In the last 7 years I’ve worked in 3 different labs. One in lichenology and botany. One in Alzheimer’s research. And one in Computational Neuroscience. I learned a lot in each lab. I made a lot of mistakes and was fortunate to work under some genius principal investigators who let me explore their fields. I’m now a school teacher in a very well run urban charter school. Along with that I’ve had the opportunity to take internships in nonprofits and tech companies. I’ve been lucky to get to see so many different types of teams and management structures. When thinking about my relationship to colleagues, superiors, goals, expectations, and workflow, one thing stands out →labs are often not well managed.
It’s a very similar story for most people I know in research. You go and work in a research group with varying degrees of management from the actual principal investigator (PI). The PI is often spending the majority of their time writing grants, writing and reviewing papers, or lecturing. You may have one unorganized lab meeting a week. You’ll spend months on projects with varying degrees of feedback and little structure to the deadlines, expectations, collaborations, and goals of the project. You can often get through many months without any clear sign of progress in the project.
Success in academia is extremely difficult, but just making it into a tenure track position does not mean that you are prepared for managing a team. In fact, the path to becoming a tenure-track researcher often seems to select for traits that don’t make many PI’s well suited to be effective managers of labs and mentors to young scientists. Whereas effective managers are often cooperative, patient, and compromising, the gauntlet of grad school, endless publishing and grant writing, and postdoc fellowships can often create competitive and uncompromising people who don’t quite have the natural skills to be amazing managers without extra training. And despite this, many new PI’s are given no management training about management.
Unfortunately there isn’t much direct research on the management strategies of effective labs. To me, this seems like a high leverage research question for two big reasons: it is a widely neglected topic that could possibly see quick improvement, and it could lead to interventions that could improve the productivity of research labs. I’m generally interested in more studies of super-effective researchers to try and develop ways to improve scientific progress since it may be slowing down. This seems like one viable and possibly neglected option.
There are a lot of ways to test this. The most straightforward first step is to try to survey professors and grad students looking for different indicators of management success and productivity that could be predictive of different measures of scientific success (ex. h-index or citation count). I’m curious about the difference between how professors view their own management and how undergraduate and graduate students view the organization of the same lab. This all could lead to the development of a program of best practices for research management according to the practices of the most effective researchers.
In general, though, any refocusing on improving management practices without doing specific research into lab specific management could be extremely helpful. You’d think that many labs would have already implemented common sense best practices in management, but you’d be wrong. Many students, both undergraduate and graduate, are thrown into projects without any systems to set expectations and create deadlines. Most labs that I know had no formalized processes to train incoming members, and I’ve never heard of a lab that has developed and consistently implemented professional systems of feedback to help improve the output and understanding of students in the lab. Many labs I know don’t even organize weekly meetings with clear agendas and goals. So even despite the fact that science is getting more complicated and costly, there doesn’t seem to be a broad rethinking of making the local research systems more productive.