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    Do Universities Need 2U To Create Digital Education?
    03 Mar 2020Cold Call Podcast

    Do Universities Need 2U To Create Digital Education?

    2U, an online program management provider, believed it was the strongest partner to enable the digital transformation of universities by enabling them to offer a variety of courses to a new student profile. Professors Karim Lakhani and Marco Iansiti discuss the case, “2U: Higher Education Rewired,” and connections to concepts in their book, “Competing in the Age of AI.”
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    Brian Kenny: A Google search for disruption in Higher Education yields 75,300,000 results. A quick scan of the titles can be a little disconcerting for someone like me who works in higher education. Forbes.com says this will be the biggest disruption ever in higher education. Bloomberg News says, “Future of Higher Ed uncertain in age of disruption.” Even Harvard Business Review fuels the flames with, “Six Reasons Why Higher Education Needs To Be Disrupted.”

    There seems to be a lot of agreement on the notion that higher education is ripe for disruption, and that's probably a good thing. After all, colleges and universities have basically used the same model since the University of Bologna, the oldest in the world, opened its doors in 1108. But what exactly does it mean to disrupt higher education? What would it look like? And will we know it when we see it?

    Today on Cold Call, we'll discuss Professor Karim Lakhani's case entitled, 2U: Higher Education Rewired. I'm your host, Brian Kenny, and you're listening to Cold Call recorded in Klarman Hall studio at Harvard Business School. Today we're doubling down with not one, but two Harvard Business School professors. Karim Lakhani's research examines crowd based innovation models and the digital transformation of companies and industries. He is also the founder and co-director of the Laboratory for Innovation Science at Harvard. Marco Iansiti's research examines the digital transformation of companies and industries with a special focus on digital ecosystems and AI-centric operating models. Together, Karim and Marco lead the Harvard Business School Digital Initiative and they are co-authors of the recently released book, Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. That sounds very ominous. Thank you both for joining me today.

    Marco Iansiti: Thank you for having us.

    Karim Lakhani: Thank you.

    Brian Kenny: Great to have you both here. For our listeners, it's late on a Friday and if we get a little punchy it's because it's late on a Friday so... And I'm really looking forward to talking about 2U and full disclosure to our listeners, 2U is a company that actually Harvard Business School works with. We partner with them and so we know you obviously have had an opportunity to write the case kind of from the inside out of experiencing them firsthand. But the case allows us to sort of step off into the ideas that are in your new book and I just got a copy of it yesterday. I've only been able to read the first chapter, but I can't wait to get to the rest of it. So congratulations on the book.

    Marco Iansiti: Thank you very much.

    Karim Lakhani: Thank you.

    Brian Kenny: Karim, I'm going to start with you. You're the author of the case, co-author of the case. Can you just start by telling us how does the case begin? Sort of set the stage for us.

    Karim Lakhani: So the case is really set at a meeting of 2U, actually where I was present, where they're presenting their vision of how this company can cooperate with universities, and bring them online in a scalable new way. And the dilemma for them is they're not trying to compete with universities, they're trying to help the universities. But it's not clear if the universities want their help. And I think that's a very interesting dilemma because it's not as if they're going to create 2U university and try to compete against Harvard or Harvard Business School or Stanford or anybody else, but really to sort of drag us into the digital age. And there are mixed reactions from their customers about the viability of this approach, as well as the viability of bringing in a much greater sense of analytics and data-driven decision making about the choices of courses, how you enroll students, how you deal with them and how you graduate them and so on.

    Brian Kenny: That's scary talk in a university setting.

    Karim Lakhani: Universities have been highly decentralized and we do our own thing and as even ourselves have tried to go online, those are big expenses and not every university can make those expenses of course. But then a third party telling you what are the right courses to develop based on a data-driven approach, the right students to target and try to attract, that sort of cuts to the core of what other people in the university might be trying to do in a non-data-driven approach because they think they have the intuition to figure all this out. And I think that's where the clash sits.

    Brian Kenny: So the opportunity that they see then is to sort of, as you said, be a partner to universities and not replace them. There have been private universities that have sprung up and tried to compete. That's not what 2U is about.

    Karim Lakhani: Not at all. I think what they recognized is that universities have a brand, have a reputation and have a mission. When I talk to the founders and the executives of the company, their view is we want to help your mission, we want to help your mission for pedagogy and for reaching students and having impact with students. So they really see themselves in that fashion. But I think the question that they are faced with is that their approach is so different at the core of both how courses and programs get developed, highly data-driven, highly analytical, based on multiple data sources and so forth coming at them. But then the second important part after you're designing the courses, how do you attract students? And that too is highly digital. They don't create brochures for programs. They don't do mailers for the programs. It's LinkedIn, Facebook, Twitter, Instagram, Snapchat marketing at scale. And again, that's something most universities are not prepared to undertake or even understand or even attract the talent to make that happen.

