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Clark Quinn’s Learnings about Learning

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Hard Fun Projects

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As a basic premise of my book on designing engaging learning, I maintain that learning can, and  should, be ‘hard fun’. When you look at learning and engagement, you find this perfect alignment of elements. And, it occurred to me, that’s also true for good project work.  And here I don’t just mean coursework assignments (though that too fits), but organizational innovation should also be hard fun!

As I’ve stated before in various places, when you’re designing new solutions, problem-solving, trouble-shooting, doing research, etc, you don’t know the answer when you begin.  Therefore you’re learning when you do so!  It’s not formal learning, it’s informal, but it’s still learning.  So what works in learning should make sense for innovation too.

And in learning, the alignment I found between elements of effective education and engaging learning make sense.  Both require (amongst others):

  • clear goals
  • appropriate challenge
  • meaningfulness of the problem to the context
  • meaningfulness to the learners
  • experimentation
  • feedback

And those also define a meaningful project for solving in the workplace.

That is, first  you need to have a clear goal. The size and scope of the task should be within the reach, but not the grasp, of the team. The project has to have a clear benefit to the organization.  And the team should be appropriately constituted with skills and committed to the project. The methods required for the innovation will be experimentation and feedback.  Of course, you also need diversity on the team, safety to experiment, accountability for the results.  (Which is helpful for formal learning too!)

We can, and should, be setting up our projects to meet these criteria. We get better outcomes, research tells us. That not only includes the product of the work, but team engagement as well. This is also a possible start to creating a culture of experimentation and continual learning. Which also has long-term upsides.

This came to me because I was asked in an interview what were the most fun projects I’d done. I realized that working with folks together to address problems, like when I led a team to develop an adaptive learning system, fit the bill.  And that’s work I love, whether having a group together to collectively work out better design processes or performance and development strategy.  Folks who’ve worked with me similarly have found it valuable. So who’s up for some ‘hard fun’?

Possible versus practical

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Last week, I gave a presentation to the local chapter of ATD. And I was surprised that their request was for mobile learning. Now that  is something I can speak to, but given that my book on the topic came out seven years ago now, it seemed like a dated topic. And I was wrong.  And the difference is between what’s possible and what’s practical.

Ok, so I am somewhat out ahead of the curve.  My games book came out in 2005, but the market wasn’t quite ready.  I similarly think my L&D revolution book, in 2014, was ahead of the market (the topic is finally getting more traction, close to four years later), though closer. But I thought the mlearning book was timely (not least because my publisher asked for it more than it was my initiative ;).

However, the audience was eager.  And it was relatively large for the group.  And it took a comment from the organizer to raise my awareness.  He said (and I paraphrase): “you think that it’s old, but it’s not old for everyone”. And that was indeed a wakeup call.  Because while mobile to me is very practical, for many it’s still possible.

I  do tend to move on once I reckon I’ve figured something out. I’m interested when it’s still something to be understood or solved. Once I have my mind around it, my restless brain is on to something new.  That’s why I have this blog, for instance, to wrestle with new thoughts. If they get organized enough, it becomes a presentation or even a book.  (Though sometimes I do ones that are requested, e.g. my forthcoming one on myths, and I’m supposed to be reviewing the second round of proofs!)

But the interesting thing to me is to look beyond my own bubble (and what my colleagues are talking about).  We’re looking at what’s possible but not yet done, or what’s on the horizon. Yet I need to remember to continue to tout what’s now on the menu, and recognize not everyone’s yet started moving.  The things that I think are already practical to implement are still on the ‘possible’ list for others.

If you’re reading this blog, you’re probably with me, but feel free to let others know that the things in my past I’m still happy to help with!  In any way: consulting or workshops or even speaking.  For instance, I’ll be talking engagement for the Guild at Learning Solutions, and in a webinar for AECT’s Learner Engagement group.  Just as I talk new things, like myths.  What goes around comes around, I guess, and what’s been possible is now practical.  Ask me how!

 

The Dearth of Science in Learning Technology

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Over the years, I’ve looked at a lot of learning technology.  And I see a dispiriting trend. There seems to be little learning science of late.  What I see are marketing driven decisions, even when there are claims to science!  And I think this is a problem.

