In a recent discussion around HR strategy, the question arose about where to start.  That is, if you’ve bought into moving into the digital age, where do you begin.  The flip answer from the host of the event, a large consulting agency, was to hire them (and my flip reply is to ask whether you want newly minted MBAs following a process designed to be ‘heavy’, or someone coming in light and fast with an adaptive approach ;). But then they got serious, and responded that  you shouldn’t be reactive to people’s stated needs, and you needed data to identify what problems are crucial.  And I wasn’t satisfied with that, for two related reasons.  In short, I thought that was still reactive and that it wasn’t going to help you focus ahead, and that you needed top-down to complement bottom up.

This was buttressed by a post pointed out to me by my ITA colleagues that was arguing a good design strategy was to find out what people needed. And I’m reminded of the quote by Steve Jobs that you can’t just give people what they want, because by the time you  do, they’ve changed their minds.  And just finding what people need and doing it is a bit reactive, it seems to me, regardless.  Even, to be honest, finding the company’s biggest barriers, and addressing them, isn’t a sufficient response.  It’s a good one, but it’s not enough.

Interestingly, an HR Director sitting next to me was nodding her head during that response about the data. So afterward I asked her what sort of data she had in mind. I asked about both survey data, and business metrics, and she indicated both (and anything else ;).  And I think that’s a good basis. But not a sufficient one.

If you look at most design in the real world, you’ll see that designers cycle between top-down and bottom-up.  It helps to check that you’re indeed draining the swamp, but also to ensure you’re not getting eaten by alligators.  And that’s the point I want to make.

I’m (obviously) a believer in frameworks. I want conceptual clarity. And I don’t want best practices, I want to abstract best principles and recontextualize them.  But I also believe you need to check how you’re going, and regularly test.  There are some overarching results that should be incorporated: culture, innovation, performance support, etc. And they can be instituted in ways that address problems yet also develop your ability.

So I  do think collecting data on what’s going on, and identifying barriers is important.  But if you’re not also looking at the horizon and figuring out where you’re going in the longer term, you could be metaphorically ensuring no flat tires on a trip to the wrong neighborhood.  My short answer to their question would’ve been to document where you are, and where you want to get, and then figure out which of the top issues the data indicate sets you on a path to address the rest  and build your capability and credibility.

For a number of years now (at least six), I’ve been beating the drum about the need for organizations to be prepared to address change. I’ve argued that things are happening faster, and that organizations are going to have to become more agile.  Now we’re seeing the evidence that the change has arrived.

Two recent reports highlight the awareness. Gallup released a report  on The State of the American Workplace recently that talks about the lack of engagement at work.  Deloitte also released a report,  Rewriting the rules in the digital age,  that documents trends shifting the office environment.  With different perspectives, they both overlap in discussing the importance of culture.  It’s about creating an environment where people are empowered and enabled to contribute.

The Gallup  report concludes with new behaviors for leaders and managers.  The first point for leaders is to use data and focus on culture. This, to me, involves leveraging technology and creating an environment. L&D could be leading using performance data captured through the  ExperienceAPI, and facilitating the culture shift in courses and developing coaching. Their prescription for managers is  to move to be coaches (and again, L&D should be both developing the skills and facilitating the processes).  And employees need to take ownership of their own development, which means L&D should focus on both meta-learning and ensuring resources (curation  and creation) as well.

The second report is the more interesting one for me, because it’s about the trends and the ways to adapt.  The top two trends are the Organization of the future (c.f. The Workplace of the Future  :) and Careers and learning.  The former is about redesigning organizations to become agile.  The latter is about a redefinition of learning.  They are a wee bit old-school, however, as while they do discuss innovation throughout, it isn’t a core focus and their definition of learning doesn’t include informal learning.  It’s still a top-down model.  But again, clear opportunities for L&D.

The key leverage points, to me, are learning and technology.  And here I mean more self-directed and collaborative learning conducted not formally, but facilitated. Social learning really can’t be top-down!  Important technologies are for communicating and collaborating, as well as tools to search and find resources.

And while the focus is on HR, including recruitment and leadership, I reckon that L&D should have a key place here, as indicated. The world’s changing, and L&D needs to adapt.  It’s time to innovate L&D to support organizational innovation. Are you ready?

One of the keys to the L&D  revolution is recognizing the full performance ecosystem and the ways technology can support performance and development.  I’ve tried to represent and share  my thinking via diagrams (including here, here, and here).  Prompted by a recent conversation, it was time to revisit the representation.

Here, I’m layering on several different ways to think about the goals, elements, etc.  (Given that this is an initial version, I’m kind of haphazard about labels like mechanisms, components, etc.)  To start, as I continually argue, at the bottom it’s about coupling optimal execution with continual innovation.  We need to do well those things we know we need to do, and then we need to continually improve.  I think that more and more of the optimal execution is getting automated.

