Let’s not start off the new year being trepidatious, shall we?  Ok,  social engineering and cultural engineering have bad connotations in a number of ways.  Yet, if I can talk about learning engineering, the desirable properties of cultures for learning, and moves in that direction, aren’t we really talking about socio-cultural engineering?  Can sense be made?

To start with, let me posit that there’s fairly good convergence on  the elements that contribute to an effective ‘learning culture’: there needs to be purpose, explicit description and development of skills, tapping into diversity, making it safe to share, responsibility, and more.  The point is that we know what makes  environments where  the best ideas are generated, developed, and put into practice.

The second thing we know, with less certainty but growing awareness, is how to get there.  It’s a ground game: being clear, working hard, walking the walk.  It’s not easy, as the stories of when the committed leaders moves (or is moved) on and subsequent regression bear out.  Yet it can be, and has been, done.

So, if  we’re choosing cultural values, and working towards them, both in ways that reflect what science tells us about doing our best, aren’t we really doing such engineering?  Yes, social engineering  also refers to another means for breaking security systems. And cultural engineering has various legacy implications including ‘culture’ (read: theatre, music, etc) and even misguided political movements in the past.  Maybe we need a better term, but I think the concept of moving in a positive environmental direction is something to be considered systematically.

The open question is, does this make sense at a societal level as well?  Ok, not going there.  But regardless, I reckon that there’s a strong link between learning and the organizational culture.  Organizational Development, I guess, is the field that does this, though they seem to not focus on actual skills as much as facilitation. That’s not a bad start, but perhaps there’s an opportunity to break down silos here. Getting these elements  aligned.  Which, of course, is an organizational change.  Pondering, and I welcome your thoughts.

OK, so I made up the term silage (and then found it was a real word with a different meaning), but here I don’t mean siloed fodder (except perhaps metaphorically).  What I’m talking about is the damage that can come from silos. And I heard a tale yesterday in the course of an investigation  into  corporate innovation that illuminated what I’m talking about.

In this case a particular business unit, with a strong bias to rigor in execution, is also working on innovation.  And it’s going pretty well, it appears.  They’re working on opening up communication, supporting it through programmatic actions, and sharing success stories.  These are powerful tools to change a culture.  But there’s a barrier.

Part of the challenge is in management. This layer, between executive desire and tactical actions, is being encouraged to support this move, but is still largely measured on outcomes.  And, the group that owns management development isn’t connected to the group supporting the programs.  Guess what? It’s a turf war.  One silo doesn’t want any incursion into it’s area of activity.  And this is a problem.

To succeed, you really need to work systemically.   It’s hard enough to make change happen without having to deal with areas that aren’t on board. There’s going to be be a far higher likelihood of success if all the elements are aligned (and a large number of other elements conducive to successful change). If the mentoring and coaching isn’t there to go along with programmatic impetus (see 70:20:10), you’re dropping the ball. You’re going to see a drop off, instead a continual upward learning curve.

As things move faster, to adapt you need to tap into the power of people. That means developing a culture that learns, and that requires both crossing silos in implementation  and in then leveraging the collective thinking.  Can we avoid collateral silage?

Someone recently asked how you would go about measuring culture change, and I thought it’s an interesting question.  I’ll  think ‘out loud’ about what might be the possibilities.  A  learning culture is optimal for organizational innovation and agility, and it’s likely that not all elements are already in place.  So it’s plausible that you’d want to change, and if you do, you’d like to know how it’s going.

I think there are two major categories of measures: direct and indirect. Direct measures are ones that are impacting the outcomes you’re looking for, and indirect ones are steps along the way. Say, for instance, one desirable outcome of a learning culture would be, well, learning!  In this case, I mean the broad sense of learning: problems solved, new designs generated, research answering questions.  And indirect would be activity likely to yield that outcome. It could be engagement, or social interaction, or…  If we think of it in a Kirkpatrickian sense, we want to generate the indirect activity, and then measure the actual business impact.

What direct measures might there be?  I can see time to solve customer problems or problems solved per time.  And/or I might look at the rate of research questions answered.  Or the rate of new product generation.  Of course, if you were expecting other outcomes from your culture initiative, you’d naturally want aligned methods.   You could just be concerned with employee engagement, but I’m somewhat inclined (and willing to be wrong) to think about what the outcome of increased engagement would be.  It could also be retention or recruitment, if those are your goals.

These latter – engagement, recruitment, retention – are also possible indirect measures.  They indicate that things are better. Another indirect but more targeted measure might be the amount of collaboration happening (e.g. the use of collaboration tools) or even activity in social networks.  Those have been touted as the benefits of building community in social media, and those are worthwhile as well.

As a process, I think about what I might do  before, during, and after any culture change initiative.  I’d probably want a baseline to begin with, and then regular (if not continual) assessments as we go.  I’d take small steps, perhaps in one unit to begin, and monitor the impact, tuning as I go along.  Culture change is a journey, not an event, after all ;).

So ok, that’s off the top of my head, what say you?

A dear friend and colleague just wrote about his recent (and urgent) chemo and surgery.  I won’t bore you with the details (the odds are you don’t know him), but one thing stuck with me that I do want to share.

As context, he discovered he had a rare and aggressive cancer, and this  ventured into the unknown, with a sense of urgency.   He fortunately had access to arguably the world’s best resources on this, but the ‘rare’ bit means that there wasn’t a lot of data:

“The treatment options were unclear because they didn‘t have enough real data  to know what was most likely to work..I didn‘t know that the lack of data was so profound that intuition and personal experience, not data, would play a central role in the decisions.”

Collaboration was critical.  There were two different domains in play, and they had to work and play well together. An oncologist and a specialist in the location were required to determine a course of action:

“If you‘re ever in a situation like this, having world-class experts is so critical! I could see the mental wheels  turning, the quick parlay  back and forth between the experts, leading to the  suggestion…”

And, interestingly, his voice was an important one:

“Amazing how much the decision seemed to also rest with me, not just with the experts.”

They knew they didn’t know, and they wanted to understand his preferences.  He had a voice, instead of being told what to do. If you don’t know, look for preferences.

This is what decision-making looks like when it matters and it’s new: open collaboration. This also reminds me of Jane Bozarth’s story about her husband’s situation, where again expertise and preparation matter.  The details are not trivial, they’re  critical.

And these situations are increasing. Whether life-threatening or not, and even with the power of data, we’re going to be facing increasingly challenging decisions.  We need to learn when and how to collaborate.  One person following a script (which should be automated) is increasingly less likely to be the answer. An individual equipped with models, and resources including others, is going to be the minimal necessary solution.