These past two weeks, I've had several conversations with executives and OD/L&D professionals who are trying to make sense of the complexities that automation initiatives are introducing into the workplace.
We found it helpful to use Cynefin to understand some of these dynamics. Now we know things tend not to fit neatly into the domains, and that this is an over-simplification of complex dynamics, but in general what we're seeing is the following.
Job roles that fall within the Obvious domain of Cynefin i.e. where we're dealing with Known Knowns and rigid constraints are already being impacted by automation. These are typically routine tasks e.g. processing transactions in a banking environment where everything is standardised and predictable. Further down stream, once AI becomes a viable option, job roles in the Complicated domain of Cynefin, where we're dealing with Known Unknowns that require expertise or analysis will be impacted.
A key question that leaders are grappling with is how to go about this transition as effectively and ethically as possible. Many are thinking about how to pro-actively re-skill their people so that they can redeploy them into other roles. It makes sense to initially focus re-skilling efforts on transitioning people from their "obvious" roles to roles in the complicated domain. This will probably not be sustainable though, as those roles will probably be impacted next. It therefore makes sense to re-skill them for work the Complex domain, but this is not an easy task. Very often, people who perform routine tasks have been taught to "do what they're told and not think". Very often they are required to follow a recipe or script to the letter. The stance and skills required in the complex domain are the opposite of that. Here we need to make sense, experiment and learn through failure, exhibit empathy, think critically - this is like trying to teach a zoo animal to survive (and thrive) in the jungle! There are multiple views on what will be needed, and no-one knows for sure, see the image below for an example of how the World Economic Forums sees it.
Transitioning from Complicated (the domain of the expert) to complex can also be hard. Often experts aren't open to new learning and need a "shallow dive into chaos" in order to become open to new ideas. In complexity, generalist skills are more useful than expertise, but for the last few decades most of us have been socialised into believing we must become deep experts in a certain field. Challenging these beliefs are not easy (but it is doable)!
Some organisations are choosing to focus on pro-actively reskilling people for artisinal roles outside of their current organisation. These roles include creative endeavors e.g. becoming a chef or baker; or technical skills like plumbing. There certainly are no easy answers or quick fixes here. Every organisation will need to find it's way in this uncharted territory. In a country like South Africa with high unemployment rates, it is imperative that companies navigate this change in a humane and ethical way.
This is a new area of applied complexity that I'm exploring more and more as I help my clients think through it. Specifically ...
- what processes will be effective in helping people to unlearn the disposition or stance that made them successful in the ordered domains of Cynefin?
- how can they most effectively learn the skills required in the complex domain?
- how do leaders start creating environments that support this transition - if we simply focus on training people, but the environment remains the same, nothing will change. Many current "obvious" environments are very compliance driven with rigid constraints. In this transitionary phase, how do we create enabling spaces within these constrained environments?
I'd love to hear your thoughts on this!