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Performance Support Second?

10 July 2013 by Clark 8 Comments

I previously argued that social should be our first recourse in addressing performance and learning needs. Does that mean courses are then second? Let me suggest otherwise.

Once we’ve determined that social isn’t a solution to meeting the need, why wouldn’t we think of a course first? Partly, because courses should be expensive. But also, unless we absolutely need a course, we should look to performance support next. Frankly, the learner ideally gets the minimal amount of help to get past their current gap, and if it’s a bit of information or decision support help, why would you make a course if you can avoid it? It’s the least assistance principle (or “what’s the least I can do for you” :), only providing what they need to get back to work.

Another way to look at it is to think that we’d rather put as much information in the world as possible. We don’t want to try to put information into people’s heads if we can avoid it. It’s hard, and we’re not really good at it. We’re great pattern matchers and meaning makers, but really bad at remembering rote information or executing against rote procedures. At these times, a job aid or wizard is just the ticket.

Job aids should be easier to keep up to date, and wizards too ideally are editable. Eventually, they may become social too, as the Community of Practice takes responsibility for keeping them up to date, but I think that will likely always benefit from L&D facilitation. Facilitation increasingly will be the role of L&D, I claim, and this is part of that path.

If you can’t find a way that the network might provide the solution, and you can’t find a performance support solution, then you should consider a course. If it’s a skill shift that’s needed. But for agility, efficiency, and effectiveness, performance support should trump courses. Done right.

So, I’m claiming that our design process in many instances should be social first, performance support second, and formal courses last. What say you?

Social First!

9 July 2013 by Clark 5 Comments

I’m convincing myself that as performance consultants assisting our organizations moving forward, we need to start thinking differently. And as an extreme version of this, let me start by saying we need to start thinking ‘social’ first. When we’re facing a performance problem in the organization, our first resort should be to ask: “would a social solution solve this”? Let me explain.

Social solutions basically suggest that we either tap into user-generated solutions, or reach out to people on the fly. It might be recorded video or user-generated job aids. It might be asking a SME via an expertise directory. Or it just might be tossing it out to our network. It may even be asking for some collaboration on a unique situation.

Here’s the thing: social networks are more likely to be up-to-date, and better able to deal with one-off questions and unique situations than our formally designed solutions. In situations where things are changing rapidly, formally designed solutions are not likely to be up to date with where things are, owing to the time to capture, process, and generate appropriate content. And unusual situations aren’t worth trying to anticipate. They’re likely to be too many to address. And, as the rate of change accelerates, these situations are more likely.

Of course, this requires infrastructure, an appropriate culture, and facilitation, but that should be already accomplished if not underway. We know that continual innovation is the only sustainable differentiator, and that this comes from creative friction (the myth of individual innovation is busted). The important outcomes are going to come from the social network, not from L&D.

Finally, formal is (or should be) expensive. If we’re doing it right, the effort to help change someone’s skill set sufficiently is a prolonged effort. We need to be looking for effective, agile, and efficient. Formal isn’t the latter two (and too frequently not the former either). We should hold formal as a last resort!

There will be times when social isn’t the answer, but for a number of reasons social should be your first solution if possible. It’s effective, it’s agile, and it’s very efficient. Anticipating quite the social reaction to this ;).

#itashare

Formal Learning is (or should be) Expensive!

2 July 2013 by Clark 7 Comments

It’s becoming clear to me that we’re making a big mistake in our thinking. We seem to think that formal learning is relatively cost-effective, and may even think that performance support and social are more costly. Yet we need to realize that formal learning is likely our most costly approach!

To start with, we should be doing sufficient analysis to ensure that the need is indeed a skill shift. If it’s an information problem, it should be solved with a job aid. Courses are more expensive. And we need to take the time that the skill shift really is needed; it’s not a motivation problem or some other problem. In other words, we need to take the time to identify what business problem this is solving that a course will affect, and the associated metric. That takes time.

Then we need to design an intervention that will address that skill shift: we need to determine what the change in the workplace behavior needs to be to impact that metric, and then design an objective that reflects that needed behavior change. This is not trivial: a poorly formed objective about knowledge, not behavior, isn’t going to have an impact on the business.

Then, to do formal learning well, you need appropriate and sufficient practice. That takes time to design properly, ideally with scenarios or simulation-driven interactions. And the practice needs to be aligned with the learner; it has to be meaningful to them. Enough of them. This takes time.

Then we need to create an appropriate model to guide their behavior, and introduce it appropriately. And find meaningful examples that illustrate the concept being applied in context, across sufficient contexts. This takes time, though no more time (once you determine a course is the answer) than other learning design once you get experienced in this more advanced way of designing. And it takes development resources.

And, of course, if you’re not doing the above, why are you bothering? It’s not going to hit the mark. We don’t, frankly, and to the extent we don’t, we undermine the likelihood that our interventions will have the desired impact. The point being that courses should not be our first line of defense!