    Brian Kenny: Marco, you're quite familiar with 2U as well. How radical is this now from your experience having been in a university setting for a long time on the academic side?

    Marco Iansiti: It's a classic, right? It's really a classic. I mean we see this kind of as an example of a much more general trend. I think that in, across the economy, whether you're in the education business or in the automotive business or in the financial services business, you're starting to see the emergence of two fundamentally different types of companies. There are traditional organizations of which Harvard Business School is, for better and worse, one of them, right?

    Karim Lakhani: Harvard University, I mean-

    Marco Iansiti: Harvard University, or any kind of university. And we're not as old as the University of Bologna, but we've been around for a long time.

    Karim Lakhani: I like to joke that we're the oldest corporation in America and we predate the U.S. Republic as well, by 100 years.

    Brian Kenny: Harvard University does.

    Karim Lakhani: Harvard University does.

    Marco Iansiti: And we predate the city of Cambridge as well, which is a subject of much discussion. 2U is a recently started organization and from the perspective of a student, it's kind of interesting. You can imagine someone wanting to learn something about the business of AI or something about machine learning or something about statistics and they really fundamentally have two different options. One option is to go to an organization like 2U or be found by an organization like 2U, who then helps deliver the content that maybe prepared by any ecosystem of partners, in this case with Karim and my collaboration with them, it's through Harvard Business School. But fundamentally 2U manages the relationship with the student in a bunch of different ways. Using lots of data, lots of algorithms to personalize the messaging and make sure we get the right students and all that kinds of stuff. In some ways it's helping the universities. But in some ways it's also threatening the traditional model of the universities because all of a sudden the students aren't necessarily coming to Harvard Business School for seven weeks or for two years anymore. They're getting their content primarily online. A lot of it is videos. We still have some cases, thank goodness. So it's not a complete competition, but it's certainly also not a complete... I mean it is a collaboration.

    Brian Kenny: It's a big disruption.

    Marco Iansiti: It's a different model. It's a different business model and it's a different operating model.

    Karim Lakhani: Absolutely. As Marco's saying, I think the thing that's so interesting in our interactions with them is the program we launched with them, which is the Harvard Business Analytics program, the Harvard Corporation approved that the program would go for approval in August of 2017, we had enrolled students ready to go March 2018. That's like light speed at Harvard, because we were able to piggy back on their processes and launch and attract the students, target the students, get them enrolled and get them going and also work with ourselves and our colleagues at the Engineering School and the Faculty of Arts and Science to generate courses in that same amount of time. It's a different beast than what we are used to.

    Marco Iansiti: It's a different kind of organization. It's a different process. It's a different timescale. It's a different structure. It's a different approach to technology. It's a different approach to data.

    Brian Kenny: Radically different in a lot of ways and counter frankly to the culture of a lot of Higher Ed institutions. I mean the case gets into some of the challenges that they faced when they were trying to get started and trying to build partnerships with universities. The culture doesn't easily accept something like this.

    Karim Lakhani: No, I mean I think part of what makes universities succeed is, I tell our Dean this, we're slow metabolism creatures, maybe of the order of whales, and change is slow and hard and we've done well because we haven't changed as fast. But in today's world, I mean I think we still need to change and adapt. I mean I think society is asking more of the universities, more of our education missions and pushing us to be more relevant. These guys present an opportunity for universities to sort of think about, how do I expand my mission and how do I expand my reach? How do I expand my scope? Yet do it in a way that is modern and not based on the fact that I need to bring everybody to my campus every single time for an education interaction. And I think that's I think where the culture clash can happen because they're a for-profit company, they want to make money and so they're trying to be efficient in dimensions that we may not care about being efficient in, but they have to be in order for their profit mission. And us as HBS professors, admire the profit mission and think that's a good idea.

    Brian Kenny: And it's not just us, they work with a lot of schools.

    Karim Lakhani: Oh absolutely.

    Brian Kenny: They are working with medical schools and others.

    Karim Lakhani: Absolutely. And business schools elsewhere too. I think that's very interesting. And as Marco was saying, you will never know that it's 2U that's marketing to you. But in fact, that's who is doing it. And 2U finds you. We just had a graduation of a program and all of them said, " Yeah, you guys found me."

