Creating startups through empathy & behavioural research: Dr. Rachel CareyPodcast April 20th, 2021
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In this episode of The Decision Corner, Brooke sits down with Dr. Rachel Carey, chief scientist at Zinc. Zinc runs a venture-builder in London that is dedicated to supporting passionate entrepreneurs who are interested in launching ventures to solve the developed world’s most pressing challenges. Since 2017, Zinc has invested time and resources into projects as diverse and impactful as improving women’s mental health, increasing opportunities for people affected by globalization, and adding five high-quality years to later life. Dr. Carey leads a team of scientists on Zinc’s Research & Development team who work with entrepreneurs to narrow their problem focus, sift through research, network, experiment, and finally, build and test their solutions.
Having come from an academic background with a PhD in psychology, Dr. Carey has a wealth of knowledge about the differences between behavioral science academia and applied research, and is eager to share her experiences and ideas about how to bridge the two worlds. In today’s episode, she discusses these differences, as well as how behavioral science shows up in the world of entrepreneurship, and the need for certain elements of research culture – including public perception – to evolve. Some specific topics discussed include:
- The differences of applying and generating behavioral science in the academic versus startup worlds
- How these two worlds, particularly research and entrepreneurship, are bridged in practice
- How behavioral science projects and ventures are prioritized
- The risks of entrepreneurship, and the privilege required to take those risks
- Current public misconceptions regarding science and research, and how these misconceptions are shaped by a lack of public access and information
- The changing face of entrepreneurship, and the new potential garnered by including more diversity
- The trade-off between statistics and anecdotal evidence, and the motivating power of stories
Taking behavioral science career turns
“At least to me, there is still a perception among a lot of people that it’s a one-way street – that you leave academia and you cease being a researcher and you can never come back. I think that’s really missing a key opportunity. That movement across boundaries, and allowing people the flexibility to explore different settings and career paths so that they understand different sides of the table – even if they ultimately end up back in academia – I think that’s really important, particularly in early career stages.”
The privilege of entrepreneurship
“I think you could say this in entrepreneurship – there’s definitely historically been a certain type of person that’s been able to take the kind of risk that it requires to be an entrepreneur, or to give up your job and throw yourself into something from scratch, which I think is one of the things we’ve been sort of battling against is trying to open that world up to people that would not be ordinarily attractive to entrepreneurship. I think it’s really important to understand how we can support people who want to swim against the tide to do so in a way that is still protective of them, to some extent.”
Science is not about certainty
“One of the things that I have been noticing and worried about over the last 12 months has been the expectation a lot of people have that science is about providing facts and certainty when it’s kind of the opposite. There’s a quote that I really like, which I won’t do justice to in paraphrasing, but it’s along the lines of, that science is about reliability, and it’s reliable because it’s not definitive, and it’s the reliability that we need rather than certainty. But I think that there’s quite a big gap in, kind of, public perceptions of science, both science in general as a pursuit and specific scientific findings.”
Being vulnerable with scientific research
“That’s not just about sharing at the end. It’s also about moving away from this mentality that we all work away in our own little bubbles in private, and then at some point when we’ve got a shiny output, we present at a conference. I think it’s more so like drawing back the curtains the whole way through, and where possible, letting people see the inner workings, learning from the process as you go along. I think it’s really important that we change the sort of default around that, especially in the applied community, understanding that there will be organizational constraints.”
A culture of collaboration
“To me, there’s a real need to move out of peer review mode, out of critical evaluative, academic high horse default mode, and into a collaborative, constructive collegiate atmosphere. I think that’s partly building a reputation of science that we have boundaries and have our own values, and what can be helpful and collaborative and productive working with other teams in other organizations. I think there’s something too about the way that we approach it as scientists, kind of keeping our own values and beliefs in place while also being maximally supportive and collaborative and open.”
Brooke: Hello everyone, and welcome to the podcast of The Decision Lab, a socially conscious applied research firm that uses behavioral science to improve outcomes for all of society. My name is Brooke Struck, research director at TDL, and I’ll be your host for the discussion. My guest today is Rachel Carey, chief scientist at Zinc. In today’s episode, we’ll be talking about behavioral science in the lab versus in the wild of applied practice. How do these different settings influence practice, knowledge, and impacts? Rachel, thanks for joining us.
Rachel: Thanks for having me. Nice to be here.
Brooke: Before we get rolling, tell us a little bit about yourself and the work that you’re doing at Zinc.
