In the last days I’ve been working round the clock — I’ve given my kNN search talk twice and several call-for-papers deadlines went by (or are coming), which meant that I was always in hurry for one reason or another.
This has been especially stressful, because for some time I had been getting everything done days ahead of the deadlines. But this month I went back to the classic regime of “crossing fingers and hitting the submit button at (literally) the last minute”.
As I move towards more complex research involving several labs, many students and audacious experimental designs I feel increasingly the need of using more formal management tools. But techniques created for Business (or even Engineering) do not seem to translate well to Academic research.
For example: I’ve tried to use Gantt charts in Microsoft Project to keep track of complex tasks and their dependencies. But I’ve found that as the work progresses, the list of tasks changes often and significantly, as some research directions reveal to be more fruitful than others. This ends up rendering the initial planning (and any chronogram based on it) useless.
Maybe is it the case of using an adapted “Spiral Model“, where risks are minimised from iteration to iteration, and creating detailed chronograms only for the lifetime of an iteration? Or are there specific management models for research projects? How the most efficient R&D labs manage their projects? How to adapt their experience to Brazilian public research?
Unfortunately, so far, I seem to have more questions than answers. I’ve bought this interesting book “Managing Science: Management for R&D Laboratories“, which is biased towards Particle Physics labs, but has (hopefully) useful concepts for all areas of experimental research and will help me to get an initial handle on the subject.