By moving from a “command and control” to an “enable and support” mindset and approach.
Here are some repurposed slides from a presentation I gave at a conference in 2011 that explain what this means in practice.
Next public social online workshop runs: 15 February – 11 March 2016
It is clear that many people find traditional classroom training approaches out of date and frustrating. This workshop looks at how to modernise classroom training through the integration of technology.
Most people have a smartphone and/or tablet, and one of the biggest bugbears is that when they go on a training course they are asked to turn them off to ensure there are no interruptions and so that they focus on the training in hand. Of course, doing so doesn’t mean they will actually focus any better, and in fact not being able to use their mobile device only serves to annoy them. So why not actively encourage participants to make use of them in training in a productive way and at the same time increase participation and engagement in the training room?
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I received some feedback on my post on Organizational Knowledge Mastery. The claim was that if you trusted to human sensing, you’d be only able to track what’s become common knowledge, and that doesn’t provide the necessary competitive advantage. The extension was that you needed market analytics to see new trends. And it caused me to think a little deeper.
I’m thinking that the individuals in the organization, in their sensing/sharing, are tracking things before it becomes common knowledge. If people are actively practicing ongoing sensemaking and sharing internally and finding resonance, that can develop understanding before it becomes common knowledge. They’ve expertise in the area, and so that shared sense making should precede what emerges as common knowledge. Another way to think about it is to ask where the knowledge comes from that becomes the common knowledge?
And I’m thinking that market analytics aren’t going to find the new, because by definition no one knows that to look for yet. Or at least part of the new. To put it another way, the qualitative (e.g. semantic) changes aren’t going to be as visible to machine sensing as to human (Watson notwithstanding). The emerging reality is human-machine hybrids are more powerful than either alone, but each alone finds different things. So there were things in protein-folding that machines found, but other things that humans playing protein-folding games found. I have no problem with market data also, but I definitely think that the organization benefits to the extent that it supports human sense-making as well. Different insights from different mechanisms.
And I also think a culture for agility comes from a different ‘space’ than does a rabid focus on numerics. A mindset that accommodates both is needed. I don’t think they’re incommensurate. I’m kind of suspicious of dual operating systems versus a podular approach, as I suspect that the hierarchical activities will be automated and/or outsourced, but I’m willing to suspend my criticism until shown otherwise.
So, still pondering this, and welcome your feedback.
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?
I was inspired by a diagram that my ITA colleague Harold Jarche included in a post, where he puts some concepts into their 70:20:20 role as either people, skills, or tools. And I obviously believe the role of L&D should be shifting (as in a full revolution :), but I realize that putting it together can seem confusing, and so it led me to think a little bit about what’s the role for L&D versus what’s the role of the community. As a first cut, as usual.
My breakout starts with the 10 (though you should start your solution thinking with the 70, as my colleague Charles Jennings suggests). Here I’m seeing what L&D can do, and what should be expected to come from a vibrant learning culture (which is also the role of L&D.
And it’s true that we see the traditional work of courses here (no, we’re not coming for your courses), though of course ones that meet the minimum daily standard of Serious learning, now set by your learning quality evangelists. And reactivating the learning, to make it stick.
Another task for L&D building in meta-learning opportunities and deliberately developing them in addition to whatever domain skills matter. Also, curating (and, occasionally) creating resources for self-study. If someone wants to learn something, resources before courses may be a more practical approach, particularly if it’s relatively unique. And, of course, curation trumps creation. And on the Culture side, the community should also be curating and creating resources.
Then we segue to the social. Here, the community is taking the role of coaching and mentoring, and the individual is engaging with the community. However, assuming good coaching and mentoring skills would be a mistake, so there’s a real for L&D to provide explicit development of coaching and mentoring, as well as ensuring that those relationships are established and occur. There’s also a role for facilitating meta-learning, helping folks learn to work out loud and reflect. These are essential components of my colleague Jane Hart’s Modern Workplace Learning. There’s also a role to ensure people can find others with useful expertise to tap into, within or across communities.
Finally, out at the personal end (and don’t think that it really transitions like this, there’s lots of overlap), individual practices are of working out loud and reflecting. The individual and the community should be building, as well as using, performance support like job aids. L&D can assist by helping ensure that there’s a ‘stretch assignment’ plan, and good rubrics about what constitutes a good stretch assignment, whether training or job aid. And, of course, L&D should be looking at what’s happening and looking for opportunities to tune and improve, as well as any emergent phenomena.