Rachel: Sure. So, I have a background in behavioral science and health psychology. I did my undergrad in psychology and then a PhD in psychology, which was focused on the impact of threat-based road safety campaigns on driver behavior. So, quite a specific applied experimental project funded by the Irish Road Safety Authority. I spent a little bit of time as a postdoc, after that project finished, working on a couple of different things. Then I moved to London in 2014 for a postdoc at UCL, University College London, and I spent a few years there working in the Center for Behavior Change with Susan Michie, working on a project that was a lot more broad and theoretical and methodological than my PhD had been.
The aim of that was to identify mechanisms of action underlying individual behavior change techniques. So, trying to advance our understanding of how behavior change interventions work. I took a step away from the academic career path after I finished that project. I guess I kind of knew that I wanted to be in research. I knew that I wanted to be in science. I didn’t have any particular draw to doing that within a university setting, although there were some things about that setting that I really liked. I decided I wanted to see what research roles outside of academia looked like, and I spent a year in a corporate setting working in a big healthcare company.
Then in 2017, I joined Zinc right after it started. Just to give you a little bit of background about what Zinc does, since we’re a relatively new organization: we started out looking to build a platform that would bring people together across traditional disciplinary and sectoral silos around particular important societal problems. So it was born, in part, out of a frustration that the research and innovation system is pretty fragmented and it doesn’t always give people opportunities to accelerate or maximize their impact on problems they care about, whether that’s unemployment, or environmental degradation, or mental ill health, et cetera.
Over the last few years, we’ve been running different types of programs. The main one has been a venture builder for innovators and entrepreneurs who want to start a new company that has a particular social problem it’s trying to tackle. So, we bring together cohorts of roughly 50 entrepreneurs full-time for nine months. They come to us pre-team, pre-idea, pre-business, so blank sheet of paper, and we work with them to create new products and services over that nine month period. Each of our programs has a particular mission at its heart. All of our work is kind of mission-led.
For example, the first program we ran back in 2017 focused on improving women’s mental health. I guess it’s a kind of space for people, including people who might not ordinarily be attracted to entrepreneurship and innovation, to come and experiment their way to having impact at scale on problems they care about with people they wouldn’t ordinarily meet. My role in that is that I lead our research and development team, a small team of scientists, and our remit is to work with our entrepreneurs and ventures to help them define the problem, translate existing research, connect with academic experts, conduct experiments, do user research, operationalize their outcomes, and measure impact.
So, it’s kind of feeding into their development and trying to build a strong evidence base into their foundation. I think behavioral science in particular can add a lot of value and gain a lot from being involved in those early stages. Increasingly, we run our own research programs as well as being a kind of internal consultancy for our ventures, so, looking to synthesize and share the learning we’re getting so that we’re contributing to, and not drawing on the kind of body of knowledge that exists.
The academic versus corporate world
Brooke: Yeah, that’s great. That’s such a powerful jumping off point for the discussion today. One of the points that you brought up in there that I want to start unpacking is this gap between what goes on in the academic world and what goes on in the corporate world. Applied behavioral sciences is predominantly done outside of academia, I would say, or that’s my perception of things. Whereas what’s going on within academic research pushes more theoretical boundaries, time to map out and push the frontier of our understanding of how the brain processes certain kinds of signals and this kind of thing.
But there are disconnects in the way that those communities communicate within themselves and also with each other. If we think about the work that’s done in corporate settings, often the focus is on impact, impact, impact. What was the ROI? What did you achieve? There’s less focus put on how it is that you got there. There’s less focus put on how that draws on the knowledge base that’s developed in the academic world. On the flip side in the academic world, it’s often like, here’s what we learned about the way that people think that we didn’t know before.
You go and look at an academic article and it’s like methods, methods, methods. Even the articles themselves, often published in academic journals, which, for people who are no longer in an academic setting are expensive and often non-accessible. What kinds of effects do we see that arise from this kind of gap between the ways that we generate knowledge and the ways that we communicate?
Rachel: Yeah, you’ve touched on a few really important points that I think is worth unpacking a little bit. The first thing I think is what we mean by applied behavioral science, the nature of applied behavioral science roles, or behavioral science roles that exist outside of university settings. There’s clearly been this huge growth in demand for behavioral scientists in various settings and big tech companies, small startups, local government, national government, national health services, insurance companies, market research firms, et cetera. We have this kind of growing global, vibrant behavioral science community, which is an incredible opportunity to do research differently for reasons I’ll come on to.
