Turning a Corner in Learning on the Job

Welcome to the Future of Education. And now here's your host, Michael Horne.

Welcome to the Future of Education, where we are dedicated to building a world in which all individuals can build their passions and fulfill their human potential. And to help us along that journey, today we have someone who is the Chief Learning Officer at Cornerstone on Demand. His name is Mark Ramos. And Mark has had a long and distinguished career in corporations, really helping drive learning of individuals and employees and frankly, the companies themselves. And so first, Mark, thank you so much for being here. It is a pleasure to have you. As you know, we've got four segments of the show. We get to kick it off with our morning warmup and I'd love you actually just to tell us about your own journey into your current role as Chief Learning Officer at Cornerstone on Demand. Because you've, you've had an interesting career path.

Yeah, well, first and foremost, thank you so very much, Michael, for inviting me on the show. I'm honored and humbled in terms of this first segment, the journey, the pathway, it's really, really interesting in the sense of, I guess there's maybe two ways to look at it. One is where am I now? The kind of working backwards. And the other one is maybe where did I start? And then moving forward. So maybe I'll munge those together in ideally some sort of understandable way. But yeah, I'm currently the Chief Learning Officer at Cornerstone, been on board for a little over 10 months. I'm actually dialing in from beautiful Cape Coral, Florida, where we've been here for roughly that same amount of time, 10, 11 months actually. Prior to coming out or coming back to the U.S. my family was based in Basel, Switzerland for three years where I headed up Novartis's learning strategy and learning innovation and different segments of that learning tech, learning analytics, knowledge management strategy, so on and so forth. And then prior to moving to Switzerland and working at Novartis predominantly in California, my family actually moved to Basel from the San Francisco Bay area where I had a variety of jobs. The one prior to moving, I was at Google for roughly seven years and had a lot of great experiences and roughly three different hats that we can talk about. And then prior to Google, I was at Accenture and Microsoft and Oracle and then a stint here or there with smaller sized companies. So that's a little bit of the corporate background, predominantly in a global setting, predominantly in a multi segment or multi vertical setting, different size companies, but for the most part around how to scale learning and a little bit across the board in terms of the Various types, portfolio types, leadership development, management development, and then working the other side of the spectrum. I was just thinking about this the other day. Where did I start my training career? I started my training career when I was maybe 13 years old. I was the head dishwasher at Mr. Cheese Chinese Restaurant in Long Beach, California. And as the head dishwasher, the experienced 13 year old guy, I was responsible for training, guess what, all the other dishwashers. So that was a little bit of my start. But in all seriousness, I actually did end up more formally starting my training career in restaurants, predominantly out of high school. And I just found myself doing well in terms of this thing called process documentation, as well as how to work with folks to kind of get them up to speed to become a server, to become a bartender, to become a chef, and then one way or another work from restaurant training to call center training, telecom training, and then in the tech space. And then if it helps, the last portion of my career, maybe at the DNA level is actually come from a family of teachers. So my mom, my brother, my sister were all teachers. And I guess I'm a little bit of the black sheep. Michael. I went the corporate route because I was thinking about, you know, why should learning be contained in a box compared to how can we scale this for bigger, broader needs? So that's a little bit of my background.

No, it's helpful just to understand from where you're coming and a separate time we'll have a different conversation about restaurants and training and learning. My wife has worked in that industry and done a lot of training and manuals and procedures and all the restaurants and the work there. But it's also interesting, I actually really like that you moved the teaching and learning from the formal, if you will, education space into companies themselves. Because I think, as Rachel Romer, the CEO of Guild, often says, you know, the 4 and 40 is dead. It's now in the 4 and 4, right? It's you're training and upskilling constantly. And on your resume you've been at a couple of the places, Google Novartis, that are really known for being incredible places, places to invest in the skills of its employees and really take that work seriously. So you have a lot of experience on that. So now you come to Cornerstone on Demand as the Chief Learning Officer. Tell us, what is Cornerstone On Demand? I know it's a talent experience platform, but I'm sure a lot of folks are asking, what does that mean? And why was this such an interesting next step for you on your career path?