    Brian Kenny: Remarkable.

    Karim Lakhani: And that's-

    Brian Kenny: Complete change. That's turning it completely on its head.

    Karim Lakhani: As used to what we are used to, which is people come to Harvard because of the brand and they seek us out. This is the other way around. They find the people based on their social media presence and their activities to say, we think this program is the right one for you.

    Brian Kenny: So let me ask you this, how does 2U help us to tee up the big ideas in your book? What makes them a good example?

    Marco Iansiti: From their perspective they're representative of a whole generation of companies that is targeting traditional problems, traditionally use cases, traditional needs but solving those needs in a fundamentally different way. Take Amazon, they interact with consumers in a fundamentally different way than the way the retail used to be done. In fact, the whole retail sector has been transformed in all kinds of dramatic ways. Trying to emulate what Amazon has done has induced Walmart to change and invest dramatically billions of dollars in new acquisitions and digital platforms and technology and the whole idea is that the traditional operating models that companies have had to serve consumers in retail and other industries, have been around for a long time. We've built organizations that have a bunch of managers and a bunch of workers and everybody kind of works together to serve the consumer. Whether it's a grocery chain or whether it's a bank. Today we have a whole new generation of organizations that essentially solve similar problems like I want to buy a book, but what goes on behind the curtain in terms of what delivers that book or how the organizations find the consumers in the first place and target the messaging to them is done fundamentally differently. The way that Amazon works has almost nothing in common with a traditional retailer. Their processes are embedded in software. Things like product planning or pricing or forecasting are done by algorithms. All of it rests on a foundation of data where they know enormous amounts about individual consumers, their prime customers and so on. And then can suggest, recommend products for those customers they can solve problems, they can encourage them to buy new things, basically solve a variety of problems and do so in a way that's more efficient and in many ways more effective than traditional businesses. Also, when you have a digital business like Amazon, they can scale at a rate that is much faster than the traditional retailer might have been able to scale. And because fundamentally what the scaling is driven by is software. So you have a process that's serving up all that the consumers want and running the front end and the pricing, the webpage and so on. It's running the back end, the supply chain and all that stuff. And so in some ways selling a million books is not that much harder than selling half a million books and selling a billion books is really not that much harder than selling a million books. It's in fact, in some ways the scaling process is much easier.

    Brian Kenny: Your book talks about an AI Factory. That's one of the principles that you start off with. What's an AI Factory?

    Karim Lakhani: Fundamentally, the view of the AI Factory is that we're going to be making predictions about some future state and we need data to come in and process. So we need a data system, a data pipeline that can absorb data with proprietary data internally, but also loads of external data. Put it through pretty much sort of off the shelf algorithms that will help you say what is it that's going on and then create an infrastructure to prioritize and make available those predictions so some action can be taken. So the example I will sort of say is, imagine you go to McDonald's and you are trying to order some hamburgers and other assorted happy meal types of things. Well the AI Factory in McDonald's by the way, is going to look very similar to an AI Factory at U.S. Steel. The AI Factory in the U.S. Steel plant will be the same. It will still have a data pipeline, will still have algorithms and will still have an infrastructure. And all of them will work in the same way. Our claim in the book is that all organizations will need to develop and get good at building an AI Factory so we know what are the future states that we need to be thinking about and automating those actions as towards them.

    Marco Iansiti: Think like Amazon sits on top of an AI Factory, right? So the stuff that interprets the massive amounts of data that they actually have and makes recommendations, does the forecasts, figures out what's going to happen in supply chain, it's all a bunch of data-driven processes that are enabled by this foundation of data. Take it back to 2U, it's really the same thing. I mean 2U has a bunch of data about individual students and what they're doing, what they're thinking about coming from the data they get from LinkedIn or Facebook or whatever it is. That's how they can target all those students. And in the back end they've got a marketplace of products, just like Amazon does, that is plugged in to the front end that the students come and visit and so when I go out there and see, I think I might be interested in learning about the business of AI, then 2U has got the right data to make the match or even the other way around, they can make recommendations. I think Karim based on... You might like this Harvard Business Analytics Program, which just happens to do all the things that you really want, which I know because I know a lot about Karim. Right? Based on my data factory and all of that stuff.