But at the same time, I think the nature and pace of that growth is coming with growing pains. As the demand for behavioral science is increasing, there’s also the potential for things to get lost in translation and oversimplified; the risk that behavioral science gets used as a buzzword. I think we talk about this as an applied behavioral science community. I know it’s a podcast, but I’m using air quotes. It’s a bit like using these terms like ‘practice’ or ‘industry’. It can be a useful shorthand, but it’s masking, I think this hugely diverse tapestry of work that’s happening underneath those labels.
I think that’s kind of an important caveat. I think that variation is particularly salient for behavioral science because of how variably that term is now used and interpreted. Partly that’s the kind of confusion and conflation around behavioral science, behavioral economics, behavioral insights behavioral design. I’ve seen job descriptions for behavioral scientists in different organizations that could not look more different from one another in terms of the scope they’re expecting or the skills they’re expecting a person to have.
That range of work makes it less easy than we might like to quantify or unify as a field. I think that’s the first thing to say. There’s not this kind of unified world of academia and then a unified world of application, and we just need to build a bridge between those two. There’s fragmentation that exists within each of those two worlds.
Then, I think to come on to your question about sort of academic and applied. First of all, I think we need to be careful and conscious about the language we use. We risk sometimes conjuring up an image that there’s a world of academic research that produces new evidence, and then a world or several worlds of practice or application in which, with varying degrees of reliability and fidelity, that evidence gets applied. I think it’s important that we’re conscious that there are researchers and scientists continuing to be researchers and scientists outside of universities. I think the language is important.
Clearly, there are disconnects between behavioral science happening in academia and behavioral science happening outside of academia. That’s in no way specific to behavioral science – I think it’s indicative of a wider fragmentation in the research and innovation landscape and ecosystem. We’ve long been asking questions about how we can get high quality research into practice, into policy, into new tech innovations.
Lots of good analysis of that problem out there, asking questions like: Are we training grad students in the right way? Does the academic culture and incentive structure support academics to engage meaningfully in applied work? Is there a visibility problem? Are academics able to see the kinds of work that’s happening outside and vice versa? How can we make collaborations more productive and less bureaucratic? How do we increase sharing, incentivize and increase sharing of knowledge?
There’s one point that I think is particularly interesting to me, and perhaps some part of the solution to all of this, which is: the growth of researchers and scientists moving out of academia, while that represents a risk of further fragmentation, it also, to me, represents the potential opportunity to tackle that.
We have this diffused network of trained scientists now in a whole bunch of different settings and sectors, and those represent potential expert clients for collaboration with academics, because we’ve been on both sides of the table, we speak both languages, we can understand both incentive structures. I think we also have a responsibility and an opportunity to stay up to speed with the latest developments and current thinking and to translate and apply that into our own work. I think the kind of visibility of the kind of work that’s happening we’re also in a position to promote, so to share what we’re doing and to get word out there.
I think this world of applied behavioral science, while fragmented and disconnected and going through growing pains, also has the potential, to me, to represent a different kind of bridge-building opportunity.
Bridging research and entrepreneurship
Brooke: I wonder if you could help us to unpack that a little bit through the experiences that you’ve had with Zinc. You made a very well-taken point earlier, that like, ‘I’m setting up a bunch of straw people here and you’re just furiously thrashing them down,’ which is exactly what you should be doing. Let’s take our archetypal individuals who bear no resemblance to real people out there in the world, but you’ve got like Mr. or Mrs., a researcher practitioner who’s kind of in the middle, who’s got a bit of academic experience, but also a bit of industry experience. Then you’ve got like, Dr., Researcher So-and-So, who has lived in the academic world for their entire life and never seen anything outside. Their parents were researchers and their whole world exists within university walls.
Then you’ve got what the academics might view as like this uncouth outsider, who’s got this idea that they want to build a business and somehow behavioral science is going to be relevant to that. So, how do those people come together and find a way to understand each other in the work that you’ve been doing at Zinc? You’ve got this entrepreneur who has an idea about an application domain that they want to be moving forward – there’s a cause that they care about, there’s a group of people that they want to be helping, they want to be bringing behavioral science knowledge into this.
You’re creating a space at Zinc where those kinds of people are put into contact with behavioral researchers and researchers from other domains as well. How do you facilitate getting those discussions rolling when those people have very different experiences and expectations about how that interaction might go down?