Yeah, first and foremost, I've known Cornerstone since, oh gosh, 2003 when it had a different name at its startup, Cyber U, I recall. So I've always been had certain levels of familiarity with the company as it grew, became more and more popular. And I've always been somewhat of a geek, for lack of better words, related to this thing called learning technologies. So I've always been very familiar with the company. And interestingly, when I came on board at Novartis, where Cornerstone was already implemented as the learning management system, I got to know the technology, its value, its impact, as well as the company in a far more detailed and wonderful and granular way to a certain degree. Granular in the sense of, you know, we really needed to make sure that we were looking at our learning platforms at scale and making sure that we're always thinking about as modern approaches. And it's not about always being the cool, shiny, you know, corporate learning entity in the block, but to stay competitive and to think about skills and to think about data and now thinking about AI and so forth, how do we really make sure that we're always on that cutting edge? So in a way, that's how I think about Cornerstone, right? Is really providing those, those human performance and worker development and building one's individual personal career platform in a variety of different ways using modern technologies, as well as having a strong ecosystem broadly in terms of, oh gosh, there's over 7,000 customers, over 100, 203 million learners that leverage and use and benefit from Cornerstone's applications. The other side of your question too, which is, I think super fascinating, is so I've never worked for a, a vendor per se, and so I had followed Cornerstone as I mentioned, for many years, Michael, but it wasn't until I was at Novartis that I got again a lot closer and I kept on mentioning it to myself as to her in terms of my own career aspirations, there's that company I want you to win. In order for me to guide you to wind, can I better influence from a customer's perspective where the company might be, might be headed? So can I provide any advice? Can I provide any use cases? Can I provide any reassurance that looking at it from a client's lens, for which I held for three years plus, how can I help the company? And the last thing to that too is given the scale of Cornerstone, can I reach far more people than what I could have done in my prior jobs? Google when I left was around 90,000 Googlers. Novartis when I left was about 110,000 Novartians. But if cornerstones reach is over 100 million and if I can perhaps provide a little bit of benefit related to my background and my experiences and my perspectives, you know, being able to really benefit the world, so to speak, at that greater scale is just really, really exciting to me.

Makes sense. And I'd love you to go a click deeper because you mentioned the applications that Cornerstone brings right. To helping companies on that journey and influencing those 102 million folks that you have connection to. What are those sets of applications look like? Because I don't think Cornerstone is providing the learning itself. It's more the platform through which you engage and find the learning and set your goals and things of that nature is my understanding. But, but I'd love to hear more about what that suite of solutions looks like.

Yeah, I think the, the best and easiest way to describe it is when you think about a workers or a learner's journey from hire to retire and maybe even beyond. Where does a learning platform or a talent platform or a build your skills and track that from the right data perspective platform, where does that reside? So we have an umbrella that we call our talent experience platform or TXP and that pretty much encompasses this hire to retire journey or perspective. And then within this talent experience platform or TXP stack there's our traditional learning management system which does provide a variety of different content and a variety of different support, particularly if you're thinking about, you know, the type of compliance training that is required or this other type of record keeping related to one's portfolio, one's transcript and so forth and a variety of other kind of features. But it's your traditional and I think very innovative learning management system. On the other side of this is the, the X in txp. Right. And that's about the experience. And so we were very, very fortunate to bring on board into our family edcast. And this happened roughly a year and a half, couple years ago. And basically this now provides this really nice harmony or complement to one would say the administrative management side of a learning management system or lms with the various experiences that might not be driven per se by the company. Right. Corporate down. It's really how do we build out those experiences? Bottoms up, employee or worker up. So how do we, you know, democratize or actually how do we provide that level of, of control and accountability to a certain degree where the average worker, for lack of a words, they're in a lot more control of their hire to retire journey rather than here's the pathway that the company says you must take? Well, actually, no, I want actually a lot more control out of my personal and professional and vocational pathway. So the learning experience platform, the LXP from edcast, that provides that nice harmony, that nice balance, and then somewhere in the middle that's very journey related, is our version of a talent marketplace or opportunity marketplace as we call it. And this is basically helping, as you mentioned beforehand, you know, how does one think about reskilling or a new opportunity or a new project or a new gig, or how can I trial, right, exactly what it's like to be a data scientist if I'm a salesperson, how do I trial that for two weeks, two months, two months, whatever that might be. Maybe receive some mentorship, maybe receive some voluntary opportunities in between. But those are three predominant aspects of our solutions, so to speak. The traditional lms, the LXP and Opportunity Marketplace. And there's so many subsets that glue all of this together are our skills layer, our data layer layers, our content layers, and a variety of the pieces that really harmonize and glue this all together. The last thing I'd say is a common theme related to what I just described. It's interoperability. We need to make sure that all these platforms within the stack, the technology, the applications, that they all can communicate and share skilled data and learner data and proficiency data and content data across one's journey, rather than looking at a pocket application or a pocket platform from a different provider along the way. So the interoperability is a big piece. And I'd also say there's a really, really important effort related to connectivity and being open. Because the brutal reality is many, many companies, SMB, small size businesses, large enterprises, they may already have something in place or they may want to bring on something totally different to bolt on right to txp. And so we need to make sure that that interoperability and that openness is also built into the program.

