Multiverse, Apprenticeships, and the Future of Work

Welcome to the future of education. I'm Michael Horne and excited by today's conversation with a classmate of mine, actually from college, who is leading the learning opportunities at a very neat company called Multiverse, which describes themselves as. We're building an outstanding alternative to college and corporate training via professional apprenticeships. There's a lot to unpack, I think, in that mission statement. I'm going to do my best to ask questions about that and try to unpack all that it means and all the promise in its approach with one of the most exciting companies. And bring up Elizabeth Barrett from Multiverse. Elizabeth, it's good to see you. Thanks for doing this.

Yeah, it's great to be here.

So let's dive in at the top level. Exactly what is Multiverse and why is it different what you're facilitating from say, you know, if you will, the old mine, your dad's apprenticeship.

Oh, my goodness, what a great question. I think when people hear apprenticeship, they still picture hard hats and things like that. That is not what we're doing. We are doing what we call professional apprenticeships. So this is applied learning in context where it's really important to understand that people are full time employees of a company. It's not an internship. So they're full time employed by a company, seen as a worker like everyone else. And then at the same time they're getting trained by Multiverse coaches through our Multiverse structure in, in context of their job in a very specific area that will result in them having, you know, qualification or specialism or an ability, for example, software engineering or project delivery capability or data analysis or data science at the end of that. So they're not paying for it. They're paying for it with their time, but they're not paying for it. The company's paying for it. They're getting that training, they're not having that debt. And they know for sure that they can do that thing not just in theory but in practice because they're applying it in context and again, again, getting coached. So definitely not your dad's apprenticeship, I would say.

And it's a set of fields that historically people have thought as not being part of apprenticeships. I'm curious, first on the company side, just to start to unpack the solution that you all are facilitating on the company side. Why are they paying for it? What's the value that they're seeing out of this approach?

Yeah, this is, this is a real question. And I mean, the problem that we're solving is one that everyone is talking about, which is how do you have the right talent and skills in your organ for the future? And we know that companies are losing money when they can't analyze their data correctly and they can't make use of better supply chain or better improvements as a result of that. We also know that companies need these skills to be able to innovate and deliver in the future. And what happened during, during the pandemic is it just highlighted and it accelerated that. So suddenly people were saying, oh my gosh, we need to pick up the pace here quite a bit. And so there's really two tailwinds here. One is people just really realizing that that digital transformation needs to happen a lot faster and now. And the second is something that we've always cared about, but which companies care about much more as it's been highlighted, which is diversity. And so we're able to actually bring in excellent people who are from diverse backgrounds and don't look like your typical software engineer or your data scientist, which again, is huge value add. How can you analyze data? How can you provide a service for an entire population if the people doing that don't represent the entire population? So we can meet that need and meet the critical skills shortage. And I guess what I would say is we hear two things from companies consistently and again, this is being talked about everywhere. It's a front end problem and then it's also an everyone else problem. So how do you have the right pipeline coming into your company, but what do you do about everyone in your company as well when the skill set doesn't quite match where the company needs to go? So how do you reskill people? And we do a lot of that as well. We don't think that this idea of one shot of learning at the beginning of your career is the solution. You need to constantly be reskilled. And we've just seen demand go through the roof in the last few years.

It's fascinating on a few levels. I just want to make sure I understand something which is are you actually then screening and finding eligible employees in the front end and how are you doing it such that they don't look like the traditional software developer, that they start to break the mold. Which sort of techniques are you all using to identify promising candidates that might have the aptitudes to be a great software developer? They just haven't had that exposure or time on learning before.

