Outside The Matrix: Tiina Likki

Tiina LikkiDr Tiina Likki is a Senior Advisor at the Behavioural Insights Team in London where she focuses on labour market and welfare policy. Prior to joining the BIT, she completed a PhD in social psychology at the University of Lausanne where her research focused on public attitudes towards the welfare state in Europe. She also helped set up Tänk, a think tank that aims to introduce to an evidence-based, behavioural science approach to public policy in Finland.

Tell us about your work: how does decision making psychology fit in it? 

I’m a social psychologist by training and work for the Behavioural Insights Team (BIT). BIT is a former UK government unit, now a social purpose company that applies behavioural science to policy-making. My current focus is on employment and health and, therefore, I spend a lot of time looking at how the government could better support people getting back to work, or to stay in their current jobs. As a social purpose company, we cover a range of policy areas including education, financial and consumer behaviour, crime, international development, and energy and sustainability. Helping people and societies achieve good outcomes in these areas often boils down to supporting people in ways that allow them to make the right decisions.

Why you decided to go into industry instead of continuing in academia?

Towards the end of my PhD, I became increasingly passionate about the popularisation of science and evidence-based policy. I felt that findings from social psychology and behavioural science were incredibly important and that they should be more widely available for everyone to use. Some academics such as Richard Thaler and Carol Dweck do a great job of sharing their findings through accessible books, but many never make it from journal pages to policy-makers’ reading lists. In my current capacity, I am able to share and apply this vast scientific knowledge to deal with issues that affect large parts of the population. At BIT I have the benefit of being able to run randomized controlled trials and maintain close ties with academics, so I feel like I’m getting the best of both worlds.

What do you enjoy the most in your current role?

I enjoy how the role requires me to look at things from many different perspectives – those of the user, the client, the academic and the civil servant. This requires developing different skillsets in parallel, which can be challenging, but also very rewarding. I get incredibly excited when I get to apply the latest evidence to real issues. For example, I have been reading a lot on mental contrasting and implementation intentions which describe how to set effective goals, maintain the motivation to pursue them, and ensure you take the necessary steps to achieve your goal. I have been using this literature to develop coaching methods for people who are unemployed. I recently came across an article on the same methods in the Harvard Business Review. It is fascinating that the same theories can be applied to both jobseekers who have been out of work for a long time, and to high-level professionals looking to advance in their careers.

Do you see any challenges to the wider adoption of decision making psychology in your field?

I feel that there is an increasing openness among policy-makers globally to make behaviourally informed policy. The huge interest created by the recent BX2015 conference was a really positive sign. In the UK, having the support of past and present senior civil servants, such as Jeremy Heywood and Gus O’Donnell, has really helped a wider audience to see the value in behavioural insights. In my experience there is a real interest among civil servants to learn more, and the number of senior decision makers who have read books like Thinking Fast and Slow and Nudge has grown steadily.

How do you see the relationship between academic researchers and practitioners?

This is a relationship where everyone stands to win from engaging genuinely with each other. Practitioners can gain some truly useful tools and ideas, as well as support in evaluation, while academics can gain an understanding of where their research will have the biggest demand and impact. There is certainly room for more academic institutions to run workshops inviting representatives from policy and industry to share their challenges. Similarly, students could learn a great deal from hands on projects that allow them to apply the behavioural theories they have learned.

What advice would you give to young researchers who might be interested in a career in your field?

If you are about to start academic work in this area (as a student or researcher), see if there are ways to partner with another organisation for field work or results sharing. This will give you a taste of running more applied projects and will help determine whether you enjoy it or whether you prefer to stay in a more traditional academic setting. If you enjoy the experience and decide to move into industry or policy, your applied research experience will give you a strong head start.

