An interview with JD Dillon about continuous learning

In this interview, Robin talks with JD Dillon about continuous learning and how it links with personalised learning.

Links from the podcast

• LearnGeek
• Behind Every Good Decision: How Anyone Can Use Business Analytics To Turn Data Into Profitable Insight
• Axonify 

Transcript - An interview with JD Dillon about continuous learning

Robin: 
Hi, it's Robin here, the host of the Learning While Working podcast and the founder of Sprout Labs. Last time I talked about a few new formats for the podcast. In actual fact, I'm going to starting a new podcast with the other Principals from LearnD. There's going to be a mixture of interviews and us discussing topics. Like the Learning While Working podcast, it should be fortnightly.

In this podcast, I'm talking with JD Dillon on continuous learning. We explore personalisation a bit, and touch on his framework of personalisation and adaptive learning.

There's been a trend for quite a while that consumer technology is driving how technology is being used. We're now starting to see, as consumers, that we're our experiences to be personalised. Recommendations on Amazon is just one small example of this. This sort of smart technology and smart content and smart experiences hasn't really started moving back into learning and development yet. 

JD touches on some really nice ideas around self-directed learning and problem-solving as well.

Now I thought I had moved on from talking about xAPI and learning data, but it's a topic that we touch on again, and I feel it's going to be one of the sub-themes for the Learning While Working podcast this year as well.

JD, welcome to the Learning While Working podcast.

JD:
Thank you very much for having me.

Robin:
What sort of trends are you seeing in the continuous learning ecosystem environment?

JD:
Sure. I think there's a couple of different kinds of big conversation points or trends that people are exploring that all kind of tie into this idea of learning as a continuous reality in the workplace. So the shift that I refer to is kind of stepping away from place and time learning, and training is the only thing that we do to help people to something that fits into how learning actually works: which is it's constant, but our support tends not to be. So I think that a couple things you see are the big micro-learning conversations, so the concept of being more targeted, more focused, more again integrated into the work as well.

I think that performance support conversation fits right alongside that, in terms of being there in the moment of need and everything that Bob Mosher talks about. Then I think that the entire conversation around self-directed learning, so the idea of giving the employee greater agency, and greater autonomy. Sometimes I think that conversation slides a little bit too far to the pull side, and there's the expectation that people are going to go and get everything they ever need.

I think it's a little bit more of a balancing act between push and pull, but obviously the pendulum tends to swing pretty hard before we correct. But those ideas, and them bleeding into the concept of personalisation and adapting by using data, are now kind of coming all together to really start to reshape what the learning and support experience can look like for an employee in today's workplace.

Robin:
I'm just going to go pick up, first of all, on the self directed learning piece. It's a really interesting one, because essentially it's quite hard to be a really good self-directed learner in modern workplaces.

So much is pushed back out from an organisation, rather than people being given the spot where they need to take more responsibility. I sit there and say, "How can you expect your learners to be self-directed if you control their navigation in an elearning module?" They have no ability to be able to navigate; there's no control, just subtle messages that you're giving people all the time about control and power.

Personally what do you think some of the keys are to helping build that environment for self-direction?

JD:
I think there's an interesting contradiction in play where - obviously this is different based on every organisation and the roles that are played inside of organisations, and everyone is obviously a different performer, different professional. I think there's the side of the conversation where we want to just give people portals, and we want to aggregate content, we want to curate a bunch of stuff, and they'll figure it out on their own.

Then there's the other side of the fence where we don't trust people to not complete everything; they have to do all the slides, they have to click next to continue, and these types of facts. And we forget about the fact I often point out - that people have pretty solid problem solving skills.

And you can tell that because they manage to get to work alive. And they're there and they have a job. So there's things happening that in everyday life - this tremendous ability to solve problems, to utilise resources; everything on the internet, the Youtube and the Google story, in order to do amazing things and overcome tremendous challenges in our everyday lives.

But that type of setup, what would kind of be a workplace version of that, doesn't exist and the support structure is missing. Or we assume that it's a learning problem. I don't see the idea of self-directed learning really being about learning. I see it being more about problem solving, and problem solving can be unpacked into a lot of different things.

It can be, "I'm in front of a customer right now and they have a question, and I can't answer it." It could be, "I can't figure out what their vacation policy is in this place." Or it can be, "I want to become that role, how do I become that role?"

