Quinnsights: Informal Innovation – by Clark N. Quinn

There are two types of learning. Last month I talked about formal learning and developing specific thinking skills. This month, I want to go deep on informal learning. I suggest this is important for one simple reason: when you’re problem-solving, designing, researching, etc., you don’t know the answer before you start; hence it’s learning. And those activities are the elements that are going to take organizations forward. They’re innovation. So, if we’re to support it (and we should) we ought to know about what makes it happen. And what makes it happen most effectively!

When we think, our conscious thoughts are patterns of activation across our neural architecture. And, “the neurons that fire together, wire together”. So formal learning is about activating patterns of activity that we’d like to be combined. Context and concept, for instance. We’ll talk more about this in my upcoming session at The eLearning Guild’s Science of Learning Summit.

However, that’s not how informal learning works. In informal learning, we’re exploring spaces of potential solutions. And we need to know what facilitates and optimizes such exploration. That’s where we go deep. We want to think of this on principle, and then go into how to make it happen.

Space search

Conceptually, we need to think of a space of possible solutions. There are better (and worse) solutions in this space. Outside the space are non-solutions. But how do we systematically explore it? That’s what many of our innovation and brainstorming processes do. And, there are ways we go wrong.

To explore this space effectively, we need to prevent ourselves from prematurely limiting the space. We want to ensure we explore enough that we don’t preclude any potential solutions. And we need to explore it systematically. Formally, we talk about finding local minima or maxima (solutions that are good in a small area) and missing the global minima or maxima. A number of approaches have emerged to address these needs.

I talk about fast and slow innovation. Fast is where we have a specific problem and assign a team to solve it. Slow is the ongoing percolation of ideas.

Let’s start with fast innovation, when we’ve got an immediate need. We know that searching for solutions alone isn’t as effective as searching together. Research tells us that ideas can combine in a number of ways, but we typically are building on old ideas, and/or combining different ideas. And while it may seem that one person goes away and comes back with the answer, Keith Sawyer in Group Genius has systematically shown that’s not true.

Ideally, we have a small team working together. To start with, they should be diverse. Diversity is to be valued and engineered, not just left to chance or barely tolerated. They should have complementary, not overlapping, skills. There needs to be some shared views, at least about the importance of the topic, and likely a shared set of values. The team shouldn’t be too big, but bigger problems may require bigger teams. Five to six has been typically construed as the ideal size, all else being equal.

You need everyone to think for themselves before sharing thoughts. If someone starts talking before others have had a chance to process the situation, those initial thoughts will contaminate the others. You also want to ensure that it’s safe to share. If your contributions will be held against you, you won’t get the best contributions. You need accountability as well, of course.

Once you start sharing, you don’t want to evaluate, yet. You want to diverge before you converge. By combining ideas, and even getting silly, you are more likely to explore the space. Ensure you push the boundaries of the space you’re exploring!

Process

Note that this can be about exploring the problem before determining the solution. One of the practices of design thinking, a methodology that has combined multiple good design principles, is to ensure a comprehensive exploration of the problem. This includes not just data collection, but generating true empathy for the individuals being addressed—whether customers, employees, the public, whoever. The “double diamond” approach has a divergence and convergence for the problem, and then again for the solution.

Convergence is important. Once you’ve explored the space of the problems or the solutions, you want to evaluate the alternatives. Typically, some are easy to ignore and others require evaluation. You want a systematic and thorough process to wade through the alternatives. Here, experimentation may make sense if there aren’t clear bases to choose between the alternatives; prototyping and testing solutions. Or even various portrayals of the problems.

The processes of design are well known. The analysis of the problem, establishing the desired outcome of the search, is important. The ethnographic methods that lead to empathy are ideally buttressed by data that delineates the nature of the gap between needed and desired outcomes. We should be looking at triangulation between sources: quantitative and qualitative, objective and experiential, and more.

With an analysis of the problem, you’re ready to explore your solutions. Your approach should be iterative and situated; you should be trialing, testing in situ, and evaluating the outcomes. One of the typical outcomes is that in testing you open up new alternatives, and your timeline and process should reflect that possibility.

Percolation

The other alternative is slow innovation. Here there’s not a specific goal per se, but instead creating an environment in which new ideas arise. The goal is to identify and optimize what facilitates these outcomes. In general, you need a learning culture. This includes, again, valuing diversity and making it safe to share, and also includes being open to new ideas and having time to reflect. That latter goes back to the freedom to experiment. Google is famous for providing 20 percent of people’s time to work on their own ideas to assist the organization. You want to also be concrete about good practices, and document the learnings.

In Where Do Good Ideas Come From, Steven Johnson talks about several specific ideas. One is having proximity to new ideas. While the ability to track developments in related fields is one, just facilitating dialogs between different segments of the organization is valuable.

Another includes allowing for serendipity. This can come from the random juxtaposition and dialogs. Jay Cross, in his book Informal Learning, suggested just putting the coffee room and the mailroom together.

Learning out loud is also important, where people not only show their work, but narrate it with the underlying thinking. Here, it’s got to be okay to share mistakes, though you really want to share the lessons learned. Jane Bozarth, in Show Your Work, makes it clear that learning from mistakes, out loud, is a valuable lesson for others.

Overall, the point is that there are elements that facilitate innovation. It’s about culture, it’s about practices, and it’s about policies. And, for L&D, it’s about facilitating all this to achieve the best outcomes.

It’s important for L&D to walk the walk. Successful implementation practices, as Sutton & Rao let us know in Scaling Up Excellence, start with a small group. I suggest that L&D work on these approaches, taking ownership and getting them working. Then, there’s the opportunity to take it forward, with credibility. And that’s a key. So, innovate, including on innovation!

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