Measuring what matters

As discussed in a previous post, intentional work, research chemists - and scientists in general - are faced with three types of work: deep, shallow, and experimental. Experimental work involves physical action (experimentation) and produces physical goods (compounds, or data measured on those compounds). This means that physical scientists do not fall perfectly under the knowledge worker banner, however, many of the ideas around efficient working/productivity can still be used to improve their output and quality of life.

For an academic from any discipline, there is a universal measure of career success: publications. There is even a cliché: publish or perish. Good research does not exist in a vacuum, and results that remain uncommunicated may as well not have been obtained. There is an unspoken caveat that successful careers are not just built on prolific publications, but on good publications. The impact factor of a journal can be used as a rough guide of the quality of the publications contained within. There are also predatory journals that will publish near enough anything as long as payment is made.

However, chemists cannot spend all of their time writing manuscripts. As well as the shallow work required for university roles, there are experiments to do in order to have results to write about. For research chemists, that means that some time is required experimenting. The experiments also have to be important, relevant, and reliable. The results should further the field with a significant contribution. To do so, one must be up to date on the literature in order to know where the opportunities lie - whether there is a gap in the current understanding or a new direction in which to take the field. There is also room for serendipitous discoveries where completely unexpected results allow for a new discovery or area.¹

So, while (good) publications are a suitable measure for a successful career trajectory, they are a lag measure. A highly cited paper is not something that is done in one step, it is the end result of a lot of work. It is an indication of the success of the work, but it requires many actions that build up to that success. These action are the lead measures, and they are what can be planned, refined, performed, and done well. In David Allen’s GTD parlance, the lag measures are the projects, whereas the lead measures are the discrete next actions that can be performed. Put another way, the lag measures should be goals, and the lead measures daily activities. Lead measures, such as the number of deep work sessions in a day - or more specifically deep work sessions reading literature to get to the cutting-edge of an area - can be tracked and reviewed during a weekly review. The lag measures are more suitable for quarterly, yearly, or longer time-frames.

It took me a while to realise this distinction. I was concerned by my lack of publications. I wanted to increase this number, and was frustrated by my slow progress. But then I realised I should be focussing more on what I can do (time spent intentionally reading, writing, and experimenting - lead measures) to move this goal (high quality publications - a lag measure) forward. Now I have a much more realistic picture of how to go about achieving success, and can concentrate on optimising lead measures knowing that they will be contributing to the lag measures that I care about.