I was pointed to a report from MIT Sloan Management talking about how big data was critical to shorten ‘time to insight’. And I think that’s a ‘good thing’ in the sense that knowing what’s happening faster is clearly going to be part of agility.  But I  must be missing something, because unless I’m mistaken, big data can’t  give you the type of insights you  really need.

Ok, I get it. By the ‘test and learn’ process of doing experiments and reading reactions, you can gather data quickly. And I’m all for this.  But this is largely  internal, and I think the insights needed are external. And yes, the experiments can be outside the firewall, trying new things with customers and visitors and reading reactions, but that’s still in the realms of the understood or expected. How can such a process detect the disruptive influences?

Years ago, with friend and colleague  Eileen Clegg, we wrote a chapter based upon her biologist husband’s work in extremophiles, looking for insight into how to survive in tough times.  We made analogies from a number of the biological phenomena, and one was the need to be more integrated with the environment, sensing changes and bringing them in. Which of course, triggered an association.

If we adapt Harold Jarche’s Personal Knowledge Mastery (or PKM), which is about Seek-Sense-Share as a mechanism to grow our own abilities, to organizations, we can see a different model.  Perhaps an OKM?  Here’s organizations seek knowledge sources, sense via experiments and reflection, and share internally (and externally, as appropriate ;).

This is partly at the core of the Coherent Organization model as well, where communities are seeking and sharing outside as ways to continue to evolve and feed the teams whose work is driving the organization forward. It’s about flows of information, which can’t happen if you’re in a Miranda Organization. And so while big data is a powerful tool, I think there’s something more required.

I think the practices and the culture of the organization are more important.  If you don’t have those right, big data won’t give big insights, and if you do, big data is just one of your tools.  Even if you’re doing experiments, it might be small data, carefully instrumented experiments targeted at getting specific outcomes, rather than big data, that will give you what you need.  But more importantly, sensing what’s going on outside, having diverse interests and a culture of curiosity is going to be the driver for the unexpected opportunities.

So yes, use the tools to hand and leverage the power of technology, but focus on motivations and culture so that the tools will be used in the important ways.  At least that was my reaction.  What’s yours?

In thinking a bit about the Future of Work, one of the issues is where to start.  If we take the implications of the Coherent Organization to heart, we realize that the components include the work teams, the communities of practice (increasingly I think of it as a community of improvement), and the broader network.  But where to begin?

A couple of principles fall into place for me.  The first is the notion of  ‘trojan mice’, e.g. small steps rather than a epic change. That, coupled with the notion of scaling up from the small, leads me to believe that the best place to start is to start small. This follows on the advice about change in general  that changes should be strategic and leveraged.

So, a natural place to start small is the team itself.  The goal would be to draw upon a diverse team meeting a real need, but facilitating their tool use. I remember an engagement with a Scandinavian oil company that I was brought in on, where they started out establishing teams for new projects that crossed geographies (and, implicitly, cultures), scaffolded them using collaboration and communication tools, and then released them back to other projects. The goal was to skill up teams and have the team members become viral influences.

Another approach, as there are already likely communities in existence, would be to migrate and facilitate communities online. I recall that the Defense Acquisition University took this approach.  However, I might like to get some project teams going with tools and then migrate out to the communities, where those team members that had participated were familiar with the tools and could be drawn upon by the community.

In fact, after the initial team work, I might facilitate a team not only working together, but working out  loud back to their respective communities.  And while it makes practical sense to be sequential, at some point it might make sense to go parallel, and be having the working out loud from the teams being worked on at the same time as the community development. But for resource reasons, I might make it sequential.  Ultimately, you want to be facilitating the communities participating in  and outside  the organizations, and looking to other communities both inside and outside for inspiration.

The point is to be finding a small way to begin, and maybe take several tries until you work out how to do it well, then start scaling up and out.  You want to build need, awareness, and ability steadily.  It can effect a change in culture too, if the principles that make this work in teams and communities begins to be made aware as well.

And this is not independent of work on going to more performance consulting and performance support in the organization, but instead is a complement.  In previous exercises, different organizations have prioritized different elements, where you begin will be dependent on your context.

So, in the social space,  this is my instinct and experience, but welcome hearing alternate viewpoints.

#itashare

In some recent work, an organization is looking to find a way to learn fast enough to cope with the increasing changes we’re seeing.  Or, better yet, learn  ahead of the curve. And this led to some thoughts.

As a starting point, it helps to realize that adapting to change is  a form of learning. So, what are the individual equivalents we might use as an analogy?  Well, in known areas we take a course.  On the other hand, for self-learning, e.g. when there isn’t a source for the answer, we need to try things.  That is, we need a cycle of: do – review -refine.

In the model of a learning organization, experimentation is clearly listed as a component of concrete learning processes and practices.  And my thought was that it is therefore  clear that any business unit or community of practice that wants to be leading the way needs to be trying things out.

I’ve argued before that learning units need to be using new technologies to get their minds around the ‘affordances’ possible to support organizational performance and development.  Yet we see that far too few organizations are using   social networks for learning (< 30%), for example.

If you’re systematically tracking what’s going on, determining small experiments to trial out the implications, documenting and sharing the results, you’re going to be learning out ahead of the game. This should be the case for all business units, and I think this is yet another area that L&D could and should be facilitating.  And by facilitating, I mean: modeling (by doing it internally), evangelizing, supporting in process, publicizing, rewarding, and scaling.

I think the way to keep up with the rate of change is to be driving it.  Or, as Alan Kay put it: “the best way to predict the future is to invent it”.  Yes, this requires some resources, but it’s ultimately key to organizational success, and L&D can and should be the driver of the process within the organization.