Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

18 January 2017

Cognitive Business

Clark @ 8:07 am

One of my mantras is that organizations need to align better with how we think, work, and learn.  However, my focus has been specifically on what L&D can be doing (as that’s the folk I mostly talk to). But it occurs to me that it really goes farther.  There are applications of cognitive science (including neuroscience, cognitive psychology, sociology, philosophy, anthropology, etc) to more areas of business than just L&D.  And it’s worth being explicit about this.

I was recently reading how marketing has leveraged understanding of behavior change at a deep level. We need to incorporate this in our learning design, but it should go beyond training and learning and be involved in helping people understand why their work is important and how they contribute.

And similarly, the notion that our thinking is both situated (e.g. reconstructed in the moment, not formally abstract) and distributed (across representations, not all in the head) has broader implications. It’s not just about performance support, but should influence policies and tools as well.

And the fact that innovation is social, and an outcome of slow percolation, influences more than facilitating communication and collaboration. It should influence corporate culture and expectations and time frames.

The list goes on: research says that organizational change works better starting small and scaling rather than a monolithic effort.  We know that design processes are better when they’re cyclical rather than waterfalls. We’ve discovered that our inability to perform rote tasks flawlessly argues for changes in work processes and expectation. And we’ve found out that treating people fairly leads to better outcomes including retention, loyalty, and more.  Ultimately, we’ll want to be making smart cyborg choices about what to have people do and what  technology should do.

In short, we can be working smarter in many ways.  It’s hard to change from the old hierarchical models, but we’re continually learning that other approaches work better.  Heck, we may even be able to start working wiser!  Here’s hoping.

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