Viewpoint: Why you should join an academic gang

academic gang

By InDecision Blog reporter and regular editorial contributor Troy Campbell

Question: How Do You Succeed in Academia?

To answer this all important question, let us start not with the truth, but with a myth. It is a myth that misguides so many students, and it is …

The Lonely Genius Myth

ron-burgundy-anchorman

There is a myth in our field and that myth is “the lonely genius.”

The lonely genius is the researcher with the exact right research style, who reads narrowly but broadly, writes at least 90 minutes a day, balances work and exercise, is always strategic, knows exactly how to target journals, and above all else, does it alone. The myth goes: we should all strive to be just like the lonely genius and any deviation from this standard is wrong.

The Truth of the Lonely Genius

glass-case-of-emotionBeing lonely sucks and it is not productive.

The Hidden Real Answer

anchorman-2-002

The real answer of how do you make it in academia, the source of the most variance in academic success, the holy grail of academic advice, is not a research style, and it is also not a certain work ethic, and it is certainly not that you should do it all alone.

The real answer is:  Academics succeed with the help and support of others.

People succeed in academia because they make friendships and connections with faculty, peers, and even research assistants. This is not “networking” but true “deep connections” where each partner cares about the success of the other and provides intellectual and emotional support.

In academia, you need to be tough, but you can’t be a lone wolf. Even the toughest of wolves usually can’t compete without a pack.

Recently, the importance of “others” has been greatly expressed at doctoral consortiums in the social sciences. Columbia University Professor Leonard Lee spoke about the role of senior faculty support for young faculty. University of Colorado at Boulder Professor Meg Campbell further argues this sentiment, stating that we too often neglect extended support networks. A recent study finds that even the most successful athletes are quick to mention the role of social support networks in their hall of fame induction speeches. And yes, even the great Anchorman Ron Burgundy admitted that he needed his news team.

On this website alone, we’ve documented many of the hidden ways colleaguesstudent peers, and mentors can benefit young academics.

The Method to the Madness

So if others are the answer, how can we starting succeeding with others?

#1 Never “Front”

front b

Professor Joey Hoegg of the University of British Columbia explains that in her first semester as a new professor she pretended that everything was going well with her research. Eventually, it became so obvious to a senior faculty member at the school that this was not the case. He kindly took it upon himself to mentor her and everything turned around.

No matter where we are in the process to tenure, many of those with tenure are here to help. Hoegg wasted months of her career because she was “fronting” with the very people who wanted to help her the most. Not everyone in academia wants to help you, but many do. So let those people help you.  

#2 Join a Gang

Screen Shot 2014-10-24 at 10.35.00 AM

Look at any successful professor. What do they have in common? As Northwestern University Profess Derek Rucker’s slyly expressed through a staged doctoral consortium: almost nothing. Some people are terrible at stats, writing, experimental design or public speaking but still make it.

The one similarity is they all join gangs, which is the best method to using the power of “others.”

These academics run with a crew that consistently publishes together or at least meets together. Sometimes a gang centers around a topic. Other times, it is just about a group of people who keep publishing together on many topics. Sometimes it’s a department, sometimes it’s a lab, sometimes it’s a cross-continental Skype-based collaboration, or sometimes it’s a larger field spanning movement (e.g. consider the recent movements and then sub movements in political psychology as different gangs).

To win this game (or war) of academia, you have to join a gang. This is the gang you see at every conference not just to catch up with but to push forward ideas with, who think like you and want to think about the same things. Professor Peter McGraw has noted that he never hung out with professors at conferences, he just made friends with peers who then become great colleagues. And Professor Dan Ariely notes that most of his collaborations started with friendship. Quality relationships make quality use of the power of others.

#3 Ask

ask

So how does one join a gang or get help?

Ask. It may be the most cliché answer, but it is the right answer.

To get help and start research collaborations, you have to ask. Ask for your advisor to bring in other people on a project so you can start entering the larger world. Let the faculty know your struggles and let your friends or conference acquaintances know you’d love to talk about research. Go to all the sessions on a single topic and don’t just sit, but engage with people. Professor Fleura Bardhi also advises getting involved with your local community as another way to jumpstart your involvement.

Remember the first step to doing things not alone, is to show up to the party so very alone. You have to make the initiative, not just receive or rely on your advisors to “hook you in.” You will never make friends if you don’t show up to the party, ready to discuss.

The All-Important We

happy team

We succeed in academia when we can turn the question what should I do? into what should we do?

