I’ve written a lot over the last few months about the significance of shifting from a training-focused paradigm to a performance-support focused one. It’s a big shift. Understandably, plenty of people feel like this is me saying, ‘do away with your training events.’

Why training still matters — but needs to evolve

Definitely not the case. But it does raise a big question that people often ask:

"What would training look like if it were designed with performance support in mind from the start?"

Let’s dig into answering that, to see how you might refine what you do during a training event, when designing for a more performance-support focused paradigm.

It’s easy to see performance support as a nice ‘add-on’. Something to highlight to the learners towards the end of the event, as a rather perfunctory ‘transition to the workplace’ segment. I confess, I’ve run my fair share of such segments over the years.

Unfortunately, this approach will pretty much guarantee that your performance support solution gets little use or has low perceived value.

From event thinking to performance thinking

So, if you are providing performance support tools or materials, then they need to be introduced and used as an integral part of the training – not as an afterthought.

The question remains: 'How to do that?'

In our impact and instructional design programme, we introduce attendees to a very simple, very flexible but nevertheless very robust design flow that works very well during in-person and live online events.

It’s a three part design flow. It starts with presenting to learners, moves to providing structured practice, and finished with much less structured extended practice. The idea being that as you go through this sequence, you are helping the learners’ capability and self-direction to increase

From a learning design point of view, this is about providing multiple points of practice that is highly interactivity. Learners gradually become more autonomous and increasingly confident in their ability to apply what they are learning.

Ideally, by the time you reach the extended practice phase of a session, the trainer will be able to fully step back, observe the learners and only provide feedback (where needed) during a group de-brief after the activity.

The good news is that from a performance support perspective, this is a very effective design flow, too. The difference comes in how you think about and design your practice activities.

What a performance-support-focused training session looks like

So, from a learning design perspective, a good flow of practice activities will help the learners to process and embed what they have learnt; the only ‘external’ assistance comes from the trainer’s input during the structured practice stage and any feedback or de-brief after the extended practice stage.

From a performance support perspective, the structured and extended practice activity stages of the flow are the perfect moments to enhance that trainer input and support by introducing and phasing in use of the performance support tools or materials.

This familiarises learners with the tools and how to use them; and positions them as the natural post-training ‘go-to’ which will help to get the job done.

Bringing performance support into the classroom

For example, imagine a training event that is focused on helping learners to plan and prepare annual performance reviews with their team members.

The course design analysis phase highlighted the benefit of providing a simple performance support tool to guide learners through the planning and preparation.

Having learners use the planning tool as part of any practice activity makes the practice much more authentic; and, ensures the learners see the tool as part and parcel of how to apply what they are learning.

Training as the gateway, not the goal

All this highlights clearly that selecting and designing performance support tools or materials must be an integral part of your existing impact and instructional design process. Not an afterthought. The training is vital but only the first stage of a journey to the really important goal: improved workplace outcomes.

Achieving this level of performance support integration requires L&D to get close to the business. To have a good understanding of what desired workplace performance looks like. To be clear about how knowledge and skills covered during a training event are applied in the learners’ workflow, once they are back on the job.

If that sounds a bit challenging, it shouldn't. In reality, performance-support-focused training isn’t a different discipline — it’s simply the next logical step in doing what great L&D has always aimed to do: help people do their jobs more effectively.

Context, they say, is everything. Very true in many areas of life, especially true of instructional design. And just as significant when it comes to performance support. Without carefully considering context (and its close relative integration) you are likely to come unstuck.

I was reminded of this just recently when I re-discovered a wonderful example from Allison Rossett. Her example was written in the 90s, meaning the original tech references are out of date now. Below, you’ll find my (minor) re-working of the example to include current tech references.

But before recounting the example, I want to add a bit of context of my own.

Why context matters 

Ever since the arrival of cognitive learning theories, we’ve recognised the importance of context in learning. Viewed through a purely instructional design lens, understanding how learners actually apply their learning in the workplace, will avoid teaching knowledge and skills in the abstract. A clear understanding of the specific ways in which knowledge and skills are being applied, helps you craft a tailored learning experience that closely reflects the workplace reality of the learners.

When thinking about supporting learners after a learning event, understanding that aspect of context is equally important. After all, the content of the support materials will need to be equally well contextualised and tailored.

But you will also want to focus on actual physical surroundings. Literally, where are they when they need that support. At a desk? At the top of an electricity pylon? In a noisy, crowded space?

