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Clark Quinn’s Learnings about Learning

Developing L&D

7 September 2017 by Clark Leave a Comment

One of the conversations I’ve been having is how to shift organizations into modern workplace learning. These discussions have not been with L&D, but instead targeted directly at organizational strategy. The idea is to address a particular tactical goal as  part of a strategic plan, and to do so in ways that both embody and develop learning and a collaboration culture. The topic was then raised about how you’d approach an L&D unit under this picture. And I wondered whether you’d use the same approach to developing L&D as part of L&D operations. The answer isn’t obvious.

So what I’m talking about here would be to take an L&D initiative, and do it in this new way, with coaching and scaffolding. The overall model involves a series of challenges with support.  You’re developing some new organizational capability, and you’d scaffold the process initially with some made up or pre-existing challenges.  Then you gradually move to real challenges. So, does this model change for L&D?

My thought was that you’d take an L&D initiative, and something out of the ordinary, an experiment.  Depending on the particular organization’s context, it might be performance support, or social media, or mobile, or…  Then you define an experiment, and start working on it. To develop the skills to execute, you give a team (or teams) some initial challenges: e.g. critique a design. Then more complex ones, so: design a solution to a problem someone else has solved. Finally, you give them the real task, and let them go (with support).

This isn’t slow; it’s done in sprints, and still fits in between other work. It can be done in a matter of weeks.  In doing so, you’re having the team collaborate with digital tools (even if/while working F2F, but ideally you have a distributed team). Ultimately, you are developing both their skills on the process itself  and on working together in collaborative ways.

In talking this through, I think this makes sense for L&D as well, as long as it’s a new capability that’s being developed.  This is an approach that can rapidly develop new tactical skills and change to a culture oriented towards innovation: experimentation and iterative moves. This is the future, and yet it’s unlike most of the way L&D operates now.

Most importantly, I think, is that this opportunity is on the table now for a brief period. L&D can internally develop their understanding and ability of the new ways of working as a step towards being an organization-wide champion. The same approach taken within  L&D then can be taken and used elsewhere.  But it takes experience with this approach before you can scale it.  Are you ready to make the shift?

Metaphors for L&D

5 September 2017 by Clark 4 Comments

What do you see the role of L&D being in the organization?  Metaphors are important, as they form a basis for inferences of what fits. We frame  our conversations by the metaphors we use, and these frames guide what’s allowed conversation and what’s not.  To put it another way, metaphors are the basis for mental models that explain and predict what happens.  But metaphors and models simplify things, making certain things ‘invisible’.  Thus, our metaphors can keep us from seeing things that might be relevant.

LEARNING & development

Thus, we should examine the metaphors we’re using in L&D.  We can start, of course, even with the term L&D: Learning & Development.  Typically, it’s the ‘learning’ part that dominates: we’re talking about helping people learn. And this metaphor implies: courses. Yet, we know that formal learning is only part of the picture of full development of capability. So the ‘development’ part should play a role, including coaching and the choice of assignments. Perhaps also meta-learning.  Though I’d suggest that these latter bits aren’t prominent, because learning  can  be a mechanism for development, and therefore the following steps lag. Which is why movements like 70:20:10 can be helpful in awakening a broader emphasis.

However, there’s more. In  Revolutionize Learning & Development, I argued that we should switch the term to  P&D, Performance & Development. Here I was trying to recognize that our learning has a goal: the ability to perform. Also, there are other paths to performance, including performance support.  I still wanted development, including formal learning, but we also want to develop the ability for the organization to continue to learn: innovation.  And I’m not claiming that this can break the problem with learning, as P&D might end up only emphasizing on performance, as L&D ends up only emphasizing learning.

The point being is that we need to have a perspective that doesn’t limit our vision. It’s the case that L&D  could be just about courses, but I want to suggest that’s not optimal.  A ‘course’ perspective allows the focus to be on the delivery, not on the outcome. With more ability for individuals to learn on their own, traditional courses are likely to wither.  I think it’s a path to irrelevance.

I’ll suggest that we want to be thinking about all the ways that an organization can facilitate doing, and increasing the ability to do. Then we should figure out what parts we can contribute to. If, as I suggest, we want to be professional about understanding learning, then we have a basis to be the best people to guide all of it.