First, I generally resist the ‘let me show you our product and give us your opinion’. That’s free consulting, and a very rude ask!  (Though I’m contemplating it but all they’ll get for free is the number of comments in each category I’ve noted. ;)  Still  I  will investigate things of my volition at times.  I end up seeing a lot of technology by checking it out when someone talks about it, or wandering expo halls.  And what I see concerns me.

For one, there are too many tools that have suites of features that are oriented towards ‘information dump and knowledge test’.  Which we know isn’t going to lead to meaningful learning.  Yet when I try to push them to the next level of engagement (cognitive and emotional), they’re uninterested.  The response: “this is what our customers say they want”.  Which, of course, isn’t what they need.

It gets worse when supposedly more advanced tools are proselytized. I recently sampled one system promoting their advanced memory model.  And the free-to-air course  on learning science was broken!  It failed on a couple of dimensions beyond drilling rote memory about one thing. That’s not a good example to be showing.  Yet people who don’t know better might be enthused.

For a quick test, check to see if there’s anyone who understands learning on the executive team of a vendor. You’ll see all the business roles filled.  Some might have advisory boards composed of learning folks, but it’s not clear what role they play.

And I get it.  Unfortunately, as an industry, we’re not informed consumers. I see continual conceptually fuzzy promotion of ideas, and even societies offering white papers on the latest buzzwords.  It’s business, and with business folks in charge (and shareholders to assuage), they’ll do what people want.  Yet this isn’t the professionalism we need.

Ok, so this rant doesn’t taint all companies, but it’s too true for many or most. It’s all too easy to look at the typical offerings and point out the fundamental flaws in what they’re doing, if you know how we learn. And you should.

So, I’ll continue on my crusade for us as an industry to lift our game. I hereby offer to assist any learning technology that wants to put it’s money where it’s mouth is to help them understand learning science, build it into their products, and help them promote the benefits. And I likewise offer any organization  using learning technology to help them lift their game and be better consumers.  I’ve done both before, and am ready to assist others. Because our learners need us to represent their true interests.

 

Listening

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Listening, as I mentioned, in this case to  Guy Wallace.  As one of the premier promoters of evidence-based design, he responded to my question  about what to post on with:

Any “How Tos” using methods, tools and techniques that you‘ve found to work in L&D and Performance Improvement.

Since I am a fan of Guy’s work, I thought I should answer!  Now, obviously I don’t work in a typical L&D environment, so this list is somewhat biased. So I mentally ran through memorable projects from the past and looked for the success factors. Besides the best principles I usually advocate, here are a few tips and tricks that I’ve used over the years:

  • Engage.  Obviously, I wrote a book about this, but some of the quick things I do include:
    • embed the decisions they should be making in contexts where they make sense
    • as Henry Jenkins put it: “put the player in a role they  want to be in”
    • exaggerate the context
    • minimize the distractions
    • hook the learners in emotionally from the start
  • Decisions. I find that working with the objectives for learning projects, it’s critical to focus on the decisions that learners will ultimately be making.  I argue that what will make the difference for organizations, going forward, will be better decisions. And it keeps the discussion from focusing on knowledge. Knowledge is needed, but it’s not central.
  • Brainstorming. When working a strategy session with clients, I seed the discussion before hand with the challenges and background material, and ask that everyone think on their own before we begin collaboration.
  • Better ‘Pair and Share’.  If, in brainstorming, you should think individually before collectively, so should you do so in all forms. So I trialed a ‘pair and share’ where I asked everyone to:
    • think on the questions (asking for 2 things) first,
    • then share with another,
    • and try to reach agreement
    • (I polled the first audience I trialed it on, and they said that the discussion was better, FWIW).
  • Shared language. I have found it valuable, when starting a new project, to run a little ‘presentation’ where I present some of the models that I’m bringing to the table (that’s why I‘m there ;), so we’re starting from a shared understanding. And of course I’ve reviewed materials of theirs beforehand so I can use their terminology.  Educating clients is part of a Quinnovation engagement!
  • Test.  In making the Workplace of the Future project with Learnnovators,  we were barreling along full tilt, working on the second module, and I was getting increasingly worried about the fact that we hadn’t tested the first.  We finally did, relatively informally, but still got valuable feedback that changed our design somewhat. Similarly on other projects, get feedback early and often.
  • Visualize. My diagramming bent had me map out the workflow of a client’s production process, to identify opportunities to tweak the process to bring in better learning science with minimal interruption.  In general, I will often jump up to the whiteboard and try to represent what I’m hearing to see if it’s shared.
  • Prototype.  Similar to the above, I will often mock up what I’m thinking about (in sort of a ‘ape with a crayon’ level of fidelity), to help communicate the idea; e.g. some sort of walkthrough.  I find that only a percentage of the audience can imagine what the experience will be without getting somewhat concrete. (And, yes, they do then complain about the production values, despite the tradeoff of cost versus value.  Sigh.)
  • Get the context.  I generally try to understand the whole ecosystem (ala ‘the revolution‘) before I engage in specifics.  What are the goals, stakeholders, what’s already being done and by whom, etc. It’s important to re-contextualize ‘best principles’, and that requires  knowing the context.
  • Architecture. Thinking through things using a design thinking approach and a systems-thinking perspective, I’ve tried to think of platforms, not just solutions. It might be content architectures, ecosystem elements, but it’s thinking in terms of systems, not just tactics.
  • Pragmatism. One final approach that has been beneficial is thinking about how to approximate the best with a budget.  I used to talk about ‘what would you do if you had magic’, and then see how close you can get with the resources to hand. It’s a heuristic that often has led to an innovative yet viable solution.

Looking at them, I see that they generally reflect my overall focus on aligning what we do with how we think, work, and learn. Your thoughts?

Reflections on 2017

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The end of the calendar year, although arbitrary, becomes a time for reflection.  I looked back at my calendar to see what I’d done this past year, and it was an interesting review.  Places I’ve been and things I’ve done point to some common themes.  Such are the  nature of reflections.

One of the things I did was speak at a number of events. My messages have been pretty consistent along two core themes: doing learning better, and going beyond the course.  These were both presented at TK17 that started the year, and were reiterated, one or the other, through other ATD and Guild events.

With one exception. For my final ATD event of the year, I spoke on Artificial Intelligence (AI). It was in China, and they’re going big into AI. It’s been a recurrent interest of mine since I was an undergraduate. I’ve been fortunate to experience some seminal moments in the field, and even dabble.  The interest in AI does not seem to be abating.

Another persistent area of interest has been Augmented Reality (AR) and Virtual Reality (VR). I attended an event focused on Realities, and I continue to believe in the learning potential of these approaches. Contextual learning, whether building fake or leveraging real, is a necessary adjunct to our learning.  One AR post of mine even won an award!

My work continues to be both organizational learning, but also higher education. Interestingly, I spoke to an academic audience about the realities of workplace learning!  I also had a strategic engagement with a higher education institution on improving elearning.

I also worked on a couple of projects. One I mentioned last week, a course on better ID.  I’m still proud of the eLearning Manifesto (as you can see in the sidebar ;).  And I continue to want to help people do better using technology to facilitate learning.  I think the Quinnov 8 are a  good way.

All in all, I still believe that pursuing better and broader learning and performance is a worthwhile endeavor. Technology is a lovely complement to our thinking, but we have to do it with an understanding of how our brains work.  My last project from the year is along these lines, but it’s not yet ready to be announced. Stay tuned!

The Quinnov 8: An online course

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Ok, so I told you the story of the video course I was creating on what I call the Quinnov 8, and now I’ll point to it.  It’s available through Udemy, and I’ve tried to keep the price low.  With their usual discounts, it should be darn near free ;).  Certainly no more than a few cups of coffee.

It’s about an hour of video of me talking, with a  few diagrams and text placeholders.  I’ve included quizzes for each of the content sections. Also, I have assignments to go away and apply the principles to your own work.  Finally, I created a page or several for each section showing some ideas, models, and more.