That’s a much narrower and much more specific aspect of context. But it’s vital because it helps determine what a usable performance support tool needs to look like. 

A job-aid printed on a piece of paper won’t be very effective at the top of a pylon. Audio support won’t be much help in a noisy, crowded workspace. Granted, these are obvious, simplified examples. But you get the idea.

Consider integration for EVEN greater effectiveness

Within that aspect of context, you also need to consider integration. What do I mean by that? Essentially, it’s about how embedded the support is within the task. Making sure that learners can get to the support they need as quickly and easily as possible, while still taking into account the type of performance support tool that will make most sense in that context.

In some cases, you only need to think about these questions for a minute or two. The answer will stare you in the face. Other times, it’s a bit more nuanced and you might need to work through a few options and possibilities before you reach the best result. Other times, you may end up having to compromise a little bit.

And this is why I like Rossett’s example, so much. It takes an example that everyone understands and readily walks us through many of the considerations connected to context and integration. So, here’s my slightly updated version of her example…

Context and integration example

Imagine that you have to drive to an event on the other side of the town where you live. Your brother works on that side of town and knows it well; but you rarely have cause to go there and only a very limited experience of driving around there.

How might you go about finding your way there?

Look at the city map you keep in your home office. 
Not very integrated and only tailored in the sense that it’s a map of the place you need to drive in.

Go to Google Maps and have it map out the route. Print out the results to have with you in the car.
There is significant tailoring here. You get the exact route that you need. The support is integrated. But dangerously so. Glancing at the print out of the directions while driving is not recommended!

Ask your brother for directions
Tailored. And depending on your memory and the accuracy of his directions, this could work quite well. But not hugely integrated.

Pull out a city map that you keep in your glove box. Look at this before your journey and keep consulting it as you drive.
As with the map in the home office, not very tailored. As with the printed directions, integrated but dangerously so.

Use your sat nav
Lots of tailoring (and adapting). Deeply integrated into the task.

Of course, in this example most people will see immediately the benefits of the sat nav over all other options. This is one of those ‘staring you in the face’ decisions. 

However, just to be a little bit contrarian, I continue to be a sat nav refusenik. I could share multiple examples where I have sat as a passenger and watched people make the dumbest of navigation decisions because they have switched off their navigation brain and rely slavishly on a sat nav master. Another post for another day, I think!

But in conclusion, whatever decisions you make regarding context and integration, the important point to remember is that the more embedded, intuitive and tailored you can make that support solution, the more your learners are likely to see value in it and engage with over and over.

You can read a more personal view of my journey to create an AI-driven performance support tool in my weekly PerformaGo Diary.

If you are an end user of AI it all feels pretty simple. Ask your question or make your request. Get an answer or response. Keep going until you are done.

But what about if you need to start engaging with AI at a slightly more strategic/technical level. “It’s all a bit too complicated for me,” is not an untypical (or unreasonable) response. After all, once you start talking about APIs, prompts, Python or LLMs you can understand why someone’s eyes might glaze over and their brain might shut down.

To the uninitiated, it does start to sound like a bunch of tech gobbledygook dreamt up by a fairly unfriendly bunch of Martians!

(By the way if you are interested in dipping your toe into the more technical aspects of AI, my goal is to unpack the jargon and concepts in an L&D-friendly manner in my PerformaGo Diary and the associated Making Learning Stick blog)

But the good news in all this is that you don’t need to become a part-time programmer to get more than end-user value from AI. Because a lot of what’s going on behind the curtain with AI is as much about design logic as it is about programming. And design logic is something that most people in L&D are already very familiar and comfortable with.

It’s About Design, Not Code

So, what do I mean by design logic and how is it different from something like coding? Well, coding is about telling a system how to execute something, step-by-step. The detailed ‘how to’ instructions that run under the hood. Whereas design logic is about the why and the what.

So, viewed from a strategic or purpose-driven perspective, what makes AI really useful is the ability of those deploying it in a work-based environment to clearly define its intent (the why) and the outcomes you want from it (the what).

Which, of course, is not that different from thinking purposefully about a piece of work-based training.

What This Means for L&D

So, if we move beyond the anxiety many people feel about coding and tech speak, what we actually discover is that AI design and learning design share the same DNA.

Both are about:

• Creating flows and structures so things make sense.
• Filtering out unnecessary complexity.
• Anticipating what people will need, when they’ll need it, and how they’ll best engage with it.

In reality, you are already thinking in systems, flows, and interactions — exactly the same kind of mental models that you need to use when thinking about deploying AI.