Super helpful. And as we shift into our work cycle, the next segment here, I will say we've seen something similar that you just laid out, which is you mentioned how a lot of employees don't want to just do the career progression as the latter has been defined. They're looking to make progress as they define it and they're much more active right now on it and part and parcel on that is there's a big push. My sense is in corporate America right now to really unlock growth and mobility for their current employees and that they see this as really mission critical in some ways and I'd love you to a comment on. Do you see that same trend that it seems that the learning agenda is much more important for companies today than it was maybe a decade ago. And secondly, you know, sort of why is this such a big push and why do they see it as so core and strategic? If you do see this as a big trend.

Yeah, maybe, maybe I can combine that together. So we're coming out of the pandemic where different definitions of work are being required. And let's not go into the work remote versus work in the office thing. I think what's interesting is the pandemic and successful ways of working. We learned so much from that unfortunate situation. One of the things that we did learn was individuals do need to have a lot more control over their work and the ideal state. But thinking about learning and one's individual development, they need to again kind of control that and call it democratization or whatever word choice you want. I think that's just a, a big reality. The other reality too is there are companies that probably over hired and we know some, some names and there's tons of others where now they need to think about, well, work is changing and maybe my workforce is not ready or capable or organized in such a way to deal with this new world. So they need to think about either shifting their folks internally or possibly in a worst case scenario, even letting some other folks go. Then I think the third vector here, the third piece, so to speak, it's all the macroeconomics that are totally unpredictable. I don't care who you talk to. It's not like everybody has a crisp, right, accurate and relevant crystal ball. So I think when you munge all this together for many, many companies, the, the smart thing to do is really to think about how do I develop the people that I already have rather than dealing with a lot of these other unknown factors or uncontrollable factors. So this whole mobility piece and the, then the reskilling across different job roles and different job families versus upskilling, making sure that that one role or that one job family is just increasing their proficiency. I think this horizontal move is actually becoming, as you mentioned, it's a lot more, it's a lot more current, it's a lot more validated and I think if anything it's probably aligned with the individual's need to control their, their aspirations. So if I'm a sales person using that example again, and let's just say I want to be a data scientist, right, you know, I would prefer doing that in the company that I already have been around that ideally I appreciate and maybe identify with its culture, so on and so forth. They got a great team, have a great management, whatever. Well, let's really take care of what's right in front of you now. And so that mobility piece is interesting and then we can talk about maybe in another segment of the show today, you know, what are some of the advances related to new learning technologies that are really helping to support reskilling more so than just vertical, what I call vertical upskilling. So it's a huge, huge, huge opportunities and I think the temperament of society and the temperament of, you know, for profit and maybe even nonprofit companies, it's happening right now. So we're seeing a lot, a lot of cool things that are happening.

So let's go into that, right, like in terms of the technology stack and what's changing and helping companies do that more efficaciously, perhaps more real time on demand. What are you seeing that has you really excited at the moment around sort of the changing nature of the technology itself?