Rachel: Yeah, it’s a really good question. There’s a few ways that we come at it. The fact that we have an in-house team of essentially translators helps us play a kind of facilitative intermediary role. We’re in a good position to be able to say, ‘This is the person you want to speak to, this is what they might be interested in, this is how the collaboration might be set up, et cetera.’ I think there’s a risk that we, again, sort of homogenize startups in – and maybe industry more generally – and there’s a hugely diverse range of different types of ventures we work with the problems they’re trying to solve.
We start with a really deep focus on the problem. We think that of having a problem-led approach, we have four missions that we are interested in, and within those there’s a whole bunch of individual problems to solve. We think that that helps create the right communities and ecosystems and collaborations among people that care about those problems. So, having a problem-led focus allows you to take a step back and think, ‘Who do we really need around the table in order to tackle this?’ To me, the sort of value of having a behavioral scientist involved is less about their individual discrete input and more about their skills as they get applied iteratively alongside other skills and disciplines, including human computer interaction, and marketing, and tech, and creative design.
I think that’s an incredible opportunity for scientists and academics and researchers as well, to be thrown in the mix with a whole bunch of people that they wouldn’t ordinarily work with. It is a different type of collaboration. I think, we’ve used terms like ‘interdisciplinary’ and ‘multidisciplinary’ and ‘transdisciplinary’ now so much that they risk losing all meaning, but if you stay problem-focused and mission-led, you can get much more concrete about what expertise you need, why everyone’s around the table, what the common purpose is everyone’s working towards. The fact that we have a kind of in-house bunch of translators also definitely helps.
We’ve played quite a hands-on role in facilitating connections and collaborations. A lot of it is just down to individuals: What are individuals passionate about and interested in, and is it the right time? A lot of it does tend to be fortuitous timing and facilitated by a particular moment in the startup’s development, for example. But I think the mission-led, problem-led focus is really key.
Capture – the monopoly of academia
Brooke: I really liked that. I liked this idea of throwing people into the mix and the opportunities that that creates. One kind of piece of theoretical background that I might pull into this is this idea of ‘capture’. So, we can think about like, there’s talk of ‘policy capture’, or ‘decision-making capture’, where you’ve got outside actors, lobbyists, who kind of capture the process and they get to set the agenda about how the discussion is going to go. We can think about that kind of capture in interdisciplinary collaborations as well.
For instance, there’s some writing about whether randomized controlled trials really should be treated as the gold standard of evidence that everyone is looking up to, and the fact that actually randomized control trials are really well adapted to some kinds of questions, but not to other kinds of questions. Therefore, if we put one type of methodology on a pedestal, we also put those types of questions on a pedestal, and that creates this kind of ‘capture’, where the people who work in disciplines that primarily lean towards randomized controlled trials get to set the agenda for how the whole project is going to unfold.
We find the same thing – if we look at sectoral capture, where if you’ve got a bunch of academics at the table who are trying to collaborate with people who are looking to get a startup off the ground and they, in the conversation, manage to get around to this point that like, ‘Well, whatever we do, something that comes out the backend of this collaboration has to be a peer review paper.’ It’s like they really get kind of this unfair advantage in setting the terms of how the engagement is going to go. Down the line, that also has impacts on the way that the startup will kind of conceive of its business and conceive of its consumers.
Incentives are an important part here. You throw everyone into the mix, and capture is one of those things that you need to have on your radar to make sure that everyone actually gets to have a place at the table to define how the project is going to unfold. You mentioned the opportunities for researchers being thrown into this mix. I wonder whether you could say a little bit more about whether those opportunities are ones that are well incentivized or not well incentivized in the institutional settings in which these researchers are working.
For instance, if there’s something really worthwhile to do and would be enormously impacted by having some top notch behavioral scientists sitting at the table – not because it’s going to create a peer reviewed paper, but because the knowledge that already exists is going to be applied in such a powerful way – what happens? How does that situation unfold? Does that opportunity – and to follow your lead from earlier, this is the podcast; I’m using air quotes around the word ‘opportunity,’ – does that opportunity have the proper incentives there for people to recognize it as an opportunity and to be able to lean into it without feeling held back by the institutional structures in which they’re operating?
Rachel: Yeah, it’s a great question. I think, at least the experience that I’ve had, has suggested that there’s quite a disconnect between what an individual might be motivated and incentivized by and what the institution is explicitly supporting and incentivizing. I think that’s really important. You talked a little bit about incentives – it is obviously important to start from where they are.