So, working more strategically and purposefully with AI isn’t about shifting from instructional designer to techie expert. It’s about applying your existing learning design skills into a slightly different arena.

You don’t need to learn a single line of Python code to work effectively with AI. But thinking like a learning designer will definitely help you get better results from it.

AI Doesn’t Replace Design Thinking — It Rewards It

So, AI isn’t something L&D needs to fear or surrender to. It’s something we can shape using our existing design skills and thinking. Because when you strip away the code, AI’s power depends on the same things that make great learning work: clear purpose, sound structure, and empathy for the learner

That’s why the future of L&D doesn’t belong to the coders — it belongs to the designers.  People who can take what they already know about how people learn and apply it to how intelligent systems perform.

Because design thinking isn’t just part of L&D’s DNA. It’s also our bridge to the future.

Curious how this post took shape?
This post was inspired by a story I shared in my Diary blog — “From Rodeo Drive to AI: The Three Languages Every Custom GPT Needs.”

Spoiler alert. It is a bit more technical in content. But it’s the tale of a California trip that unexpectedly helped me understand how several bits of tech work together to make AI more effective.

You can read that story here

Ask anyone outside of L&D what comes to mind when they think of “learning,” and the answer is almost always the same: classrooms, courses, qualifications.

That’s not surprising. From the time we’re four or five years old, we spend hours of our lives in an education system where the ultimate prize is being good at school. Success is measured in grades, certificates, and diplomas. Society reinforces the message: the more successful you are at completing formal learning, the more valuable you are.

So, it’s no wonder that when business leaders run into a performance problem, their first instinct is to ask L&D for training. Courses feel like the answer because courses are what we’ve all been conditioned to believe in.


The Blind Spot This Creates
The problem is, formal learning isn’t always the lever that moves performance. In fact, often it’s not even close.

Sometimes what’s needed isn’t weeks of training. Sometimes it’s something as simple as a single page of A4 paper — a job aid, a checklist, a quick reference — that gives people exactly what they need, when they need it.

But here’s the counterintuitive part: because these solutions look so simple, they often get dismissed. People inevitably think, “How could something that small make a real difference?”

This bias towards formal learning is a big blind spot in how we approach workplace learning. It’s why L&D so often gets trapped in the order-taking cycle — asked to churn out courses because they’re seen as the “serious” answer, even when simpler, leaner performance support would have more impact.


Why Simplicity Works
The irony is that simplicity is exactly what makes performance support powerful:

•    A well-designed checklist can significantly reduces errors.
•    A short job aid can save hours of wasted time.
•    A contextual nudge can shift behaviour more effectively than any course module.

None of these examples look like the formal learning solutions we’ve been trained to overvalue. But they work; and often, they work better.


Shifting Our Mindset in L&D
If we  want to increase learning impact, we need to challenge the cultural over-perception of formal learning. That doesn’t mean courses don’t matter. It means we stop treating them as the default solution.

It means educating our stakeholders that effectiveness isn’t about how long or formal a learning solution is, but about how well it supports performance. Sometimes that’s a course. Sometimes it’s workplace support. And sometimes it’s a combination of both.


A Closing Thought...
The world has taught us to equate learning with classrooms, exams, and certificates. But in the workplace, those aren’t always what move the needle.

Performance improves when people have the right support at the right time. And sometimes, that support looks a lot less like school — and a lot more like a single sheet of paper.

We’ve all been there. “We need a course on…” or “Can you put together a workshop about…” And before you know it, you’re scoping out slides, activities, and maybe even booking rooms.

It’s the classic “training order-taking” scenario. The problem is, fulfilling training orders doesn’t always lead to better performance. Sometimes it just leads to more training.

The Limits of the Order-Taker Role

When we accept training requests at face value, we miss the bigger question: what’s the real problem we’re trying to solve?

Is performance lagging because people don’t know how to do something? Or is it because the process is broken, the tools are clunky, or expectations are unclear? In many cases, training isn’t the answer at all.

That’s the trap of being an order-taker. It turns us into a busy L&D function, but it doesn’t necessarily make us impactful.

The Shift: From Training to Performance

To increase impact, L&D needs to move from being an order-taker to becoming a performance enabler.

Sometimes, that means asking harder questions up front:

• What’s really getting in the way of performance?
• Is this a skills gap, a motivation gap, or an environmental issue?
• If training is part of the answer, what else needs to be in place for it to work?

