The business of scientific research

Author: Paul Krzyzanowski, 12/14/10

One of the biggest choices graduate students and post-doctoral fellow face is whether to stay in academia or go into the business world.

But what if the two weren’t really that different?

Traditional advice about running a successful academic research group focuses on the development the Principal Investigator. A recent article by David A. Stone in The Chronicle of Higher Education splits the role of a PI into three: the scholar, the researcher, and the grant writer. The scholar generates and identifies good ideas to pursue and how to place them in well published papers, the researcher actually manages to get the work done, and the grant writer sells the potential of future research projects to funding agencies and foundations.

While most labs are called “The [Insert PI Surname Here] Lab”, the idea of a lab as a one-person show is limiting. A good lab is a functioning entity, with many people contributing to many projects. Beyond the three academic roles mentioned above, “the role of a Principal Investigator involves elements of fiscal and personnel management, supervision, and time management, as well as scientific expertise”, says Stone. Finally, “You need a management plan to guide and coordinate everyone’s work.”

A management plan?

Research group management is critical to the success of each member, but is often understated during scientific training. While many universities don’t offer basic management courses for graduate students, the trend is changing. The Howard Hughes Institute has put together “Making the Right Moves“, a book that offers some guidance in scientific management for those interested in a tenure-track research career. The chapters cover lab staffing, mentoring, and setting up collaborations, with some project and budget management as well.

In a way, a research group is like a small not-for-profit business, with its own revenues and expenses, strengths and weaknesses, customers and clients (granting agencies). Where it gets tricky is how to define the criteria for a “successful lab”. Publication activity is usually the first measure considered when evaluating a lab, and if one simply goes by the number of articles published per year, there is research to suggest that mid-sized labs are most effective, when measured by annual funding levels.

That said, this study shouldn’t be used to claim that an ideal ‘average funding level per paper’ exists, but points to possible problems associated with size that affect publishing ability. In particular, groups with increasing funding may just grow to a scale where past management methods don’t work well. Growth produces complexity and things start to slip through the cracks, projects are forgotten, and resources can be wasted.

These problems aren’t even unique to science; small businesses are well known to stifle or even fail once they’ve grown past a certain size. As any business grows, some questions simply get more challenging to answer: Is work still being done by the right people on the team?; Are we still focusing on what we do best?; Do we have enough staff and supplies in inventory?

This leads to the final question: If research groups can be managed like any other business, how exactly should we measure their productivity?

The answer really isn’t clear, but out of the three P’s that research labs can produce — Papers, People, and Patents — papers get most of the attention, as I’ve indicated above. The other two products of research activity, People and Patents, are measurements typically more important to government. Training and educating people is clearly essential but whether there should be more or less people trained in science is a huge debate, and one I might wade into someday.  Patenting also matters, as it is a proxy for what is actually being produced with novel research, according to The Economist. Whether an emphasis on patents is good or bad for academic research is another contentious topic, and one I will leave for a later time.

Despite the challenges in quantifying research productivity, competition for research funding increasingly directs research groups to be productive and continually find ways to improve. Why not use readily available business tools to make scientific research the best it can be?

The following two tabs change content below.

Paul Krzyzanowski

Paul is a computational biologist and writer living in Toronto. He's been a contributor to Signals for three years, writing articles for the general public about how biotechnology and biomedical research can be used to solve pressing medical problems. Alongside Paul's experience in computational biology,
 bioinformatics, and molecular genetics, he's interested in how academic research develops into real world, commercial technology, and what's needed for the Canadian biotech industry needs to grow. Paul is currently a Post-doctoral Fellow at the Ontario Institute of Cancer Research. Prior to joining the OICR, he worked at the Ottawa Hospital Research 
Institute and earned a Ph.D. from the University of Ottawa, specializing in computational biology. And finally, Paul earned an H.B.Sc. from the University of Toronto a long time ago. Paul's blog can be read at
Tags: , ,

Leave a Reply