BIT profile | LinkedIn

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Outside The Matrix: Paul Picciano

pmp.headshotIn our first 2014 Outside The Matrix interview  we meet Paul Picciano who is a Senior Human-Systems Engineer at Aptima, Inc., a leading human-centered engineering firm based near Boston, MA. At Aptima, he applies a diverse set of cognitive engineering methods to improve human performance in the military, intelligence community, air traffic management, and health care. His approach to supporting humans operating in complex environments leverages system design and training to enhance decision processes. Dr. Picciano earned a Ph.D. in Cognitive and Neural Science from the University of Utah, a M.S. in Human Factors and Ergonomics from San Jose State University, and a B.S. in Mechanical Engineering from Tufts University.

Dr. Picciano was also one of the speakers at the InDecision dinner for young researchers organised at the recent Society for Judgment and Decision Making conference in Toronto. 

Tell me about your work: how does decision making psychology fit in it? Most of the work we do involves human operators that must collect data from the environment, analyze and make sense of the input, and select and execute a course of action. The conditions under which they work typically involve uncertainty and time pressure, modulated by goals, objectives, and priorities that change over time.

My favorite part of the job is getting out there and observing and interacting with the experts (and sometimes novices), performing their craft. This has garnered provided access to operating rooms, air traffic control towers, Navy ships, and various command centers for organizations ranging from the Air Force to the CDC. When it’s time to run a more controlled study, there is great access to high fidelity simulators at some of the top government and academic labs.

At Aptima, psychology plays a large part in much of our work.  We provide services such as training, organizational analysis, and system design, by employing practitioners from industrial/organizational, cognitive, and neural disciplines across our portfolio. Most of my work is rooted in cognitive science, looking at perception, attention, and decision making as a mechanism for behavior and resultant task performance. It’s critical to understand how people process information. Empirical findings continue to demonstrate the magnitude of the influence of environments and decision architectures on the human operator in all domains.  Many operators confront stressful situations, data overload, and conflicting objectives, so having a grasp of these psychological aspects help us design more accommodative systems and better training programs to prepare them. But of course, we don’t always get it exactly right…

Why you decide to go into industry instead of continuing in academia? I was in industry before I went to graduate school – I worked for five years after college, and thought I would just go back for an MS and return to the workforce. Plans changed when I realized how much I enjoyed being back in school and doing applied research (at NASA Ames). I found Aptima during this time and was tempted to leave, but  I decided to continue school.
One might ask why I didn’t change my target over the next few years. First, I was committed to completing the PhD program. Second, I continued to be enamored with the academic environment. It is a great opportunity to interact with bright colleagues and an energetic student population with the benefits of a flexible schedule. I was even able to coach lacrosse in grad school and that may have been an option if I had chosen to work on campus long term.
However, I really enjoy the diversity a consulting role provides, interacting with customers in a wide range of domains and problems. I believed industry would provide me more of those experiences and greater opportunity to travel to see different types of operations. I was also very fortunate to find advisors that supported my path away from academia.

How did you first become interested in decision making psychology? Psychologists run such clever experiments. That’s probably what hooked me. The experimental designs and results from people like Milgram, Festinger, Tversky & Kahneman, Loftus, and Ariely are not just fascinating, they’re also actionable. Designers of systems, policies, and organizational structures can leverage these finding to make things better.

I view so much of behavior as a result of decision making – whether it be implicit or explicit, automatic or deliberate, intuition or reason mechanisms as the driving force. Even at the perceptual and instantaneous level, these reactions I still see as decision making. In the heart of the NFL playoffs now, the analysts always talk about quarterback decision making. These are trained, perceptually-driven, goal-directed actions that are dictated by the environment, expectations and training. Similarly, coaches are making decisions on fourth down and general managers are making draft decisions. For all of these decision types, there is a great deal in the scientific literature that could improve these decision processes (if any NFL owners are reading this I can make myself available for a consulting gig!)