All of those are different types of problems that require different types of solutions and support. So for me, it's about providing a mechanism and a structure, and a way to access resources whether it be content, whether it be other people, whatever that means.

Having the resources like I have in the real world, but applying them inside the workplace and inside that context in that situation, and then enabling people to be able to solve problems, to be able to drive their own behaviour, to drive their own development when it's the right thing, but then at the same time balancing that with the fact that businesses have priorities; that compliance and regulations exist; that not every person knows what they want to become, or where they are good and where they are bad.

People tend to overstate their own abilities. We all have blind spots; we can't tell if there's something that we need to be working on, and that's where things like data can come in to help us. But for me it's really a balancing act to enable people's problem solving abilities, give them agency on autonomy when it's the right thing to do and people want to take the ball and run with it.

But when there is a need for scaffolding and structure, be also able to provide that at the right times for the people who need that or when the business needs that to be provided.

Robin:
Yes. There are some layers to that problem solving and being self guided. The way I think about it is whole industries are being transformed through digital technologies. Quite often through start-ups doing small things very quickly in a mode where they're real, true learning organisations, and that transfers down to the people on the ground floor, the developers, whose essential job role every day is to solve problems; to learn to do things that have never been done before.

They're quite often really good self-guided learners, but what they're doing is solving problems constantly. There's no separation, there's no notion of, "Oh, I have to go off and learn how to do something." Learning's a constant stream of things.

It's interesting because we've been doing some recruitment for a developer at Sprout Labs, and, "How do you learn?" was one of the defining questions about whether or not they would be great in our environment.

JD:
Completely. I think it's that in a traditional business environment you see people on kind of both sides of that fence. In my background I came out operational management as we discussed earlier; I live in Orlando right behind the Magic Kingdom at Walt Disney World because I spent about ten years working for Disney.

Even in that environment there are people who needed structure, they needed to go to classes. They needed to have more scaffolded conversations in order to develop their skills.

And then you had people like me. I had a management background coming in to Disney, and this is before I'm formally in learning and development. I'm the type who is going to go digging and find resources. I'm going to find the people that I need to talk to who have been there before, and can share the experience.

I'm the type of person who likes to take the ball and run with it. Not everyone behaves like me, so I think we have to figure out that certain types of roles require certain types of people to be able to run with that, especially if you're a smaller organisation. If you do work for - my current company is 140 people. We're obviously not going to provide a structured learning experience for all 140 people because we have one internal learning and development person dedicated.

So it's more about having people who can lean in, and go where they need to go, and raise their hand when they do need support, and then are looking for the right places where we can provide structure and more pushed experiences because it's the right thing to do for the business.

Robin:
That more structured and pushed experience is leading into the personalisation that you talked about before. And we're now seeing, as consumers, we expect Amazon to be personalised to what our interests are, and where we are and what we did with the last thing.

One really nice moment was when I downloaded one of your presentations from Slideshare, JD, and LinkedIn within two or three minutes was sending me a message saying, "You might also be interested in ... ". It was a really sweet moment to sit there and go, "Yes, in the rest of our lives we've got these really complicated systems that are giving us recommendations and personalising things." Quite often from a marketing point of view, and sales as well.

But in learning we're not quite there yet.

JD:
Yes, and I think that there's this glut of content, right? And I mean, imagine the internet without recommendations. Imagine the internet without Google's search capability, and its ability to add relevance based on everything that it knows about you.

I think in the workplace we've got similar challenges today, because there's a difference between search ability and findability. Even if you've got a great knowledge database and a decent search engine behind it, how do I necessarily know what's there? One of the biggest projects of my career was building a giant Wiki for one of my former employers, and by the time I left the company we had built this thing that had 70,000 pieces of content in it. I ran it, and I couldn't tell you what's in there, at that point because we had just scaled beyond a certain point.

My estimation was always that we had 40 percent of institutional knowledge, somehow touched at that point, by that scale. So we were nowhere near done. You'll never be done, but we were nowhere near comprehensive for that organisation given it was a global company. So how do you overcome that?

I think that's where the sheer volume of data that we have inside of our organisations, not necessarily all in the same place and not necessarily being used effectively, is going to open a door to us in terms of solving business problems and developing people and providing opportunity in similar ways that, over the last 15 years have swung the door open for marketing. To be able to attribute and target and focus on what works for them, as opposed to throwing spaghetti at a wall and hoping something sticks, and say we did a good job.

