The Business of Learning, Special Episode: Learning Transformation - the Science, Strategy and Tech Behind Real Impact

Speaker A: When you invest in training, you need to know it will pay off. According to G2 Talent LMS customers launch training twice as fast as the industry average. They also report seeing ROI in less than a year. While many LMS platforms take closer to 16 months, that means you're not just getting started faster, you're proving value sooner, looking to launch training without the complexity. Learn more at talentlms. Welcome to the business of Learning, the Learning Leaders podcast from Training Industry, where we speak with industry experts and thought leaders on all things learning and development. Hi, and welcome back to the business of learning. I'm Sarah Gallo, a senior editor here at Training Industry.

Speaker B: And I'm Michelle Eggleston Schwartz, editor in chief. Learning transformation is a term that's often used in L and D conversations, but it can mean very different things in practice. To unpack what it truly looks like and how organizations can enable it, we're speaking with Nick Jonas, vice president of Learning Transformation and company ambassador@talent LMS. Nick, welcome to the podcast.

Speaker C: Thanks for having me.

Speaker A: Yes, welcome, Nick. It's great to have you on. I think in the L and D space, there's a lot of terms we hear thrown around right, pretty frequently, and learning transformation is really one of them. I'd love if, kind of setting the scene for this conversation, you could offer some insight onto, um, what learning transformation actually means in practice. Like, what are we talking about here?

Speaker C: So I would say there are two schools of thought, and I'm going to go contrarian on it, but I think the first school of thought is transforming learning as a capability, as a muscle. I would say in an organization is probably the traditional L and D leadership, perspective and approach. And, um, our view of the world is specifically my view with regards to the background that I bring to the table in the role that I play in the company is to heavily focus on what I call. So if we basically look at the term learning transformation and break it down into an acronym. We have enough acronyms in the world. That's cool. Let's give another one. Let's call it lt. In the traditional L and D space, I would say there's a. It's a capital L and a small T, which means a focus predominantly on pedagogy and many other ways of looking at things and methods. And there are 600 million methods of how we should teach and learn and go through the process, uh, of educating and training and so forth. And what gets displaced, what gets not focused enough, is on the transformative side, on the transformation that's required and so our view, my view very much in this capacity that I play in thought leadership around this space around learning transformation. I focus heavily and I think there needs to be a reshifting in mindset around a capital T or what I call an uppercase T learning leadership model now, which focuses heavily on the transformation that is happening in organizations that is going to happen faster than we expect thanks to the new era of AI and the way organizations are going to be redesigned together with new digital workers. Right. So this is a fundamental shift in, hasn't existed in the past I would say. And it's a very important requirement to really move into learning transformation with a uh, uppercase tier as I call it. What that forces us to do is to start looking at how does, how do we focus more on alignment with the business outcomes the organization's trying to achieve. And, and also lastly I would say going out and sort of thinking about it in an ecosystem mindset of resources, capital and capabilities, including people in the table. Obviously love that.

Speaker B: Thank you for sharing. Um, I love if you could kind of walk us through those core elements of a learning transformation strategy and what kind of separates organizations that achieve it from those that simply deliver training.

Speaker C: So I think it really comes from the basis around what the software sector has done for at least a couple of decades now, which is sort of becoming a little bit more prevalent ever so slowly in the rest of the world. I could tell the rest of industries out there is this notion of focusing on not perfecting everything, getting stuff out the door based on a minimal viable product model and, and getting continuous feedback loops from the front line, from the teams that you're operating within and so forth. And this really, when uh, you think about it, it's the application of shifting from lead startup thinking, uh, and also the approach around design thinking that's come out of the D school, out of Stanford University, funny enough, and really focusing on an individual's journey and a new behavior change that needs to happen versus a uh, production of a program and a set of modules in a course that people have to complete. So what does success look like in that sense is when and when we actually really having uh, the L and D function, shifting, moving into sort of the frontline and becoming integrated into the frontline or business units per se and gathering as much knowledge and know how on the fundamental problems of business that are occurring and then trying to apply behavioral science and learning disciplines to solving for the new behavior change or the new capability that's required going forward, but in a way that isn't over engineered. It's very much mvp. Driving faster feedback loops in order to be able to prioritize and drive that. And then secondly, I think the other aspect here is also, uh, an expectation, I wouldn't say an expectation, but a drive culturally, a drive of pull from employees and teams to want to actually learn more and through this continuous feedback loop, being able to participate in the journey of driving this learning change. One thing that I'm big on as well at the moment is very much looking at how do we build class, how do we build world class. Not just world class organizations but, but world class learning organizations. Because the new frontier of best practice in organizations will be the ones that actually can learn and adapt and be resilient with learning at the center of it all and learning, which actually also is relevant. Right. In many ways. So I don't know if I've actually answered your question specifically, Michelle, but it's actually how I think about things and very much comes from um, you know, being in business for over three decades and really transforming software companies over that period of time when I've done it three times over.