What type of research do you find most interesting, useful or exciting? In my opinion, the most valid research emerges when we have the opportunity to marshal a diversity of research techniques that includes observations in naturalistic settings, high fidelity simulations, and tightly controlled and focused research settings. Converging evidence from these perspectives offers the best opportunity to build a strong case for your findings. However, rarely can we pull all of that off in a single project. There usually are not enough resources to cover the problem space to this degree (the government labs seem to more often have the time and funding for such investigations). It’s pretty impressive how realistic well-crafted simulations can feel to participants. We have been able to make senior physicians and air traffic controllers break into a sweat even though no human lives were ever at risk.

One of my most exhilarating days of “research” involved observing the training procedures for landing U2 aircraft. The U2 has a long nose making it difficult for pilots to see the ground. The training method involves other pilots on the ground guiding the aircraft down by calling out the number of feet the jet is above the ground just prior to touching down (“15ft…10ft…8ft…etc.). These callouts come from fellow pilots in zippy little sports cars waiting for the U2 to pass overhead and then chase it down the runway at over 100mph. I was fortunate enough to ride shotgun in one of two chase cars that followed down the runway, in formation, close enough to make accurate distance calls between the landing gear and the runway.

Do you see any challenges to the wider adoption of decision making psychology in your field? There are always challenges; one constantly in need of solutions is that of establishing useful, collectible measures. Part of this requirement stems from the responsibility of presenting a strong return on investment (ROI) argument. In research and development, technology often grabs attention and funding.  It is compelling when a company makes a battery that is small and has longer life – that’s justified spending. It’s more difficult to convince a sponsor that you have improved the decision making process for a group of analysts. The bright side is the military is responsive to decision making research. There are specific programs (and funding) in place for efforts such as training small unit leaders and building decision support elements for tasks including weapons deployment, intelligence analysis, and air traffic management.

How do you see the relationship between academic researchers and practitioners? I think the classic model is that academia is doing the ”basic science” and practitioners are applying that science, to real world problems. I believe it is much more that. We have great partnerships with universities on many active projects, and they are involved in the full range of project activities. They are more than just a place to run first year psych students through a basic experiment.  They are great thought partners and often the first to have produced or read about a new study. Many academics have security clearances, and many are consulting on the side. This makes it easy to engage them on a few levels beyond traditional roles. I also believe that practitioners can help develop new problems of interest for academics to investigate. We really enjoy our interactions with academia.

What advice would you give to young researchers who might be interested in a career in your field? Don’t be afraid to shape your own future. Figure out what you really like to do. Find companies and people that are doing that type of work and engage them. Don’t be frustrated by the fact that your keyword search returns 0 matching job titles. This is a growing field, and most people don’t know much about it. Tell them about it. Show them how you can be useful. If you can help them understand or even predict (with some accuracy) the decisions that will be made by their clients, staff, or management, you can be useful to them. Show that you can help them design choice architectures in their favor, impacting their bottom line, or contribute to community improvements-it will be hard to ignore you.

In my job search, I looked for companies, not job titles or employment ads. Go to conferences and interact with as many people. They won’t all help you, but many are willing. Build your network. There is so much going on out there, so many roles that we don’t even know about. Get yourself out there so you can stumble upon it.

Paul’s profile on Aptima website (incl. publications)

Outside The Matrix: Florian Bauer

Bauer-Florian_Druckvorlage
Following on from Kiki Koutmeridou, we’ll continue this week with another Outside the Matrix interview: Florian Bauer from Vocatus AG in Germany, who studied psychology and economics at the Technical University in Darmstadt, at MIT, and at Harvard University. He has devoted himself to research into behavioural economics and the psychology of pricing, which were also the subject of his doctorate (“the psychology of price structure”). Starting his career as a strategy consultant at Booz, Allen & Hamilton 1996, he joined with two colleagues in founding Vocatus AG (a full-service market research and consulting company) in Munich in 1999. He’s also a member of the board of the German Market Research Association (BVM), and regularly teaches as a visiting professor at several universities in Germany. In 2005 and 2010 he won the ‘German Market Research Award‘ for the ‘Study of the Year‘ and in 2010 the ‘Best Methodological Paper Award’ at the ESOMAR Congress (global market research conference), and has subsequently won the the ESOMAR “Research Effectiveness Award” both in 2012 and 2013. 

