I’m more and more interested in how employees are navigating their career pathways and how they learn to keep up with the fast-changing nature of work. The corollary to that is also how are companies helping their employees stay up to date. Chief Learning Officer Marc Ramos of Cornerstone OnDemand joined me to talk upskilling and reskilling for adult learners and the changes companies need to make to stay ahead of the curve. We also dove into the implications of AI on the future of work and learning.
My favorite comment from the interview? When I asked Marc how he talks to companies about the importance of investing and training their employees. His response? “You’re reminding me, Michael, of Sir Richard Branson's quote of, "What if I train my people and they leave?" And his comment was, "Well, what if you don't train them and they stay?"
As always, subscribers can listen to the audio of our conversation, watch the video, or read the transcript below.
Horn: 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 OnDemand. His name is Marc Ramos. And Marc 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, Marc, thank you so much for being here. It is a pleasure to have you.
Morning Warmup
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 OnDemand, because you've had an interesting career path.
Ramos: 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 back to the US, 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 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, brother and 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 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.
Horn: 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 the 4 and 40 is dead. It's now in the 4 and 4 it's you. 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 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 OnDemand as the chief learning officer. Tell us what is Cornerstone OnDemand? 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?
Ramos: Yeah, first and foremost, I've known Cornerstone since, oh gosh, 2003 when it had a different name at its startup, I recall. So I've always 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 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 corporate learning entity in the block, but to stay competitive and to think about skills and to think about data. And now I'm 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, is really providing 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 102, 103 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 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 in terms of my own career aspirations, there's that company I want you to win in order for me to guide you to win. Can I better influence from a customer's perspective where the company 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 Cornerstone's 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, being able to really benefit the world, so to speak, at that greater scale was just really, really exciting to me.
Horn: Makes sense. And I'd love you to go a click deeper because you mentioned the applications that Cornerstone brings to helping companies on that journey and influencing those a 102 million folks that you have connection to. What do 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 I'd love to hear more about what that suite of solutions looks like.
Ramos: Yeah, I think the best and easiest way to describe it is when you think about a worker's 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 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 X in TXP, right? And that's about the experience. And so we we're very, very fortunate to bring onboard into our family EdCast, and this happened roughly a year and a half, a couple years ago. And basically this now provides this really nice harmony or compliment 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, corporate down. It's really how do we build out those experiences, bottoms up, employee or worker up. So how do we democratize, or actually how do we provide that level of control and accountability to a certain degree where the average worker, for lack of better 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, how does one think about re-skilling or a new opportunity or a new project or a new gig, or how can I trial? 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, 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. Our skills layer, our data 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 piece.
And then 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, SMBs, 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, to TXP. And so we need to make sure that that interoperability and that openness is also built into the program.
Work Cycle
Horn: 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, 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?
Ramos: Yeah, maybe that 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, and one of the things that we did learn was individuals do need to have a lot more control over their work in 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 big reality.
The other reality too is there are companies that probably overhired and we know 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. And 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 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 than the re-skilling across different job roles and different job families versus up-skilling, making sure 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 current, it's a lot more validated.
And I think if anything, it's probably aligned with the individual's need to control 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, 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, what are some of the advances related to new learning technologies that are really helping to support re-skilling 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 for-profit and maybe even non-profit companies, it's happening right now. So we're seeing a lot of cool things that are happening.
Horn: So let's go into that, right? In terms of the technology stack and what's changing and helping companies do that more efficacious, perhaps more real time on-demand, what are you seeing that has you really excited at the moment around the changing nature of the technology itself?
Ramos: Yeah, I know that we'll definitely get into the generative AI topic. I think for me, be 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 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 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 is if you really want to, for lack of better words, unleash the expertise or the talent that you have in your company for up-skilling or maybe re-skilling 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, in 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.
And 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 have 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 one I think was a huge sign. And this ties into this whole aspect of we live in a creator society, 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 OpenAI, the company OpenAI, the company that they released ChatGPT 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, from an HR and from a learning perspective, 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. 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, are they also being far more matured from an efficiency standpoint, from an operation 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.
Specials
Horn: 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 maybe 80% of the foundation of skills are common across companies, but it's really that 20% that special sauce, the cultural specifics of working in a particular organization. That's what 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 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 you seeing that right now or does that sound right to you? Where do you expect that to go?
Ramos: Oh, absolutely. In the restaurant, 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've 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 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 have the ability to identify the right content at the right proficiency level for that learning asset that you're building. And then we talk about all the different modality stuff, building really cool videos and building really cool 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 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's 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 X, Y, Z 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 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, in mood 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 in your play, you working with the machine is phenomenal. There's a great saying, and I'll stop. There's a great saying, well, there's a great set of questions. Is AI going to replace my job? And the saying that I love the most, is AI going to replace my job? No, but the human that has more skills regarding AI probably will.
Horn: And so 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 even back as far as Peter Drucker and the effective executive some 50 plus years ago, he said, "Well, the computer replaced 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, it 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'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?
Ramos: Yeah, that's a great question, Michael. So Cornerstone is deep into really understanding what's our play, what's our perspective 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, we did 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 ask them the same thing. And what's really, really interesting is regardless of their region, their location or the company size, one of the things that we found was just interesting is everyone is starting to tap into it to some degree.
I'm just looking over here in terms of some of the responses that I just happen to have up. A lot of folks are already close to 25, almost 35%, we're already 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 already 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 the other thing too, I was 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, Marc Zao-Sanders, at a company called Filtered. They do a lot of great AI and data and content focus.
But my point was very simple in a sense of where's the demand? That's like the Y axis 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, whether it's ChatGPT 4.0 or the current version of Bard, or you name it, still ain't there. This whole term about AI hallucinating, it's becoming a former minimized, 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, you are going to play with in an area where there's enough user base, enough data to work with as well.
Closing Time
Horn: 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, because you sort of hinted at it 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 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. I'm making them more valuable. I want them coming to me already prepared. I want someone coming into the entry level role that already has experience." 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? 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.
Ramos: Yeah, you reminding me, Michael of Sir Richard Branson's quote of, "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 a very reality based scenario is that if you want to stay competitive, if you want to stay loyal to your people, 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. Some companies that are maybe a little hesitant and kind of setting aside the two by two decision matrix that I mentioned beforehand, at some point you do need to recognize that it's in the best interest 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 recipe books related to how to experiment with minimal risk and with moderate to maximum controls. And so experiment where you must give it a try. The other piece that I said with that is let your workers do it. I mean, don't have 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 a 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 important.
And then even when we come down with all this generative AI stuff, I think using OpenAI, the company who put together ChatGPT, I believe the 3.5 version, which was released last November, I believe it's still free. And the cost on a monthly basis of ChatGPT 4.0 was 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. Just see what it's all about. Ask it sophisticated questions.
But remember my comment regarding smart questioning or prompts, don't settle for the first response, ask it again, validate, validate. Look at it from a right hand view or left hand view angle, whatever that might be. But just try it because a lot of this stuff's for free. In fact, a lot of the different kind of modality builders, building video from scratch, building cool photos from text-based inputs, building music, a lot of that stuff's free. So 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.
Horn: Makes sense. Marc, 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 keeps doing.
Ramos: Thank you so much for the invite, Michael, and really excited to join you.
Share this post