Speaker A: So yeah, definitely love what you mentioned about keeping learning at the center of this transformation. And like you mentioned that that Capital T, that transformation piece is really challenging for a lot of companies. And I'd love if you could dig into some of those challenges that often hold organizations back from learning transformation and, and how can our listeners begin to overcome those challenges?

Speaker C: Yeah, I think the first point, I think the fundamentally, probably three, uh, I love threes. There's fundamentally three. The first one really is a mindset issue. Right. With all due respect to our L and D profession and leadership fundamentally based around a, uh, cost center versus profit center as a shared services function, really predominantly the case, I would say not all is really puts it in a position of a mindset of traditionally order taking, you know, taking in requests, being able to determine what, how we can actually sort of serve the needs of that particular request. Sometimes it's heavily reactive as well. And so that challenge needs to be overcome by having learning and development leaders and practitioners shift in mindset to becoming what I would call performance engineers or performance consultants. Right. Performance enhancers in that sense. And performance really relating to culture, people and capabilities and driving the organization to where it needs to get to. So this shift in sort of mindset is the first thing. The other thing is actually I would say the legacy mindset of still operating in silos. Uh, we sort of have these platforms, we have our LMSs, we have our LXPS and content libraries and they're sort of all sitting in these separate systems and that we sort of, you know, to be fair, one of many, many a uh, plethora of players in the marketplace from talent lms. And why, unfortunately the way the organizations operate is based on the way these systems are uh, designed and geared. Doesn't mean we actually are solving real problems from an L and D perspective, from a learning and development perspective in marketplace. So there's a thinking that needs to be recognized is that most organizations configure their organizational design from an LD based on the systems they actually implement versus it being the right thing, speaking about it objectively. Right. So I mean I think then the third thing really is this whole over engineering aspect which we need to get it all right. Um, when we roll out a particular program with 10 or 20 modules, how do we service it for different needs in the marketplace, different bases and stakeholders versus actually going out testing the water, not having even, not even, let's say it's a temp. If we're just speaking about courses per se or programs, not even having rolled out all 10 or designed all 10 before we actually get feedback, loop feedback from our uh, target stakeholders we're serving by just rolling out the first few. Right. Doesn't have to be all at once. It really is this sort of continuous mindset of rolling out in that perspective. I think that that is something that organizations need to overcome and I think just at high level again it's really going out and being, you know, as I say, half glass, full mentality, front forward, going out talking proactively, you know, two ears, one mouth. I mean it's a classic. It's a classic. So there, there's a lot of that anyway but really feel that there is an opportunity to really go out in terms of engaging directly proactively versus basically waiting for requests to come in. So uh, and it's actually going to get. Reality is going to get worse and worse as organizations are going to redefine how they operate. Right. So. And I haven't even spoken about AI, but I think we will. But that all changes the whole game as well. So. But they're the fundamentals in my view.

Speaker B: I love that you noted like the mindset shift like that is, that's everything like in how you view transformation within your company and in shifting those mindsets is kind of difficult.

Speaker C: I might just say. Michelle, one thing here on that is that uh, I remember reading a book about 20 years ago, might have been over 20 years ago, sitting on a Greek island. Actually I shouldn't have been reading a business biography, but I was, which was Lou Gerstner's. I love business biographies. Just so you know. And it was Lou Gerstner's the, the ex IBM CEO from over 20 years, 25 years ago, 20 years ago I would say, when IBM was actually going bankrupt. I don't know if you're aware of this but 18 months before they were going bankrupt, Lou uh, Gersha came in and actually was given the role to work out what he was going to do with this organization that was multi matrixed and everyone was everywhere and you know, people interconnected with everybody and ultimately the, the what he, I was able to unpack after 18 months of many trips around the world understanding and communicating and conversing with many different leaders and business units and so forth was the fact that people respect what's inspected of them as a human behavior. And so fundamentally when we start looking at L and D or leadership, learning, leadership across the board, it ultimately comes back to what to be. What ultimately are we inspected on and disappointingly what we are bonused on at the end of the year. Uh, ah, sort of being quite open and transparent about things. And so that is probably at the core of organizational design and rethinking is what are we going to respect going forward in what we do as in the function and as it adapts and learns to becoming the new normal that is coming.