It also means widening our toolkit. A course might sometimes be the right solution — but often it’s just one piece of a broader picture.

What Performance Enablement Looks Like

Performance enablement is about making it easier for people to succeed in their work. That might look like:

• A job aid that reduces reliance on memory.
• A checklist that ensures key steps aren’t missed.
• A guided conversation that helps managers coach effectively.
• A performance support tool that provides answers in the flow of work.

These may not look as impressive as a full-blown course, but their impact can be huge. They get used in the moment of need. They reduce errors. They increase confidence. And they show the business that L&D is directly connected to performance outcomes.

Why This Matters Now

People don’t always have time to attend courses, however well designed. They need solutions that fit into their flow of work, not outside it.

That’s why the order-taker mindset feels increasingly out of step. The future belongs to L&D teams who can enable performance: diagnosing real needs, designing for usability, and delivering support that works in the moment.

How This Shapes PerformaGo

This shift is also shaping the design of the AI-powered tool I’m currently working on, called PerformaGo. From the ground up, it’s being built around the principle of performance enablement.

Instead of just asking, “What training can we deliver?”, it encourages us to consider, “What support will make performance easier?”

The goal isn’t to replace courses. It’s to give those of us in L&D a way to extend learning into performance — so the business gets the impact it needs, and learners get the support they want.

A Closing Thought

The order-taker model has kept many in L&D busy for many decades. But if we want to stay relevant, we can’t just take orders. We need to enable performance, too.

That’s the shift PerformaGo is designed to support. If you would like to stay connected and receive regular updates about what we are doing, you can register your interest.

If you prefer a more personal, behind-the-scenes take on all this, check out The PerformaGo Diary.

Indulge me for a second and let’s try a little thought experiment.

Imagine your colleagues outside of L&D — managers, frontline staff, sales reps, new hires etc — each had their own always-available, always-supportive AI performance coach. No set-up time, no searching for materials, just instant, intelligent support in the moment they need it.

What would you want that coach to do for each of those colleagues?

• Offer reminders on key tasks?

• Help them prepare for or reflect on a difficult conversation or meeting?

• Serve up step-by-step guidance during their first few weeks in a new role?

This isn’t the stuff of fantasy anymore. AI is becoming sophisticated enough to do all of that — and more. But let's not get carried away.

Your answers to the 'learner need' question matter more than any tech solution. Because performance support is about learner need first and tech delivery second — not the other way around.

That's why the PerformaGo AI tool that we are developing, starts with performer needs, not content or clever tech. It help's you to think through: What do learners struggle with most, post-training? What’s hard for them to remember? What gets skipped when things get busy? What barriers exist in the workplace that might be holding them back or discouraging them from applying their new skills?

Then we make it super-easy for you to design lightweight, AI-powered assistants that:

• Provide authentic and accurate help, advice and reminders

• Reference the specific skill sets and content that an individual learner needs to complete a specific task 

• Prompt the learner to plan, complete or reflect, based on real-world application and challenges

This is about providing real-time learning and support that lives in the workplace — not inside the LMS.

So, what would you want an AI coach to help your learners do? 

Interested in finding out more about how PerformaGo could help your learners achieve more successful workplace application? Register your interest at pacificblue.ai -  help us shape the tool and get early access.

This isn’t the first time that I’ve made reference to what I call Storyline’s ‘secret weapon’. A Storyline ‘advanced’ feature that gets buried away in the background because it’s not very ‘sexy’ nor particularly easy to market. Yet learning to use it can transform the e-learning courses you build.

In case you are wondering? I’m talking about Storyline variables.

However, the purpose of today’s post is not to write extensively about Storyline variables. (If you are interested, I have written about Storyline variables here).

What interests me today is the fact that lots of software/technologies often have some kind of ‘secret weapon’. In other words, a hidden something that a majority of users don’t know about, which is incredibly powerful or useful but somehow never gets the attention it deserves.

Typically, the hidden something is conceptually abstract or technically a bit complex; so, it takes some care and effort to explain it clearly and easily. And it often takes some care and effort by software users to really reap the benefits of it.

Which usually leaves it friendless. Tucked away in an obscure corner of the interface by UX and UI designers. Shunned by the marketers (just not ‘sexy’ enough). Glossed over by the technical writers and technology evangelists.

And you can understand why. In the push to get a piece of software or a technology widely adopted as quickly as possible, the most popular and easiest to use features are, inevitably, going to get the most attention.

