by NADINE LEVIN, Facebook
In the fall of 2016, I made the jump from academia to UX research. As opportunities for permanent employment in the social sciences are becoming more and more scarce, this move is becoming increasingly common. And yet, I made this transition with few resources or mentorship, feeling unprepared and unsupported by my discipline.
During my undergraduate and postgraduate studies, I was self-confident and passionate about my work. But after a couple of post-docs, a handful of scholarships/prizes, several “you were our second choice” responses to tenure track job searches, and a full book manuscript that got rejected by a press (which shall remain nameless), I found myself unhappy and full of self-doubt. Worst of all, I became increasingly pessimistic—not just about academia, but about life. So, I decided to try out industry. I left my NSF postdoc (and bewildered mentor) three months early, and started exploring jobs in the tech sector.
During this liminal time, a friend of mine mentioned that some companies hired social scientists to do work in a field called “UX research.” I scoured the internet for articles describing what UX research was and what the jobs were like. Reading articles like The Atlantic's “Anthropology Inc.”, I was intrigued that industry might find my anthropological skills useful. I found websites that listed the top methodologies, but I had a hard time figuring out where my skills from academia fit in. I found a few articles describing “success stories” for UX research, but the research process was still a black box. I found tons of reviews on Glassdoor from people who had gone through UX interviews, but I still didn't understand what people meant when they said the word “impact”.
Essentially, none of these online resources helped me understand how to convince a company to hire me, how to translate my skills into the language of industry, or what to expect in this very different role.
As I started interviewing, I learned some hard lessons. In my first interview, I presented my theoretical work to a team working on self-driving cars without showing what my actual skills were. In my second and third interviews, I couldn't speak to any “impact” I had during my academic work, because I thought impact was only about product metrics. To avoid these mistakes, I had to go through the process and I had to network. Looking back, there are so many simple things I wish someone had told me, which could have made the transition from academia to industry smoother.
Talking about this transition from academia to industry shouldn’t be taboo. We need to “unhush” these conversations to empower PhDs and post-docs to make educated decisions about their career options, and to create working models that people thinking of transitioning can look to.
Those of us who have made the jump from academia to industry give out lots of advice on LinkedIn or to former academic peers. But this approach doesn’t scale, and it doesn’t create sustainable resources for others to use. So here I’ve collected my “top 10” pieces of advice to help anyone who is thinking of transitioning from academia to industry.
- You will have to learn, and use, methods other than ethnography. UX research is often scrappy, and that means using the best tool for the business and research question at hand. Sometimes, a question needs to be answered with a survey, and other times, it can be answered with exploratory ethnographic research. Unlike in academia, in industry you don’t need to be an “expert” to use a methodology. Many companies won’t care if you are a "quantitative" or "qualitative" expert, and instead will expect you to utilize a wide range of methods and approaches. You should be prepared to learn new methods (and, it can be fun!). It’s helpful to think of ethnography as a lens, and to embrace the diversity of methods that can be used within an ethnographic framework.
- "Ethnography" in industry might not be the "ethnography" you recognize from academia. The definitions for "ethnography" are much looser in industry than they are in anthropology, sociology, communications, STS, and other academic disciplines. Researchers in UX, marketing, or design might refer to any in-context interaction—one day of immersion with a participant or a series of in-home interviews—as ethnography. I've found that instead of policing these disciplinary boundaries, it's more helpful to focus on what your ethnographic training can bring to the table that other disciplines (e.g. psychology, neuroscience or behavioral economics) can't.
- Your job will be collaborative, and your success in your job will depend on your ability to work with others. One of the best aspects of working in industry is that you don't have to work by yourself. Instead, you get to work with a team of people who might have different backgrounds and roles. At Facebook, researchers work alongside designers, engineers, and data scientists, and everyone is working on a common problem and toward a common solution. This is amazing for combating the loneliness that comes with a lot of academic (especially social science) research, but it also means that you have to learn to be a team player. Translating the substance and value of your work, so that people with different backgrounds can understand it, is an important and daily part of your job.