    Karim Lakhani: And just to build on an example of this, so we've become obsessed with Amazon recently because our book's on Amazon. So then you're always looking at, well what the sales figures are but what's interesting is like the price that Amazon is charging for a book keeps changing, right? There's a list price and then you see them discounting and there's no manager sitting there going the Iansiti-Lakhani book, well these next five minutes we're going to make it $18, then we're going to make it $24, then we'll make it $28, right? That's all algorithmically driven. They have demand data from customers. They know what other books are being bought and then they are basically changing the prices on the spot, which is incredible. So that's the AI Factory, right? The AI factory is making some prediction about the likelihood of me buying that book as the price is varying and changing.

    Brian Kenny: It sounds like the magic here is for the firm that has created the AI Factory, right? And then obviously there are many businesses that exist that don't have the capacity to build their own factory. So they have to find one to plug into. Is that the idea?

    Marco Iansiti: That's kind of the quandary that the Harvard Business School is saying, do we work with 2U, who has got this great data foundation, the technology, the AI Factory, all those kinds of things and they can bring us students but hey, they're going to take it a big cut of the revenues. Same thing. Are you going to sell your products on Amazon, which can dramatically increase the revenues that you have, but then goodness, they're going to take a nice cut of the profits that come out of it. This new generation of organizations is cutting across, whether it's Amazon, whether it's Google, whether it's Ant Financial in China in financial services, whether it's 2U in education have similarly kind of changed the model and offered, from the consumer's perspective, a way to solve their problem. But doing so in a fundamentally different way and the traditional companies like the Harvard Business Schools of the world or the banks in China or the merchants that are on the Amazon marketplace are trying to figure out, is it better for me to play with these guys or should I just try to do it on my own?

    Karim Lakhani: Another good example actually is we have this case on Marriott as a company and the evolution of the company. And one of the questions I ask students in the case, because of course you talk about Airbnb as well, is should Marriott list its rooms on Airbnb? Is Airbnb a competitor or in fact a complementor to you? And that's a fundamental question that even Marriott is faced up with because they're trying to create, on a high end, an Airbnb competitor. But it's like the scale of the AI Factory at Airbnb doesn't even compare to anything that Marriott has and even their investment choices of where you invest in technology versus where you invested in real estate aren't comparable. And so then the question becomes, if I'm Marriott, if I have these boutiquey hotels and funky rooms, should I actually just list them on Airbnb? And by the way, they will charge me less money than booking.com because Airbnb is like in the 5-6% versus 30% on Booking.

    Marco Iansiti: Or if I am to Harvard Business School and I have this big bunch of executive programs, should I put more of them up 2U and see if I can make the match in different ways and match their model. And you see it from industry to industry to industry. You have these hub companies or these platforms, these sort of these digital things that are built on all this data and so on. They can do a more effective process of actually aggregating the data, targeting consumers, personalizing the offerings, figuring out who the right people are and then delivering the product that are essentially providing an alternative channel for a lot of traditional organizations. And then it's almost like this Faustian thing, do play with this potential devil, I'm not saying they are at all, or do you go at it your own way without having the scale to necessarily be competitive?

    Karim Lakhani: Well, one of our beliefs though is that, I mean I think all organizations will need to sort of start to develop a strategy around their data. Develop a view of consolidation of their data. A single point of view on their data instead of the silos that have sort of persisted in the past. Even if you're not going to be a full Ninja AI Factory, you still need to be able to plug into the other factories and that will still require you to become good at those problems.

    Brian Kenny: It's so hard though, right? Where do you even begin if you're one of a large organization that's been around for a long time and you've got all these different pockets of data that are living everywhere across your enterprise, how do you even think of that?

    Marco Iansiti: Well I mean the good news is that technology is straightforward. So the technology in many ways is the easy part. It's all available on the cloud, there's a bunch of big vendors that can essentially give you an AI Factory in a box if you like. A lot of the individual pieces are easy to get. The capabilities are the next thing, and those are hard because you have to hire different kinds of people, different kinds of skill sets. But the number of analytics graduates, data scientists out there is increasing rapidly and organizations sometimes have a hard time hiring this kinds of people, but if they do it right, with rethinking incentives a little bit and rethinking compensation maybe along those lines, they can do it. And that problem is also solvable by many of the large traditional players. The thing that's the hardest part is that you kind of have to restructure the way the organization works and what is the traditional vertically oriented siloed organization where everybody's protecting their own turf, with their own individual technology, with their own individual data, all of a sudden has to behave as an integrated piece.

    Marco Iansiti: You want to have one AI Factory, you don't want to have 17 different AI Factories with data scattered in the same company, right? Where, when you go and visit one of your customers, you have to bring 17 different printouts, one from each of the different departments that tells you what you're doing with that specific customer.