Yeah, it's a great question. So I think that if you think about the amount of time that a hiring manager has and the amount of bandwidth, they just have a limited Ability to screen for who's going to be at the right level for what they need for their job. And that's why people use shortcuts like a bachelor's degree. So bachelor's degree has been seen as a proxy for intelligence, for preparation for all these different things. But we know a few things from the research. One is that the correlation between having a bachelor's degree and being able to do certain jobs just isn't what we thought it was. But also that there's a lot of people who aren't even eligible. So more than more than 2/3 of Latinx and more than 2/3 of African Americans are screened out because of this bachelor requirement, which says a lot. Now what we do, cause it's a great question, is we look for those characteristics that allow people to be successful in the workplace. So things like grit and perseverance, things like the way they show up in customer service, the way that they're gonna work with other people and those raw skills. And we've seen incredible Results. In the US alone, we have a 97.2% retention rate for our apprentices on program that's head and shoulders above corporate training programs or against, you know, college college rates. And our pass rates are at 99%. So we, that that screening does work. We like to say there's not a pipeline problem, there's a sight line problem. How do you actually get sight of the talent coming in? And again, hiring managers just don't have time to do that nitty gritty screening. But we can do that through the expertise that we've built in the technology that we have.

Love that line. It's not a pipeline problem, it's a sight line problem. I want to dig in deeper then into the solution that you're presenting because those pass rates and retention rates are astounding, frankly, relative to what we see not just in college, but across all of the lifelong learning landscape right now. So are you all actually building and delivering the learning modules alongside the work itself? You already said you do the coaching, but is the learning modules and so forth, you all develop that. That's proprietary. How are you making them so engaging and effective?

Yeah, that's exactly right. So that's exactly what we do. So I actually started my career, Michael, you know this, but I started my career as a teacher. And one of the things that I learned really early on is that learning happens forward, but the planning for it, when it's really effective, happens backward. So while if you're a student, you rock up to class, you Know, you're like, okay, I'm going to learn this thing and do some stuff and then I'm going to take a test and then you keep doing that. But if you have a great teacher, a great educator, what they've done is they've started with the end in mind and, and they've cleverly backward plan the whole thing so that by the time you get to the end, you know everything and it's done efficiently and it's done really, really well. So the one of the magical things that we do is we work directly with companies in order to design and plan what needs to happen. So, for example, when we built our data and analyst program, kind of our foundational data program, we work with companies to understand what do they need people to be able to do on day one, you know, in month one, by the end of year one, and we built the whole thing in that way. One thing that I really love about it is accountability. We have real accountability to our clients, to the employers to get that right. And we're hearing directly from them what's needed. So we work back, we plan all of that, Our teams design that content, we iterate it, we keep it up to date. Because, I mean, that's the other problem with traditional training in academia is things change fast. So we're constantly updating our curriculum to make sure that's right. And the really, really important element of our learning is it's applied. So this is not people kind of off on their own learning a thing in theory and then struggling for how to apply it. They are being taught, and then they're being asked to practice it and they're being coached on it and they're. And we check that they implement it and we have a really tight feedback loop between the apprentice and their coach, who's an instructor, but we call them a coach because we want them to have that mentality of coaching, not sitting on the sidelines. And then the manager of the Apprentice, so we know that they're performing in their role, they're learning what they need to do and that progress is happening. And yes, we own all of that. So they're obviously employed by the company, but the company entrusts us with making sure they get where they need to go and we can measure that. So we measure what they're able to do. We measure are they becoming more efficient and what skills do we have? And we can play that back and again, then we're checking it in real time. Some managers are telling us, and we're able to intervene and the last thing I would say is you asked about our success rates. I mean, part of that is because we're so good at tracking individuals. And then our coaches are absolutely phenomenal. So they're all full time multiverse, you know, phenomenal human beings who not just teach what's there, but really listen for what's not being said. Because the reason why a lot of people fall out of education and training isn't just the hard skills, it's confidence. I have not met a single apprentice at graduation from our data fellowship who won't say, I had a moment where I really thought, well, I'm not really sure that I'm cut out for this data stuff. I don't know if I can do it. And their coach said, yes, you can. And they got them through that. So that's a really critical part of it.