Finally, of course, one final role for L&D is to ensure that there is a learning culture. This is an important process. Recognize that it’s about a performance ecosystem organized to facilitate organizational learning at the individual and community level. It’s about having the individual have the tools ‘to hand‘ to continue to develop and perform. The goal is a coherent organization.
(I looked because I’m sure I’ve talked about this before, but apparently not a full post, so here we go.)
If we want our learning to stick, it needs to be spaced out over time. But what sorts of things will accomplish this? I like to think of three types, all different forms of reactivating learning.
Reactivating learning is important. At a neural level, we’re generating patterns of activation in conjunction, which strengthens the relationships between these patterns, increasing the likelihood that they’ll get activated when relevant. That’s why context helps as well as concept (e.g. don’t just provide abstract knowledge). And I’ll suggest there are 3 major categories of reactivation to consider:
Reconceptualization: here we’re talking about presenting a different conceptual model that explains the same phenomena. Particularly if the learners have had some meaningful activity from your initial learning or through their work, showing a different way of thinking about the problem is helpful. I like to link it to Rand Spiro’s Cognitive Flexibility Theory, and explain that having more ways to represent the underlying model provides more ways to understand the concept to begin with, a greater likelihood that one of the representations will get activated when there’s a problem to be solved, and will activate the other model(s) so there’s a greater likelihood of finding one that leads to a solution. So, you might think of electrical circuits like water flowing in pipes, or think about electron flow, and either could be useful. It can be as simple as a new diagram, animation, or just a small prose recitation.
Recontextualization: here we’re showing another example. We’re showing how the concept plays out in a new context, and this gives a greater base upon which to abstract from and comprehend the underlying principle, and providing a new reference that might match a situation they could actually see. To process it, you’re reactivating the concept representation, comprehending the context, and observing how the concept was used to generate a solution to this situation. A good example, with a challenging situation that the learner recognizes, a clear goal, and cognitive annotation showing the underlying thinking, will serve to strengthen the learning. A graphic novel format would be fun, or story, or video, anything that captures the story, thinking, and outcome would work.
Reapplication: this is the best, where instead of consuming a concept model or an example, we actually provide a new practice problem. This should require retrieving the underlying concept, comprehending the context, and determining how the model predicts what will happen to particular perturbations and figuring out which will lead to the desired outcomes. Practice makes perfect, as they say, and so this should ideally be the emphasis in reactivation. It might be as simple as a multiple-choice question, though a scenario in many instances would be better, and a sim/game would of course be outstanding.
All of these serve as reactivation. Reactivation, as I’ve pointed out, is a necessary part of learning. When you don’t have enough chance to practice in the workplace, but it’s important that you have the ability when you need it (and try to avoid putting it in the head if you can), reactivation is a critical tool in your arsenal.
In the Coherent Organization model that we (the ITA) came up with, it talks about how work teams are fed by and feed up to communities as they too feed up to and are fed from social networks. And while this is all good, it may not be completely clear. So I tried to take a pass at representing it another way.
So, at the center are people, the individuals who constitute the organization. They are the ones who form teams. Ideally, for the most powerful outcomes, they come with different backgrounds, as we know diversity helps. And they’ll work together in those teams, for short term needs or on an ongoing basis.
Those background are tied into the Communities of Improvement that they are members of. A good team member will bring their community expertise into the team, and likewise feedback their learning from their team work. Note that most folks are usually members of several communities.
Those communities span both internal to the organization (if it is big enough), but also across the firewall out to other practitioners that are in other organizations. There are obviously things you can, and can’t, share across the boundaries, but the communities should be continuing to evolve across boundaries. Proprietary approaches may not, but general learning should be.
And the individuals are, or should be, learning on their own as well, tapping into personal searches inside and outside the organization for immediate needs and ongoing development. Similarly, communities should be looking for ideas and practices from other communities that can be absorbed, and sharing out to other communities as well.
The main change here is showing how people are members of different teams and diverse communities, and how the links are to communities and to one’s own development. Not enough, I know (should I show links between people as well), and certainly I’ve got a sparse representation of interconnections here to be indicative, not representative. Does this help?
I was on a case. I’m a performance detective, and that’s what I do. Someone wasn’t performing they way they were supposed to, and it was my job to figure out why. My client thought he knew. They always do. But I had to figure it out myself. Like always.
Before I hit the bricks, I hit the books. Look, there’s no point watching anyone if you don’t know what you’re looking for. What’s this mug supposed to be doing? So I read up. What’s the job? What’s the goal? How do you know when it’s going well? These are questions, and I need answers. So I check it out. Even better, if I can find numbers. Can’t always, as some folks don’t really get the value. Suckers.