    Brian Kenny: That defeats the purpose, right?

    Karim Lakhani: But it's hard because technology is asking for integration and horizontal connections. Most of our organizations are vertical silos and so we now need to do organizational change to adapt to what the technology is asking for and that's really hard. Right? And that's in many ways-

    Brian Kenny: That's the hardest thing.

    Karim Lakhani: Yeah, and that's the barrier. So I mean our view is that the technology, there are plenty of templates and roadmaps on how to do this, but I think the big challenge is actually the org change and to change the architecture of the organization to match the architecture of the technology.

    Brian Kenny: One of the things your book talks about is the competition collision. And I thought that was an interesting concept too and we've touched a little bit on it here, but I'd love to hear more about how do you define what that is?

    Marco Iansiti: I think all of these examples that we've talked about 2U and HBS or Amazon and the local merchant or Ant financial and one of the more traditional banks in China, is an example of what we call a collision event. And collision as we define it is when you have essentially the same use case. I want to take a machine learning course or I want to buy a book. That use case can be solved now by two fundamentally different kinds of organizations that work in fundamentally different ways. If you look at a traditional bank is a siloed, structured, organized in a certain way as they have been organized literally for hundreds of years as the Harvard Business School. They can solve a problem for the consumer, a very different kind of organization, whether it's Ant financial or 2U or Amazon can solve that same problem, but will do so in a fundamentally different way. More scalable, is able to generate much greater scope, this organizations can serve all kinds of different services to all kinds of people and also is able to change and innovate more rapidly than traditional organizations are able to do. The old model has been around for hundreds of years. Organizations have been built in silos for hundreds of years. Organizations have-

    Brian Kenny: For good reason.

    Marco Iansiti: For good reason because you try to manage human complexity and try to focus efforts into smaller groups and so on. If your organization is run by networks and algorithms, you want to organize it differently to make it work well.

    Brian Kenny: I'm going to project what I think listeners might be thinking right now, which is they're hearing that you can take people out of this equation and it's much more efficient and scalable and it learns by itself and what does that mean for jobs and the things that people do.

    Karim Lakhani: Just thinking about this in the first case, right? Which is a company like Ant financial has 1.2 billion customers. They have processes where if you want to open up a bank account, they say it takes you three minutes to fill out the application, one minute for approval, zero human interaction. Because there's no way you can think about offering loans to 1.4 billion people with a human based system or you think about Amazon, I think their SKU count is somewhere in the billions, right? There's no way you're going to have enough managers to sit there and think about the pricing structure. So the scale, the ambition of scale that these organizations have is such that you have no choice but to go to the algorithms.

    Marco Iansiti: You still have people in the organization, they're designing the systems and they're also doing all the tasks that the algorithms and robots aren't able to do yet. The center of the organization essentially is a bunch of algorithms and it's a bunch of data. That's a little bit our predicament right now because I mean the natural thing is that there is a bunch of different things that software and algorithms are just better at doing than having a bunch of individual workers. The organizations in this generation are colliding against traditional ones. Essentially taking over many of the traditional roles, business opportunities and use cases. The role of humans in the management and in the execution of tasks changes. The next question is what is going to happen to jobs? And the estimates that I've seen is that virtually every job is going to change. We're all going to be transformed by this. There is going to be a lot of dislocation. There's going to be a lot of transformation and a lot of people thinking and learning hopefully how to do their jobs in a different way.

    Karim Lakhani: I think what we know for sure that there will be dislocation. I think we're fooling ourselves to think dislocation won't happen. I think then it's a question of our companies and our societies on how we handle dislocation, how we think about worker retraining because the types of jobs that will exist will be different. I think that's both a research question, but also a really important policy and social question for us. What are the support systems we'll provide to our workers in terms of retraining and reeducation and reallocation when these things start to happen across the board.

    Marco Iansiti: These kind of issues sort of the job transformation, replacement, retraining and so on is just one of the issues that is emerging out of this massive change that we're seen across the economy. There's many other things that this new generation of companies bringing along. Sitting on top of a data factory-

    Brian Kenny: Yeah. I was going to raise that one.

    Marco Iansiti: Exactly.

    Brian Kenny: It's a lot of information to have about people.

    Marco Iansiti: There's a lot of information. There's a lot of risk and so, you have cybersecurity, it's been a problem for many years, but it's becoming an increasing problem. We have privacy issues that are becoming front and center. There are issues around algorithmic bias, for example, when you make a pricing decision or it's a matching decision in the Airbnb marketplace, you can apply bias. There's a whole range of consequences out of this. As the economy changes and becomes structured in a fundamentally different way that we're going to have to pay attention to.