I think when I started this journey outside of academia, I kind of just continued the way that I had been going: ‘Research is good because it’s research, and science is good because it’s science, and here’s what that looks like,’ as opposed to thinking, ‘What does this person or an organization or team care about right now, and how can I be helpful to them in a way that is advancing science and having positive impact?’
There’s two different ways to come at this kind of academic incentive and collaboration question. One is, ‘How do we make collaborations between – again, this analogy or metaphor of like a bridge between worlds – how do we make that more streamlined, incentivized, supported?’ Then there’s a separate question, I think, which is facilitating movement of researchers across boundaries. At least to me, there is still a perception among a lot of people that it’s a one-way street – that you leave academia and you cease being a researcher and you can never come back. I think that’s really missing a key opportunity.
I know that there’s a lot of progress being made in this, and there are initiatives to support it, but that kind of movement across boundaries, and allowing people the flexibility to explore different types of settings and career paths so that they understand different sides of the table – even if they ultimately end up back in academia – I think that’s really important, particularly in early career stages, particularly given that we know that a lot of the postdocs and PhD students now coming out are going to really struggle to get an academic job. So, we need to be providing supportive opportunities for movement across boundaries, which includes increasing the visibility of those opportunities, what they involve, what the transferable skills are, et cetera.
I think the question about incentives outside of that – so outside of the movement of individuals, but back to the point about collaboration – at the moment, it feels mostly to me like individuals are fighting against the system. They are doing things that they feel passionate about and they’re interested in, but it’s an uphill battle often, and increasingly, I think in some ways, working in a new organization in a new team has given me some space to think about the nature and impact and value of research.
I’ve been more and more interested in [the idea that] if we were to take the best parts, the best ingredients of these different worlds – the best of academic research, the best of creative design, the best of entrepreneurship and tech and innovation – [we] would kind of lose some of the institutional norms and structures that currently make it less than optimally designed. What might that look like? What might a new research and innovation culture represent that was neither the sort of extreme end of academic research, nor the extreme end of sort of, [for example] applied product development? If that’s the context we’re working within.
But there is something new in the middle, and that kind of takes the ingredients, but bakes them in a new casserole, something like that. My analogies never quite work out but, taking ingredients that we think work and being able to make them into something that better represents the outcomes we’re trying to collect to be achieved.
Who are the best entrepreneurs?
Brooke: You mentioned individuals needing to swim against institutional currents in order to find themselves in these spaces. I would note that the same kinds of realities apply in contexts like government, for instance, where the easiest way to have some government involvement in your career is to do that as like the first thing that you start in your career, and you sign on to be a lifer, right? You start out as this kind of low level frontline analyst. Then 30 years later, you have progressed to some degree in your career, or to some greater or lesser degree. Then you retire and your career is over. You’ve probably never left the comfortable womb of government to see what else is out there.
Collaborations are often very much kind of captured in this way. It’s dictated by the terms of the institutions that you’re working in. But there are those who decide that they’re going to swim against the grain. One of the points that you and I have discussed in a previous discussion is about how much the outcomes that we get through these innovation projects are influenced by these super, super early stage elements, specifically around who decides that they’re going to swim against the stream. Who the entrepreneurs are has such a massive influence on the kinds of outcomes that we see.
Brooke: I would venture the supposition that the same is true of researchers as well. If we think about the history of cognitive psychology research and the mapping of cognitive biases and all these things, which were really touted as being universal features of human cognition derived more or less from groups of Psych 101 students in white affluent settings. Then, all of a sudden, someone had this extreme countercultural idea, like, ‘What if we went and tested these things out and tried to reproduce the findings with people who looked very different from this kind of initial, very controlled test group?’
The history of cognitive science – well, I mean, even the present of cognitive psychology – is very much grappling with which of those elements were actually universal in the way that we thought they were, and which need to be tweaked a little bit. Maybe like there’s kind of a local flavor, but there’s some underlying function that is consistent across, let’s say, cultural ecosystems. What happens when these individuals either do or do not decide that they’re going to swim against the current? Some of them decide they’re going to jump into these things, even though that’s not the kind of clear path forward. It’s not the path of least resistance, but they’re going to do it anyway.