So find others, join a gang, and then you can start slaying it as a researcher. Whatever metaphor you like, a gang metaphor, a wolf pack metaphor, a Fellowship of the Ring metaphor, or an economy of scale metaphor; they are all true.

People spend so much time thinking about what to research and how to research it, but not enough time thinking about who to research with. Figuring out the latter almost always helps with the former.

How to advance science and look good in a talk

Many conference presentations have become more about impressing the audience than advancing science. While presenters should, of course, strive to be engaging, impressive, and proud of their work, they should also be more open about their limitations and not view their project as a lone watershed moment in science but as a piece in an ever-advancing timeline of inquiry. Here are some ways to have presentation that will not just look good but will also be good for the scientific enterprise.

#1 Have a true and guided discussion of the limitations.

Let’s be honest: there’s probably no chance that you’ve tested your theory in the absolute best way possible – funding and constraints almost always prevent this.

There’s also little chance that you’ve removed 100% of the potential confounds. If you have any doubts about this, just submit your manuscript to any journal club and the feedback you will receive will make it abundantly clear that there are at least six thousands potential confounds. Psychological research is imperfect—and as Anna Kirmani and Michelle Pham have recently argued, it is important we realize this.

So what does this mean for your conference presentations?

It means you need to take control over the discussion of your limitations. Maybe you are worried about a hidden ceiling effect in the Likert measure or an undetected mood effect; mention those things. Further, tell us how we as a field could better test your theory. Maybe it is with larger more diverse samples or maybe it is with different dependent variables.

#2 Have a true and guided discussion of the relevance of your findings.

When the first choice overload studies came out, the authors made it seem that lots of choice was almost always bad. Turns out that although choice overload does exist, the original idea as the author of The Paradox of Choice Barry Schwartz explains was overstated.

Instead of looking back at how awesome their choice overload work was, in their original presentations and papers the choice researchers should have looked forward and said to their audiences, here’s how we can test the breadth of this choice overload work. Rather than assume its ubiquity for a few studies, they should have been more humble.

Recently, my colleagues and I have tried to use a humble approach by starting many presentations with the statement: “Today our only goal is to have you leave here thinking: ‘Hey, this phenomenon happens sometimes, isn’t that interesting, and shouldn’t we explore it more?’”

#3 Don’t be a theoretical imperialist and always remember the motto: “Death to Dichotomy”

Many researchers seem to feel the need to explain why their theory explains everything. This can make one can look very good and lead to a type of prominence in one’s field and the popular press. Yet, rarely is one perspective as completely explanatory as it seems.

For instance in the field of motivated cognition, people often have dichotomous debates between the existence of a motivation explanation (e.g. self-deception) versus a completely non-motivational explanation (e.g. informational differences, self-presentation bias). Scientists often try to explain lab and complex real world phenomena within one psychological theory with nearly unqualified general claims.

This leads to a theory versus theory approach. It forms a “dichotomous” view of reality when as Michelle Pham argues, this is often far from the truth. The majority of the most interesting phenomena in real life are determined by multiple factors. For example, in the case of motivated cognition, there is a synthesis of factors in self-deception that can occur due to concerns over self-presentation.

Dichotomous type of thinking does not lead to our goal of optimally advancing science. Instead of pitting psychological mechanisms against each other in absolute terms, we should develop models that allow for a multiple psychological mechanisms. We should not ask does X mechanism explain this phenomenon better than Y mechanism? Instead we should ask, when do X and Y matter most when consider phenomenon Z?

A final consideration: Does all this humble limitation focus actually improve your presentation and make you look better?

As a young scholar, I am always so saddened when I attend talks by famous scholars or rising stars in academia only to see that they are biased toward the prominence of their theories. Their self-aggrandizing style can hurt them at least in some people’s eyes. Scientists appreciate when other scientists act like humble scientists, and yes – that is only a “usually,” not an “always,” but still, it’s worth playing the percentages.

We need to stop focusing on looking good and we to need to start focusing on doing what’s good for science. Arguably, doing the things that are good for science can also make you look good.

Viewpoints: “Becoming a Professor” Podcasts

On InDecision Blog we write a lot about how be the “ideal candidate” featuring the “ideal advice.”  While advice is great, there’s something special about hearing first hand about the intimate struggles and personal journeys people had that can enlighten both those in and outside of academia.