    Brian Kenny: What I hear there is that there's an opportunity here that people may not even have thought of yet. I think about the program that we're doing with 2U, which is in some ways a reaction to this. We're offering a certificate in business analytics right in sort of the heart of thing, right?

    Karim Lakhani: Absolutely. The program is designed for mid-career executives to learn the technical stack. So you understand statistics and you learn R, you understand programming and systems, you learn Python and then also machine learning. But also those elements aren't in a vacuum. It's about how they help you create opportunities in digital strategy, in marketing, in operations, in people analytics and it's a dialogue between what the technology enables you to do and also what the business side is as well. So we've been fortunate to have amazing participants. Average age in our program is 42, two thirds have a master's degree already. Most of them are retooling because they see this as happening in their industries and so they want to retool and get ready for this.

    Marco Iansiti: It's a great example really of the more general response you get on the one hand there are challenges, but there's also opportunities even for an all style organization like the Harvard Business School, we can create this program and all of a sudden we have access to all of these great students and doing all of this really cool stuff.

    Karim Lakhani: It's incredible. The case study in the classroom is so sacrosanct at HBS. We run cases in our program on Zoom, with 60 people doing a case method. And none of us thought that would ever work. We were like, we're going to try it. We're going to try it. We're going to try it. And some of our most gifted case teachers come in and say, " Wow, this is a totally different experience than the classroom. But it's different but good as well." And they love it as well. So it's been quite a learning experience for all of our faculty that are used to teaching in the HBS classrooms to now be on this online approach. They've shot videos, they get questions. The funniest was, I thought, was there's a chat box in the Zoom interface and we told everybody else no chatting. Right? We have a no device rule in the classroom. No chatting. Of course our students didn't listen to it. They started chatting. For me what it did though was, Oh I can see your thought bubbles because you were chatting about the topic I'm saying so that I can say, Hey Melissa, you mentioned this thing. Can you... So I can do a lot of cold calls, based on the chats because they have one way to express it and I can bring that in. In the classroom, I don't get access to the thought bubbles.

    Brian Kenny: So what I'm hearing there too, Oh and I'm thinking as a brand manager now, which is my main job, we were trying to export an experience into a different environment in the same way that people experience it here. And by doing that may have missed out on an opportunity to actually enhance the experience.

    Karim Lakhani: Yeah, it's been quite fascinating. So I think we've learned tremendously in this interaction.

    Marco Iansiti: As you're saying it's part of the more general problem is we all think about how our old style organization is going to evolve. I think it's much better to go out there and embrace the change, work with it, learn how to work with it and play with it well, take some risks, learn a little more, do some more things, and evolve the older organization into the new environment and figure out how it's done.

    Brian Kenny: That's a great way to end our conversation. Thanks guys.

    Karim Lakhani: Thank you.

    Marco Iansiti: Thank you so much.

    Brian Kenny: If you enjoy Cold Call, you might like other podcasts on the HBR Presents Network. Whether you're looking for advice on navigating your career, you want the latest thinking in business and management, or you just want to hear what's on the minds of Harvard Business School professors, the HBR Presents network has a podcast for you. Find them on Apple podcasts or wherever you listen. I'm your host, Brian Kenny, and you've been listening to Cold Call, an official podcast of Harvard Business School on the HBR Presents network.

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    Brian Kenny: A Google search for disruption in Higher Education yields 75,300,000 results. A quick scan of the titles can be a little disconcerting for someone like me who works in higher education. Forbes.com says this will be the biggest disruption ever in higher education. Bloomberg News says, “Future of Higher Ed uncertain in age of disruption.” Even Harvard Business Review fuels the flames with, “Six Reasons Why Higher Education Needs To Be Disrupted.”

    There seems to be a lot of agreement on the notion that higher education is ripe for disruption, and that's probably a good thing. After all, colleges and universities have basically used the same model since the University of Bologna, the oldest in the world, opened its doors in 1108. But what exactly does it mean to disrupt higher education? What would it look like? And will we know it when we see it?