On top of that, we have components – content and people  – and the tactics to leverage them. We create or curate content (curation over creation!), and we develop relationships through community or find appropriate expertise through recommendations or search.   The goal is to have the right content and the right people ‘to hand’ to work with.

We develop content elements like performance support to support performing in the moment, and learning resources for self-directed learning over time.  We also use courses, whether individual or collaborative, to develop people (particularly when they’re novices). I’d  put courses to the left and performance support to the right (above content) if we were talking about developing people (as I have here). So,  for novices we first use courses, then  practitioners need resources and coaching, and experts need interaction.   However, performance support is on  one side on a continuum of mechanisms from performing, to developing, to innovation.  That’s what I’ve captured here.

Similarly, we use social elements like coaching, mentoring, and informal learning to develop ourselves and our organizations over time.  We use  processes  like consuming and completing to execute. Then we  develop our ability to execute and the continue to learn through  communicating and collaborating.

There are lots of ways to represent the ecosystem, and given that elaboration theory tells us multiple representations help, here’s another stab. There are lots of elements to consider and fine tune, but I like to share my thinking to help it develop!  Overall, however, the opportunity is the chance to be contributing to organizational success in systematic and valuable ways. And that, I’ll suggest, is valuable. I welcome your thoughts.

At the recent DevLearn conference, I had a chance to present  in  xAPI Base Camp on Content Systems.  This is a topic I’ve been thinking about since working on an adaptive learning system back in 1999-2000. And I think it’s now an even bigger big opportunity.  In the course of responding to an interested attendee, I aggregated this list of my (non-blog) publications on the process, and I thought it might be useful to share  them here (from most recent to earliest):

Talking about  lifecycle and opportunities in the Litmos blog

Perspective from visiting the Intelligent Content conference in eLearnMag

The possibilities and necessities of adapting  to context in Learning Solutions magazine

New ways of looking at learning content in Learning Solutions magazine

Moving from text to experience for publishers in eLearnMag

A discussion paper  including granularity and tagging in the IFETS journal

What you see is a transition in focus.  From thinking about content objects at the right granularity and with the right tagging, I transition to thinking about  strategy for content publishers. Ultimately, I have shifted  to looking at the learning industry and opportunities to adapt learning to context (which includes location, current task, current role, and more).

While I think that adaptivity is a ways away, I also believe that the initial efforts in getting more rigorous about content strategy, engineering, and governance are a worthwhile investment now. The benefits are in less redundancy, tighter design, tracking, and greater flexibility.  The long term benefits will come from analytics, adaptivity, and contextualization.  I reckon  that’s an opportunity that’s hard to ignore. I’ll suggest that it’s  past time to be thinking about it, and time to start acting.  What about you?  Are you ready?

Karen McGrane closed the DevLearn conference talking about adaptive content. She had addressed mLearnCon in the past, a great presentation, so my expectations were high.  Plus, given that I riffed on background integration in my ELearning strategy pre-con and then content strategy as a session in the xAPI camp the next day, this is a talk I was eager to hear (congrats to the eLearning Guild for putting the topic on the table).

In this entertaining and illuminating session, she made the point that responsive is better than customizing to screen, and adapting is hard, so responsive is a good starting point.

When I wrote the L&D Revolution book, I created a chart that documented the different stages that L&D could go through on the way.  I look at it again, and I see that I got (at least) one thing slightly off, as I talked about content and it’s more, it’s about integration and infrastructure.     And I reckon I should share my thinking, then and now.

The premise of the chart was that  there are stages of maturity across the major categories of areas L&D should be aware of.  The categories were Culture, Formal Learning, Performance Support, eCommunity, Metrics, and Infrastructure. And for each of those, I had two subcategories.  And I mapped each  at four stages of maturity.
Let me be clear, these were made up. I stuck to consistency in having two sub areas, and mapping to four stages of maturity.  I don’t think I was wrong, but this was an effort to raise awareness rather than be definitive. That said, I believed then and still now that the chart I created was  roughly right.  With one caveat.

In the area of infrastructure, I focused largely on two sub categories, content models and semantics. I’ve been big on the ways that content could be used, from early work I did on content models that led to flexible delivery in an adaptive learning system, a context-sensitive performance support system, and a flexible content publishing system. I’ve subsequently written about content in a variety of places, attended an intelligent content conference, and have been generally advocating it’s time to do content like the big boys (read: web marketers).  And I think these areas are  necessary, but not sufficient.

I realize, as I review the chart for my upcoming strategy workshop at DevLearn, that I focused too narrowly.  Infrastructure is really about the technical sophistication (which includes content models & semantics, but also tracking and analytics) and integration of elements to create a true ecosystem.   So there’s more to the picture than just the content models and semantics.  Really, we want to be moving on both the sophistication of the model, and the technical underpinnings of the model.

We’ll be discussing this more in Las Vegas in November. And if you’re interested in  beginning to offer a richer picture of learning and  move   L&D to be a strategic contributor to the organization, this is the chance for a jump-start!