Ever had to explain a complex concept to a customer? Is creating metrics to analyze product performance a part of your job description? Need to develop plans under multiple constraints? These are some of the most commonly requested skills in job postings by tech, finance, and consulting companies, yet most candidates don’t have formal training in any of them. Know who does, though? Scientists.
Many people think “doing science” means plugging numbers into equations and messing around with lab equipment. That’s definitely part of what we do, but most of our work entails thinking of creative solutions to problems and then communicating our findings. How are scientists able to do this? Aside from knowledge of math and physics, we’ve practiced certain skills and developed a mental framework we use to approach problems. That’s something everyone can do, and if you practice it, chances are it’ll make you better at your job, too.
Here are a few steps you can take to start thinking like a scientist.
Learn to distinguish between observables and learnables
Your brain is bombarded with billions of pieces of information every second, so it has adapted to take shortcuts in processing that information by jumping to conclusions and making assumptions. It’s when those conclusions and assumptions are wrong that gets you into trouble at work.
One way to avoid this is to consciously separate the things you’re actually observing from the things you’re inferring. Can you tell directly that it’s warm outside, or can you just see through your window that it’s sunny and cloudless? Did your clients explicitly tell you how they felt about a product, or did you just infer their satisfaction based on their buying record?
Obviously, you can’t question every single assumption your brain makes. Instead, pick one situation–maybe during your commute to work or when you interact with a particular colleague–and practice separating “observables” from “learnables” then. After a couple of weeks, you’ll be better at recognizing when you might be jumping to unreasonable conclusions. This will help you avoid making mistakes and put you in a better mind-set to ask good questions, which brings me to my next point . . .
Approach your work with questions, not tasks
I was talking to a friend a few months ago who does research for an AI-driven tech startup. I asked him what types of questions he’s trying to answer in his research, and he said something about making sure the company’s product could perform a certain task. “That’s a goal,” I told him, “not a question.”
When you approach problems by working toward a task, you run the risk of developing tunnel vision. You can become so focused on doing the thing you’re “supposed” to do in the way you’re “supposed” to do it that you miss potentially better solutions or more interesting problems. Asking the right questions can help you identify what you’re really looking for while leaving room to explore all possible solutions.
For every question you ask, create a working hypothesis
Speaking of knowing what you’re looking for, how will you realize when you’ve actually found it? Scientists form hypotheses before we conduct our research because it gives us something to check our findings against. You should do the same every time you approach a new problem at work.
Whether you’re building a product, investing in new markets, or analyzing sales patterns for another company, make a list of all of the factors you think could potentially affect your outcome. Predict whether each of those factors will have a positive or negative impact, then roughly estimate the magnitude of each effect.
Yes, it involves some educated guesswork, but these predictions can serve as a sanity-check for assessing your work. They give you a baseline against which to determine where your initial expectations were wrong, which could reveal biases that might be influencing other parts of your work.
In case you’re worried, adopting a scientific mind-set doesn’t mean completely abandoning creativity. In fact, good scientists use logic and creativity simultaneously in their pursuit of the truth. It’s time that more people started doing the same.
Moiya McTier is a PhD candidate in astronomy at Columbia University and the creator of Pendulum, an interactive workshop series that teaches people how to think like scientists. She is a science communicator and advocate for equity in STEM, and can be seen regularly giving public talks around NYC.