    Today on Cold Call, we'll discuss Professor Karim Lakhani's case entitled, 2U: Higher Education Rewired. I'm your host, Brian Kenny, and you're listening to Cold Call recorded in Klarman Hall studio at Harvard Business School. Today we're doubling down with not one, but two Harvard Business School professors. Karim Lakhani's research examines crowd based innovation models and the digital transformation of companies and industries. He is also the founder and co-director of the Laboratory for Innovation Science at Harvard. Marco Iansiti's research examines the digital transformation of companies and industries with a special focus on digital ecosystems and AI-centric operating models. Together, Karim and Marco lead the Harvard Business School Digital Initiative and they are co-authors of the recently released book, Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. That sounds very ominous. Thank you both for joining me today.

    Marco Iansiti: Thank you for having us.

    Karim Lakhani: Thank you.

    Brian Kenny: Great to have you both here. For our listeners, it's late on a Friday and if we get a little punchy it's because it's late on a Friday so... And I'm really looking forward to talking about 2U and full disclosure to our listeners, 2U is a company that actually Harvard Business School works with. We partner with them and so we know you obviously have had an opportunity to write the case kind of from the inside out of experiencing them firsthand. But the case allows us to sort of step off into the ideas that are in your new book and I just got a copy of it yesterday. I've only been able to read the first chapter, but I can't wait to get to the rest of it. So congratulations on the book.

    Marco Iansiti: Thank you very much.

    Karim Lakhani: Thank you.

    Brian Kenny: Karim, I'm going to start with you. You're the author of the case, co-author of the case. Can you just start by telling us how does the case begin? Sort of set the stage for us.

    Karim Lakhani: So the case is really set at a meeting of 2U, actually where I was present, where they're presenting their vision of how this company can cooperate with universities, and bring them online in a scalable new way. And the dilemma for them is they're not trying to compete with universities, they're trying to help the universities. But it's not clear if the universities want their help. And I think that's a very interesting dilemma because it's not as if they're going to create 2U university and try to compete against Harvard or Harvard Business School or Stanford or anybody else, but really to sort of drag us into the digital age. And there are mixed reactions from their customers about the viability of this approach, as well as the viability of bringing in a much greater sense of analytics and data-driven decision making about the choices of courses, how you enroll students, how you deal with them and how you graduate them and so on.

    Brian Kenny: That's scary talk in a university setting.

    Karim Lakhani: Universities have been highly decentralized and we do our own thing and as even ourselves have tried to go online, those are big expenses and not every university can make those expenses of course. But then a third party telling you what are the right courses to develop based on a data-driven approach, the right students to target and try to attract, that sort of cuts to the core of what other people in the university might be trying to do in a non-data-driven approach because they think they have the intuition to figure all this out. And I think that's where the clash sits.

    Brian Kenny: So the opportunity that they see then is to sort of, as you said, be a partner to universities and not replace them. There have been private universities that have sprung up and tried to compete. That's not what 2U is about.

    Karim Lakhani: Not at all. I think what they recognized is that universities have a brand, have a reputation and have a mission. When I talk to the founders and the executives of the company, their view is we want to help your mission, we want to help your mission for pedagogy and for reaching students and having impact with students. So they really see themselves in that fashion. But I think the question that they are faced with is that their approach is so different at the core of both how courses and programs get developed, highly data-driven, highly analytical, based on multiple data sources and so forth coming at them. But then the second important part after you're designing the courses, how do you attract students? And that too is highly digital. They don't create brochures for programs. They don't do mailers for the programs. It's LinkedIn, Facebook, Twitter, Instagram, Snapchat marketing at scale. And again, that's something most universities are not prepared to undertake or even understand or even attract the talent to make that happen.

    Brian Kenny: Marco, you're quite familiar with 2U as well. How radical is this now from your experience having been in a university setting for a long time on the academic side?

    Marco Iansiti: It's a classic, right? It's really a classic. I mean we see this kind of as an example of a much more general trend. I think that in, across the economy, whether you're in the education business or in the automotive business or in the financial services business, you're starting to see the emergence of two fundamentally different types of companies. There are traditional organizations of which Harvard Business School is, for better and worse, one of them, right?

    Karim Lakhani: Harvard University, I mean-

    Marco Iansiti: Harvard University, or any kind of university. And we're not as old as the University of Bologna, but we've been around for a long time.

    Karim Lakhani: I like to joke that we're the oldest corporation in America and we predate the U.S. Republic as well, by 100 years.

    Brian Kenny: Harvard University does.

    Karim Lakhani: Harvard University does.