Tell us about your work: how does decision making psychology fit in it? Well, all I do is in fact decision making research. I see market research as nothing else than trying to understand the basic building block of an economy – the customers decision making process. And here, there is no better theoretical and methodological basis than behavioral economics even though this is often neglected in classic market research approaches.

Why you decide to go into industry instead of continuing in academia? Well, it was primarily “anticipation of regret”. I had a hard time deciding which path to follow. The reason why I picked business was for one part the idea that I could regret it later not having taken the chance to start my own company. For the other part it was the fact that I really wanted to apply the stuff I was doing and put it to test in the real world. Still today, this a thrill to me.

What do you enjoy the most in your current role?  Do you see any challenges to the wider adoption of decision making psychology in your field? I love that I can do what I like most: Focusing on applying behavioral economics in marketing in general and pricing in specific. I love that we were able to attract a team of more than 70 colleagues that share the same interest and want to rock the boat. The only challenge I can see is the reluctance to adopt new approaches when the old ones are still massively promoted by large international research agencies. But quite frankly, the solution to this is to seek for more innovative clients that are willing to switch gears and go beyond the classic market research approaches. And that works quite well.

How do you see the relationship between academic researchers and practitioners? I think the perspectives are extremely different although they could profit much more from each other. While academia is focusing on a specific effect, on a specific theory, and the analysis of different ways of looking at the issue, practitioners are focusing a broader array of different questions. Where in the end they have to make a recommendation fast and still good enough.

What advice would you give to young researchers who might be interested in a career in your field? Test and decide, maybe try to do academic and market research in parallel. In any case, find your own way and do not focus on traditional career paths.

Website

Outside The Matrix: Kiki Koutmeridou

Kiki_20130929135455608Third in our series of those who moved into the private sector after completing their PhD in decision making psychology is Kiki Koutmeridou – a behavioural economics researcher within GfK NOP, a global market research agency based in London. She has a background in Psychology (BSc) and Neuroscience (MSc) and she completed her PhD in Cognitive Psychology at City University in 2013 focusing on memory and the strategic processing of retrieval cues. In her role as the head of the Centre for Applied Behavioural Economics, Kiki works in collaboration with City University, GfK and clients trying to explore how behavioural economics can be incorporated in the traditional market research.Since joining GfK NOP London in September 2012, Kiki has introduced behavioural economics theories to numerous research projects which focus on the application of academic findings to real-life situations.

Tell us about your work: how does decision making psychology fit in it? I’m currently the head of the Centre for Applied Behavioural Economics at GfK NoP, part of the GfK Group, an international market research organization. The Centre for Applied Behavioural Economics is a partnership between City University and GfK NoP in an effort to promote applied knowledge in the decision-making field. So, by definition, my work is all about decision-making psychology. I’ve just completed my PhD in cognitive psychology and more specifically in memory. When the opportunity presented itself to explore human decision-making behaviour in an applied setting, I didn’t think twice and have been working at GfK for two years now.

My role at GfK is two-fold. I contribute to the various client research proposals across the company by integrating the academic knowledge on decision-making into the suggested research design. I’m looking into ways in which the client’s research question can be answered via the various theories and findings from the behavioural economics field. For this purpose, I help at all stages of the project (experimental design, client meetings, field work, data analysis, presentations). In addition, I work in unison with several external (academic or not) collaborators to conduct fundamental research promoting applied knowledge of decision-making behaviour. As a consequence, we are in a position to subsequently approach suitable clients, to share our findings with them and to make a proposal that would be in their best interest.