And in lots of ways, that is a good, user-centred approach. After all, if the software or technology in question isn’t obviously solving some kind of problem or making it easier or possible to do something that was previously difficult or impossible to do, what’s the point?

But this also misses an important point. Hiding that more difficult-to-explain feature probably results in inferior user output. Returning to the example I opened with, this is absolutely true in the case of Storyline variables. It’s not that you need to use them in every single course that you create. But never using them at all will absolutely reduce the creative potential and the effectiveness of your instructional design.

So, why am I obsessing about all this, at the moment? Well, you may already know that I’m working on a new software tool for L&D called PerformaGo. And the AI technology that this software is designed to help L&D folk like yourself unleash, definitely has its own buried treasures. (Something I’ve been writing about here). In essence, it’s about how you provide specific knowledge to your custom GPT so that you get reliable, accurate output when it’s being used by a learner.

Which means that this particular ‘buried treasure’ is going to play a very significant role in making the PerformaGo tool a success. The question of how that specific knowledge is packaged up and accessed can’t be glossed over, in the hope that some users will find it and work out how to use it. It needs to be front and centre.

And that will be a challenge. Because in some respects this element is a bit abstract. It will definitely require some careful thought around how it is presented and explained to users within the software interface itself and in any related ‘help’ content or software onboarding.

But once you consider the benefits for L&D folk of getting this ‘buried treasure’ front and centre, the challenge of achieving that goal seems small by comparison.

If any of this interests you, or you like the idea of becoming an early adopter or pilot user of PerformaGo or you would just like to find out some more about the tool, why not register your interest.

And you can follow a more ‘behind-the-scenes’ take on the journey to build the PerformaGo software tool in my online diary.

I think there are many people in an L&D role who spend their days quietly tearing their hair out in frustration. They are what I call the order-takers. They came into the profession, like most of us do, because they like and care about people. They believe that learning can (and should) make a meaningful difference in someone’s professional life and career. Perhaps they experienced this in their own lives and wanted to help others achieve the same.

But somewhere along the way, something went horribly wrong. The job they thought they would be doing wasn’t the job they actually found themselves doing.

They became a harassed (and not very well-respected) internal supplier. Taking orders for courses and workshops others demanded from them. Courses and workshops that satisfy the demands of the order-giver but don’t do much to benefit the learners or the organisation they work in.

Perhaps this describes your situation right now. Or perhaps you’ve been there, done that and escaped to pastures new. Either way, being caught in a cycle of delivering training that doesn’t really solve problems and doesn’t really improve workplace performance is deeply frustrating and ultimately, very demotivating.

I’ve worked with scores of L&D teams over the years and witnessed people caught in the order-taking trap in a variety of sectors and industries. Almost everyone wants change. But how? How can we make the impact and build the influence that we keep saying we want, if just delivering excellent training is not enough.

The truth is, we need to get better at enabling performance. Which means getting much, much closer to our learners’ real moments of need. For example, when someone is:

• facing a new challenge on the job
• making a decision under pressure, or
• trying to apply a skill they should remember, but can’t quite recall

Those are the moments where performance can either bumble along as always or start to excel given the right support. Things like a timely nudge; a helpful prompt; a short, smart answer that moves someone forward, in the flow of work.

I learnt the importance of supporting those moments of need about 15 years ago, during a workshop run by Jim Kirkpatrick. And since then, I’ve spent years deeply frustrated by the fact that the concept is simple; but effective implementation of that concept is not.

However, that frustration is no more. Right now, I’ve finally found a way to do something I’ve wanted to do for years. A way to help L&D professionals design and deliver intelligent, contextual support for those very moments of learner need just described above.

This is not about trying to replace the learning experiences we already do well. It’s about adding a layer of performance-first thinking that gives our work more credibility, more relevance, and yes, more respect.

The future of L&D isn’t about smarter content. It’s about smarter integration with how workplace performance actually flows.

So, this is my new mission. And over the coming weeks, I’ll be sharing more about the journey that’s got me here — and the tools we’re building to help others add that layer of performance-first thinking.

If any of this resonates and you’ve felt the same frustrations, then I hope you’ll come along with me.

And if you would like a more personal take on this new mission of mine? I’m keeping a ‘behind the scenes’ diary of this new journey. You can follow the story here. 

What I really want, what I’ve always wanted, is for L&D to actually make a difference.
To stop being side-lined. To stop doing good, hard work that goes unrecognised.