Yeah, I know that we'll definitely get into the, the generative AI topic. I think from a very, from an, from maybe a more simplistic perspective, one of the things that I've seen is a big, big, big trend and it kind of ties to the prior subjects, Michael, about you know, workers and learners having more control, the democratization piece and so forth. One thing that I see is really kicking off and it's not overly, you know, generative AI or AI dependence, even though it can be, is this whole aspect of user generated content or ugc. And the whole intention here, right is you know, if you really want to, for lack of it a words, unleash the expertise or the talent that you have in your company for upskilling or maybe reskilling or maybe just to keep their current state, you want to give that type of recognition or maybe from a knowledge management perspective, you want to capture all that tacit knowledge, that tacit information, those unique insights. I think it's fascinating in the sense that a lot of companies now are really starting to think more about how can I leverage the expertise within my own corporation, my own workers to help build the type of learning or informational or instructional assets to support the growth of the company. So I came from Novartis and Novartis, we deployed a learning experience platform, edcast, before the cornerstone acquisition. And so we were just looking at edcast as a solo opportunity. And because similar to a lot of large science based companies, we Had a lot of scientists, researchers and so forth working at the molecular level to build new medicines. What's fascinating is a lot of these folks had so much expertise related to the science of building phenomenal medicines, it was never really unleashed. And so we had the opportunity to use user generated content at Novartis to identify the right expert, have them dip into. Creating a UGC asset would be as simple as recording something cool in your phone, putting together a deck or maybe identifying some cool paper, then adding your perspectives to it and then how to release that asset. And I don't know the specific numbers, but when I left, the total number of consumed learning hours was far more leaning towards user generated assets from our own people than from other providers externally. And that I think was a huge sign. And this ties into this whole aspect of, you know, we live in a, in a creator society, right? So anybody now can create something pretty darn cool for a variety of different reasons and then possibly monetize it. So we really, really tapped into that. Then the other thing I'd say now thinking about from a gen AI perspective, just kind of high level, then I'll stop because maybe we're going to kind of break it down. But it wasn't until, you know, open API the company, or Open API the company that they released, you know, chat GPT 3.5 last November and then 4.0 just a few months later, this whole thing kind of took off. And now there's a lot of other players in the space. Microsoft, Google, with Google, Bard. And anyway, what was a fascination and what was shiny, it's now real. And so what does it mean to us at least at a high level perspective, from a talent perspective, from an HR and from a learning perspective, you know, it is about providing a better experience. It is about providing a more engaging and adaptive set of learning opportunities for folks. I kind of call that the stuff that learners see, right? Maybe it's the menu of stuff that you would see in the kitchen. So I'm a learner. Here's the stuff I want to do. I want things to be personalized, adaptive, tailored, whatever. And the other way to look at it, which I think is the huge untapped opportunity that I don't hear a lot about in a lot of the AI things that I track has to do with what's happening not in the kitchen per se, but what's happening behind the scenes. I'm sorry, not in the restaurant per se, but what's happening in the kitchen. What's happening behind the scenes? How is the menu and the tactics and the ingredients and the pots of pans also being, are they also being far more matured from an efficiency standpoint, from an operations standpoint, from an automation standpoint. So you've got this really, really interesting blend in terms of the benefits of generative AI for learning and also for other functional aspects, whether it's formal HR or talent and beyond.

Yeah, so let's shift into our third segment on specials and use that window actually as our question into this, which is you just talked about user generated content as a big piece of this, which I think is really interesting because it strikes me that, you know, maybe 80% of the foundation of skills are common across companies, but it's really that 20% that, that special sauce, the cultural, you know, specifics of working in a particular organization that's it really distinguishes and that can get really expensive unless you make it easy for your internal employees to create learning content and learning trainings. But of course, doing that well is really hard. And it strikes me that AI, you couple that with user generated content, all of a sudden you can take the best of learning science, couple it with the know how of, of the folks inside your organization, and create a lot more reps at creating really good modules to help people learn different skills, whether it's horizontal or vertical. We can do both now actually far more easily. Are, are you seeing that right now? Is, is it? Or you know, does that sound right to you? Where do you, where do you expect that to go?