Why you decide to go into industry instead of continuing in academia? Actually, I don’t think I’ve made such a decision. I haven’t excluded one for the other (yet!). Like I said, the Centre for Applied Behavioural Economics is in strong collaboration with City University. I spend a day per week at City University, where I finished my PhD, meeting with academics, discussing potential projects and visiting the library. Being still part of an academic institution gives you opportunities for collaborations, fruitful discussions and knowledge sharing. Being part of the industry gives you the chance to apply all this knowledge in the real world and observe the outcome. I consider I get the best of both worlds.

What do you enjoy the most in your current role? My role is not restricted to market research. On the contrary, I explore ways in which people can make better decisions in a variety of settings (consumer, health, financial etc…). What really thrills me is the opportunity to either apply the academic knowledge in the real world or derive new knowledge from the applied experiments towards this end. This is a two-way street that can change the status quo of how things function. The idea that I can be part of these changes gives meaning to what I do and great satisfaction.

Do you see any challenges to the wider adoption of decision making psychology in your field? While there is great conversational interest about the academic findings and some recognition of their benefits, it can at times be a challenge to encourage clients to move beyond tried and tested approaches. When I first joined the market research industry I was surprised that psychology wasn’t incorporated more in the everyday business. In every meeting about any project, the discussions were ringing bells about possible psychological theories that could be applied. But experimenting is often not on the table. However, Applied Decision-Making or Applied Behavioural Economics if you like, is still at its infancy. The challenge is to provide strong evidence of its benefits. It’s a matter of finding the right people, in the right places that can promote this line of research and highlight the benefits of decision-making psychology and its methods until they become part of the norm.

How do you see the relationship between academic researchers and practitioners? In a word: complementary. Academics and practitioners bring different but equally important elements into the equation. My current role is an example of just that: the academic environment provides new findings, old and new theories and innovative methodologies; businesses offer the opportunity to apply all this to the real world and they can provide large sample sizes (the nemesis of the academic world along with the funding). In addition, practitioners have hands on knowledge of the effects that academics describe. Collaboration between the two can only lead to better formulated, more accurate theories and predictions about human behaviour.

What advice would you give to young researchers who might be interested in a career in your field? The irony is that I’m in need of that advice too as a young researcher myself! However, based on my experience so far I have 3 suggestions

  1. Seize every opportunity as you never know where it might lead. I started working at GfK as a part-time data analyst. If you had asked me back then I wouldn’t be able to foresee my current role.
  2. Be open-minded. Nowadays, the boundaries are hazy and every field can be combined with just about any other. Do not limit your imagination about potential new applications or approaches.
  3. Be confident and proactive. There isn’t one right way of doing things so always voice your opinion. You are not supposed to know everything and quite frankly no one does. Remember that we learn more from our failures than from our successes. The important thing is to keep trying to find the answers and to keep reading around your field of interest. Brain is like a muscle – keep it fit!

Also from GfK NOP: interview with Colin Strong (In The Wild series)

Viewpoint: Why social science grad students make great product managers

Litvak
A couple of months ago we featured Paul Litvak from Google in our Outside the Matrix series. After his interview, his inbox was inundated with questions from readers and he recently wrote a response on his own blog which we thought was so fantastic we wanted to republished it on InDecision as well. So, this week Paul shares his views on why social science grad students make excellent product managers. Note: even if you’re not a grad student yourself, it’s worth reading Paul’s views in case you’re ever in a position to hire one! 

After my interview with InDecision Blog, a number of graduate students emailed asking me about careers in technology (hey, I asked for it). They were a very impressive lot from top universities, but their programming skills varied quite a bit. Some less technically minded folks were looking at careers in technology aside from data scientist. Enough of them asked specifically about product management, so I thought I would combine my answers for others who might be interested.