I do  not recommend going through it in one run. I can’t control it, but as I mention in the course, you want to space it out. We know that that leads to better outcomes. Instead, I recommend spacing it out a section a week or so perhaps, and doing the work and coming back to reactivate before moving on.

The content is organized around what I’m terming the Quinnov 8, the eight elements I think are core to making the step to better elearning design.  While the ideal is to push to a robust iterative and prototyping model, I’m focusing mostly on the small steps that will give you the greatest leverage. The elements are:

  1. Performance consulting: what to do  before you decide to course
  2. Objectives: making the  right decisions about what to focus on
  3. SMEs: working with them for objectives and more
  4. Practice: making practice meaningful
  5. Models: the conceptual frameworks that guide performance
  6. Examples: the link between concepts and application.
  7. Engagement: wrapping the front and back to create  experiences
  8. Process: the extra steps to make this work

I’m trying to go  deep, that is to unpack the levels of cognitive depth to explain how the Quinnov 8 elements work.  I’ve identified the challenges I’ve faced, and I may well update it over time, but it’s at a stage I think I can at least give you the chance to explore.  I welcome your feedback, but I reckon this is one way you can further your understanding on a significant budget.

Transparency

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I believe that transparency is a good thing. It builds trust, as it makes it hard to hide things.  And trust is important. So, in the spirit of transparency, it occurred to me to share a little bit about me and this blog. Here I lay out who I am, why I write it, and what I write about.

You can find out more via the ‘about Clark Quinn’ link in the right column, but in brief, I saw the connection between computing and learning as an undergraduate, and it’s been my career ever since. It’s not just my vocation, but it’s my avocation: I  enjoy exploring cognition and technology. And while I’ve done the science and track it, what I revel in (and have demonstrable capability for), is applying cognitive and learning science to create new approaches and fine-tune existing ones.  Learning engineering, if you will.

And, for a variety of reasons, I do this as a consultant. I make my living providing strategic guidance for clients.  I speak at events, and write books, but my main income is from consulting. Which means you  should hire me.  I assist organizations to improve their processes and products, both tactically and strategically. My clients have been happy, and find it’s good value. What you get are unique ideas that are practical and yet effective. Ideas you aren’t likely to have come up with, but are valuable. I really do Quinnovate! Check out the Quinnovation site for more.    Of course, I do have to live in the real world, and so I need to find ways to do this that are mutually beneficial.

Yet generating business isn’t why I write this blog.  I started writing this blog as an experiment and originally tried to write 5 days a week (but was happy if that ended up being 2-3 times a week).  My commitment now is 2 per week (which rarely yields 1 or 3).  And I haven’t monetized it: there’s no advertising, and while I occasionally talk about where I’m speaking or the like, I haven’t used this as a way to sell things. Hopefully that can continue.

So, the reason I write is to think ‘out loud’.  It’s largely for me: it makes me think. I’m just always curious!  I’ve previously recounted the story about how I was on a panel answering questions from the audience, and one of my fellow panelists commented that I had an answer for everything. And the reason is in the ongoing attempt to populate the blog, I’ve looked at lots of things. As my client engagements have been in many different areas, I also have wide-ranging experience to draw upon.  And I just naturally reflect, but getting concrete: diagramming and/or writing, provides additional benefits.

Thus, the process of continually writing (for over 10 years now) means I’m looking at lots of things, reflecting on them, and sharing my thoughts. I also make a point to look at related fields, and look for connections. I also look at what’s happening with technology. In general, I look with a critical eye, as I was trained as a scientist.  I think that’s valuable as well, because there still is a lot of nonsense trotted out, and there’s always some new buzzword that’s being loosely tossed about. Blogging’s given me cause to continue to tune my thinking, and at least some folks have commented that they’ve found it useful.

Mostly I write about things related to technology, learning, and individual and organizational implications. It includes diversions to innovation, design, wisdom, performance support, and the like, because they’ve implications for practice. In many ways I see approaches that aren’t well aligned with how we think, work, and learn, and that strikes me as both a shame, and an opportunity to improve. And that’s what I enjoy, finding ways to improve what we do.