So I think that same type of transition is happening, because of these other conversations we're having in workplace learning, are setting the stage for meaningful personalisation and adaptive experiences that fit the workplace today.

Robin:
I did a really great podcast with Lori Hoffman around her notion, the way she's working with data-driven learning design. I've been thinking quite often about the reasons why L&D is not more data driven.First of all people need to be in a spot where they can collect the data to start with, and then they need to be able to think and contemplate about understanding it. I'm wondering whether or not being actually data-driven is the right word, JD? Whether that's too complicated for most learning and development people more interested in learning?

JD:
I think we've historically, as a profession, been curious about measurement, right? I mean, have you gone to a class that didn't have a survey? Did you do the survey, is a whole other question. But we've tried, we've been looking for ways. One of maybe five things that everyone in this profession has heard of and/or can recite is the Kirkpatrick model. Everyone knows what adding is, everyone knows what Kirkpatrick is, and then after that I couldn't tell you where consistency is in this field, because there's no one regulating it and we all come from different places.

But within that, we've always had limitations to what we can do in order to design to and collect data, so we've been able to do surveys, we can do tests, but usually we can only do tests when we have access to the employee, and that's usually a very limited amount of time. In order to do any type of level 3 behavioural activity, we need someone else to help us or we need a lot of project resources. We have a hard time getting there.

In order to get to level 4, we need access to business data, which in some cases is just hard to get, because maybe the business hasn't really figured out that whole data conversation yet and if they have, are they willing to share? Because L&D historically hasn't been involved in that conversation, or maybe been known how to have that conversation in a very targeted and meaningful value added way.

I think the limitations in terms of our ability to partner with the right people, and in order to get access to the employee consistently, so that we're consistently gathering data just like marketing engines are on us every time we touch the internet - that changes things.

So, when we re-look at how we support people, the experience we provide, and the ability to get access to increase the number of touchpoints and to use those touchpoints in meaningful ways in order to grow a robust data profile on our organisation and on individuals; that changes the conversation around how we can design for and meaningfully use data.

So I think it's an evolution; I agree that not everyone in this field is going to be able to jump into this tomorrow. I have done presentations on things like data, and I've been involved in conversations around the xAPI and whatnot, where people in the audience have said, "We can't make effective use of what we've got right now, how can I possibly go down this path you're talking about?"

So I completely recognise that. I think it's, again, an incremental evolution, and I think people also have to partner up and bring in people who can have these conversations. So whether that's inside your organisation, you have a BI function; someone who plays in data, someone's a data scientist that can help you evolve and learn this, but I don't think you need to be a data scientist to make better use of data.

I just think it's having the right conversations, reading some of the right material, following some of the right people in terms of social networking and building a professional network. That can really help bring you along the journey to a point where you can start to integrate some of this stuff into the work you're doing every day.

Robin:
Yes, and that's a really nice sentiment: not every learning person needs to be a data scientist. It's quite often about accessing those people. You talked very quickly about the notion or idea that data can be collected and analysed and then used for personalisation.

You're probably the first person I've come across who seems to have a framework for personalisation in learning. There was data curriculum, and was there something else?

JD:
Sure. So I made a couple presentations recently breaking down the different elements that you have to take into account when we're talking about things like personalisation and adaptive learning, and the four elements I tend to speak to are data, because one without the right type of data and what you'd call a multidimensional data profile, you can only go so far, so what are the different types of data we can acquire?

Two, we have to change the way that we design content in order to match this world, because if we're still locked in these ideas, bloated long form courses, that doesn't match up with our ability to use data to pivot an experience that really fits the employee and helps them solve their problem. So there's the content consideration.

Technology, because technology's required to scale that type of idea, so if you're a team of 30 supporting 300,000 employees, in order to personalise you're going to need to leverage a technology that can take advantage of these types of ideas. Whether it be 'learning technology' or whether it be business technology, and the tools and complexities for doing our jobs every day.

And then the fourth piece that I always highlight specifically is the person themself. One thing I don't want them to get lost on is saying that this is just a data conversation, or just a technology conversation. At the end of the day it's about an experience that we provide for people, and I see this type of an idea and personalisation as a way of making us that much more human in the work that we do, and the choices we make, because we can knock away some of the things that get in our way, whether it be content we never needed to consume.