That's incredible. I want to come back to that coaching piece because when we talked a month or two ago, it jumped out to me that you have developed an incredible model for supporting learners. So I want to come back to that. Let's stay on the content for just another beat. Which is to say, so essentially you're building digital content. It sounds like that probably there's some commonalities across employers, but then there's also some specific modules or elements based on the specific skill package or things that an individual employer needs, if I'm understanding you right. So there's some general layer and then there's some specific for different companies, if that's correct. So first, first I'll let you confirm that. But second, what are the, what's the profile of employer that you're typically working with and what does customization look like in that context?

Yeah, great question. So I would say there's a lot more common than one might expect. So if you, again, if you need like really excellent data analyst, then there's going to be a set of common things that they need to be able to do. Now they might use different types of packages, they might use, you know, one might be using tableau and other ones using something else. So you, we do take that into consideration. If you think about what's really interesting, for example, about software engineering is that there is a thing about what language they need for their employer. But every software engineer will tell you that you need to be able to teach yourself to learn multiple languages. So all of our software engineers, for example, learn at least two languages and then we teach them how to continue to learn. And we have front end and back end pathways within our program. So there's that optionality. So I would say there is a very clear, clear set of outcomes we have to achieve by client. And then what coaches are able to do is personalize that to the apprentice and in that situation. So every apprentice has personalized objectives that they're working to meet and they can do things slightly differently. That's the general way that we plan things. But again, I think you'd be surprised that the level of commonality is pretty high for most of the stuff that we need. And then there is some optionality.

Yeah, that's interesting. So essentially now that means you're screening on the front end, finding great people, helping them come in, developing them through the content. In some cases, you're upskilling people who are already at the company so that they can continue to find productive roles and contribute within the employers. And then you're doing all this coaching to help make it successful. I want you to go deeper into that coaching model because it was clearly something that stood out when we talked and about how your coaches approach both proactively and reactively, the challenges that students have as they learn.

I would love to. You'll probably have to reign the end because it is, I think, I think it's a really, it is a really exciting model for so many reasons. And I mean, one of the things I think I shared with you is that when I joined Multiverse, like my bar is so high now for what I would work on and I wanted this to be a model that I would want family, friends, you know, anyone in my life to go on and, And Multiverse really is that. So the coach allows for a personal relationship with that apprentice. And there is a science behind all of this. Like there's a science behind the way that we design our programs so that apprentices and coaches build a relationship early on in the program and they're designed so that the relationship is kind of front loaded and then tails off so that apprentices become more and more independent at the same time. Really, the apprentice ramps up more and more on what they can do on their own. Now that coaching relationship's really, really important because again, if you think about the way that, that learning typically works, you're. You're given a piece of information and then there's a delay before you implement it. And then hopefully when you do implement it, you might get some feedback. So again, you know, it's really interesting to think about a university cycle. If you go and get a bachelor's degree, learn some stuff and you'll find out like in three years, if you can actually apply it, you know, in a, in a good context. But even most training that people do, or if you do an online course, there's going to be a delay. So we really close that loop and the coach closes that loop and is able to see right away if that person is being effective and then they can correct that right away and teach them. So if you, if you were to kind of visit one of our instructional sessions, you would see people working through real problems in context, like working through case studies and working through different examples. And one thing I just love is we have this concept of, that we build into our programs this idea of nuance, which is the difference between someone who's good at something and someone who's excellent at something, is that you can nuance it. So if you think about, you know, think about a project manager, you can teach someone how to be a project manager, but project managers who are, okay, they follow a formula. Here's how you engage stakeholders, you know, here's how you do a plan. Project managers are really good. They know what shortcuts to do in certain situations. They know where to shorten things or lengthen things or go deeper. And we practice stuff enough with apprentices and they get enough coaching and that they really have that nuance and that critical thinking. We also build in a lot of reflection and feedback. So one of the things we know is that for people to continue to be successful in their career, they need to be open to feedback, especially feedback they don't like, by the way. And they need to be reflective. And so they, so they build this way of operating in this practice that makes them effective, but then extends into the future. So the type of individual you get who's been through a multiverse program, whether they're existing employee or a new employee, is someone who's going to kind of be highly trained in this model of development as well and expanding that growth mindset, which we know pays dividends.

