not the humanities. We’ve moved away from celebrating people who have many, many interests, and therefore are exposed to many concepts and ideas because as researchers our job is to knit together those insights and extrapolate from all different sources to make new metaphors or to learn from other industries.
The type of curiosity I’m most interested in is both broad and deep, but broad very importantly. Also, that we’re using all of our senses—one of the areas that concerns me is that there’s too much of an appreciation or emphasis on intellectual curiosity in our culture.
After that, I would say making and doing experimental curiosity. When you start to look at the styles of people exploring visually or sensorially or intellectually or through experimentation—seeing and feeling and thinking and doing—we’re a little lopsided as a culture. When we explore fully—visually, sensorially, intellectually, and experientially—we unlock creativity. It’s outstanding and it unlocks creativity and insight. So, I implore the community to work on their curiosity muscles, to exercise their polymathy, and to explore beyond just intellectually, which I know we can often be rather guilty of in the research world (being heady and intellectual), but also to explore through sensory, visual, and through experiments.
Kay: Perhaps the whole “maker” movement is a way for people to implement ideas and explore the world with their hands.
Sarah: To that point, I was conducting a piece of research for a client at the Maker Faire. We interviewed hundreds of attendees—passionate maker folks. The hypothesis going in was this would be the most exploratory and creative group of people that we could possibly work with. Right?
To my surprise, a preponderance of people had deep passion for only one topic, and almost no awareness, understanding, or interest in topics outside their one topic. That was a huge insight and surprise. We just assumed, being makers, they would have breadth and it was hard to get them to stretch beyond their area of interest, so I think it’s an example of how we’re the T-shaped specialists as opposed to the generalists these days.
Kay: Well Sarah, this has been a great interview. Thanks for sharing your thoughts with the QRCA community!
Sarah: Thanks, Kay.
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