So I don’t know the best metaphor.  What I do believe is that ‘course’, and even ‘learning’ can be limiting. (I’ve also thought that ‘talent development’ is not sufficient.) I’ve suggested P&D, but perhaps it’s organic and about organizational growth. Or perhaps it’s about performance and increasing. So, now, it’s over to you: what do you think would be a helpful way to look at it. Do we need a rebranding, and if so, to what?

Evidence-based L&D

31 August 2017 by Clark Leave a Comment

Conducting ScienceEarlier this year, I wrote that L&D was a ‘Field of Dreams‘ industry, running on a belief that “if you build it, it is good”.  There’s strong evidence that we’re not delivering on the needs of the organization. So what  is a good basis for finding ways to support people in the moment  and develop them over time?  We want to look to what research and theory tell us .  In short, I think L&D should be evidence-based.

What  does  the evidence say?  There are a number of places where we can look, but first we have to figure out what we  can (and should) be doing.  I suggest that L&D isn’t doing near what it could and should, and what it  is doing, it is doing badly.  So let’s start with that latter.

One thing L&D should be doing is making learning experiences that have organizational impact.  There’s evidence that organizations that measure impact, do better. There’s also evidence that there are principles on which to design learning that leads to better outcomes.  Yet, despite signups for the eLearning Manifesto, there’s still evidence that organizations aren’t following those principles, if extant elearning is any indication. Similarly, the number of L&D units actually measuring their impact on organizational metrics seems to be lagging those that, for instance, just use ‘smile sheets‘. And even those are done badly.

There’s also an argument that L&D could and should be considering performance support as well. There are certainly instances where, as I’ve heard it said (and I’m paraphrasing, I can’t find the original quote): “inside every course there’s a lean job aid waiting to get out”. Certainly, performance can improve with a job aid instead of training (c.f. Atul Gawande’s  Checklist Manifesto).

Further actions by L&D include facilitating communication and collaboration. Again, organizations that become learning organizations succeed better than those that don’t. The elements of a learning organization include the skills around working together and a culture where doing so can flourish.  We know what makes brainstorming work, and more.

In short, there’s a vast body of evidence about how to do things right. It’s time to become professionals, and pay attention. In that sense, we’re organizational learning engineers. While there may be a lack of evidence about the linkage between individual learning and organizational learning, we do know a lot about facilitating each.  And we should.  Are you ready?

 

Dual OS or Teams of Teams?

23 August 2017 by Clark Leave a Comment

I asked this question in the L&D Revolution LinkedIn group I have to support the Revolutionize L&D book, but thought I’d ask it here as well. And I’ve asked it before, but I have some new thoughts based upon thinking about McChrystal’s Team of Teams. Do we use a Dual Operating System (Dual OS), with hierarchy being used as a base to pull out teams for innovation, or do we go with a fully podular model?

In a Dual OS org, the hierarchy continues to exist for doing the work that is known that needs to be done. Kotter pulls out select members to create teams to attack particular innovation elements.  These teams change over time, so people are cycled back to work and new folks are infused with the innovation approach.

My question here is whether this really creates an entire culture of innovation. In both Keith Sawyer’s  Group Genius and Stephen Johnson’s  Where Do Good Ideas Come From, real innovation bubbles along, requiring time and serendipity. You can get innovative solutions for known problems from teams, but for new insights you need an ongoing environment for ideas to emerge, collide, percolate/incubate/ferment.  How do you get that going across the organization?

On the other hand, looking at the military, there’s a huge personnel development infrastructure that prepares people to be members of the elite teams. Individuals from these teams intermix to get the needed adaptivity, but it’s based upon a fixed foundation. And there are still many hierarchical mechanisms organized to support the elite work.  So is it really a fully teamed approach?

As I write this, it sounds like you do need the Dual OS, and I’m willing to believe it.  My continuing concern again is what fosters the ongoing innovation?  Can you have an innovative hierarchy as well? Can you have a hierarchy with a culture of experimentation, accepting mistakes, etc? How do the small innovations in operating process occur along with the major strategic shifts?  My intuitions go towards creating teams of teams, but  completely. I do believe everyone’s capable of innovation, and in the right atmosphere that can happen. I don’t think it’s separate, I believe it has to be intrinsic and ubiquitous.  The question is, what structure achieves this?  And I haven’t seen the answer yet.  Have you?  Perhaps we still have some experimentation to do ;).