L&D professionals genuinely care about helping others grow. We want to have impact. We want to make a difference. But time and again, we share the same frustration:

“We’re doing all this work and the business still doesn’t recognise our effort.”

It’s a painful feeling. One I’ve heard expressed countless times across countless courses and workshops. But over the years, I’ve also had to face up to an uncomfortable truth:

That lack of respect feels unfair but sometimes, it might be the symptom of a deeper problem we haven’t fully acknowledged.

What do I mean by that? Well, people come to us with a ‘training’ need and ask us to create a course. If we see ourselves as the “training people” then, naturally, we want to oblige. So, we design workshops. Build e-learning. Roll out programmes. And then we wait for results - that rarely come.

And the reason those results rarely come? Because, I believe, we’re focusing too much on delivering learning solutions… rather than supporting workplace performance.

It’s not that training we are providing is bad. Far from it. But training alone doesn’t move the needle - especially when people forget most of what they’ve learnt before they get a chance to use it. What actually makes a difference is what happens after the training: in the messy, unpredictable reality of work. The part L&D rarely reaches. The part where support and follow-up could really make a difference.

Now, let’s be honest, the idea of supporting learner performance in the workplace is hardly a new idea. In fact, it’s been around for decades. And we are already very familiar with this kind of ‘just-in-time support’ when using apps and systems.

But the ways and means to make this kind of support simple, scalable, and genuinely useful in other areas of the workplace just hasn’t been there. Until now.

Because the arrival of AI, I believe, completely changes the performance support game.

Of course, AI is being widely used in L&D already. But most of that use is focused on content production. Quicker instructional design. Faster course creation. Automating aspects of e-learning production.

Useful? Absolutely. Transformational? Probably not. Because speeding up training design and production doesn’t fix the core problem. We don’t need more training, created more rapidly. We need smarter workplace support.

We need tools that help people in the flow of their real work, not just when they happen to have time for a course.

We need smarter ways to support problem solving, decision-making, and action-taking
right at the moment of need.

Over the last 12 months, I’ve become a bit obsessed with all this and with thinking about how we can turn this new technology into a practical, performance focused solution. One that L&D teams can deploy easily. One that’s practical, low-friction, and grounded in the work people are actually doing.

So, I’m working on a new approach. A new platform I’m calling PerformaGo that puts performance support at the heart of L&D.

If you’re ready to move beyond training delivery and start designing for real-world results,
join the waitlist and be the first to know more about PerformaGo and when it goes live.

P.S. Curious about the journey behind this shift in focus?
You can follow my personal diary, where I share the highs, lows, and learning curve of building an AI-first product from the ground up.

Read my diary here

You may not have heard of Rob Brinkerhoff but you really should have. ( You can google him, naturally). His main focus is on moving away from solving workplace performance issues through a single 'hit' of training.

Brinkerhoff is interesting because he's both a practitioner and a researcher. His focus has primarily been about looking at how best to follow up with and support learners after training to improve overall learning outcomes.

You may not be surprised to hear that placing less emphasis on a single event and more on following up and supporting learners after an event sees massive improvements in workplace performance and application of learning.

You'll notice there are two parts to this. First, having actual support in place (more on this is a minute). Second, doing some follow-up with a sample of learners to see how they are getting on, what's working and what's not. The important point being that the intelligence gathered from this follow-up is used to evolve the learning event and the support so it's more effective still for the next group of learners.

It's a sort of 'kaizen' for learning and development. In case you are not familiar with 'kaizen', it's a concept that started life in Japanese manufacturing as a method to continuously improve the quality of a product.

In a learning and development context, this approach feels problematic. Will you get people not involved with training to give of their time and expertise willingly? Possibly not, or only up to a point.

So, while you might not get non-L&D people to coach and mentor their colleagues repeatedly, there are some relatively simple things that they might be willing to once.

• You might persuade them to record a video talking about their expertise. You can edit and package this up into bite-sized nuggets of learning.
• You might get people to write a short blog post or contribute to a wiki that you can direct learners to at a pre-determined point after their training. 
• You might get people to record a brief webinar where they walk learners through a worked example of a complex task or skill-based scenario.

Perhaps you can begin to see the picture.

It's about being a bit smart and savvy in the ways you provide that follow-on learner support, using technology to help create the kind of success scenario Rob Brinkenhoff's research highlights.

Interested in finding out more about this alternative approach to designing and delivering learning? Take a look at our on-demand webinar How to Amplify Learning Impact - it's about making the journey from learning and development order-taker to valued and trusted expert.