Oh, absolutely. You know, what's, whether it's in the restaurant, you know, learner facing or behind the scenes, the stuff that's happening in the middle. And I think UGC is a really interesting proposition because I think it's happening in the middle in the sense that the learner, the guy or gal in the restaurant, they have the power to build any one of those awesome items on the menu that would have traditionally come from somebody behind the scenes, but now they can use the behind the scenes new areas and functionality of generative AI, such as, you know, doing needs analysis a lot faster when I have no clue about what needs analysis is because I'm a regular quote unquote user or individual that doesn't know the instructional domain or whatever. But now I can do rapid needs analysis, now I can do rapid investigation of what's the type of learning outcome that I should have. Now I can use my access to a skills taxonomy, a skills catalog, or just a skill in general to make sure that we, that we have the ability to identify the right content at the right proficiency level for that, that learning asset that you're building. And then we talk about all the different modality stuff, you know, building really cool videos and building, you know, really cool, you know, photos from scratch or whatever the heck it might be, doing your own audio, creating your own music from scratch. So, yeah, what has been the traditional model and expensive model in many cases where the folks behind the scene, content developers, instructional designers, so forth, they had to go through the art and the science of building something really, really awesome. But it did take time and there's some complexity and then you have to deal with subject matter experts to validate and validate and validate and validate. Well, if you can grab all those different items, everything from, you know, understanding how to design something correctly to validating it with SMEs subject matter experts, but have quote unquote, the machine do that for you, that is such a, that's a, an efficiencies play. But I don't want to send the message that the machine should be doing stuff for you all the time. And at XYZ level of depth or detail, I think it's so important to make sure that there's still the human, there's still humanity involved. Right. Because the machine is probably not going to be correct to begin with. But if you do this thing called smart questioning or prompting, and there's a whole science behind that called prompt engineering, but if you ask the right questions against the first response that the machine gives you, okay, how about this and this and this to validate, you look at the second response. Well, it moved from 60% accuracy to maybe 67% accuracy. You refine, you refine, you refine. Then you meet something that's generally going to be in your ballpark in terms of relevance. So that human interplay working with the machine is phenomenal. There's a great saying, and I'll stop. There's a great saying. Well, it's a great set of questions. Is AI going to replace my job? And the, the saying that I love the most is, you know, is AI going to replace my job? No. But the human that has more skills regarding AI probably will.

And so I, that actually takes me to a question I had a little bit further down the line. But I'm going to bring it up here because it strikes me that there's so many people saying AI is going to replace jobs or it's going to replace functions, et cetera, et cetera. And you know, even back as far as Peter Drucker and the effective executive executive some 50 plus years ago. Right. He said, well, the computer replace management. And I think the clear conclusion is actually it made management more important because it increased the velocity of decisions that individuals had to make on a daily basis. And AI, it strikes me is, you know, could have a similar effect based on what you just described is that the power of the human with the AI tools really increases the velocity, if you will, of information flow, of activity, of efficiency, and creates more need maybe for human capacity and all this, which of course creates more need for human learning and training for people to be able to do this new set of skills and so forth. Are the companies that you're working with, do they see this dynamic? Where are they not seeing it? What, what's it going to take for companies to realize that this learning agenda is actually going to be core, if you will, to their strategic advantage in the industries in which they work?

Yeah, that's a great, great question, Michael. So we, you know, we're, we're, we're deep into cornerstone is deep into really understanding, you know, what's our play, what's our perspective with, with generative AI and all the different AI families and where do we play, how do we win? But ultimately how do we provide even that much more value to our customers or new customers from a prospect perspective? And it's interesting, you know, we, we did a, a survey just earlier this month in June where we surveyed 25 top CLOs and heads of learning within our Cornerstone community and we kind of asked them the same thing. And what's really, really interesting is regardless of their, their region, their location or the company size, one of the things that we found was, was just interesting is everyone is starting to tap into it to some, to some degree. I'm just looking over here in terms of some of the responses that I just happen to have up. You know, a lot of folks are already, you know, close to 25, almost 35% were already, you know, toying with it, playing with it, experimenting with it. So that level of, I guess, accommodation in terms of what they want internally, it's really kind of kicked off. I do think it's also interesting in the sense of people kind of get it in terms of the benefits, but they don't know exactly where to start. And, and the other thing too, I was just, just really, really fortunate to have an article out in Harvard Business Review. Hbr. Really coming back to your question about so where do I start? Where do I play? And this kind of ties back to some of the insights we gathered from some of our key customers. And this was written with a co writer, colleague of mine, Mark Zao Sanders, at a company called Filtered. They do a lot of great AI and data and content focus. But my point is this. GMIT was very simple in the sense of where's the demand? That's like the Y AIs and you compare the demand to the risk. So in other words, if you have something that maybe is of high demand, in other words, you're going to be able to really test and experiment and explore, ideally at scale with a good size base, but where is there less risk? So if you can have something with a high demand with less risk, maybe that's where you should start. Because again, you know, whether it's, you know, chat, GBT 4.0 or the current version of Bard or, you name it, it still ain't there. This whole term about, you know, AI hallucinating, it's becoming a former minimize, but it's still there. So you need to be able to start in an area where there's actually less risk, which I think is the big key here related to this matrix. But you still want to play, we're going to play in an area where there's enough user base, enough data to kind of work with as well.