Rapid elearning is cheap and fast, but it’s not going to have any impact. Most of what we do doesn’t have any impact. If we want to have impact, we have to do it right, and that’s not a cheap proposition. We need to worry about measuring more than cost/bum, and worry about hitting the business goal. Then we can truly determine whether we should go this route, rather than another. But, seriously, you shouldn’t be throwing formal learning at a problem unless you’re willing to do it right. There are times it will be the right answer, but right now we’re throwing too much money away. Let’s stop, and do it right when it’s right. And that will be both expensive and worth it.

Designing Learning is a Probabilistic Exercise

26 June 2013 by Clark Leave a Comment

At the Guild’s recent mLearnCon, I was having a conversation in which I was reminded that designing performance interventions is a probabilistic exercise, and it occurred to me that we’re often not up front enough about it. And we need to be.

When we start our design process with a performance vision, we have an idea of what ideal performance would be. However, we make some assumptions about the performer and their ability to have comprehended our learning interventions and any resources we design or are available in the context. We figure our learning was successful (if we’re doing it right, we’re not letting them out of our mitts until they’ve demonstrated the ability to reliably perform what we need), and we figure our performance solutions are optimal and useful (and, again, we should test until we know). But there are other mitigating factors.

In the tragic plane crash in the Tenerife’s – and pilots train as much as anybody – miscommunication (and status) got in the way. Other factors like distraction, debilitating substances, sleep deprivation and the like can also affect performance. Moreover, there’s some randomness in our architecture, basically. We don’t do everything perfectly all the time.

But more importantly, beyond the actual performance, there’s a probability involved in our learning interventions. Most of our research based results raise the likelihood of the intervention affecting the outcome. Starting with meaningful objectives, using model-based concepts, contextualized examples, meaningful practice, all that increases the probability.

This holds true with performance support, coaching/mentoring, and more. Look, humans don’t have the predictable properties of concrete or steel. We are much more complex, and consequently variable. That’s why I went from calling it cognitive engineering to cognitive design. And we need to be up front about it.

The best thing to do is use the very best solutions to hand; just as we over-engineer bridges to ensure stability (and, as Henry Petrovski points out in To Engineer is Human, on subsequent projects we’ll relax constraints until ultimately we get failure), we need to over-design our learning. We’ve gotten slacker and slacker, but if it’s important (and, frankly, why else are we bothering), we need to do the right job. And tarting up learning with production values isn’t the same thing. It’s easier, since we just do it instead of having to test and refine, but it’s unlikely to lead to any worthwhile outcomes.

As I’ve argued before, better design doesn’t take longer, but there is a learning curve. Get over the curve, and start increasing the likelihood that your learning will have the impact you intend.

Defining Mobile

25 June 2013 by Clark 11 Comments

At the recent Guild mLearnCon mobile learning event, I had a thought that seems to answer a long time debate. The debate centers on the definition of a mobile device. The feature/smart phone is obviously a candidate, and tablets seem pretty clearly included too, but the ongoing issue has been whether a laptop counts. And I may have finally discovered a way of looking at it that answers the question.

Eschewing the more abstract and academic definitions, the one that has most resonated with me has been Judy Brown’s. As I recall it, her characteristics are:

small enough to fit in a pocket or purse,
you’re familiar with it,
instant on,
and a battery that will last all day.

And this has been pretty good, because most laptops don’t fit the latter criteria, their batteries didn’t used to be able to go all day. However, this is a characteristic-based definition, e.g. about inherent properties of the device, and this can change. The new MacBook Airs, for instance, now have a battery that will last all day. And, even if the 13″ is too big, the 11″ or some other might soon fit the criteria. That is, we’re hitting a moving target.

What struck me the other day, however, was looking at it not from inherent properties of the devices, but from usage affordance, i.e. how one uses the device. Because it struck me: to me, it’s not really a mobile device unless you can use it with two hands, standing up or in motion. More importantly, it has to be a natural usage: holding up a netbook with one hand and hunt-and-peck with one hand doesn’t qualify. In short, if you can’t use it with two hands while moving, it’s not really mobile.

This strikes me as a way that will inherently allow new devices and new capabilities, yet still clearly distinguish what’s mobile and what’s not. So, for instance, devices with keyboard that turns around and becomes a tablet? A tablet’s mobile: hold with one hand, touch with the other. A two-handed keyboard is not. Will this fall apart? Probably, as the ultimate mobile test is whether it’s a device that goes with you everywhere: to the market, to a party, even to the bathroom. And some may be able to, but which ones really do? Regularly? If I had a small enough tablet, or iPod touch, probably, but the phone, yes! However, in some contexts, e.g. work, a tablet might go with me to all my work contexts, and then it qualifies if it meets the criteria: of being able to used naturally, standing up.