Then I had to get a move on. You need what you find from the background, but you can’t trust it. There could be many reasons why this palooka isn’t up to scratch. Everyone wants to throw a course at it. And that may not the problem. If it isn’t a skill problem, it’s not likely a course is going to help. You’re wasting money.
The mug might not believe it’s important. Or not want to do it a particular way. There’re lots of reasons not do it the way someone wants. It could be harder, with no obvious benefit. If you don’t make it clear, why would they? People aren’t always dumb, it just seems that way.
Or they might not have what they need. Too often, some well-intentioned but under-aware designers wants to put some arbitrary information in their heads. Which is hard. And usually worthless. Put in the world. Have it to hand. They may need a tool, not a knowledge dump.
Or, indeed, they may not be capable. A course could be the answer. Not just a course, of course. It needs more. Coaching, and practice. Lots of practice. They may really be out of their depth, and dumping knowledge on them is only going to keep them drowning.
It’s not always easy. It may not be a simple answer. There can be multiple problems. It can be all of the above. Or any combination. And that’s why they bring me in. To get the right answer, not the easy answer. And certainly not the wrong answer.
So I had to go find out what was really going on. That’s what detectives do. They watch. They investigate. They study. That’s what I do. I want the straight dope. If you can’t do the hard yards, you’re in the wrong job. I love the job. And I’m good at it.
So I watched. And sure enough, there it was. Obvious, really. In retrospect. But you wouldn’t have figured it out if you hadn’t looked. It’s not my job to fix it. I told the client what I found. That’s it. Not my circus, not my monkeys. Get an architect to come up with a solution. I find the problem, and report. That’s what I do.
This quite literally came from a dream I had, and my subsequent thoughts when I woke up. And when I first conceived it, I wasn’t thinking about the role that Charles Jennings, Jos Arets, and Vivian Heijnen have as one of five in their new 70:20:10 book, but there is a nice resonance. Hopefully my ‘hard boiled’ prose isn’t too ‘on the nose’! More importantly, what did I miss? I welcome your thoughts and feedback.
A comment on my earliest blog post (thanks, Henrik), made me realize that this post will mark 10 years of blogging. Yes, my first post came out on January 14th, 2006. This will be my 1,200th post (I forced one in yesterday to be the 1199th so I could say that ;), yow! That’s 120 a year, or just under every 3rd day. And, I am happy to add, 2,542 comments (just more than 2 per post), so thanks to you for weighing in.
It’s funny, when I started I can’t really say it was more than an experiment. I had no idea where it would lead, or how. It’s had some challenges, to continue to find topics, but it’s been helpful. It’s forced me to deliberately consider things I otherwise might not have, just to try to keep up the momentum.
I confess I originally had a goal of 5 a week (one per business day), but even then I was happy if I got 2-3. I’m gobsmacked at my colleague Harold who seems to put out a post every day. I can’t quite do that. My goal has moderated to be 2 a week (very occasionally I live with 1 per week, but other weeks like when I’m at conferences I might have 3 if there are lots of keynotes to mind map). Typically it’s Tuesday and Wednesday, for no good reason.
I also try to have something new to say every time. It’s hard, but forcing myself to find something to talk about has led to me thinking about lots of things and therefore ready to bring them to bear on behalf of clients. I think out loud relatively freely (particularly with the popularity of Work and Learn Out Loud and Show Your Work). And it’s a way to share my diagrams, another way to ‘think out loud’. And I admit that I don’t share some things that are either proprietary (until I can anonymize them) or something I’m planning on doing something with.
And I’ve also resisted commercializing this. Obviously I’ve avoided the offers to exchange links or blog posts that include links for SEO stuff, but I’ve even, rightly or wrongly, not allowed ads. While it is the official Quinnovation blog, it’s been my belief that sharing my thinking is the best way to help me get interest in what I have to offer (extensive experience mapping a wide variety of concepts onto specific client contexts to yield innovative yet practical and successful solutions). I haven’t (yet) followed a formula to drive business traffic, and only occasionally mention my upcoming events (though hopefully that’s a public service :). There’re other places to track that.
I’m also pretty lax about looking at the metrics. I do weekly pop by Google Analytics to see what sort of traffic I get (pretty steady), but I haven’t tried to see what might improve it. This is, largely, for me. And for you if your interests run this way. So welcome, and here’s to another 10 years! Who knows what there will be to talk about then…or even next week!