3 E’s of Learning: why Engagement

16 August 2017 by Clark 1 Comment

Letter EWhen you’re creating learning experiences, you want to worry about the outcomes, but there’s more to it than that.  I think there are 3 major components for learning as a practical matter, and I lump these under the E’s: Effectiveness, Efficiency, & Engagement. The latter may be more of a stretch, but I’ll make the case .

When you typically talk about learning, you talk about two goals: retention over time, and transfer to all appropriate (and no inappropriate) situations.  That’s learning effectiveness: it’s about ensuring that you achieve the outcomes you need.  To test retention and transfer, you have to measure more than performance at the end of the learning experience. (That is, unless your experience definition naturally includes this feedback as well.) Let alone just asking learners if they  thought it was valuable.  You have to see if the learning has persisted later, and is being used as needed.

However, you don’t have unlimited resources to do this, you need to balance your investment in creating the experience with the impact on the individual and/or organization.  That’s  efficiency. The investment is rewarded with a multiplier on the cost.  This is just good business.

Let’s be clear: investing without evaluating the impact is an act of faith that isn’t scrutable.  Similarly, achieving the outcome at an inappropriate expense isn’t sustainable.  Ultimately, you need to achieve reasonable changes to behavior under a viable expenditure.

A few of us have noticed problems sufficient to advocate quality in what we do.  While things may be trending upward (fingers crossed), I think there’s still ways to go when we’re still hearing about ‘rapid’ elearning instead of ‘outcomes’.  And I’ve argued that the necessary changes produce a cost differential that is marginal, and yet yields outcomes more than marginal.   There’s an obvious case for effectiveness  and efficiency.

But why engagement? Is that necessary? People tout it as desirable. To be fair, most of the time they’re talking about design aesthetics, media embellishment, and even ‘gamification‘ instead of intrinsic engagement.  And I will maintain that there’s a lot more possible. There’s an open question, however: is it worth it?

My answer is yes. Tapping into intrinsic interest has several upsides that are worth the effort.  The good news is that you likely don’t need to achieve a situation where people are willing to pay money to attend your learning. Instead, you have the resources on hand to make this happen.

So, if you make your learning – and here in particular I mean your introductions, examples, and practice – engaging, you’re addressing motivation, anxiety, and potentially optimizing the learning experience.

  • If your introduction helps learners connect to their own desires to be an agent of good, you’re increasing the likelihood that they’ll persist  and  that the learning will ‘stick’.
  • If your examples are stories that illustrate situations the learner recognizes as important, and unpack the thinking that led to success, you’re increasing their comprehension and their knowledge.
  • Most importantly, if your practice tasks are situated in contexts that are meaningful to learners both because they’re real  and important, you’ll be developing their skills in ways closest to how they’ll perform.  And if the challenge in the progression of tasks is right, you’ll also accelerate them at the optimal speed (and increase engagement).

Engagement is a fine-tuning, and learner’s opinions on the experience aren’t the most important thing.  Instead, the improvement in learning outcomes is the rationale.  It takes some understanding and practice to get systematically good at doing this. Further, you can make learning engaging, it is an acquired capability.

So, is your learning engaging intrinsic interest, and making the learning persist? It’s an approach that affects effectiveness in a big way and efficiency in a small way. And that’s the way you want to go, right? Engage!

Innovative Work Spaces

15 August 2017 by Clark Leave a Comment

working togetherI recently read that Apple’s new office plan is receiving bad press. This surprises me, given that Apple usually has their handle on the latest in ideas.  Yet, upon investigation, it’s clear that they appear to not be particularly innovative in their approach to work spaces.  Here’s why.

The report  I saw says that Apple is intending to use an open office plan. This is where all the tables are out in the open, or at best there are cubicles. The perceived benefits are open communication.  And this is plausible when folks like Stan McChrystal in  Team of Teams are arguing for ‘radical transparency’.  The thought is that everyone will know what’s going on and it will streamline communication. Coupled with delegation, this should yield innovation, at the expense of some efficiency.

