Your job description changes significantly when you transition into a managerial role.
Your job becomes less about the science and more about hiring, training, and motivating people. Your role may also become administrative—building a framework for your lab to run smoothly, or even securing and allocating financial resources (through venture capital financing, writing grants, or department budgets).
Being a scientist on a team is often quite social, if you want it to be. One can develop close camaraderie working shoulder-to-shoulder with teammates every day in the lab. But as a manager, you can no longer be the person in the lab who is friends with everybody. You can act as if you are equals, but you ultimately have the power to fire or promote the lab worker. Your relationship with the people in your lab has to change. You are now their boss.
As a scientist, you also have the option never to connect with people. But as a manager, that’s not an option—management is a team sport. You must learn to work effectively with others, understand everybody’s strengths and weaknesses, and promote transparency and collaboration.
The difference between industry and academia
Many scientists who join your team will either be coming straight from academia or have recently come from academia. You, yourself, may have been in academia until very recently.
This transition comes with a significant learning curve, and you must unlearn many practices common in academia.
In academia, the duration of each stage of your career is pre-set. A Bachelor’s degree is four years; an American Ph.D., 5 to 7 years; postdocs, 1 to 3 years each. Working extra hard may net you another paper or shave a year or two off at best. Regardless of your competence in the lab, shortcutting the process is generally impossible. Even if you are speed-oriented, most academic groups have to choose saving money over saving time.
In industry, you have minimal time, money, and people to figure out what is necessary to push your project forward to completion. While big companies have the luxury of basic science research, most industry scientists must eschew studies they may want to conduct to have the resources to complete the studies they need to conduct. In industry, scientists are expected to choose to spend money to save time. Each week lost is a week lost on your timeline, an extra week burned yet without increasing the de-risking of the company. This type of ruthless prioritization is uncomfortable but necessary to quickly and efficiently find a product that may work.
Academic communication tends to be technical, formal, overtly humble, and somewhat pedantic. In comparison, good communication in industry is concise, information-dense, and direct. After all, you’re communicating with someone who isn’t as scientifically in the weeds as you are most of the time.
Many academic scientists do not understand how others think. Commercial labs require scientists to adapt to working across functions, with diverse skills and knowledge, and across levels of management.
A product that works vs. a product that can be commercialized
A scientist might spend their entire career unraveling a single cell signaling pathway. You learn to learn, to increase the world’s understanding of a small corner of biology.
But in industry, it’s not just about whether your research might work—you need to consider whether your research would contribute to a good product.
One must consider commonly neglected variables in industry, which include:
- The final price point relative to competitors
- Manufacturing complexity and logistics
- Market preferences
- Regulatory considerations
- Go-to-market differences
Managing your team
The first week of work will set the tone for the rest of the person’s stay.
In the first week, you should:
- Clarify the responsibilities of the position. Discuss expectations. Explain the lab culture and customs.
- Talk about the project. Have papers or references ready. If you can, get the new employee to do an experiment as soon as possible, with an experiment commonly done in the lab with known results. Provide the experiment overview and background reading on the theoretical side of the experiment. Show how to find and use protocols, inventory items, lab data management systems, etc.
- Schedule a 1:1 with everyone that the employee will be interfacing with. If the individual will be working on a small team, then it will be beneficial to introduce them to key people on different teams. The new hire will likely find it uncomfortable to grab someone’s time on their own (especially if they’re on a different team), and it’s a good idea for people on your team to know how your team’s work interfaces with the work on other teams.
When setting goals, make sure they are clear and that the objectives are well understood by everyone. Often, the SMART system helps define these goals:
- Specific: goals are well-defined
- Measurable: every goal has a measurable outcome
- Achievable: goals are obtainable
- Realistic: resources are made available to reach goals
- Time-bound: goals and milestones have deadlines
You should be deliberate and thoughtful about managing the people on your team. Goal setting should be a collaborative undertaking that matches the experience and role of the employee. Different people need different types of goals and different levels of guidance.
You will almost always be better off asking the employee to develop some of their own goals. You do not need to accept these at face value and can use them as learning tools to help the employee set challenging and worthwhile goals.
The idea of matching the goals to the person is illustrated below.
The temptation to grant unearned independence is a seductive one. After all, this would buy you more time to do whatever you want to do. But, in the beginning, you must make sure that everything is done the way you want it.
The best way to have clear oversight over your employees is weekly one-on-ones. Over time, you can adjust the frequency, length, and timing to better suit each employee.
A good template for one-on-ones from Manager Tools is provided below.
Most scientists don’t know how to provide feedback because they’ve never been provided feedback.
In 2010, MIT performed a survey among its postdocs. Of the 844 responding postdocs, 54% said they had never had a performance evaluation while a postdoc; 31% said they had received “informal” feedback; and only 15% have ever received a performance review. A similar survey from the University of Chicago, done in 2011, asking the same questions as the MIT survey, revealed very similar statistics. 16% answered “Yes” to the question, whereas 84% answered “No.”
When providing feedback to your team members, consider the following best practices:
- Focus on starting in a way that doesn’t assign or assume blame. You could say, “There is a work-related matter I’d like to discuss with you. Is this a good time?”
- State the problem, being as concrete as possible. Be specific. For example, do not say the team member has made “a lot of mistakes” but “eight mistakes.” Focus your comments on what was done wrong rather than on what’s wrong with the person. (Say, “You made eight dosing errors” rather than “You have become careless.”)
- Ask for their views or their comments on what you said. Ask for clarification frequently (“What do you mean by…?”). Ask if anything you said is unclear and repeat what you heard to confirm that you understand what they said.
- Defining the problem illuminates things that may not have been visible before. You are not necessarily pushing for a solution, but one may present itself. Ask them what ideas or solutions they have. If they do not suggest anything, offer suggestions yourself about what they or you can do to improve the situation. If it looks as though the problem is theirs and not yours, then your objective is to help the other person change their behavior. As potential solutions arise in your discussion, write them down.