Differences between Academic and Industry Research (from a recovering academic)
A little bit about myself.
Hi, my name is Katherine, and I am a User Researcher at Buildertrend, a project management software for the construction industry. Within this article, I’d like to share with you a little bit about the differences that I’ve noticed between psychology research in academia and User Experience (UX) research.
As a quick background, when I started working on my PhD in social psychology I was completely unaware of the field of UX Research. I loved my graduate school research but quickly realized that academia was not my forever home for a variety of reasons: the extreme competition, the workaholic culture, the administrative paperwork, and, in the very, very slim chance that I got a tenure-track position, the limited choice in pay and location. So, I explored other career fields and found the field of UX, which utilized similar research skills and methods to understand product users and improve their experiences.
As it turns out, social psychology is quite applicable to UX research. Social psychological principles lend themselves very well to understanding how people interact with technology and can be utilized to create pleasing and intuitive user experiences. Topics like attitude formation and change, attention and perception, intergroup processes, and bias help us understand users’ attitudes, emotions, and behavior, and shape their experiences in a way that meets their needs. As a UX researcher my primary goal is to elevate the voice of the customer, to make sure their needs are being prioritized, their problems are being solved, and their experiences are positive.
So, what are the differences? Academic Research vs. Industry Research
Are you in academia and considering a transition to industry and want to know how the research might differ? Or just curious and want to learn a little bit more about the two? Below are a few main areas that I’ve noticed differences in academic versus industry research.
Scope/Impact. In industry, you’re not studying the abstract concepts that you might be used to in academia such as motivation, attention, prejudice, coercion, and conformity, which are widely-studied topics in social psychology. Instead, you’re researching real world phenomena to solve an actual problem. The focus of your research in industry is primarily to identify what problem needs to be solved or provide information to solve problems related to a product or organization’s functioning.
Goal. Academia is highly discovery focused and much of the research is motivated by satisfying an intellectual curiosity, as opposed to a direct, real-world application. In contrast, industry work is mostly focused on understanding or solving a problem that has an immediate impact on everyday people’s lives. Ultimately the goal of industry is profit, which is why it’s important to find a company whose values align with yours to still find that intrinsic meaning to the work you do. As UX Researchers, we elevate the voice of the customer by identifying their problems and needs and synthesizing the findings into actionable insights to improve the user experience, which ultimately will result in increased profits.
Timeline. Timelines are a major difference between academia and industry research. In academia projects can range in duration, but they generally span a couple years from conception and ethics board approval to manuscript revisions/acceptance. This is due to the rigorous expectations of the scientific method and peer-review process in addition to time requirements to apply for grants and secure funding. In industry, projects generally range from a few weeks to months. Most of my projects have a two- to four-week deadline, and I usually work on two to three research projects at a time. Often, this means conducting good-enough research within the time allotted, but it also means you get to do so much more in the same time frame.
Deliverables. Because of the short timeline, the deliverables in industry are different than those in academia. In academia, the most important deliverable is the final manuscript which, ideally, gets published as an article in a top-tier journal. In industry, the most important final deliverable is your communication of insights to stakeholders. You don’t have time to write a 30 page manuscript, nor would anybody read it if you did. You might produce a report, but it is generally only a few pages containing an overview of the research methods and main actionable insights, written in clear, easy to understand language.
Outcome Measurement. In industry, people do not really care about “statistical significance.” Yes, you might get some stakeholders who understand significance testing and p-value, but what most people really care about is the direction of movement. Are the numbers going up or down in a meaningful way? What is contributing to that change? Are people clicking on this button more than when it was over here? Why is that location better? Will changing it increase revenue? Running statistical tests is important, but more important is being able to describe the direction of the effect in a way that aligns with organization and business goals.
Ok clearly there are many differences between the two, but what are the similarities?
What are the transferable skills between academic and industry research?
Scientific thinking. You still need to know the scientific method and how to use it to craft a research study. You need to know how to identify the key research questions, determine the most appropriate research method, conduct the study, analyze the data, and share the findings in a compelling way. Once you have this foundational skill set, you can apply it to any topic.
Methodological expertise. A lot of the research methods you use are the same, and–although some methods are more common in industry–surveys, interviews, and experimental design are consistently utilized to provide insights.
Statistical analysis. We regularly utilize our statistical training to analyze and interpret data, running regressions, t-tests, ANOVA, and other inferential statistics. There are also new statistics you might need to learn, and a strong statistics foundation will help you pick up new techniques quickly.
Data interpretation. Just like in academia, you need to know how to look at the data or statistical output and interpret what it means in real-world language. In industry, you are a data expert, and your teammates will look to you to help them understand patterns in and limitations of the data. Your ability to interpret findings and synthesize them into actionable insights will be valuable to companies that want to make data-driven decisions.
Communication skills. As a UX researcher, my work is useless if individuals who need my insights do not get it. Therefore, identifying and synthesizing insights and conveying them in a digestible way is of the utmost importance. Your ability to communicate convincing insights and recommendations succinctly and effectively across multiple formats — written reports, presentations, etc. — will make you a strong asset to your team and company.
Teaching skills. When you communicate insights, oftentimes this involves not only presenting insights but educating your colleagues about the appropriate application of data and research methods. Being able to convey this information in a digestible way to a varied audience will distinguish you from your peers.
Dealing with ambiguity. Chances are that sometime during grad school you were asked to do something that you didn’t know how to do. That might have been using a new methodology, or running a new statistical test, or sampling a hard-to-reach population. Most likely you were able to figure out how to do it by improvisation and resourceful thinking. In industry, those problem-solving skills are still just as valuable. The ambiguous tasks might be different — different subject matter rather than a new statistical test–but your process for figuring out how to deal with them is the same.
Experience studying people. Regardless of the context, people are complex and hard to study! If you come from a social science background, another similarity is that your participants are people, and you will experience the same challenges in studying them as you did in academia. Even if you didn’t study people, with the skills listed above, you can land an industry job with the skill set you gained during graduate school, regardless of the topic you studied.
In conclusion, while there are many differences between industry and academia, there are many similarities and transferable skills. While there are some trade-offs, I love UX research for the pace of the research and impact I have on people’s lives.