However, research hasn’t backed that up. Open space office plans can even drive folks away, as Apple’s hearing. When you want to engage with your colleagues and stay on top of what they’re doing, it’s good.  However, the lack of privacy means folks can’t focus when they’re doing heavy mental work. While it sounds good in theory, it doesn’t work in practice.

When I was keynoting at the Learning@Work conference in Sydney back in 2015, a major topic was about flexible work spaces. The concept here is to have a mix of office types: some open plan, some private offices, some small conference rooms. The view is that you take the type of space you need when you need it. Nothing’s fixed, so you travel with your laptop from place to place, but you can have the type of environment you need. Time alone, time with colleagues, time collaborating. And this was being touted both on principled and practical grounds with positive outcomes.

(Note that in McChrystal’s view, you needed to break down silos. He would strategically insert a person from one area with others, and have representatives engaged around all activities.  So even in the open space you’d want people mixed up, but most folks still tend to put groups together. Which undermines the principle.)

As Jay Cross let us know in his landmark  Informal Learning,  even the design of workspaces can facilitate innovation. Jay cited practices like having informal spaces to converse, and putting the mail room and coffee room together to facilitate casual conversation.  Where you work matters as well as how, and open plan has upsides but also downsides that can be mitigated.

Innovation is about culture, practices, beliefs,  and   technology.  Putting it all together in a practical approach takes time and knowledge to figure out where to start, and how to scale.  As Sutton and Rao tell us, it’s a ground war, but the benefits are not just desirable, but increasingly necessary. Innovation is the key to transcending survival to thrival. Are you ready to (Qu)innovate?

L&D Tuneup

8 August 2017 by Clark Leave a Comment

auto engineIn my youth, owing to my father’s tutelage and my desire for wheels, I learned how to work on cars. While not the master he was, I could rebuild a carburetor, gap points and sparkplugs, as well as adjust the timing. In short, I could do a tuneup on the car.  And I think that’s what Learning & Development (L&D) needs, a tuneup.

Cars have changed, and my mechanic skills are no longer relevant. What used to be done mechanically – adjusting to altitude, adapting through the stages of the engine warming up, and handling acceleration requests – are now done electronically. The air-fuel mixture and the spark advance are under the control of the fuel injection and electronic ignition systems (respectively) now.  With numerous sensors, we can optimize fuel efficiency and performance.

And that’s the thing: L&D is too often still operating in the old, mechanical, model. We have the view of a hierarchical model where a few plan and prepare and train folks to execute. We stick with face-to-face training or maybe elearning, putting everything in the head, when science shows that we often function better from information in the world or even in other people’s heads!  And this old approach no longer works.

As has been noted broadly and frequently, the world is changing faster and the pressure is on organizations to adapt more quickly. With widely disparate paths    pointing in the same direction, it’s easy to see that there’s something fundamental going on. In short, we need to move, as Jon Husband puts it, from hierarchy to wirearchy.  We need agility: experimentation, review, and reflection, iteratively and collectively. And in that move, there’s a central role for L&D.

The move may not be imminent, but it is unavoidable. Even staid and secure organizations are facing the consequences of increasing rates of change and new technology innovations. AI, networks, 3D printing, there are ramifications. Even traditional government agencies are facing change. Yet, this is all about people and learning.

As Harold Jarche tells us, work is learning and learning is the work. That means learning is moving from the classroom to the workplace and on the go. L&D needs a modern workplace learning approach, as Jane Hart lets us know. This new model is one where L&D moves from fount of knowledge to learning facilitator (or advisor, as she terms it).  People need to develop those communication and collaboration, but it won’t come from classes, but from coaching and more.

And, to return to the metaphor, I view this as an L&D tuneup. It’s not about throwing out what you’re doing (unless that’s the fastest path ;), but instead augmenting it. Shifts don’t happen overnight, but instead it means taking on some internal changes, and then working that outwards with stakeholders, reengineering the organizational relationships. It’s a journey, not an event. But like with a tuneup, it’s about figuring out what your new model should be, and then adjusting until you achieve it. It’s over a more extended period of time, but it’s still a tuning operation. You have to work through the stages to a new revolutionary way of working. So, are you ready for a tuneup?