What does a product manager do?
Brings the donuts. The nice thing about social science grad students for whom reading about product managers is news is that we can skip over the aggrandized misconceptions about product management that many more familiar with the technology space might harbor. The product manager is the person (or persons) that stands at the interface between an engineering team building a product and the outside world (here includes not only the customers/users of the product, but also the other teams within a given company who might be working on related products). The product manager is in charge of protecting the “vision” of the product. Sometimes they come up with that vision, but more often than not, the scope of what the product should be and what features it needs to have today, next week, or next year is something that emerges out of interactions between the engineers, the engineers’ manager, the product manager, company executives, etc etc. The product manager is really just the locus of where that battle plays out. So obviously there is a great need for politicking at times as well.

But wait, there’s more! Once the product is actually launched, it is typically still worked on and improved (or fixed). So the product manager is also the person that gets to figure out how to prioritize the various additional work that could be done. But how do they figure out what needs to be changed or fixed? This is one of the places where research comes in! So someone like me might do analysis on the data of people’s actual usage of the product (the product manager prioritized getting the recording of people’s actions properly instrumented, right? RIGHT?). Or a qualitative researcher might conduct interviews of users in the field and try and abstract an understanding from that. Either way, the product manager has to make sense of all this incoming information and figure out how to allocate resources accordingly.

Why would social science graduate students be good at that?
Perhaps you can see where I’m going with this. Products are increasing in scope. Even a simple app has potentially tens of thousands of users. Quantitative methods are becoming increasingly important for understanding what customers do. In such an environment, being savvy about data is hugely advantageous. In the same way that many product managers benefit from computer science degrees without coding on a daily basis, product managers will benefit from knowing statistics, along with domain expertise in psychology, sociology, anthropology even if they aren’t the ones collecting and analyzing the data themselves. It will help them ask the right questions and to when to trust results, and when to be more skeptical. It will help them operationalize their measures of success more intelligently.

The soft skills of graduate school also translate more nicely. Replace “crazy advisor” with “manager” (hopefully a good one) and replace “fellow graduate students” with “other product managers” and many of the lessons apply. Many graduate social scientists will have plenty of experience with being part of a lab and engaging in large-scale collaborative projects. Just like in graduate school, a typical product manager will spend hours fine tuning slide decks and giving high stakes presentations meant to convince skeptical elders of the merit of a certain course of research (replace with: feature, product, or strategy).

Finally, building technology products is a kind of applied social science. You start with a hypothesis about a problem that people are having that you can solve. Of course, as a social scientist, the typical grad student understands just how fraught this is! Anthropologist readers of James Scott and Jane Jacobs and economists who love their Hayek will have a keen appreciation for spontaneous order (“look! users are using this feature in a totally unexpected way!”), as well as the difficulties of a priori theories of users’ problems or competencies. In fact, careful reading of social science should make a fledging PM pretty skeptical of grand theories. For instance–should interfaces be simpler or more complicated? How efficient should we make it to do some set of common actions? If everything is easily accessible from one click on the front page, will there be overload of too many buttons? Is that simpler or more complicated? These sorts of debates, much like debates about the function of particular social institutions or legal proscriptions, are not easily solved with simple bromides like “less is always better”, or “more clear rules, less discretion” (I am reading Simpler: The Future of Government by Cass Sunstein right now, and he makes this point very well with respect to regulations). The ethos of the empirical social scientist is to look for incremental improvements bringing all of our particularist knowledge to bear on a problem, not to solve everything with one sweeping gesture. This openness is exactly the right mentality for a product manager, in my opinion.

Conclusion
I hope I have at least partially convinced you that as an empirical social scientist, you would make a great product manager. Now the question is, how do I convince someone in technology of that? The short and most truthful answer is, I’m not 100% certain. It might take some work to break into project management, but I see lots of people with humanities background doing it, so it can’t be that hard (One of my favorite Google PMs is an English PhD). One thing I would suggest is carefully framing your resume to emphasize your PM-pertinent skills–things like, group project management, public speaking experience, making high stakes presentations, etc. You might also consider making a small persuasive deck to show as a portfolio example of a situation where you convinced someone of something (your dissertation proposal could work?). This would be a great start. Another thing is consider more junior PM roles initially–as a PhD coming out of grad school you are still going to make a fine salary as an entry-level product manager. If you apply these principles I have no doubt that you will quickly move up.