As The Professor Job Market season dawns this year, we wanted to share four unique stories about four young scholar’s recent journeys on the job market. If you’ve ever wanted an honest behind the scenes look, this is it: four young scholars explain their non-traditional paths with frank honesty and in personally revealing ways. These podcasts will give you an opportunity to connect with their stories and hear their views on research and life outside it. You’ll also get the perspective of people who chose not to take the “top 20” school path – a perspective we have not covered as despite the fact that majority of the field does not resides in the top 20 schools.

These short podcasts are hosted by InDecision contributor Troy Campbell who is starting a series of InDecision podcasts aimed to get at both the professional and personal side of research. Note the conversations are with people who got placements in business schools – particularly marketing. If you are a nonacademic we put the podcast in order “general topical appeal.” All podcasts can be downloaded to be listened to offline (e.g. during a work out).

Jim Mourey
Being a presenter, being true to yourself, quality of life, and personally valuing teaching.
Ph.D: University of Michigan
Professorship: DePaul University
Rob Smith
Choosing not to go the top schools, quality of life, importance of teaching.
Ph.D: University of Michigan
Professorship: Ohio State
Caroline Roux
Choosing a different path: policy research and being a different type of scholar.
PhD: Northwestern
Professorship: Concordia University, Canada
Adrian Camilleri
Being interdisciplinary, reflecting on your Identity, dealing with Marketing Interviews.
Post Doc: Duke University
Professorship: RMIT University, Australia
Coming soon.

—————-

troy-resizedYour podcast host Troy Campbell is a Ph.D student at Duke University and hopeful on the Job Market this year. For some of his viewpoints and his always animated Indecision Blog reporting, click here.

Viewpoint: Life as an Assistant Professor

joebwWe recently had a chat with Joseph Redden about his happy life as an assistant professor. From this conversation, we found out that Professor Redden had a lot answers to some of the questions that stressed out graduate students often have about being a young professor so we asked him to do a Q&A with a representative stressed out graduate student.

So far, we’ve been interviewing the established greats and focused a lot on life after tenure. But as a blog dedicated in part to helping young researchers find their way, we thought it would be good to have some more posts about your most immediate concerns and fears. So here’s Joseph Redden with some guidance and comfort in the first of many soon to come InDecision Blog posts on the two topics that on all young researchers minds: the job market and being a quality young faculty member. Joseph Redden is an Assistant Professor of Marketing at Carlson School of Management at the University of Minnesota, and he is an emerging expert on the topic of satiation.


Hi Joe, I am a stressed out student in graduate school – or actually I’m not just stressed but also worried and afraid. I am worried that my impostor syndrome is not just a syndrome but real: I look at the top people on the job market recently and I just feel inadequate. I look at the greats in our field and their theoretical might and publishing powerhouse make me feel like I’ll never make in the field, and even if I can get a few publications I am worried my work won’t matter. So if you don’t mind, I have a bunch of questions... 

SOS: How stressed are you? Do you have free time?

Professor Redden: Like any academic or human for that matter, I feel like my life has plenty of stress. That being said, I do find that my stress seems to diminish a bit every year. I like to think that is not just adaptation, but rather a reflection of my active efforts to manage stress in two ways. First, I’ve focused my time more on problems that really pique my interest and leverage my areas of expertise. Second, I make sure some of the time “savings” I get from being more productive translates into free time for me to enjoy. I personally find this last point the most attractive aspect of an academic life.

SOS: What’s daily life like for you?

Professor Redden: Like any other academic, there is not really a protypical day. Some days are mostly teaching, others mostly writing, some mostly reading while others might be service. Even so, I really try to keep a regular schedule (a 9-to-5 if you will) to avoid burnout. If you don’t do this I think it’s very easy to burn yourself out because there is always more we could do on every research project or teaching topic. I find it helpful to set a goal for what I want to get done in a week. If I happen to get lucky and get things done quickly, then I might leave early. If instead things take quite a bit longer, then that becomes a longer week (and possibly weekend). Over time, I’ve found that I’ve become much better calibrated at setting what is reasonable for a week.

SOS: Do you ever have fun?

Professor Redden: Of course. Otherwise, what is the point? In fact, I explicitly carve out time for fun. As an example, I often teach on Wednesdays until noon and then often go catch an early movie. Interestingly, I have found this increases my productivity as I come back Thursday morning refreshed and ready to work. I think everyone should carve out some of these hobbies to take advantage of the flexibility academia offers. For me, this is movies, tennis leagues, my kids’ sports teams, etc.