Ethics and AI

2 August 2017 by Clark 1 Comment

I had the opportunity to attend a special event pondering the ethical issues that surround Artificial Intelligence (AI).  Hosted by the Institute for the Future, we gathered in groups beforehand to generate questions that were used in a subsequent session. Vint Cerf, co-developer of the TCP/IP protocol that enabled the internet, currently at Google, responded to the questions.  Quite the heady experience!

The questions were quite varied. Our group looked at Values and Responsibilities. I asked whether that was for the developers or the AI itself. Our conclusion was that it had to be the developers first. We also considered what else has been done in technology ethics (e.g. diseases, nuclear weapons), and what is unique to AI.  A respondent mentioned an EU initiative to register all internet AIs; I didn’t have the chance to ask about policing and consequences.  Those strike me as concomitant issues!

One of the unique areas was ‘agency’, the ability for AI to  act.  This led to a discussion for a need to have oversight on AI decisions. However, I suggested that humans, if the AI was mostly right, would fatigue. So we pondered: could an AI monitor another AI?  I also thought that there’s evidence that consciousness is emergent, and so we’d need to keep the AIs from communicating. It was pointed out that the genie is already out of the bottle, with chatbots online. Vint suggests that our brain is layered pattern-matchers, so maybe consciousness is just the topmost layer.

One recourse is transparency, but it needs to be rigorous. Blockchain’s distributed transparency could be a model. Of course, one of the problems is that we can’t even explain our own cognition in all instances (we make stories that don’t always correlate with the evidence of what we do). And with machine learning, we may be making stories about what the system is using to analyze behaviors and make decisions, but it may not correlate.

Similarly, machine learning is very dependent on the training set. If we don’t pick the right inputs, we might miss some factors that would be important to incorporate in making answers.  Even if we have the right inputs, but don’t have a good training set of good and bad outcomes, we get biased decisions. It’s been said that what people are good at is crossing the silos, whereas the machines tend to be good in narrow domains. This is another argument for oversight.

The notion of agency also brought up the issue of decisions.  Vint inquired why we were so lazy in making decisions. He argued that we’re making systems we no longer understand!  I didn’t get the chance to answer that decision-making is cognitively taxing.   As a consequence, we often work to avoid it.  Moreover, some of us are interested in X, so are willing to invest the effort to learn it, while others are interested in Y. So it may not be reasonable to expect everyone to invest in every decision.  Also, our lives get more complex; when I grew up, you just  had phone and TV, now you need to worry about internet, and cable, and mobile carriers, and smart homes, and…  So it’s not hard to see why we want to abrogate responsibility when we can!  But when can we, and when do we need to be careful?

Of course, one of the issues is about AI taking jobs.  Cerf stated that nnovation takes jobs, and generates jobs as well. However, the problem is that those who lose the jobs aren’t necessarily capable of taking the new ones.  Which brought up an increasing need for learning to learn, as the key ability for people. Which I support, of course.

The overall problem is that there isn’t a central agreement on what ethics a system should embody, if we  could do it. We currently have different cultures with different values. Could we find agreement when some might have different view of what, say, acceptable surveillance would be? Is there some core set of values that are required for a society to ‘get along’?  However, that might vary by society.

At the end, there were two takeaways.  For one, the question is whether AI can helps us help ourselves!  And the recommendation is that we should continue to reflect and share our thoughts. This is my contribution.

What is the Future of Work?

25 July 2017 by Clark Leave a Comment

which is it?Just what is the Future of Work  about? Is it about new technology, or is it about how we work with people?  We’re seeing  amazing new technologies: collaboration platforms, analytics, and deep learning. We’re also hearing about new work practices such as teams, working (or reflecting) out loud, and more.  Which is it? And/or how do they relate?

It’s very clear technology is changing the way we work. We now work digitally, communicating and collaborating.  But there’re more fundamental transitions happening. We’re integrating data across silos, and mining that data for new insights. We can consolidate platforms into single digital environments, facilitating the work.  And we’re getting smart systems that do things our brains quite literally can’t, whether it’s complex calculations or reliable rote execution at scale. Plus we have technology-augmented design and prototyping tools that are shortening the time to develop and test ideas. It’s a whole new world.