It's interesting. It also combats the stereotype, I'll say, of the millennial generation and sort of their reaction to that sort of feedback, directly building that competency into the individuals with whom you're working. Something else that strikes me from listening to this is really these coaches are acting as tutors in a mastery based learning system. It strikes me where they say, you're still not quite mastering this. We're not going to let you just sort of skate by with a 70% or something like that. We're really going to develop you from that. Novice learner to an expert learner, as you said, and make sure we stick with it. How much of the intentionality is there, you know, of this mastery based approach as opposed to the traditional, traditional or conventional school based approach that's time based or credit hour based, but not focused on learning?

Yeah, I love that question. So I think a lot about this. So we have three pillars of our learning. One is that it's applied, so it's all about real world applications, about real world context. It's about that accountability for what the person can do and what companies need people to be able to do in the future. The second one is that it's personalized. So again, as an individual, you're having a personal, personalized experience that works for you, meets you where you are. And the third one is actually valuable. And it's really important that the, that the learning itself is valuable and results in, you know, in someone being able to do something in the real world. So when I think about valuable, it's exactly the opposite of seat time. It's not about, oh, I wrote out this situation and I, you know, showed up for all these lectures or I showed up for whatever, now I can take do it. We want to know that they can do it. And actually one of our principles in our assessment process is as many of that as is needed. So it's not about, you know, again, it's not a gotcha system. It's about we'll train you and we'll support you until you get there. And we have amazing data tracking. So one of the things that we did in the last two years is we built an amazing data system to track the individual outcomes and the learning and a lot of indicators for all of our apprentices so we know where they're struggling and why. And again, sometimes it's learning and sometimes it's not. But it allows us to catch things really, really early and then to group people or to support them further to get under the root cause of what's going on. It's exactly what you said. It's a master based system. It's really not about checking boxes. I mean, ultimately we want to know if people are able to do stuff in context. And again, I love that because there's no distance between us and employers. Our clients don't wait for a year to ask for more apprentices. The majority of our clients after a quarter say, oh, this is working. We want more right away because they're seeing it in practice and they're seeing the value add. Wow.

I mean, that's stunning because to have a feedback loop around learning that quick answers the question of ROI in ways that I think aligns both short and long term, which is one of the big questions that at least I often get with training programs, is how am I going to demonstrate that value? I want to turn in our time now to that traction that you're seeing in the marketplace. Obviously, you all recently raised around, got a gaudy valuation of well over a billion dollars. So that got a lot of attention. What's the real traction on the ground? Let's start on the Europe side because I want to talk a little bit about those dynamics before we talk about.

The move into the U.S. i mean, it's astronomical. I will say that we're backed by really the best venture capital venture capitalist in the world. I mean, you can't get better than the folks that we have that sit on our board, folks like Index Ventures, Lightspeed, General Catalyst and others. I mean, it's remarkable. And during the pandemic, we actually were told to lower our targets and we didn't. And actually every other company that I know did. And we actually significantly outperform those every year. We set really ambitious targets and we outperform those. So that's a. So our valuation is really a reflection of the fact that I don't think there's any other company growing at the pace that we're growing, you know, at Series D. And we're talking about, you know, people who are working with, you know, the best SaaS companies in the world and are still saying, you know, this is, this, this doesn't happen. So. So the pace really has been pretty insane. When I, when I joined Multiverse two years ago, we had about a thousand apprentices. Now today we've got 10,000. And that's just, you know, accelerating really, really, really fast. In the uk, where always talked about, when we talked about when you hear about apprenticeships, it's kind of becoming synonymous with Multiverse. And we're working with all the major employers you could possibly expect. And then the US is a really interesting story because actually the problems that you see are more acute. So, so when you look at things like student debt, I mean, it is a much more acute problem in the US when you look at a problem like diversity and access to jobs. I mentioned those statistics about screening out Latinx and African Americans. That is, you know, that is super, super acute in the U.S. so, for example, you might have heard of Oneten, which is a really impressive organization with a mission to have a million black professionals in, in high performing jobs in the next 10 years. We are a partner to them to actually make that happen and are working at pace to do that. We work with the likes of Cisco, Verizon, Google and are talking to pretty much every board that you can name and that pace has been very, very fast. So our valuation in the round that we just raised reflects the immediate traction and continued success that we've had in the U.S. market, which, you know, really isn't going away. The, the, you know, the urgency is there and just to be able to solve that problem, I think is, is really important again for people coming into the workforce, but then again keeping that workforce relevant.