SOS: How do you manage your choice of projects?

Professor Redden: That is a great question. I found that early in my career I tended to work on anything I found interesting. This led me to jump from project to project chasing after the “shiny new object”. You can imagine how this hampered my productivity. I now try to decide what enters my portfolio in three stages. First, I make sure that any new idea leverages an area of my expertise. I want to avoid one-off projects that require me to learn an entirely new literature each time. Second, I go ahead and write a potential contribution paragraph to flush out whether this idea could be in an A-journal. The worst outcome is for an idea to work perfectly yet have no chance to be published. Third, I try to run a quick study to see if the idea seems promising at all. If it works, I try to quickly replicate it so I’ll know I have something real. If it fails at first, I’ll give it one more shot if I think the idea is super promising. If it works at first and fails on the replication, then I’ll often give it one more go as a sort of tiebreaker. I’ve found this approach has really helped me weed out effects that will be difficult to establish and understand.

SOS: What do I really need to do to get tenure in this field?

Professor Redden: The answer to this question is both ambiguous and varied across schools. At my university, the guidance is centered on achieving distinction in your field. Of course, this could mean something very different for everyone. Personally, I tried to make sure that two things would hold true. First, that there was a topic (satiation in my case) such that I would be one of the first few names mentioned if one asked who was doing research in that area. Second, that it worked the other way such that when asked what I researched people would have a consistent answer. I think if both of those are true then you will have achieved distinction in your field.  

SOS: How do you choose collaborators?

Professor Redden: A great deal of this is serendipity so I’m not sure there is a conscious effort to “choose” collaborators. I can say that the collaborators I want are those that share my interests, possess complementary skills, and make research fun. I’d say the last one, having fun, is by far the most important.

SOS:  I am worried that only the Thaler’s and Loewensteins of the world will make a difference. I know now that I’ll never be them, so I am thinking, what’s the point, what will I really do for this field?

Professor Redden: It matters how you define making a difference. If you consider yourself a success only if you make a difference for an entire field, then that is a really high standard for nearly anyone. I like to think of making a difference at a more micro level. Think about how your presentation at a conference may affect how a listener writes their paper, how a conservation may lead a doctoral student to their thesis idea, how teaching a topic may spark a student’s interest, how seemingly minor coverage of a paper may affect a marketer at a company (and hence millions of people). I believe that many of these unknown differences are happening — as long as we work on interesting problems.

If you have any questions for future interviews, let us know at indecisionblogging@gmail.com

Interview by Troy Campbell

ACR 2013 Doctoral Consortium: Contradictions are Part of the Point

ImageOn Thursday, October 3, 2013, a lot of information was shared at the Doctoral Consortium.  Interestingly, some of the advice contradicted one another: contradictions occurred between and across sessions. As an attendee or someone who just read the tweets, you might be wondering, “What’s a grad student to make of speakers giving different opinions?”

Indecision Blog caught up with Consortium Co-Chair Derek Rucker after day to talk about the themes and goals of the day. The full video interview will be coming soon but we wanted to post a few quotes to help clarify some things.

What did you hope the students got from today?

Rucker: “As a Ph.D student you are at a particular graduate program with a limited set of faculty… The big thing here is exposure to different thoughts, and different ideas, and different ways of doing things.”

How should students deal with hearing contradictory information?

Rucker: “One of things I want students to get is that there are different ways to approach research. Sometimes these are represented as contradictions – Faculty A says do it this way and Faculty B says do it that way. But instead, with many great minds in the room you see that there are different paths to success.”

 “For instance students that just listened to talk that discussed, ’Should I do more field experiments or should I start with theory?’ whereas probably both are paths to success. You can come to [ACR] and say, ‘Wow there are some real luminaries in the field. What’s their style? Which ones resonate with me? Which ones don’t? [At ACR] you get this nice exposure to different ways of reaching the same goal.”

Across the Consortium

At many places across the Doctoral Consortium, Rucker’s sentiments were shared. At the Consumer Culture Theory session, the researchers talked about connecting with “what vibrated with you.” At the “What I was Glad I Did/What I Wish I Would Have Done Differently” session, the speakers openly contradicted each other. But the contradictions were not mean – instead they openly laughed about the contradictions. Likewise the journal editors talked about differences and even used a funny metaphor (to varying degrees) of “too hot, too cold, and just right” to describe the journals’ unique characteristics and goals.