Rachel: I think that’s really important is how we can support people who want to swim against the tide to do so in a way that is still protective of them, to some extent. You raised another point, which is important, too. The early stages are key. In our world, we start with individuals, we invest in individuals who are passionate about a particular problem and are otherwise coming with a blank sheet of paper. The early stages, the formative stages, are really important in deciding what problem they go after and which variables they hold constant.
We have a role, and I think in my job, I have a role and a responsibility to shine a spotlight on some of the more neglected thorny, complex problems. Look for people that are passionate about solving them and help them to do so. There is definitely a sort of overwhelming default that you need to correct towards slightly, kind of, lower hanging fruit – easier problems to solve, easier populations to focus on – that takes actively correcting, it doesn’t just happen organically. That is, in at least our experience, hugely down to the person or people that are at the helm. What do they care about? What’s going to keep them getting up in the morning?
Entrepreneurship is super tough and it takes quite a lot of commitment and energy and time and risk and resource. You really want to believe in what you’re doing. I think, in the context we’re in – trying to kind of tackle, create scale commercial solutions that are also tackling important social problems – we are looking for people that are not just kind of committed to ambition and scale, but also to very specific problems that they will jump over lots and lots of hurdles to try and tackle, including often fighting back against investors and trying to persuade partners that what they’re doing is important and worthwhile.
I think in research, we often try to distance ourselves from that type of attachment. We try and be the objective voice. Actually, in the early stages, especially of entrepreneurship, one of the things I’ve realized is, when we have entrepreneurs going out doing user testing and user research, that is often when they start to build this incredible kind of empathy and attachment and connection to the problem, which is the fuel that then drives them forward. That personal or professional deep connection and commitment is so important in keeping them going.
Public access, information, and understanding
Rachel: The other thing that you touched on is to do with the kind of the nature of psych research and the history, and evolution, and how that’s been progressing. To me, that raises something: We’ve been talking about disconnection and fragmentation, and to me, that brings up what I think is one of the most important disconnections and fragmentations, which is a disconnection with sort of public perceptions of science and research and evidence, and the impacts of the replication crisis, and fragmentation itself is having on trust and confidence and understanding of science.
I think we’ve seen that pretty clearly over the last 12 months as well. I really think we have some way to go in improving communication and accessibility of research findings. You talked about journal paywalls at the start, but having access to paper doesn’t help if you can’t digest the content. There’s a real risk of an echo chamber or multiple echo chambers. I think that a lot of the people that read accessible research summaries, or really good science journalism – of which there’s been some great examples during the pandemic – or go to science fairs, tend to be the kinds of people that are already interested in science.
One of the things that I have been noticing and worried about over the last 12 months has been the expectation a lot of people have that science is about providing facts and certainty when it’s kind of the opposite. There’s a quote that I really like, which I won’t do justice to in paraphrasing, but it’s along the lines of, that science is about reliability, and it’s reliable because it’s not definitive, and it’s the reliability that we need rather than certainty. But I think that there’s quite a big gap in, kind of, public perceptions of science, both science in general as a pursuit and specific scientific findings.
To come back to behavioral science, I think that’s really been the case because we’ve got a whole bunch of pop psych textbooks and have had, which have been incredibly engaging and did a really good job at raising the profile of behavioral science, but which have also created an expectation of certainty and facts in findings that have since not replicated or been debunked. I think there’s a whole bunch of issues related to fragmentation there that are, in some ways, even more important than the fragmentation we’re having within ourselves and the scientific community.
New people discover new problems
Brooke: One of the things that you mentioned in that last chunk was about how it’s very problem-led, I think, that you really want to get people who are hooked on a problem that they want to solve or perhaps hooked on a community that they want to help. One of the things that I found so interesting about Zinc is the way that you map out the problem landscape, and you decide where in that landscape you want to focus. What I find so innovative there is that, by going after neglected problems, you pull in neglected entrepreneurs and neglected groups of innovators and entrepreneurs, which I think is so interesting.
I would ask you to just kind of elaborate a little bit about how it is that you do that and the impacts that you see downstream from this kind of early moment of choosing who’s going to show up and who’s going to be at the table for these conversations, and two years later, how do you think things are different in virtue of you having done that upstream?
Rachel: Yeah. Let me give you a concrete example. The most recent venture builder we run was centered on the mission of adding more years of high quality to later life, so, a healthy aging related mission. In the run-up to that, I spoke with a bunch of academics, mostly in the UK though, not exclusively, who work in various aspects of gerontology and aging, and asked them to talk me through what they consider to be the most important neglected areas. If they had a chunk of money or resource, or if they had 50 entrepreneurs, where would they want their energy to go?