I have to admit that I’m continually flummoxed by those who rail against the 70:20:10 model. Recent posts by Mark Britz and Ryan Tracey both take this on, Ryan’s in particular pointing to a poll where more than half of the respondents said it wasn’t relevant. And there’s been quite some vehement opposition. Really? Really.
There’s a chapter in a book about myths by a few academics who claim that it’s not bolstered by academic research! Similarly in a complaint linked off of Ryan’s post. And I’ve already riffed on how I don’t get people who are flummoxed by the numbers. If you created a study that tried to simulate the workplace and test to see where the numbers fell, your data would be hard to claim to be valid in a real workplace. And extracting the data from the real workplace will come (I think we can use xAPI for this), but here’s the real kicker: the exact numbers don’t matter! There’s plenty of data showing the numbers are roughly this, and that is the point.
Or, rather, using the numbers as a way to think differently about your interventions in the workplace is the point. It’s easy to think that your courses are the answer. It’s certainly what I see way too often. Instead, you need to recognize that you need to follow up on a course with coaching and mentoring, and continuing practice through real assignments. And, yes, formal learning does suggest this (read the elements of the Serious eLearning Manifesto), but it doesn’t seem to happen.
And, of course, if you start with the 70, as my colleague Charles Jennings suggests, you end up more likely to consider the full spectrum of solutions, including performance support (similar to my suggesting designing backwards). It’s a way to incorporate performance consulting and job aids and a richer solution to performance problems than just courses.
The validity of the 70:20:10 framework (and it’s deliberately labeled that to deemphasize a focus on the numbers) comes from the utility it offers, and it’s offered plenty. Organizations are using it (and not just L&D) to take more appropriate solutions. It’s even been documented down to the nth degree in a newly released book.
So, I’ll leave academic ‘angels dancing on the head of a pin’ arguments to others. I’m going to go out and drive real solutions as part of the necessary revolution L&D needs to have. 70:20:10 is a great way to think more broadly about learning, as part of the bigger picture of facilitating performance and development. I’m not yet convinced that it helps on the ‘continual innovation’ side, but it is a very useful tool to help get the ‘optimal execution’ side of the picture nailed down.
Noodling: I’ve been thinking about Working Smarter, a topic I took up over four years ago. And while I still think there’s too little talk about it, I wondered also about pushing it further. I also talked in the past about an interest in wisdom, and what that would mean for learning. So what happens when they come together?
Working smarter, of course, means recognizing how we really think, work, and learn, and aligning our processes and tools accordingly. That includes recognizing that we do use external representations, and ensuring that the ones we want in the world are there, and we also support people being able to create their own. It means tapping into the power of people, and creating ways for them to get together and support one another through both communication and collaboration. And, of course, it means using Serious learning design.
But what, then, does working ‘wiser’ mean? I like Sternberg’s model of wisdom, as it’s actionable (other models are not quite specific enough). It talks about taking into account several levels of caring about others, several time scales, several levels of action, and all influenced by an awareness of values. So how do we work that into practices and tools?
Well, pragmatically, we can provide rubrics for evaluation of ideas that include considerations of others inside and outside your circles of your acquaintances, and in short- and long-term timeframes, and the impacts on existing states of affairs, ultimately focusing on the common good. So we can have job aids that provide guidance, or bake it into our templates. These, too, can be shown in collaboration tools, so the outputs will reflect these values. But there’s another approach.
But, at core, it’s really about what you value, and that becomes about culture. What values does the organization care about? Do employees know about the organization’s ultimate goal and role? Is it about short-term shareholder return, or some contribution to society? I’m reminded about the old statements about whether you’re about selling candles or providing light. And do employees know how what they do fits in?
It’s pretty clear that the values implicit in steps to make workplaces more effective are really about making workplaces more humane, that is: respecting our inherent nature. And movements like this, that provide real meaning, ongoing support, freedom of approach, and time for reflection, are to me about working not just smarter but also wiser.
We can work smarter with tools and practices, but I think we can work better, wiser, with an enlightened approach to who we are working with and how we work to deliver real value to not only customers but to society. And, moreover, I think that doing so would yield better organizational outcomes.
Ok, so have I gone off the edge of the hazy cosmic jive? I am a native Californian, after all, but I’m thinking that this makes real business sense. I think we can do this, and that the outputs will be better too, in all respects. No one says it’d be easy, but my suspicion is it’d be worthwhile.