In recent weeks, the Career Development Center for Postdocs and Junior Faculty has had the good fortune to present two articles on project management written (or, in the case of the first article, co-written) by project management (PM) expert Stan Portny. Portny is one of the nation's most influential PM educators, with former students numbering in the tens of thousands.
During the preparation of those articles, and also in preparing for the excellent presentation Stan delivered to the recent Howard Hughes Medical Institute/Burroughs Wellcome Fund Course in Scientific Management, I've had the privilege of corresponding with and talking to Stan extensively. One of the key themes of those conversations and correspondences was the challenge of maintaining an appropriate balance between planning and flexibility in scientific work. How well do project management ideas, which evolved in a production-oriented business environment, apply to the discovery-intensive world of science? How much planning should scientists do, and how hard should they try to stick to those plans? How valuable are long-term work plans in science? No one, to my knowledge, has investigated these questions systematically, and tentative answers to the questions vary widely.
Stan himself readily admits that he doesn't know the answer in a scientific context, and he agrees that more study is needed. But he acknowledges that in the PM orthodoxy a plan is, or should be, a very concrete thing, taken very seriously by managers. Plans must be revisited and revised as circumstances change, but at the beginning of a project it is assumed that a project will be completed eventually, more or less according to the plan set out at the beginning.
With certain exceptions (like clinical trials) science rarely works that way. In their earliest stages, we rarely know where our explorations will take us.
Interestingly, opinions on applying PM principles to science seem to correlate closely to age and experience. Experienced investigators support the use of PM techniques in the laboratory far more than younger scientists--postdocs and new faculty--who often express intense skepticism.
Younger scientists, it seems, believe disproportionately that too much planning inhibits creativity in what is, fundamentally, a creative endeavor. Experienced investigators put less emphasis on the creative aspect of the work, privileging, instead, the necessity of structuring the lab's work in order to enhance productivity. This is hardly surprising considering that older PIs tend to spend less time at the bench and more time managing time and dealing with funders and institutional matters. Furthermore, experienced investigators are more likely to have been through the wringer of building a career while raising a family--a challenge that puts a premium on efficiency and productivity.
With Stan's two articles we may convince many of you that applying PM techniques to science is, in principle, a good idea. There's little question that it can help to make your lab more efficient. If we've failed to convince you then we urge you to seek out just about any highly productive, experienced scientist--especially one who has had to cope with the huge demands of raising a family while also managing a large laboratory. For those folks, accomplishing the most in the least possible time is key.
But then there is the question of implementation: What is the best way of applying PM to science? If we do it right, science will benefit. If we do it poorly, we may set science back a bit.
According to Harvard management theorist Rob Austin--who is also my brother--it is much the same way in the business world. Rob has studied the misapplication of management techniques to sectors--including creative endeavors like the arts and software development--where, he believes, they often do more harm than good. In this week's feature essay , Rob presents an alternative formulation of the PM cycle that, he believes, is more appropriate to science than the approach presented by most business-oriented trainers.
The strong support PM enjoys among experienced scientists is a vote in favor of its use, but one suspects that none of these folks applies PM techniques wholesale. Rather, these senior scientists pick and choose from among the available techniques to fashion a management approach that suits their research goals, working styles, and laboratory personnel. No one, I suspect, applies business-world PM techniques wholesale. This is a fine approach--one that we wholeheartedly endorse--but it would be good if we could discover some general principles, an approach to PM that works especially well for science, that will assist new PIs investigating management issues for the first time. It is in that spirit that we present this week's feature, Project Management and Discovery .