Strategy is Informal Learning!

by Clark Quinn

So, I’ve just finished reading Richard Rumelt’s Good Strategy Bad Strategy (possibly on a recommendation; memory fails). It’s a book about, surprise, strategy. It’s old now (the examples are dated, versus for instance, Tim Harford’s The Data Detective), but I liked the clear statement about what strategy requires. In reading Matt Richter’s recent post here, I also realized that strategy is informal learning. How can that be?

So, Rumelt says strategy has three major components:

  1. A diagnosis of the situation that needs to be remedied.

  2. A policy that guides you in addressing that diagnosis

  3. A set of concrete actions that implement the policy.

Importantly, he says that if there were a clear answer, it wouldn’t be a strategy. Instead, a strategy is like science, in that there’s a hypothesis, and you take steps to confirm or deny. A strategy can turn out to be wrong or right. In fact, you should expect to collect data (which was the basis of the diagnosis) to see if it’s working, or correct your course.

Matt suggested that, channeling Keith Grint’s characterization, there are three types of situations: tame, crisis, and wicked. Tame are ones you can apply expertise to, as there’s a known answer (this is where you manage). Wicked problems are uncertain, and require bringing people together to figure out a good approach (this is leadership). Then there are crisis situations, with time critical elements (here you command).

As an aside, this reminds me of David Snowden’s Cynefin framework. Here there are four areas: simple, complicated, complex, and chaotic. Each has its factors. Simple should be automated, basically, complicated requires expertise, complex requires exploration, and chaotic try to move it to one of the other three. It appears chaotic might be the crisis of Grint, while complex requires leadership and complicated requires management.

Leadership, here, is the art of determining strategy. With the relationship to science, it taps into my claim that informal learning – research, design, trouble-shooting – is where you don’t know the answer when you start. Similarly with strategy, taking Rumelt’s position. You make an educated guess, take some steps, and monitor the outcome. You’re learning!

It’s not like formal learning, of course, as there’s no one with the right answer (or you’d be in management and tapping that expertise whether internally or via a consultant). You’re testing to see whether you’ve made the right choice, looking for feedback. You get it, and learn whether you were right or not. You add that information into your knowledge base; you’ve learned something!

My main point here is the one I regularly make: to do this optimally, you really want to apply what we know about learning. While it’s informal, it still benefits from assessing data, systematically evaluating the options, making smart choices, and ensuring that your experiments provide the right feedback. Thus, there’s a role for L&D in this. While we may not have the domain knowledge to choose the strategy, we can assist in facilitating the process to optimal outcomes.

Besides the principled basis, of course, there’s also the argument that being involved in strategy is, well, a strategic move for L&D. It gets us involved in the activity that’s most critical to ongoing success, continual learning. Which is a better position that simply making sure we execute against what we know we have to do. Strategy is informal learning, and we should be involved. We will need to know learning (and cognitive) science to be able to execute against this, but then, we should be doing that regardless, right?