Read Paul’s original interview here.

Outside The Matrix: Paul Litvak

LitvakPaul Litvak is currently a Quantitative Researcher working on the Google+Platform team to improve people’s social experiences online. Prior to that he was a Data Analyst at Facebook working on fighting fraud, tracking the flow of money and improving customer service. He also has a PhD in Behavioral Decision Research from Carnegie Mellon and his dissertation was on the impact of money on thought and behavior. During graduate school he co-founded a boutique data science consulting firm, the Farsite Group, which is consulting for some of the largest retailers and private equity firms to improve their data-informed decision-making processes. Through these various activities he’s managed to keep a foot in both the academic decision science and business data science worlds for the last 6 years. 

Tell us about your work: how does decision making psychology fit in it? I work at Google as a quantitative user experience researcher–I use quantitative methods to try and understand how people are (or aren’t using) features of Google products with the hopes of recommending ways to improve upon them. Often times this involves running an experiment but can also often involve correlational analyses instead. Sometimes the sample sizes are so large (millions or even billions!) you don’t need to run any statistics at all–you just count the rate at which some event happened.

Decision-making psychology fits into this work in at least three ways. First, in hypothesis generation and testing, knowing which  effects from psychology are relevant in a situation gives you great product intuition. For example, you might be analyzing how users bid on ad space and remind the engineers and designers of how much the anchor matters. Second, it’s useful in designing and conducting good experiments. In online experiments you are always weighing the pros and cons of different operationalizations of user constructs (e.g. what is “engagement” or “satisfaction” in the context of a particular website?). Being able to operationalize a variable intelligently is the difference between an experiment that convinces a Product Manager to change things accordingly and one that is totally ignored. Third, decision science lets you think clearly about analytic problems that come up a lot in software design. Nowadays it is common to use some machine learning algorithm to classify some otherwise messy data. In doing so, it is crucial to be able to think clearly about false positives and false negatives, and tradeoffs between the various costs of being wrong versus not making predictions for some cases. Fundamental statistical reasoning concepts (e.g. Bayes rule) never go out of style!

Why you decide to go into industry instead of continuing in academia? For me, it was a combination of factors. First, for many reasons (some outside my control), my research hadn’t been as successful as was needed to secure a good tenure track job. In order for me to have continued I would have had to have taken a postdoc for some number of years and continue working hard in the hopes that I could get sufficient papers published. I felt some amount of despair over my floundering career. (In retrospect, I’m not sure how overblown that was.)

Also, I had always had some interest in technology and business. I majored in computer science (and philosophy–I contain multitudes!) and had an interest in technology since I was a 10-year-old programming BASIC in my friend’s basement. Meanwhile I had co-founded a boutique statistics consulting group, Farsite (http://farsitegroup.com), that had had some early successes. Through trying to sell a variety of large businesses on consulting services (which I did in between running lab studies for my dissertation) I learned more and more about the business world. We even won a few contracts! More and more, I was enjoying applying the same scientific thinking I was using in research to solve business problems, like where to put pharmacies.

There were also quality of life issues. I wanted to have a life outside my job, and that seemed close to impossible as an academic. I noticed my advisor, who was a young tenure-track faculty, worked like a madman, seemed very stressed and unhappy. (He seems better now, and might dispute my contention that he was unhappy then.) Consequently, when a job opportunity came along to work for Facebook, pre-IPO, in Austin, Texas, where my best friend was living, it was nigh impossible to turn down.

What do you enjoy the most in your current role? By far the thing I enjoy the most about my role is having a large impact on the world. While I worked for Facebook, my analyses and code affected literally millions of dollars of revenue, and helped keep the site clean of a lot of bad content that would have made people’s daily experience much less pleasant. At Google, my research has launched whole product initiatives, determined whether to keep or get rid of product features, and literally affected what millions of people see across all of Google’s products every day. I have a huge amount of flexibility to work on research projects that interest me, in part because I love working on, and am good at formulating impactful research.