This, to me, seems to provide a better criteria, at least for now. What say you?

Technology Architecture

11 June 2013 by Clark 1 Comment

A few years ago, I created a diagram to capture a bit about the technology to support learning (Big ‘L’ Learning). I was revisiting that diagram for some writing I’m doing, and thought it needed updating. The point is to characterize the relationship between underpinning infrastructure and mechanisms to support availability for formal and informal learning.

Here’s the accompanying description: As a reference framework, we can think of a hierarchy of levels of tools. At the bottom is the hardware, running an operating system and connecting to networks. Above that are applications that deliver core services. We start with the content management systems, from the delivery perspective, which maintains media assets. Above that we have the aggregation of those assets into content, whether full learning consisting of introductions, concepts, examples, practice items, all the way to the summary, or user-generated content via a variety of tools. These are served up via delivery channels and managed, whether through webinars, courses, or simulations through a learning management system (LMS) on the formal learning side, or self-managed through social media and portals on the informal learning side. Ultimately, these activities can or will be tracked through standards such as SCORM for formal learning or the new experience API (xAPI) for informal learning.

I add, as a caveat: Note that this is merely indicative, and there are other approaches possible. For instance, this doesn‘t represent authoring tools for aggregating media assets into content. Similarly, individual implementations may not have differing choices, such as not utilizing an independent content management system underpinning the media asset and content development.

So, my question to you is, does this make sense? Does this diagram capture the technology infrastructure for learning you are familiar with?

No Folk Science-Based Design!

4 June 2013 by Clark 2 Comments

When we have to act in the world, make decisions, there are a lot of bases we use. Often wrongly. And we need to call it out and move on.

As I pointed out before, Kahneman tells us how we often make decisions on less than expert reflection, more so when we’re tired, and create stories about why we do it. If we’re not experts, we shouldn’t trust our ‘gut’, but we do. And we will use received wisdom, rightly or wrongly, to justify our choices. Yet sometimes the beliefs we have about how things work are wrong.

While there’s a lot of folk science around that’s detrimental to society and more, I want to focus on folk science that undermines our ability to assist people in achieving their goals, supporting learning and performance. Frankly, there are a lot of persistent myths that are used to justify design decisions that are just wrong. Dr. Will Thalheimer, for instance, has soundly disabused Dale’s Cone. Yet the claims continue. There’re more: learning styles, digital natives, I could go on. They are not sound bases for learning design!

It goes on: much of what poses under ‘brain-based’ learning, that any interaction is good, that high production values equal deep design, that knowledge dump and test equals learning. Folks, if you don’t know, don’t believe it. You have to do better!

Sure, some of it’s compelling. Yes, learners do differ. That doesn’t mean a) that there are valid instruments to assess those differences, or more importantly b) that you should teach them differently. Use the best learning principles, regardless! And using the year someone’s born to characterize them really is pretty coarse; it almost seems like discrimination.

Look, intuition is fine in lieu of any better alternative, but when it comes to designing solutions that your organization depends on, doing anything less than science-based design is frankly fraudulent. It’s time for evidence-based design!

Starting Strategy

15 May 2013 by Clark 4 Comments

If you’re going to move towards the performance ecosystem, a technology-enabled workplace, where do you start? Partly it depends on where you’re at, as well as where you’re going, but it also likely depends on what type of org you are. While the longer term customization is very unique, I wondered if there were some meaningful categorizations.

What would characterize the reasons why you might start with formal learning, versus performance support, versus social? My initial reaction, after working with my ITA colleagues, would be that you should start with social. As things are moving faster, you just can’t keep ahead of the game while creating formal resources, and equipping folks to help each other is probably your best bet. A second step would then likely be performance support, helping people in the moment. Formal learning would then backstop for those things that are static and defined enough, or meta- enough (more generic approaches) that there’s a reason to consolidate it.

However, it occurred to me that this might change depending on the nature of the organization. So, for example, if you are in an organization with lots of new members (e.g. the military, fast food franchises), formal learning might well be your best starting point. Formal learning really serves novices best.

So when might you want to start with performance support? Performance support largely serves practitioners trying to execute optimally. This might be something like manufacturing or something heavily regulated or evidence based, like medicine. The point here would be to helping folks who know why they’re doing what they’re doing, and have a good background, but need structure to not make human mistakes.

Social really comes to it’s fore for organizations depending on continual innovation: perhaps consumer products, or other organizations focused on customer experience, as well as in highly competitive areas. Here the creative friction between individuals is the highest value and consequently needs a supportive infrastructure.

Of course, your mileage may vary, and every organization will have places for all of the above, but this strikes me as a potential way to think about where you might want to place your emphasis. Other elements, like when to do better back end integration, and when to think about enabling via mobile, will have their own prioritization schemes, such as a highly mobile workforce for the latter.

So, what am I missing?

#itashare

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