So that’s it: I blog to facilitate my understanding, because cognitive science and technology  is my passion. It isn’t a direct business move.  I do need to make a living, and prefer to do it in the area of my passion, and fortunately have been successful so far.  (Which isn’t to say you shouldn’t find a reason to use me, there are never enough opportunities to assist in improvement, and I’m not a sales person ;).  And yes, this life is a learning experience all in itself!  I hope this is clear, but in the interests of transparency I welcome your inquiries and comments. Stay curious, my friends.

 

Simulations versus games

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At the recent Realities 360 conference, I saw some confusion about the difference between a simulation and a game. And while I made some important distinctions in my book on the topic, I realize that it’s possible that it’s time to revisit them. So here I’m talking about some conceptual discriminations that I think are important.

Simulations

As I’ve mentioned, simulations are models of the world. They capture certain relationships we believe to be true about the world. (For that matter, they can represent worlds that aren’t real, certainly the case in games.). They don’t (can’t) capture all the world, but a segment we feel it is important to model. We tend to validate these models by testing them to see if they behave like our real world.  You can also think about simulations as being in a ‘state’ (set of values in variables), and move to others by rules.  Frequently, we include some variability in these models, just as is reflected in the real world. Similarly, these simulations can model considerable complexity.

Such simulations are built out of sets of variables that represent the state of the world, and rules that represent the relationships present. There are several ways things change. Some variables can be changed by rules that act on the basis of time (while countdown timer = on, countdown = countdown -1). Variables can also interact (if countdown=0: if 1 g adamantium and 1 g dilithium, Temperature = Temperature +1000, adamantium = adamantium – 1g, dilithium = dilithium – 1g).  Other changes are based upon learner actions (if learner flips the switch, countdown timer = on).

Note that you may already have a simulation. In business, there may already exist a model of particular processes, particularly if they’re proprietary systems.

From a learning point of view, simulations allow motivated and self-effective learners to explore the relationships they need to understand. However, we can’t always assume motivated and self-effective learners. So we need some additional work to turn a simulation into a learning experience.

Scenarios

One effective way to leverage simulations is to choose an initial state (or ‘space of states’, a start point with some variation), and a state (or set) that constitutes ‘win’. We also typically have states that also represent ‘fail’.  We choose those states so that the learner can’t get to ‘win’ without understanding the necessary relationships.   The learner can try and fail until they discover the necessary relationships.  These start and goal states serve as scaffolding for the learning process.    I call these simulations with start and stop states ‘scenarios’.

This is somewhat complicated by the existence of ‘branching scenarios’. There are initial and goal states and learner actions, but they are  not represented by variable and rules. The relationships in branching scenarios are implicit in the links instead of explicit in the variables and rules. And they’re easier to build!  Still, they don’t have the variability that typically is possible in a simulation. There’s an inflection point (qualitative, not quantitative) where the complexity of controlling the branches renders it more sensible to model the world as a simulation rather than track all the branches.

Games

The problem here is that too often people will build a simulation and call it a game. I once reviewed a journal submission about a ‘game’ where the authors admitted that players thought it was boring. Sorry, then it’s not a game!  The difference between a simulation and a game is a subjective experience of engagement on the part of the player.

So how do you get from a simulation to a game?  It’s about tuning.  It’s about adjusting the frequency of events, and their consequences, such that the challenge moves to fall into the zone between boring and frustrating. Now, for learning, you can’t change the fundamental relationships you’re modeling, but you can adjust items like how quickly events occur, and the importance of being correct. And it takes testing and refinement. Will Wright, a game designers’ game designer, once proposed that tuning is 9/10’s of the work!  Now that’s for a commercial game, but it gives you and idea.

You can also use gamification, scores to add competition, but, please,  only after you first expend the effort to make the game intrinsically interesting. Tap into why they  should care about the experience, and bake that it.