However, that doesn’t mean you should just run free without worries as there are definitely poor ways to do things and internally inconsistent ways to approach things. Doing things in a certain way means you will have to sacrifice something else – life and research come with trade-offs, so don’t let cognitive dissonance convince you otherwise. The point simply is that there are different ways to do great things and if the consortium seemed contradictory to you, you should know that it was, in fact, one of points of consortium: to let help you connect with a great path that works for you.

Special thanks to the co-chairs and all the panelists who took time to talk to Indecision Blog and provided us with your materials. 

N.B. Blogged and edited semi-live so mistakes and typos may have slipped in! 

Outside The Matrix: Jolie Martin, Quantitative UX Researcher, Google

jolie martinAfter a long break we return to the Outside the Matrix series with Jolie Martin, a quantitative user experience researcher at Google. She received her PhD in Science, Technology, & Management at Harvard through a joint program between Harvard Business School and Computer Science department, and did post-docs both at Harvard Law School Program on Negotiation as well as the Social and Decision Sciences department at Carnegie Mellon. Prior to joining Google, she was also an Assistant Professor in Strategic Communication at the University of Minnesota.

Tell us about your work: how does decision making psychology fit in it? My title for the last year or so has been Quantitative User Experience Researcher at Google. However cumbersome, all the words are necessary to indicate what I do. Like my colleagues who do “regular” (qualitative) user experience research, my goal is to understand when users successfully satisfy their information needs using Google products. In my case, working on the Search Analysis team, I specifically develop metrics that describe how users interact with features on the Google search results page. The key distinction from other user experience researchers is the data source I draw upon, and as a result the types of analyses I do. Rather than running lab studies or even large online studies through tools like mturk, for the most part I rely on data recorded in logs to tell me how real users behave under natural conditions. The benefit of this approach is massive amounts of data. Nearly everything of interest is significant, sometimes even with very minor tweaks to the product that are imperceptible to the average user. The drawback – although it’s sometimes the fun part – is that I have to draw inferences from behavioral signals about users’ preferences, intentions, and satisfaction.

Judgment and decision making to the rescue! My theoretical background in this field has been extremely helpful in formulating hypotheses about why users search the way they do, from the queries they enter to the sequence of clicks that they take. For example, in considering ways to improve the user experience with exploratory tasks that require large amounts of subjective information (say, choosing where to go on vacation), I need to be mindful of contrasting interpretations of a user’s behavior. If she spends more time and clicks more links, this could be a bad signal that she simply didn’t find the information necessary to make a decision, that she suffered from information overload, or that she was distracted and continued browsing to procrastinate on a more worthwhile task. On the other hand, it could be a good signal that we offered her a rich set of information sources – increasingly tied to her personal characteristics and social networks – that offered insights worth delving into. To tease apart these interpretations requires testing mental and behavioral models of an extremely diverse set of users.

Why you decide to go into industry instead of continuing in academia? Unlike many of my academic colleagues – and even many people I know in industry who jumped ship – I never embarked on a PhD specifically to pursue a career in academia. In fact, I was clueless that this was the expectation of my advisors until several years into my PhD program! I was operating under the assumption that building theoretical knowledge and methodological skills would serve me well in any career. At some point right around my third or fourth year of grad school, I did become somewhat indoctrinated to the notion that academia is the “highest calling” and we should leave the actual implementation of our ideas to others. And of course I realized how difficult it would be to return to academia should I leave, so with this in mind, I gave it the old college + MBA + PhD + 2 post docs + assistant professorship try before finally divesting myself of those sunk costs. I liked each of my academic positions, but often felt as if I was spinning my wheels to achieve an objective (publishing in journals read almost exclusively by other academics) that I didn’t really care about, so when Google contacted me, I figured it couldn’t hurt to interview. During the process, I was surprised to find many other people like me with PhDs and interests in “pure” research. These were very smart people, and all had various personal and professional reasons for leaving academia, but it became clear to me that it was a choice, not necessarily indicating that someone couldn’t make it in academia.

That said, I am a firm believer that people enjoy things that they are good at, and where they can continue improving over time. I thought Google would offer exactly this for me. I have always loved building cool stuff, which is really the core of what we do. At the same time, there would be a lot to learn. When I accepted the offer at Google, I took a one-year leave from my assistant professorship (which was extremely generous of my department chair to offer), and it was nice to have that safety net should I dislike my new job. During the week of orientation with mostly software engineers, I thought more than once that I might need to use it. Just about everything flew over my head. But once I settled in with my teammates, I realized that everyone was willing to help, and no one had all the answers; doing logs analysis from end to end is complex by its very nature, and no one could step into the role as an expert. The expectations of me were that I be persistent and keep asking interesting questions. After a year in my position, the torrent of learning opportunities hasn’t tapered off in the least.