I wonder if you'd comment a little bit. A lot of people when they look at this problem and you just started to answer that there is traction in the US because you are really solving a pressing problem that doesn't need government action yet. Nonetheless, I think people looking at this space historically have said, gee, apprenticeships have been way more present in European countries than in the us And I'm just curious, sort of your perspective structurally, why that is, why it made sense for Multiverse to start over in the UK and Europe first before it came to the us Sort of just reflect on the differences structurally and how maybe those are fading away or if they are not, what lessons should we draw from that?

Sure. So I think there's a few things. Definitely it's more, the apprentice model is more intuitive in Europe, but one thing I would say is you still get articles in the FT about apprenticeships with people with hard hats and neon vests. So there's still, even here, there's still work to be done. I'm sitting in London today, but I'm often not here. And so I would say that's one, that's one thing, but I'd also say, you know, you have a more government driven model for a lot of things in Europe and in the UK than you have in the us. So the British government recognized, you know, some time ago that the university system wasn't getting the whole job done and there needed to be alternative pathways. And they said, okay, well how do we, how do we address the fact that a lot of people are being screened out of universities and again that universities are a bit too slow and how do we solve this massive job shortage and the skills issue? So the government was looking at this crisis around software engineers, around data folks and others, and saying for us to stay competitive, we need to address this. And they created a mechanism that supports the funding of apprenticeships for companies where companies basically pay their own money into a pot and then use that to fund apprenticeships here. So the government has accelerated that process here to get things mo. Like the innovation of the American business community. Like nothing. Right? So if you want to solve a problem and you want to do it well, the American business community is going to figure out a way to do that. And what you see, and what you, what we see in the US is the ability to measure very tangibly that you talked about, return on investment. So if you look at, we talk to companies all the time. We look at the people that they're recruiting for the gaps that they have in their current workforce, what that doesn't enable them to do, and then how much they're paying, for example, recruiters and external recruitment fees. And the maths are really simple. So of the, you know, of the, of the conversations that we had in the last quarter, look, of every conversation we had in the US we presented business cases to our clients, we won 92% of those bids. Right. So it's very easy to show what that progress looks like. And then, and then again, once folks are in, we can measure the contribution in terms of skills and efficiency. But I mean, we're talking about, we're talking about significant money here. We're talking about hundreds of thousands of pounds of dollars, for example, for an FMCG company that we're speaking with, where that was their loss last year by not being able to analyze their data properly and act. So, I mean, this is a pretty clear return on investment. This is, you know, this is not like a nice to have. This is, this is urgent. And the final thing I would say is, again, when it comes to diversity, there are just whole areas that were written off. Like, I don't know how many conversations you've been in, but I've been in many where people say, oh yeah, our company's super diverse, I mean, except for the engineers. And then that's accepted. Well, yeah, yeah, sure, the marketing team is diverse, but not the engineering team. And, and, and no one's been able to crack that. So if, if, if, if Amazon was to hire every single computer science graduate this year in the US they would still have a shortage of the number of engineers they need to hire. Right. Then you pile diversity on top of that so that, so that the ROI is very concrete. This is, again, not a nice to have.