- You will be expected to offer solutions, not just critiques. In academia, we get taught to question everything and to be critical of systems that we take for granted. This is an amazing skill, and you should never let go of it. But in the real world, we have to learn how to turn criticism into something constructive. Tone and delivery matters a lot (I learned that the hard way!). It will be your role, even if you don't feel equipped to do it, to help people come up with solutions to the problems that you identify. If you only deliver criticism, it will hold you back in your career.
- "Impact" means change, and you need to learn to show this in your job applications and everyday work. It isn't good enough to say you did a study with x number of people, that your study had a theoretical finding, or that the finding is inherently “important”. You need to clearly articulate what change that study made: Did it change the way people framed a problem? The way an organization pursued its key goals? The way a process, service, or product was developed or used? Even if you've never made it outside of the walls of academia, you should think of some way to frame your work in terms of the change it has made. This will help you get hired, and it will help you when you start delivering your research to a company.
- You will be expected to deliver work on a shorter time frame than you ever imagined. Most projects at Facebook take place over a two to three week period, from planning to communicating out results. Sometimes, we're expected to turn things around in a matter of days. Even the longer projects in the business world are relatively short compared to projects in the academic world. This means you have to prioritize what you work on, ask a question at a smaller scope, pick the right method, and focus on delivering something of value on time, even if it's not perfect. This can be really hard if you come from a PhD program, where you've spent years perfecting a single artefact like your dissertation.
- Your job will be 50% research and 50% networking (at least) to sell/socialize that research. In academia, the end goal of a project is usually a publication, like a book, a report, or a journal article. In industry, writing a report is just the beginning. You need to spend an equal, if not greater, amount of time telling people about your work, why it matters, and why they should care. You need to figure out how different formats—reports, short presentations, videos—are useful to different kinds of people. You need to spend time garnering support and buy-in for the project well before it starts. (This is actually the way academia works as well, but no one tells you that.)
- You will probably be hired at a more junior level than you expect. When I first started my job, I thought that since I had several years of postdoctoral experience after my PhD, I should be hired at a senior level. I thought, this job is basically like getting a tenure track job. I resented being hired into a more junior level, and it ate away at me. Only a year and half later did I look back and realize that I was hired in at my level because I had a lot of learning to do in terms of executing basic industry research methods, communicating out my research, interacting with stakeholders, managing multiple projects. After being in a junior role for so long in academia, it can be frustrating (and feel like a demotion) to get hired into a junior role in industry. But it's an opportunity for you to learn, and it's ultimately setting you up for success without the pressures of immediately performing at something you haven't really done before.
- If there's a particular job you want, you should do a few practice interviews before you go for that job. With a PhD or Masters in hand, you have the skills required to get a job in UX. But your main obstacle will be translating your skills into the lingo of the UX world. My top piece of advice for overcome this barrier is practice. Don’t spend your time taking courses or learning new methods. Instead, do mock interviews based on questions you find on Glassdoor, and apply for jobs that aren't your top choice first so that you can get a sense for how interviews are done and get better at them.
- Use your network to get a referral from someone you who works at the company you’re targeting. When you submit a generic application on the internet, the chance that the right recruiter will see it is very low. The best way to get through the first part of the interview process (which is usually an informational interview with a recruiter) is to find someone on LinkedIn who works at the company and—even if you don't know them—ask them to submit your resume. While you're at it, use your networking skills to reach out to them and have an informational conversation to see if the role is a good fit. Industry conferences like EPIC are a great place to meet the people who can refer you.
Some graduate schools are starting to understand the importance of preparing students for the job market beyond the academy—as well as the value of the contributions that researchers in private, public, and non-profit sectors are making to our disciplines. But the progress is slow, and our community of practice, rather than the academy, is still the best place to learn about this transition.
