Upskilling

I was recently in a conversation about upskilling, and realize that there are a couple of issues at play here. There are organizational issues, and learning issues. Given the timeliness of the topic, it’s worth talking about. So here’s a quick riff on upskilling.

First, there’s the issue of the need. As a result of the pandemic, and the supposed ‘great resignation’, orgs are both needing to address new skills related to distributed working, and are finding it difficult to hire new folks so need to train, or retrain, existing workers. I’m not too sympathetic about the difficulty of hiring; it’s pretty well demonstrated that orgs haven’t been distributing benefits of increased productivity fairly. Also, old management approaches aren’t conducive to creating workplaces people want to participate in. 

Yet there is a fair cop about the need for continual learning. Things are changing faster, and as we find what we can automate, we increasingly recognize that where folks add value are the things that can’t be automated. That is, making contextual decisions. That requires cognitive skills as well as model-based knowledge. Thus, there is a legitimate need for continual skilling. 

Which brings us to the learning part. What develops cognitive skills are two things, having the background knowledge, and then practice in applying it. At least for situations that are likely to occur frequently enough to be worth preparing people to deal with the situations. If they’re too infrequent, and aren’t important enough (e.g. lives depend on it), it makes more sense to help in the moment with decision support tools. However, when performers really do need to be able to make those contextual decisions, we know what develops and then maintains that capability.

First, you need minimal models that allow you to predict the consequences of different actions. This enables performers to mentally simulate (or model) the outcomes, and choose the better one. Then, learners need practice in applying those capabilities to situations. This requires meaningful problems via scenarios, resourced with examples, framework references, and feedback. 

This initial practice tends to be resource-intensive (time, money), so as little as possible to get learners up to speed makes sense, but the interventions don’t stop there. Learners then need to be given responsibility within their capability to practice, with oversight. That is, someone (a manager, a colleague) needs to be checking and addressing any particular performance issues.  One org I know didn’t develop training without also developing manager training, to not have their investment squelched as soon as they left training. 

Over time, they should be checked against performance metrics and gradually improved, with greater responsibility, and growing requirements for self-check. This includes initially asking their own thoughts about their performance, and feedback on that as well as their performance. We want to improve their monitoring as well as their performance, turning them into self-improving performers.

This longer term view is critical to creating skill development that is persistent and continual. It is assisted, of course, by creating an environment where you can ‘learn out loud’ by showing your work and sharing feedback amongst colleagues.

Upskilling, done properly, is a necessary and useful component of a learning organization. There’s a role for formal efforts, which are optimized by creating an environment for more informal learning. It’s a continuum from training, through coaching, to individual and collective learning. Which naturally follows the apprenticeship models that evolved before formal schooling, and aligns with how our brains learn. So, go forth and upskill!