That meant that, in addition to doing quite a lot of literature analyses and reviews, we were able to start the program working with a whole bunch of experts and partners and our own in-house team, not by dictating where our entrepreneurs needed to go – because for the reasons we’ve just described, it really needs to feel, to be authentic to what they really care about – but at least to be able to say, ‘Here are some issues that we know are underserved, here are some groups that we know are underrepresented,’ and to be able to shine a spotlight on those in a way that gets people interested.
We do that in a number of different ways. We have a kind of residential to start off the programs where we bring everyone to a particular area, where we work with local community groups and charities. It’s a way of partly starting as we mean to go on around user centered design and not staying in a boardroom in central London with Post-Its, but getting out and talking to people and working with people and understanding people’s needs. That’s important.
I think I’ve said this before in other settings, but I think it has definitely been the stories that our entrepreneurs hear from people that stick with them, as opposed to me or a colleague saying, “79% of people are….” It’s really the kind of human stories that get them energized and motivated. I think the additional element is we bring in experts often academics, but also people that work in charities, people with lived experience, people that work in government and policy. We ask them to give a talk that, in some ways, is kind of being a sales person for the problem they most care about.
So, giving them the opportunity to sort of present their problem as something that needs tackling as a way to get people interested in finding out more. We put a huge emphasis on not just problem-led thinking in general, but particular types of problems that we think are particularly important to solve. I think, in terms of kind of downstream impacts, it’s early days. We started in 2017, so our oldest startups are still less than three years old. But we have definitely seen, I think, among the people that have been most passionate about problems, they’ve kind of really stood the test of time. Yeah, I think there’s a responsibility and an opportunity for us to redirect this incredible amount of energy and resource in the right direction.
Bringing a human face to the data
Brooke: You mentioned stories. The human stories are what get people hooked, not the stats. The relationship between evidence and anecdotes, the relationship between statistics and narratives is a challenging one. I mean, our training as researchers, for the most part, kind of minimizes the importance of anecdotes. At best, they’re sometimes portrayed as like this kind of way to just feel some kind of human connection to what the numbers are telling you.
At worst, they’re portrayed as these grotesque distortions of reality. But those really need to live together. The ability of statistics and narratives to live together is the ability of researchers and entrepreneurs to live together. How do we get over the hump of these things often being portrayed as so distinct from one another and not really understanding the relationship between them? Is there something in the process that you have at Zinc that helps to mediate those conversations, to help people to see the thing that they’re looking for in the discussions with the other?
Rachel: Yeah. I mean, the key word here is ‘triangulation’. Well, the first thing to say is that some of our entrepreneurs are researchers and scientists. We end up attracting quite a lot of people that have come out of PhDs and are wanting to build a new product or service. So, the founders or early hires themselves are scientists and researchers. The key thing I think is about finding the synergy and complementarity rather than seeing them as kind of diametrically opposed. Because, for example, we do a lot of pre-work in signposting to particular areas – which is often based on stats and data and trends and published research – then within the kind of early stages of the program, we’re essentially trying to bring those to life through stories.
To me, they’re not at odds with each other. They can be used really complementarily together, but it’s partly back to this point about understanding the nature of science and making clear, as long as people understand the nature of the data they’re dealing with and its various pros and cons, I think it’s fine. I think where you get into risky territory is where, which you do see a lot, especially in the hype-filled world of tech innovation, people kind of using data misleadingly, knowingly or unknowingly, that’s a problem.
I think we really need to push back hard against that, getting to good quality data and evidence.
To summarize and move forward
Brooke: Right. This conversation has been an amazing kind of journey of a whole bunch of different topics that I think are really germane to the kind of work that both of our organizations are trying to do, and to a lot of the work that our listeners out there are either already doing or interested in doing. What I’d like to do now is snap back to the extremely practical, like: What’s the thing that I should start doing tomorrow morning if I’ve just been drinking all of this in, and Just waving my giant foam finger and cheering on all of the discussion that’s been happening up to now?
If I can sum up a little bit of what we’ve discussed and my understanding is that this lines up, in some respects, with the work that you’re doing at Zinc. The first is, start from the problem, but get diverse views in, really early on about what the most pressing problems are or what the most pressing facets of the problem are. In terms of the people that you’re bringing in, look for individuals who are either accustomed to, or willing to, swim against the flow a little bit, but also identify where the flows are that push hardest against them, because you need to create some kind of bulwark to protect them.