Because this blog post is meant to be a communal resource, please use the comments section below this article to add resources that have been helpful for you and share your stories and advice.
Arnal, Luis and Roberto Holguin. Ethnography and Music: Disseminating Ethnographic Research inside Organizations. EPIC Proceedings 2007.
Churchill, Elizabeth. Ethnographic Lens: Perspectives and Opportunities for New Data Dialects. EPIC Perspectives, 26 September 2016.
De Paula, Rogerio, Suzanne L. Thomas and Xueming Lang. Taking the Driver’s Seat: Sustaining Critical Enquiry while Becoming a Legitimate Corporate Decision-Maker. EPIC Proceedings 2009.
Habecker, Shelly. Advice for an Anthropologist Breaking into Business. EPIC Perspectives, 5 February 2018.
Hasbrouck, Jay. Beyond the Toolbox: What Ethnographic Thinking Can Offer in a Shifting Marketplace. EPIC Perspectives, 10 March 2015.
Lombardi, Gerald. The De-skilling of Ethnographic Labor: Signs of an Emerging Predicament. EPIC Proceedings 2009.
Payne, John. From Experience Models to Immersion Tools: Transferring Ethnographic Knowledge in an Agile World. EPIC Perspectives, 14 August 2014.
Radka, Rich. Enabling Our Voices to Be Heard. EPIC Proceedings 2007.
Reese, William, Wibke Fleischer & Hideshi Hamaguchi. Hyper-skilling: The Collaborative Ethnographer. EPIC Proceedings 2010.
Robinson, Rick E. “Let’s Bring It up to B Flat”: What Style Offers Applied Ethnographic Work. EPIC Proceedings 2009.
Rohrer, Christian. When to Use Which User-Experience Methods. Nielsen Norman Group, October 12, 2014.
Speakman, Robert et al. Market Share and Recent Hiring Trends in Anthropology Faculty Positions, Figure 3. PLOS ONE 13(9). DOI: https://doi.org/10.1371/journal.pone.0202528.
Teehan, Geoff. Facebook's Product Design Director Explains One of Its Biggest UX Changes in Years. Fast Company, February 24, 2014.
Yury, Carrie. Breaking It Down: Integrating Agile Methods and Ethnographic Praxis. EPIC Perspectives, 4 August 2015.
Wood, Graeme. Anthropology Inc. The Atlantic, March 2013.
Here are some resources I’ve found useful. Please add yours in comments, focusing on recommendations oriented toward early-career professionals and folks transitions from academia to industry.
Cultural Anthropology. Academic Precarity in American Anthropology: A Forum. Member Voices, Fieldsights, May 18.
Duckles, Beth M. What I Wish I Had Known before Leaving Academia. 13 March 2018.
Ulaby, Laith. Getting Started in User Experience and Design Research. December 10, 2018.
White, Bill. It Is OK to Use Your Anthropology Degree in Another Industry. Succinct Research, March 26, 2018.
Ethnography Hangout Slack - hosted by EPIC, Anthrodesign, and Ethnography Matters.
Anthro-Meets-UX (Google Group) - Request invitation
Anthrodesign - fill out the form to join.
Nadine Levin is a molecular biologist turned anthropologist of data turned strategic tech researcher. As a mixed methods UX researcher at Facebook, she uses ethnographically minded qualitative methods to challenge assumptions about how and why various populations use Facebook. She also leads a Research Bias Initiative, which focuses on educating researchers about how to do more inclusive global research. Prior to Facebook, Nadine was a researcher at University of Exeter and UCLA; she's also done collaborative research at the Imperial College London, Cambridge University, the European Bioinformatics Institute, and the Scripps Research Institute. She is currently finishing up a book called "Metabolizing Data". Nadine's PhD from Oxford University, funded by a Rhodes Scholarship, explored the challenges researchers face as they try to integrate big data into biomedical research.