Similarly, we’re seeing a growing understanding of work practices that lead to new outcomes. We’re finding out that people work better when we create environments that are psychologically safe, when we tap into diversity, when we are open to new ideas, and when we have time for reflection. We find that working in teams, sharing and annotating our work, and developing learning and personal knowledge mastery skills all contribute. And we even have new  practices such as agile and design thinking that bring us closer to the actual problem.  In short, we’re aligning practices more closely with how we think, work, and learn.

Thus, either could be seen as ‘the Future of Work’.  Which is it?  Is there a reconciliation?  There’s a useful way to think about it that answers the question.  What if we do either without the other?

If we use the new technologies in old ways, we’ll get incremental improvements.  Command and control, silos, and transaction-based management can be supported, and even improved, but will still limit the possibilities. We can track closer.  But we’re not going to be fundamentally transformative.

On the other hand, if we change the work practices, creating an environment where trust allows both safety  and accountability, we can get improvements whether we use technology or not. People have the capability to work together using old technology.  You won’t get the benefits of some of the improvements, but you’ll get a fundamentally different level of engagement and outcomes than with an old approach.

Together, of course, is where we really want to be. Technology can have a transformative amplification to those practices. Together, as they say, the whole is greater than the some of the parts.

I’ve argued that using new technologies like virtual reality and adaptive learning only make sense  after you first implement good design (otherwise you’re putting lipstick on a pig, as the saying goes).  The same is true here. Implementing radical new technologies on top of old practices that don’t reflect what we know about people, is a recipe for stagnation.  Thus, to me, the Future of Work starts with practices that align with how we think, work, and learn, and are augmented with technology, not the other way around.  Does that make sense to you?

Accountability and Safety

18 July 2017 by Clark 4 Comments

In much of the discussion about tapping into the power of people via networks and communities, we hear about the learning culture we need. Items like psychological safety, valuing diversity, openness, and time for reflection are up front. And I’m as guilty of this as anyone! However, one other element that appears in the more rigorous discussions (including Edmondson’s Teaming and Sutton & Rao’s  Scaling Up Excellence) is accountability. (Which isn’t to say that it doesn’t appear in other pictures, but it’s certainly not foreground.) And it’s time to address this.

So, the model for becoming agile is creating an environment where people learn, alone  and together.  But it’s informal learning. When you research, problem-solve, design, etc, you don’t know the answer when you start! Yet it’s not like anyone else has the answer, either.  And we know that the output is better when we search more broadly through the possible solution space. (Which is what we’re doing, really.) This means we need diverse inputs to keep us from prematurely converging.  Or searching too narrow a space. We also need also those different voices to contribute, or we won’t get there. And we have to be open to new ideas, or we could inadvertently cut off part of the solution space. We also need time and tools for reflection (hence reflecting out loud).

Typically, the process is iterative (real innovations percolate/ferment/incubate; they aren’t ‘driven’): going away, doing tasks, and returning.  Here,  we need to ensure people  are  contributing, doing the work.  We don’t want to micromanage it, but we do want to assist people because we shouldn’t assume that they’re effective self and social learners.  In short, we can’t squelch the feeling of autonomy to accompany purpose (ala Dan Pink’s Drive), yet the job must get done!

Accountability and SafetyWhen there’s purpose, and community, accountability is natural. When we comprehend how what we’re doing contributes, when we have reciprocal trust with our colleagues that we’ll each do our part, and when there’s transparency about what’s happening, it’s a natural. A transactional model, when it’s a network and not a community, doesn’t feel safe, and doesn’t work as well.  As Edmondson documents it, you want to be in the learning zone where you have both accountability  and safety. And that’s not an easy balance.

So one of the steps to get there is to ensure accountability is part of the picture. And it’s not just calling someone on the carpet. Done right, it’s a tracking and regular support to succeed, so accountability is an ongoing relationship that suggests we  want you to succeed, and we’ll help you do that. Accountability shouldn’t be a surprise! (Transparency helps.)

When we talk about the high-minded principles of making it safe and helping people feel welcome, some can view this as all touchy-feely and worry that it won’t get things  done.  Which isn’t true, but I think it helps if we keep accountability in the picture to assuage those concerns.  Ultimately, we want outcomes, but new and improved ones, not just the same old things. The status quo isn’t really acceptable today. In this increasingly dynamic environment, the ability to adapt is key. And that’s the Learning Zone. Are you ready to go there?

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