If you don’t have some kind of safe space for experimentation, you’re just going to exclude a lot of people who have a lot of value to bring to the table. Because certain people are able to take on that risk and others are not. Let’s just say that’s not a neutral filter. Once you’ve done that and you’ve got the people there and you’ve created this kind of protected space, where they’ve got a bit of runway to get something off the ground, then there’s a really, really important facilitation role that needs to be played. So, you’ve got people who are probably coming from different backgrounds and have different, kind of, styles of conversation and different priorities and different things that they’re looking for, both in the way that the conversation happens and in the kinds of outputs that they will be hoping for, or expecting to come out of the collaboration, to have that facilitation role there to mediate these differences of background, differences of expectation. Is there something there that I’ve missed in encapsulating that process?
Rachel: I think that’s a really nice summary. A couple of points that I would add. One is the importance of sharing. We’ve seen these really positive trends around open science. In other domains, we’ve seen the likes of GitHub and other collaborative platforms that have done a good job at transcending silos. I think there is an opportunity for us as an academic and applied behavioral science community to really step up the nature and quantity of our sharing, building on the momentum from those types of initiatives. I’ve spoken about, for us, that’s about capturing the learning from our ventures, the kind of trail of breadcrumb that’s left through their successes, their failures, their pivots, and everything in between.
That’s not just about sharing at the end. It’s also about moving away from this mentality that we all work away in our own little bubbles in private, and then at some point when we’ve got a shiny output, we present at a conference. I think it’s more so like drawing back the curtains the whole way through, and where possible, letting people see the inner workings, learning from the process as you go along. I think it’s really important that we change the sort of default around that, especially in the applied community, understanding that there will be organizational constraints.
But again, is there a way that we can mobilize towards this common purpose, where if we all agree that it would generally be helpful for us to share more, how might we make that happen in a way that is possible and feasible and desirable to as many organizations and individuals as possible?
Brooke: Yeah, that’s really nice. I think that that adds this kind of meta-layer to what it is that I had summarized, where you’ve created these propitious conditions for the innovation team to be doing their work, but it’s important to keep that innovation team connected to the wider knowledge community. One point that I kind of tag onto that is the importance of keeping that innovation team connected to its wider corporate setting as well. There’s this insight – which I think comes from Eric Reis – the idea that he puts out there is not that the innovation team needs to be protected from the rest of the organization. It’s that the rest of the organization needs to feel that it’s protected from the innovation team.
Essentially what’s happening there is the business is creating the means of its own disruption, and the people who are kind of in this – what we would call in the research world, “normal science world,” the people who are doing what is now core business – see the innovation team as creating the core business of the future that’s going to displace them and make them redundant or obsolete. In the same way that the innovation team needs to be opened up and more connected with its surrounding knowledge world, we should also think about how it is that that innovation team is opened up and connected to the wider corporate world in this safe way that neither of them sees the other as a threat. That people see the people who are in the current core business, see what’s going on in that innovation world as actually just the next stage of their evolution, not as their upcoming extinction event.
Rachel: Yeah. A nice example of that, or a nice analogous example of that, to me is the potential fit between designers and behavioral scientists. Quite a few of my former academic colleagues who’ve moved out of academia are now working with designers, and experienced this initial tension of like, ‘We’re sort of doing the same thing, but in a different way, and there’s definitely a middle section of the Venn diagram that we’re battling for,’ and who have over time universally found this incredibly productive relationship, but it took a little bit of wrestling to start out with.
I think that’s a really good point. The additional point, which is important, is the mentality – you call it an innovation team, but if we’re talking about behavioral scientists in the air quotes, real world – it is also about the mentality that we have. To me, there’s a real need to move out of peer review mode, out of critical evaluative, academic high horse default mode, and into a collaborative, constructive collegiate atmosphere. I think that’s partly building a reputation of science that we have boundaries and have our own values, and what can be helpful and collaborative and productive working with other teams in other organizations.
I think there’s something too about the way that we approach it as scientists, kind of keeping our own values and beliefs in place while also being maximally supportive and collaborative and open.
Brooke: That strikes me as such a wonderful note on which to wrap up this conversation. Rachel, thank you very, very much for your time and your generous insights today. We really appreciate it and we hope to have you back soon.
Rachel: Thank you so much for having me. It’s been a pleasure.
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