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Speaker B: Definitely, that's such a great example there. I'd love if you could kind of share a little bit more about how cognitive science shapes learning transformation. Go a little deeper there.

Speaker C: This is a topic that I love. So uh, at the end of the day I try and apply first principles thinking to anything that we try and do, which is heavily quite difficult. And if we just unpack, we unpack the whole L and D ecosystem and assume it's a big, you know, onion with so many different layers and rings at the core of it. At the core of the onion, uh, is the cognitive thinking. And ultimately there's an amazing study that was done so many, many years ago that I love, which is all about the forgetting curve. And I'm sure that you guys are aware of it. I'm not aware of it. For me, it's at the core of everything. Everything else is just noise in the grand scheme of things. If we don't respect and validate the forgetting curve which is being validated. Herman Ebbinghaus in 1885 did a test upon himself to actually demonstrate and find himself scientifically how much he remembered within a 24 hour period. Right. And 24 hours later he validated on himself. Uh, and it's not just, it's not enough of a scientific breakthrough to be able to do it on yourself, but validated, he only remembered 70, 70% of the stuff that he learned, but got forgotten within 24 hours. Right. This was also validated probably in 2015 when another study was done to demonstrate that is the case when you do it with many, many, many, many different people, as well as part of a bigger sample set. And when you look back and take a very simple perspective on things, what's happening is our metaphysical biological adaptation of surviving as a human is heavily dependent upon how we metabolize things and the, and our energy usage. And for what it's worth, our brain, actually what it all is worth is the fact that our brain every day is metabolized, is, is utilized, is, is 20% of our metabolism and energy that gets really basically is used, is being used by our brain. And so our body and mind naturally is eliminating and getting rid of excess data. Right, all the time. And it happens again when we sleep as well. That's why we need things to sleep properly and so forth. So really with that comes the first area which is really recognizing that forgetting curve at the core, at the kernel of every single learning activity is required and recognized across the organization. And with that comes the area that we need to go into spaced intervals around learning over a period of time, which in the tech industry are called nudges. Just so you know, to nudge people to do something and so forth. And sometimes systems don't allow that quite easily. Or you might send out an email, it might coming through Slack or whatever it was, it might be through your lms, the lxp, whatever it might be. Uh, and then it's obviously this whole notion of active repetition sort of bringing that off. And even with those, it actually only gets to a point of sort of doubling or just double two and a half times improvement on learning. So with that then comes the other aspect around the other Thing that I'm sort of driven by is actually the area around simulation and pattern awareness over time. I think the combination of the forgetting curve together with simulation and you think about where is their best practice in simulation. Formula One, my. The sport that I love the most, Formula One, Formula One Racing, has each team invest 20 to 30 million dollars a year in the simulation environments for these two or three drivers to actually memory test and build pattern recognition around the circuits that they're riding in, where they crashed last time, where they slowed down every single millisecond is all about pattern matching and recognition over time through simulation and feedback loops, through people around them over time. You take that and you apply it in the real world. Well, it's taken into industry and operations. Simulation is critical for us to be able to enable us as humans to build pattern matching over time. And so therefore, the combination of improving on the forgetting curve and bringing simulation together with coaching and mentoring is sort of the trifecta in that sense from a cognitive point of view. So I'm very passionate about this space. And the reality is there's a mismatch between the systems that are out there together, what we need to do as humans, and we're trying our best with talent, lms and trying to improve on that over time.

Speaker A: Exactly. No, I love that you mentioned the forgetting curve, since it's kind of mind blowing to think, you know, that came about all those years ago and it's still just such a challenge today and still remains kind of especially so with learners navigating constant distractions and pings like you mentioned, and emails and all of those things which can really lead to this information overload. Um, so I'd love to kind of get your insight on how L and D can better design and deliver learning that engages employees kind of with all of that, all of that distraction and overload in mind.

