I have mixed feelings about the announcement earlier this week of a further round of spending cuts to government departments. As government agencies are my principal customers, the prospect of smaller budgets brings with it a sense of foreboding. But there is another part of me that is intrigued by the challenge of keeping organisations functioning in times such as these. How, in particular, do you maintain a high standard of evidence based on naturally variable data – when you have fewer resources?
The most senior tiers of management need to maintain the illusion that the organisation is delivering an equivalent level of service to previous years. This means that effort has to spread more thinly. We have two broad options: collect fewer samples (or conduct fewer surveys), which means either visiting fewer sites or visiting the same number of sites less frequently, or put less effort into each sample or survey. Most of us ecologists have an obsessive streak (think Sheldon from The Big Bang Theory) which recoils at the latter prospect but, given finite resources, maybe we need to think again?
I spend hours hunched over my microscope producing data of a standard that is consistent with all the other analysts who do the same type of analyses as me. Nonetheless, I usually have a pretty good idea of the outcome within five minutes or so of starting the analysis. I could tell you, at this stage, whether the river from which the sample was collected was clean or polluted, acid or neutral, hard or soft. In other words, the information content of the sample is not linearly related to the amount of effort I expend. Economists refer to this as the law of Diminishing Marginal Utility, and the principle is common in many disciplines. You may have heard it called the 80:20 rule: that 80 percent of the solution to any problem comes with the first 20 percent of the effort.
Might it be possible to harness this principle in ecological analyses, to unravel exactly what it is that helps us form those quick impressions of a sample, and then to focus on just those elements, in order that the organisation as a whole can continue to function? It seems obvious when put in these terms but is riven with complications, not least because it means accepting that there is a parting of the ways between the data-hungry attitudes of academic science and a fit-for-purpose pragmatism. I’ve started working on this with a small group of colleagues from the Environment Agency and SEPA and have a rapid assessment technique almost ready to trial over the summer.
The danger is always that the need for cost savings forces you to find justifications for “cutting corners”; however, as I’ve explored this topic, I have found support from unlikely perspectives. The first was in a philosophy journal, in a paper discussing how we understand complex systems (reference below). Robust understanding, argued the author, came from having evidence from several sources. Effort spread between a number of bite-sized nuggets of information, in other words, added up to more than mining a single vein of data intensively. Of course, if you have spent years developing a very narrow expertise you might, naturally, argue for the merits of a more intensive approach but, sometimes, we all need to stand back and look at the bigger picture.
The second perspective came from my recent involvement in a public consultation exercise and the realisation during this that many of the methods we had developed were incomprehensible to all but a small coterie of experts. As we were working on the rapid assessment techniques, I imagined myself teaching it to a group of students. Could I get the principles across in an afternoon’s practical class? If so, I reasoned, the method was not just providing us with information, it may also be a means by which we could engage with stakeholders.
The final perspective was simply that most of the techniques used by family doctors are quick, robust high-level screening methods that allow them to home in on the problem that the patient presents. They might prescribe a treatment directly, or they might refer the patient on for more tests, or to see a specialist. Part of the essence of these high-level methods is that we all know their limitations and when more detail is required. It is all about efficiency, again. Environmental professionals often use metaphors from the medical professions yet, at the same time, we pay too much heed to the wannabe “consultant surgeons” who write in academic journals. Somewhere along the way we forgot that the environment needs its “family doctors” too.
Wimsatt, W.C. (1994). The ontology of complex systems: levels of organization, perspectives and causal thickets. Canadian Journal of Philosophy 20: 207-274.