But we're doing one size fits all stuff and it's getting in our way, and it doesn't provide value, or it helps us solve some of our foundation problems, and it helps us aspire to bigger roles, bigger challenges, these types of ideas. I think it's critical to keep a person at the centre of this conversation, and then using those other elements in order to boost that individual and make their experience that much better, just like different services are trying to do for us in the consumer experience when it comes to personalisation.

Robin:
That's a really sweet idea. Essentially, when I talk about learning ecosystems and design I sit there and go, "So the first thing is you put the employee learner at the centre, and then you give them options to be able to do things and give them guidance about where they need to go, but you let them have some freedom." And that freedom then helps with problem solving, and self guiding learning skills, but it's also naturally personalised isn't it? Compared to the whole first reaction about making it data driven.

It might be data-augmented, but essentially it's a different way of thinking through that continuous learning experience - so if someone's in a spot where it's expected that they're learning. It's also interesting to think about how collecting data can be used as a reflective learning experience for employees as well. That's another thing I'm starting to see happen a little bit as well.

It doesn't always have to be automatic data collection. Does that make sense?

JD:
Yes, completely. There are so many simple things that we could be doing to create more personal experiences when it comes to the kind of continuous nature of learning.

So the idea of embedding reflective activity, or having those conversations that can really help a person focus down on what they're doing and how they can do better the next time, is something that just came naturally and I think it's something that we miss the opportunity to do, that doesn't require a lot of mechanisms or things like that.

Then the more complicated conversations when we get into data and content and automation can further help to boost those moments. In some cases it could be as easy as reminding someone to take a moment, to think about the last customer interaction they had, to think about the last time they had a challenging situation, or a safety incident took place in the workplace, just because we tend to get so busy.

Everyone tells me the same things: "We're in highly regulated organisations, and a results-focused company. So we don't have time. People are overburdened. We can't take them off the floor." All these things.

And we forget about all those moments to say, "Well if you pull back and think about it that's how you learn, by assessing the mistakes of the past and moving forward past them."

So I agree, there's kind of a dual nature to this, and again it comes back to the person, in some of the simple things we can do as well as some of the more complex and innovative future-focused ways that we can also support them, in ways they haven't seen before.

Robin:
It's a loop-back to something else you said before. You made it sort of a binary thing between having a set of content curated resources that people pull in when they need them, and then the push back out of that highly regulated process.

Did you make that binary because in some ways you're not seeing that either end of those tools, that they're able to, from a digital learning point of view, really help people do what you're talking about?

JD:
Whenever I talk about the concept of support within a modern ecosystem, these types of ideas, I always start the conversation with access to information on demand and performance support. Because I, as a practitioner, have experienced the change that when you make information available to people, and they can light up that Google reflex, start to solve problems on their own, start to share information in meaningful ways, everything else changes.

So the rest of the equation in terms of the push-pull balance, anything that you have to make in learning and development, anything that we have to provide completely shifts when that happens. So for me that's always the starting point, is the pull side of the conversation, because once you've enabled pull that works for the people you're trying to support, the push conversation shifts and you can target that more strategically.

So I kind of separate the two considerations. But in execution they blend together, right? When I worked at Kaplan I had one simple rule for anything we built as a training team. Before we could build anything, people had to be able to look up that information. Because no one goes back into the elearning 6 months later to find that one thing they forgot, right?

That's also not how the internet works. I'm sure everyone here has had that moment where you were looking up something real quick, and then you slammed into a video. And you didn't want it to be a video, because you didn't want to watch a video. You wanted control of your screen and find the one thing you needed. So you went looking somewhere else.

It's that idea. So for me, all of the unstructured types of shared knowledge performance support ultimately support the more formal structured stuff when it's necessary, and they flow together. So the framework I tend to talk about around the idea of ecosystems, fits all about these topics we're talking about, but it really goes from working with unstructured content to the people who can try and solve their own problems, up to when we do need to get involved with a more formal structured, created experience because that's what's necessary for whatever reason.

Robin:
Yes, it's one of the sad things that sometimes the only way to actually access that organisational knowledge because it hasn't been put into performance supports, or learning portals, or on the intranet; it's actually a training experience. And they're becoming information dumps where people could be pulling those when they're needed; it's just a really subtle change.