Speaker C: So, uh, first and foremost, I'd say it's not all about tech. That's not all about tech. Tech only enables one part of learning, I would say. Right. Sort of that, that sort of programmatic stuff and that sort of. Having said that, we can shift towards personalized things at scale over time. So we'll probably talk a bit about that maybe when we forget if we get to talk about AI in some sense, I'm not sure, but there's an aspect around. I think relevancy is an important area. So, uh, and how do you bring relevancy, if you think about relevancy, back to what we spoke about with forgetting curve and simulation bringing Relevancy to the center, front and center is critical. It's the most important thing, right? And one of the interesting terms that's get used right now a lot is, you know, in the flow of work, right? So everything's in, everything needs to be in the flow of work. I just talk about it when work needs to be done. We need to be also be learning on the go right when we need it most. And I think that in itself is where the opportunity brings an, you know, a life to start to bring some form of performance. Uplift is sort of the relevancy of having the ability to learn on the go when's required. I think the other aspect as well is from a learning leadership point of view and practitioner perspective, really the aspect around shifting mindset to curation versus creation of content is critical. I would say that there are so many different. There's a plethora of learning libraries out there and content libraries, but there still isn't enough of a focus and mindset around curating the learning journey for people, depending on the different type of learning pathways they want to take, including offline hybrid, uh, mentoring guilds, experiences and many other aspects to what it means to learn. Right? To learn doesn't mean just mean to take half a dozen courses and you're done. And we know the fact that people forget those, as we just said before, very much. Also, having been shepherded or shadowed by an individual or people or group where you can actually do things, one of the aspects that I'm very big on is we're shifting into the world. We're shifting into a world now where each or each member in an organization are going to have. We're going to have superheroes in organizations because of AI. And with that will come an ability for us to rethink what it means to be humans in work because we're going to have digital labor forces coming through. Right? What it means to be humans in work and in work environments will be very much around having a strong sense of. Having a strong sense of emotive connection and reasoning. And the ability to do that over time is going to be critical. So, and then the, the last aspect I think really is the ability to remove friction from the equation. Right? And this is probably the most important. One of the most important aspects is that unfortunately I'm a big believer and we're working, we're heavily working towards is how can you get to one or two clicks to achieve an outcome is critical when it comes to learning. Unfortunately, we're very, very much stuck in checkbox learning as we call it, and really gearing people towards a journey based on the systems that we have versus unlocking them and delivering value where they need, where they are, where we should be, where they are, versus forcing them to come down the path that we have because we're using a piece of technology or the like or type of process and system. So uh, you know that this is a whole discussion but uh, we've only got so much time.

Speaker B: Yes. And in that relevance piece that, that you talked about, it's so important for engaging learners and enhancing recall. It's really what's going to help our learners today, who are so distracted, um, retain the information that they need. And so getting them that information in the flow of work is so important for learning leaders. And I'd love to dig into kind of the role of technology and learning transformation and really with the emergence of AI tools, what is an effect of learning tech stack even look like today?

Speaker C: Okay, so this is. We are going through a fundamental shift in what it means to. We use the term tech now. Right. As we know, having been in industry for 30 years, over 30 years now, I've seen the evolution from client server to cloud to SaaS to, to now AI, right. Or generative AI. And there's many flavors of that now as well coming through. And we're still at the early stage of that paradigm. So if we reflect upon what we've been doing for the last 50 years at a macro level, we really have taken what we've done with cabinets and folders and classifying in folder structures in an offline world. Right. We had typewriters and pages and I remember that, remember I had a pager back in the day when I was, when I was a young pup, so to speak, working, doing what I did back in the day in Sydney, Australia, all the way through to taking those existing systems and flows and processes in a digital manner and applying them in what we now what we call software in the current type of model, which ultimately what software is a store of record in a powered by. A database with that is powered by a set of functions that we input as humans. There's some logic that happens with the software and then it spits out some output that we can either view on reports at the end of the day. Right. So if you think about it, we've been, we've been, I was going to say we've been forced, we've been guided towards having to work and utilize these software capabilities under this new software as a service model that Enables us to access the same type of technology over a period of time anywhere in the world. We can be thanks to the Internet. Right. So we've unlocked a lot of value. Having said that, what's happened is we've been forced to really have, have operate in a, an industrialized model at the end of the day. Right. And being a very much a one to many model, anything non one to many, super expensive as we know. Right. Especially when it comes to content as well. So it's been a factor of people, resources and capital that has challenged us in where we're at. So systems of records is where we're at, where we're entering now. Uh, the new era is what I call systems of intelligence. And systems of intelligence, I try not to use the word AI as much as I can because it means so many different things. And it's become the crazy new buzzword because it's the new era that we're living in. But ultimately it's a systems of records with systems of intelligence where we, there's a big digital brain that operates in some way similar to the way our brain works with neural networks that we ask it questions openly in a natural way, as though we're speaking now and it responds back to us. What it's telling us, how much we trusted or not at the moment is an issue in itself. The believability of this stuff at the moment.