What do you enjoy the most in your current role? The main appeal of my job is the rapid pace that I can have impact on products that improve people’s lives in a tangible way, sometimes just through offering them a whimsical break from a busy life. I love working for a company that takes this mission seriously, and always holds it above monetary factors. Of course, this is not true of every company, so I feel lucky in that regard. I also have a nice variety of projects that result from mutual selection, and work with people in just about every role. There are only about 10 of us across the company in the Quantitative User Experience Researcher position, and our ability to glean insights from large data sets is highly valued by others. There is no prescribed way to perform these analyses, so we have freedom to use novel methods in distributed computing, machine learning, and natural language processing, among others. Last but not least of what makes my work stimulating is the chance to witness the evolution of cutting edge new technologies, such as riding in a self-driving car, wearing Glass, and seeing a prototype of a balloon that may one day provide internet in developing countries. Making these products useful requires not only tech savviness, but also political and legal knowhow.

Do you see any challenges to the wider adoption of decision making psychology in your field? Google and many other large companies are quite receptive to using decision making psychology in some ways. For example, I was involved in a “20% project” (whereby we can spend 20% of our time on something completely unrelated to our job function) running consumer sentiment surveys during the Democratic National Convention and presidential debates. I’m now working on another 20% project that draws upon academic research to test how environmental and informational factors shape food choices in our cafes. Similar studies have been conducted at Google to examine how defaults affect 401K allocations, and programs have been implemented based on the findings, with material effects on employee well-being.

However, for several reasons, there is more resistance to using basic research in the creation of products for end users. First, many companies in the technology industry are comprised mainly of software engineers (at last count, about 75% of Google employees) who may not consider psychology relevant. They often expect that users are “rational” in the sense of taking optimal actions given the set of options and information at their disposal, whereas we know this is rarely the case. Second, what research we do has focused on user response to specific technologies, with little ability to then generalize to a broader set of stimuli or outcome measures. This is related to the fast product development cycle I mentioned previously; we simply don’t have time to test fundamental psychological principles or the product will be launched and onto v2 before we have anything to say about it. This is changing gradually as the value of longer-term focus is realized. Third, while publishing is encouraged, there are not huge incentives to do so, especially given the more rigorous hoops we have to jump through in obtaining approval. Even in cases where we have interesting findings applicable to psychology more broadly, we often can’t disclose them for proprietary or privacy reasons.

How do you see the relationship between academic researchers and practitioners? In my opinion, the ideal relationship between academics and practitioners is one that takes into account the comparative advantages of each. While academics are usually more in touch with trending or provocative research topics that are likely to interest audiences and gain traction, practitioners are more aware of the available data sources and product use cases. Similarly, in terms of resources, academic connections provide legitimacy and wider dissemination of research findings, while those of us in industry can potentially be more useful in supplying funding, a sample population for experiments (be they users or employees), and analysis infrastructure (i.e., computing power). Collaborations would be more synergistic if there was greater engagement in both directions, with academics developing research questions based on real business or social issues, and practitioners making the additional effort to share findings via peer-reviewed conferences and journals.

What advice would you give to young researchers who might be interested in a career in your field? I’d suggest that students contemplating a transition to industry try a temporary or part-time internship; it’s a relatively low risk way to test the waters, and realistically, given the scarcity of professorships at top research universities, your advisors should support your consideration of other options. However, also be aware that one company isn’t going to fully represent all of industry, the same way stepping into a random graduate program or postdoc could be quite different from the one that is the best fit for you. I interned at a hedge fund during grad school and knew pretty quickly that it wasn’t for me, but it was a valuable experience nonetheless.

Perhaps more feasible for faculty members who are dissatisfied with certain aspects of their careers (e.g., working weekends and responding to emails at 3am), consider reaching out to people at companies of interest to you. You will likely find that they are excited to talk to someone with the wherewithal to do in-depth analysis of their users, and may even be open to handing over data or running experiments with you. Ask if you can present at company meetings to get a sense of the culture and style, or invite industry folks to present at your university. And don’t just build your network, but also maintain it by staying in touch with people you’ve worked with in the past. Referrals from a company’s current employees will make a big difference if you decide to apply!

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.