No, it makes a ton of sense and it makes it a problem that I think will be more durable in its solution than on the other side. Because that pain is felt so much. And at least my read is that the supply demand dynamics, at least in the market, are not changing anytime soon. There's a shortage of skilled people for the roles that we need. There's demographic changes that are going to exacerbate that I think in many cases and a lot of growth needs. In our remaining time, I want to ask two more questions. One is from, is from one of our viewers and there have been a number of comments trying to get in touch, I think with Multiverse for partnerships and the likes. I'll let your team comb that afterwards. But this is a question of how Multiverse's lessons learned work or apply to the tech digital versus sort of more blue collar frontline jobs. And I guess the question there is, you know, how expansive, right, in terms of field you've named a lot of digital skills that you all are starting to work and make the apprenticeship model work in. How extensible is it? Where are lessons learned and where do they transfer across different fields?

Well, it's interesting, I would actually say this is one of those places where the blue collar fields are way ahead. So, you know, apprenticeship models are obvious in that field and they've been around for a long time. In fact, you know, when I talk to people about this, people who themselves were trained through apprenticeships, you know, in those kind of, in those kind of careers, they're always saying, well, yeah, that's how I was trained. You know, it makes a lot of sense. So in lots of ways we're actually learning lessons from them and applying it and then applying it in the professional context. But there's the kind of key principles hold, right, which is you have to be able to do things in context. You need the right kind of training and mentorship to be able to do that. You need a structured program to be able to do that. And ideally, again, we really believe that people shouldn't go into debt to get into these kinds of careers, especially where companies really need it.

Yeah. And that earn and learn component of what you're doing I think is critical. Last question for me is sort of projecting forward because it's on your website you all have named that this is an alternative, maybe even a replacement placement to the traditional college pathways that we've known and seen. How do you all think about that internally? If you project 5, 10 years forward about what, you know, the role of a multiverse or other ecosystem players like what you're doing might mean to the future of learning vis a vis college?

I can't Tell you how fast this conversation is shifting. A year ago people were saying things like, gosh, I wonder if, you know, people would consider taking people without a bachelor's degree or how, how would there be credibility that that's done, you know, that that conversation is, has switched. And instead people are saying, we know that we need something other than a bachelor's degree to judge people. You know, how do we do that? And that's where our admissions machine that we were talking about, you know, is so, so powerful. So, so when I project into the future, I imagine people are, instead of saying, you know, where did you go to school? They'll say, where did you train? You know, I project that people will do multiple apprenticeships throughout their career, that people there will be, you know, much more hands on way of learning. And what's really interesting too is I feel like there was kind of a trend toward technology and education technology, which wasn't wrong, but it sort of boiled people down into a set of a checklist of skills which is, oh, if you can do these 20 things, then you're going to be good at your job. And I think you're going to see a major shift away from that. You're going to see people saying we need technology for content and we need to kind of expose people to things, but actual learning still needs to happen between humans and how do we get that to scale? The final thing I would say is there's been a conference every year since really the MOOC era that's about learning at scale. It's called the Learning at Scale conference. Name is what it does, what it says, but it was really about all these exciting things. And education technology this year was about blended learning. Very, very, very kind of interesting shift to say how do you, how do you combine technology but then combine other things to have learning be highly effective? And that's what we're doing. So I don't, I, I would be very surprised and I actually don't think it's the right thing to think that universities will go away. I think they're very stable and important institutions. We're just using them for the wrong thing. We're expecting them to be our employment feeder and using them to do all of our skills training. And that's not what they're for.

It makes a ton of sense and it's a good way, I think, of reframing because as you know, institutions and organizations are really good at doing what they're built to do and they're not good at doing things that you task them to do for which they were never built. So I think it's a good way of reframing. Definitely something to keep an eye on, though, the continued growth and evolution of what you all are doing as you come into the US Market and continue to expand and change the nature of learning for work. Elizabeth, just really appreciate you being here today.

I love the conversation. Thank you. It's been really fun. Obviously, I'm really passionate and just excited about what we can make possible.

Terrific. For all you who've tuned in, keep an eye out for more on this on the channel, the Future of Education. And I will make sure that Elizabeth sees the comments in here so that she or others can engage where it makes sense. So thanks so much for joining us again.

Thank you.