Speaker B: The.

Speaker C: So there's some guardrails that need to be put in place. And so where we're going is, um, There is, there is, there are these sort of, I would say these two or three silos that exist right now. We're seeing organizations that are, you know, using the different, uh, artificial intelligence technologies to roll out and build questioning capabilities and learning and quizzes and courses on the go right along the way. They are, uh, in addition to the systems of records that we have. So where are we going, I see is the interfaces will change over time. They will become more frictionless with AI technologies. Uh, and secondly, our systems of records will become a place where we will actually value them from a trust and governance point of view in terms of tracking and measuring and sort of maintaining presence on what people are actually doing. And ultimately with the combination of these two together proactively driving intent of where things need to be done and what people, what we anticipate people would need as they transition in their organization or even in their flow of work, in their daily work to be done. So we're in a beautiful, we're in a very, very we're in very, very interesting times and for me I see it as a half glass full opportunity. Um, you know, many L and D leaders right now and practitioners are thinking, oh my God, what does it mean right now in my profession in industry that we're in? And I'm like, I'm saying, well let's take a front, you know, a positive look at this and ultimately unlocks. It actually unlocks the opportunity to deliver greater value across the organization faster and better ultimately over time.

Speaker A: Yeah, I love that, that perspective. Well, that's a great note to end us on, Nick. I appreciate you offering some clarity around this topic. Before we wrap up. Do you have maybe one practical step or action our listeners can take after the episode really just to start moving closer toward learning transformation?

Speaker C: Yeah, I think uh, I would look at probably a couple, I would say for first thing is really just looking at all the different initiatives that ah, L and D activities that you know, your organization is doing and really trying to see where is there a high effort, low impact program. Right. If you looked at a two by two chart, I said where is there high effort? It's so much friction, a lot of effort to be done. But low impact and value, we just got to stop it makes no sense anymore. Just uh, cut it, it's not worth it. If you valued your time, you cut it. You don't value your time, you continue. It's really simple, right? Uh, and so with that comes the reallocating the uh, resources and people and effort and mindset and mindset to solving going out into the organization and trying to partner with the organization of solving a high impact problem, business problem, organizational problem is the first thing. The second thing I would say is great opportunities to go and actually just shadow learners out there in the field in the organization. Get out of the ivory tower as we say and start to get out and have coffees and lunches with people and start talking to them in terms of how they operate. Right. Versus versus thinking how they do, but actually finding out how they do. I think the last thing I would finish up with is actually really getting into um, a mindset shift around being agents of behavior change at the end of the day. Right. Together in partnership with HR or people. Right. So I think they're the fundamentals, I would say is sort of, I would say very mindset oriented shift and also just starting um, to reconsider where, how you're allocating your time in terms of much more higher value outcomes ultimately. Because if you don't do that, you will become irrelevant. Let's be frank, right? Let's be frank. Let's not beat around the bush as they say in Australia. Um, you will be irrelevant. And it's for this reason. It's exactly not Massive opportunity to step up and uh, be set free to do what we need to do in our organizations and build them as, build them up as being world class learning organizations, in my view.

Speaker B: Nice. Well, on that note, Nick, thank you so much for talking with us today. How can our listeners get in touch with you after the episode if they'd like to reach out?

Speaker C: All right, uh, really simple. LinkedIn. I love LinkedIn. So yeah, they can reach out and it's Nick Gonios. Nick N I C K Gonios. G O N I O S. Ah, really, really active on that on a daily basis, I would say. And secondly, we're going to be at Training Industry Conference tice this year as well. So we'll be there mid June and would love to see see everybody come along and say hi to the Sydney side of Australian who now lives in Athens, Greece.

Speaker A: Awesome. For more resources on this topic, check out the episode description or visit the show notes on our website@trainingindustry.com podcast and don't forget to rate and review us wherever you tune into the business of learning. Until next.