Skills Toolbox: Research
By Madeleine Peckham
While the “real” world isn’t very good at sizing up humanities grads’ skills, most people are aware that we have a lot of experience doing research. But what exactly does “research” mean, and how can this academic task be translated into a workplace skill?
Research involves far more than leafing through books or doing online searches. Research is a process.
Knowing how to research is one of the most transferable skills you possess, and one of the most valuable. Sure, you will probably never again be on JSTOR looking for peer-reviewed articles critiquing Juergen Habermas’ characterization of the 18th-century “public sphere”– bummer? hardly– but every job that requires analysis and decision-making requires research.
As I often tell my undergrads, the first part of research is crafting a good question. In a class, this is usually done for you by the professor. At work, it’s often up to you. How you develop your question involves what information you have available, what your time constraints are, and in what format you will be presenting your results and conclusions. A good research project can be seriously hampered by a bad starting question. As in academic research, it’s very important to get a clear handle on what demands the project needs to fulfill before you begin to execute it. Making brilliant conclusions tends not to impress people if you weren’t addressing the question they wanted an answer to.
Second, come up with a data-gathering plan. In grad school, we call this “methodology,” but in the real world, it’s often framed as a response to time constraints. What is the most efficient way of collecting data will allow you to maximize the amount of relevant information on your topic? When I worked at a DC non-profit, I often had to compare pending legislation in several different states. State legislatures used conflicting terminology and organized their databases differently. It was imperative to come up with a plan so that I didn’t have to waste valuable time viewing the thousands of database entries that were irrelevant to my study.
Choose your data wisely. As a TA, I often read papers that I know were “researched” entirely from the first hit on Google. Be sure to consider possible sample biases and be ready to justify your choices of what you select. In the work sphere, this often involves thinking about your sources of data– do they have political leanings? What’s the funding source? Who’s doing the work? What other work have they done?
And now the fun part– analysis. Data, contrary to what a lot of people think, doesn’t just speak for itself. It’s critical that you interpret what you find, keeping in mind how it specifically relates to your research question. Try to make your analysis as clear and concise as possible. The point here is to help people understand what you found, not to wow them with how much effort you put in.
Finally, draw meaningful conclusions. In undergrad papers, most students assume this just means restating what you’ve already presented. In a work situation, you will probably be expected to explain how this will advance company goals, support related projects, or offer an important new perspective. The key to this is to think about why your research question originated in the first place. What was the point of your study and what’s next?