JD:
Yes, it's an interesting version of that in our own profession, with the concept that - if you've done any presentation in the industry, you know what I'm talking about. The first question that audiences asks you is will the slides be made available? And I'm a solid example of this.

My slide deck without me is useless, because I put big pictures on screen so I can talk in front of a visualisation of whatever I'm saying. You have no idea what I said when that picture of a sunset was on screen, but I was demonstrating some type of point. So to that end, I've started to annotate my own slides, so if you've pulled any of my slide decks you'll see there's more text on screen than there would have been in a real delivery of that, because that happens so often.

But it's a great example of: my slide decks should not be a reference material. There should be other assets that you can Google, look up all this information in a way that's more compelling and useful to you than trying to decipher a slide deck presentation that I built for a very specific reason.

I tend to build my own stuff that way, so most of what is in my slide decks is also living inside of my blog, or I wrote articles somewhere for it, because the slide deck is a natural evolution of the bigger story that I'm trying to develop.

It's funny to see us do the same thing that we shouldn't be doing to people, which is making people reliant on a training material as opposed to some type of reference support or performance support to help them overcome some type of challenge or grow their knowledge on their own.

Robin: Yes. Sprout Labs webinars are interactive experiences, which is lots of whiteboard activities and we limit the numbers because of that sometimes. People are shocked all of a sudden when they turn up to a webinar and they have to do things. But the slide decks are terrible, because half the content that happens during the session is missing.

JD:
Exactly.

Robin:
I've had a senior L&D person say, "Oh, could you write that out for me?" And it's like, "Turn up to the webinar, have the experience, do the thing, be active. It's not about the resources." It's interesting because then I'm in a spot where I hardly ever turn up to a webinar. If it's not going to be a real experience then I might as well just get the recording and listen to it on the way to work.

It is interesting how we confuse that sense. I think it's Jane Hart - one of her strong messages is as an L&D team you have to be the change you want to see. We have to role model that as well.

JD, we've covered a lot of ground, and I think this whole area of personalisation and continuous learning is a really complicated area. If people want to dive into it more, what are your thoughts on where to start? What are some good resources?

JD:
Sure. Particularly with adaptive learning and personalisation, I think we're still so early in the conversation there aren't a lot of great straight recommendations I would have. I'm still writing a lot on this topic, I'm leaning hard into this conversation right now, so if you ever go to my website, which is learngeek.co, I'm blogging on this concept. The organisation I work with, Axonify, has been in this space for quite a while and we're curating additional assets. I'm in the process right now of outlining and starting to write an ebook on the topic, that'll help people navigate through the noise and try to figure out the different types of personalisation, the different tactics they can use to start going down this path.

The other places I would recommend is really starting to look at different components of this conversation, data being a huge consideration. The xAPI conversation is obviously something great to pay attention to, and see how it's evolving and how people are designing for and making use of data. Megan Torrence tends to be the person that I recommend people take a look at and follow. I tend to refer to her as the queen of xAPI conversations, so she's great. Melissa Milloway is another person who works for Amazon, who is doing a lot of hands on work with designing for data and the Experience API.

The other thing that I always recommend for any topic really, especially this one, is looking outside of our space. I had a conversation with Trish Yule recently around the concept of analytics, how she's evolving her thoughts around these types of ideas. A lot of what she's referencing has nothing to do with learning and development. It's more about the business side of data and decision making.

I'm currently reading a book that she recommended called Behind Every Good Decision: How Anyone Can Use Business Analytics To Turn Data Into Profitable Insight. Like we referenced earlier, marketing has been through this conversation about personalisation and the effective use of data to improve results of their work.

I think that we have to look outside our space to those influences and not necessarily do exactly what they're doing, but take what they're doing, apply those principles to the types of challenges we face, and see how we can take advantage of it.

I suggest to everyone to get outside the L&D space if you can. Follow the L&D practitioners who are obviously addressing these types of topics, like the folks I mentioned, but go looking for people who have been successful in applying these principles in their fields, and take away what you can.

Robin:
Great series of resources JD. For anyone who is new to the Learning While Working podcast, there's one of my favourite interviews with Megan Torrence the archive, as well as one about data- driven learning design. Thank you so much for joining me today JD, it was great. Might even have another conversation about this at some time in the future as well.

JD:
My pleasure, happy to do it.