Is it worth it to actually expend effort to make the experience engaging?  I believe that the answer is yes. Perhaps not to the level of a game people will pay $60 to play, but some effort to manifest the innate meaningfulness is worth it. Games minimize the time to obtain competency because they optimize the challenge.  You will have sticks as well as carrots, so you don’t need to put in $M budgets, but do tune until your learners have an engaging and effective experience.

So, does this help? What questions do you still have?

My policies

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Like most of you, I get a lot of requests for a lot of things. Too many, really. So I’ve had to put in policies to be able to cope.  I like to provide  a response (I feel it’s important to communicate the underlying rationale), so I have stock blurbs that I cut and paste (with an occasional edit for a specific context).  I don’t want to repeat them here, but instead I want to be clear about why certain types of actions are going to get certain types of response. Consider this a public service announcement.

So, I get a  lot of requests to link on LinkedIn, and I’m happy to, with a caveat. First, you should have some clear relationship to learning technology. Or be willing to explain why you want to link. I use LinkedIn for business connections, so I’m linked to lots of people I don’t even know, but they’re in our field.

I ask those not in learntech  why they want to link. Some do respond, and often have a real reason (shifting to this field, their title masks a real role), and I’m glad I asked.  Other times it’s the ‘Nigerian Prince’ or equivalent. And those will get reported. Recently, it’s new folk who claim they just want to connect to someone with experience. Er, no.  Read this blog, instead. I also have a special message to those in learntech with biz dev/sales/etc roles; I’ll link, but if they pitch me, they’ll get summarily unlinked (and I do).

And I likely won’t link to you on Facebook.  That’s personal. Friends and family. Try LinkedIn instead.

I get lots of emails, particularly from elearning or tech development firms, offering to have a conversation about their services.  I’m sorry, but don’t you realize, with all the time I’ve been in the field, that I have ‘goto’ partners? And I don’t do biz dev: develop contracts and outsource production. As Donald H Taylor so aptly puts it,  you haven’t established a sufficient relationship to justify offering me anything.

Then, I get email with announcements of new moves and the like.  Apparently, with an expectation that I’ll blog it.  WTH?  Somehow, people think this blog is for PR.  No, as it says quite clearly at the top of the page, this is for  my  learnings about learning.  I let them know that I pay attention to what comes through my social media channels, not what comes unsolicited.  I also ask what list they got my name from, so I can squelch it. And sometimes they have!

I used to get a lot of offers to either receive or write blog posts. (This had died down, but has resurrected recently.)    For marketing links, obviously. I don’t want your posts; see the above: my learnings!   And I won’t write for you for free. Hey, that’s a service.  See below.

And I get calls with folks offering me a place at their event.  They’re pretty easy to detect: they ask about would I like to have access to  a specific audience,…  I have learned to quickly ask if it’s a pay to play.  It always is, and I have to explain that that’s not how I market myself.  Maybe I’m wrong, but I see that working for big firms with trained sales folks, not me. I already have my marketing channels. And I speak and write as a service!

I similarly get a lot of emails that let me know about a new product and invite me to view it and give my opinion.  NO!  First, I could spend my whole day with these. Second, and more importantly, my opinion is  valuable!  It’s the basis of 35+ years of work at the cutting edge of learning and technology. And you want it for free?  As if.  Let’s talk some real evaluation, as an engagement.  I’ve done that, and can for you.

As I’ve explained many times, my principles are simple: I talk ideas for free; I help someone personally for drinks/dinner; if someone’s making a quid, I get a cut.  And everyone seems fine with that, once I explain it. I occasionally get taken advantage of, but I try to make it only once for each way (fool me…).    But the number of people who seem to think that I should speak/write/consult for free continues to boggle my mind.  Exposure?  I think you’re overvaluing your platform.

Look, I think there’s sufficient evidence that I’m very good at what I do. If you want to refine your learning design processes, take your L&D strategy into the 21st century, and generally align what you do with how we think, work, and learn, let’s talk.  Let’s see if there’s a viable benefit to you that’s a fair return for me. Lots of folks have found that to be the case.  I’ll even offer the first conversation free, but let’s make sure there’s a clear two-way relationship on the table and explore it.  Fair enough?

 

 

What is the Future of Work?

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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?