Best practice used to be best practice, but increasingly the argument is made that best practice isn’t necessarily best practice at all. This post does a through job of explaining why that might be.
It’s pretty clear that in complex real world systems, attempting to specify the steps towards an outcome with complete precision is unlikely to be helpful. It’s also pretty clear though, that many tasks and processes do have a substantial technical element for which there are best (or at least better) ways of doing things. The value of checklists – of structured compliance with a predetermined sequence of actions – has been clearly demonstrated for pilots and surgeons despite (or perhaps even because of) the fact that there is substantial variation in the context in which tasks are performed.
There are also more subtle – but no less real – forms of best practice. The shift in many areas of activity from basic competence to real expertise comes from the acquisition of tacit knowledge. Best practice is thus what best practitioners do – which doesn’t mean that what they do can be readily codified and copied, both because distillation of that kind is hard, and because the subtlety of judgement which experts bring is almost certain to be lost in the attempt. So perhaps the problem with best practice is not that people try to find it and apply it, but that they conflate adaptivity to complex systems with process compliance.
The argument of this post is that it’s worse than that, that best practice is an intrinsically unhelpful concept. In the specific context of organisational change – which is the starting point for the post – that may be so (though even there it is not meaningless to talk of best practitioners). But perhaps a better conclusion would be that for all its risks and limitations the idea of best practice shouldn’t be wholly abandoned. There is best practice on best practice which is worth understanding and developing.
This chimes with some of Toby Lowe’s research into performance management in conditions of complexity, where he concludes that the answer is not to quest after ever better outcome measures but instead to increase adaptive capability