Do you see any challenges to the wider adoption of decision making psychology in your field? Yes, there are at least three challenges:

1) Because of disproportionate incentive to produce positive results and an increasing amount of researchers chasing fewer dollars and jobs, I do think the pressure to cut corners has increased significantly. This is impacting the quality of research that is being produced. Not just in terms of replicability and p-hacking, but also in terms of theoretical comprehensiveness. I read a lot of papers and I can’t help but feel like decision science isn’t very cumulative. Most researchers are chasing individual findings instead of trying to integrate our understanding of decision-making into a cohesive model or theory. It feels like it’s stagnated a bit to me–the best papers I read were written in the 70s, 80s, and 90s. I think the grab-bag nature of our findings makes it difficult to know which findings to apply in a given new context.

2) Another related problem is interactions. Social scientists uncover many many effects, but in real life many different effects could be active at the same time. It’s hard to know if all these effects should be additive, or what will win out when certain psychological antecedents suggest opposite effects. Perhaps more experiments at large scale can help this.

3) A third problem is entrenched attitudes toward experiments. I’ve definitely seen companies and executives resistant to the idea of running experiments. Sometimes they are worried about what will happen if the press finds a weird version of a product or feature. Sometimes they object to a lack of uniformity and vision in a product offering. Sometimes they are just ignorant about statistics, and have basic skepticism about generalizability and research. I’m happy to say that I think this has changed a great deal over the last 5 years. Nate Silver has done some good work in this area.  🙂

How do you see the relationship between academic researchers and practitioners? I see the relationship as fundamentally symbiotic.

Academics help practitioners in at least 4 ways (even setting aside direct collaboration, which is quite common nowadays): creating new methods, discovering findings in the lab that can then be applied, creating new theories from which to base products on (e.g. Goffman’s work on self presentation and different identities could affect the sharing model in social networks), and giving a sense of context and history. The last one is particularly important for various techno-utopists out there who think that they can use technology to fundamentally alter social relations without considering the results of previous attempts to do just that.

Practitioners help academics as well; they provide lots of data and invent useful technology. Have decision scientists and psychologists started thinking yet about what Google Glass will do to transform research? Imagine field studies were you could record what the subject is seeing when they make their choice? Or think about what the second screen could offer in terms of real time experience sampling or extra information to alter a choice. The possibilities are endless. Finally, and most obviously, practitioners often have access to lots of money… which is helpful, I’m told.

What advice would you give to young researchers who might be interested in a career in your field? Three things:

1. Come talk to me. 🙂

2. Learn some programming. R, then SQL, then Python, or some other scripting language. The more programming you learn the higher up the food chain you can go. If you know a lot of programming, you aren’t limited by what data exists, but only by what data you can create. This is hugely empowering, and increases your impact considerably. However, if all you learn is R, that is still incredibly useful,and will still get you into a variety of jobs.

3. Be curious! So many useful insights come from a broader curiosity about the world. This applies to both academic and worldly knowledge. Very random papers have led me to business/product insights. Similarly, keeping curious about what’s going on in the world is what enabled me to get into technology in the first place. Keep learning!

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New series: Outside The Matrix

As if one new interview series wasn’t enough for March, we’re now kicking off a second one!

As much as you love research, you may feel like academia is not necessarily your place after all, or maybe you want to mix it with some applied work – but what else is out there? As we’ve seen from our first couple of In The Wild interviews, there are plenty of exciting opportunities for PhDs in the ‘real world’. 

But what does it really feel like to make the leap and go outside the parallel universe that is academia? What’s it like there? What skills does one need? And, most importantly, how does it compare to the academic world?

To answer some of those questions we’re speaking to people who changed gear after finishing their PhDs and moved into the commercial sector. First up we have Paul Litvak from Google – buckle up and read on!

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