No, it makes a lot of sense. So let's shift into our last segment of the show. Closing time, if you will get to look a little bit around the corner and sort of wrap up some thoughts here. And the one that I'd love you to talk to, you sort of hinted at a bunch of times around helping companies get started down this pathway, making it easier for them to involve their employees, creating content, all the rest. But I do think it should be said, right, that a lot of companies, they still have this sort of old school mindset, if you will, of, well, if I train them, they'll go somewhere else, right. I'm making them more valuable. I want them coming to me already prepared. You know, I want someone coming into the entry level role that already has experience. Right. You see all those sorts of things. There's this friction in the system still around learning in companies. Do you see that going away? What's the big, you know, how do you talk to companies about that friction and show them, no, this is a good investment. This is going to help you strategically. It's probably going to help you retain your employees, probably going to help you move them into the roles that they want that they're more excited about.

Yeah, you reminding me, Michael, of you Know, Sir Richard Branagh's quote of, you know, what if I train my people and they leave? And his comment was, well, what if you don't train them and they stay? And I think it's, it's a, it's a very reality based scenario is that if you want to stay competitive, if you want to stay loyal to your people, if, if you want to really strengthen your brand from an attraction as well as a retention standpoint, this is a necessity. It's a requirement for survivability, just to be very honest. So how do you get there? Getting back to the core of your question, if there's a, some companies that are maybe a little hesitant, kind of setting aside the two by two decision matrix that I mentioned beforehand, you know, at some point you do need to recognize that it's in the best interest of, of your people to at least experiment and trial and test and prototype and MVP or whatever. Whether it's generative AI, whether it's user generated content, if there's something that you think is worth trying and you think it can be centered around or maybe built around or built by your people, do an experiment. There's a lot of really great, you know, recipe books related to how to experiment with minimal risk and with moderate to maximum controls. And so experiment where you can, you must give it a try. The other piece that I said with that is, you know, let your workers do it. I mean, don't have, you know, management, don't have the folks in the castle, for lack of better words, dictate or mandate, hey, you must kind of do this stuff. No, open it up, do it from more grassroots perspective. But let your folks kind of do that. Then give them the accountability, give them the charge, maybe give them those small budgets as necessary to really kind of take control of that. So I think that's, that's important. And then even when we come down with all this, you know, generative AI stuff, I think using OpenAI, the company who put together chat GPT, I believe the three point, the 3.5 version which was released last November, I believe it's still free. And the cost on a monthly basis of chat GPT 4.0, what's the latest and greatest, I think it's like 20 bucks a month. So whether it's free or 20 bucks a month, there's no reason why you can't go out and just experiment to see what it's all about, ask it sophisticated questions. But remember my comment regarding, you know, smart questioning or prompts, you know, don't settle for the first response. Ask it again. Validate, validate. Look at it from a, you know, a right hand view or a left hand view angle, whatever that might be. But just trial it because a lot of this stuff's for free. In fact, a lot of the, the different kind of, you know, modality builders, you know, bidding, building video from scratch, bidding, building cool photos from text based inputs, building music. A lot of this stuff's free. So you know, experiment, try because the stuff might not be free in the next few months. So definitely take advantage of the timing of where we're at.

Makes sense. Mark, thanks so much for joining us on the Future of Education. Really appreciate you being here and sharing these insights from the corporate learning world and the work that cornerstone On Demand man keeps doing.

Yep. Thank you so much for the invite, Michael, and really excited to join you.

Yeah, you bet. And for all those listening, watching, tuning in, we'll be back. Next time on the Future of Education.