    Marco Iansiti: And we predate the city of Cambridge as well, which is a subject of much discussion. 2U is a recently started organization and from the perspective of a student, it's kind of interesting. You can imagine someone wanting to learn something about the business of AI or something about machine learning or something about statistics and they really fundamentally have two different options. One option is to go to an organization like 2U or be found by an organization like 2U, who then helps deliver the content that maybe prepared by any ecosystem of partners, in this case with Karim and my collaboration with them, it's through Harvard Business School. But fundamentally 2U manages the relationship with the student in a bunch of different ways. Using lots of data, lots of algorithms to personalize the messaging and make sure we get the right students and all that kinds of stuff. In some ways it's helping the universities. But in some ways it's also threatening the traditional model of the universities because all of a sudden the students aren't necessarily coming to Harvard Business School for seven weeks or for two years anymore. They're getting their content primarily online. A lot of it is videos. We still have some cases, thank goodness. So it's not a complete competition, but it's certainly also not a complete... I mean it is a collaboration.

    Brian Kenny: It's a big disruption.

    Marco Iansiti: It's a different model. It's a different business model and it's a different operating model.

    Karim Lakhani: Absolutely. As Marco's saying, I think the thing that's so interesting in our interactions with them is the program we launched with them, which is the Harvard Business Analytics program, the Harvard Corporation approved that the program would go for approval in August of 2017, we had enrolled students ready to go March 2018. That's like light speed at Harvard, because we were able to piggy back on their processes and launch and attract the students, target the students, get them enrolled and get them going and also work with ourselves and our colleagues at the Engineering School and the Faculty of Arts and Science to generate courses in that same amount of time. It's a different beast than what we are used to.

    Marco Iansiti: It's a different kind of organization. It's a different process. It's a different timescale. It's a different structure. It's a different approach to technology. It's a different approach to data.

    Brian Kenny: Radically different in a lot of ways and counter frankly to the culture of a lot of Higher Ed institutions. I mean the case gets into some of the challenges that they faced when they were trying to get started and trying to build partnerships with universities. The culture doesn't easily accept something like this.

    Karim Lakhani: No, I mean I think part of what makes universities succeed is, I tell our Dean this, we're slow metabolism creatures, maybe of the order of whales, and change is slow and hard and we've done well because we haven't changed as fast. But in today's world, I mean I think we still need to change and adapt. I mean I think society is asking more of the universities, more of our education missions and pushing us to be more relevant. These guys present an opportunity for universities to sort of think about, how do I expand my mission and how do I expand my reach? How do I expand my scope? Yet do it in a way that is modern and not based on the fact that I need to bring everybody to my campus every single time for an education interaction. And I think that's I think where the culture clash can happen because they're a for-profit company, they want to make money and so they're trying to be efficient in dimensions that we may not care about being efficient in, but they have to be in order for their profit mission. And us as HBS professors, admire the profit mission and think that's a good idea.

    Brian Kenny: And it's not just us, they work with a lot of schools.

    Karim Lakhani: Oh absolutely.

    Brian Kenny: They are working with medical schools and others.

    Karim Lakhani: Absolutely. And business schools elsewhere too. I think that's very interesting. And as Marco was saying, you will never know that it's 2U that's marketing to you. But in fact, that's who is doing it. And 2U finds you. We just had a graduation of a program and all of them said, " Yeah, you guys found me."

    Brian Kenny: Remarkable.

    Karim Lakhani: And that's-

    Brian Kenny: Complete change. That's turning it completely on its head.

    Karim Lakhani: As used to what we are used to, which is people come to Harvard because of the brand and they seek us out. This is the other way around. They find the people based on their social media presence and their activities to say, we think this program is the right one for you.

    Brian Kenny: So let me ask you this, how does 2U help us to tee up the big ideas in your book? What makes them a good example?

    Marco Iansiti: From their perspective they're representative of a whole generation of companies that is targeting traditional problems, traditionally use cases, traditional needs but solving those needs in a fundamentally different way. Take Amazon, they interact with consumers in a fundamentally different way than the way the retail used to be done. In fact, the whole retail sector has been transformed in all kinds of dramatic ways. Trying to emulate what Amazon has done has induced Walmart to change and invest dramatically billions of dollars in new acquisitions and digital platforms and technology and the whole idea is that the traditional operating models that companies have had to serve consumers in retail and other industries, have been around for a long time. We've built organizations that have a bunch of managers and a bunch of workers and everybody kind of works together to serve the consumer. Whether it's a grocery chain or whether it's a bank. Today we have a whole new generation of organizations that essentially solve similar problems like I want to buy a book, but what goes on behind the curtain in terms of what delivers that book or how the organizations find the consumers in the first place and target the messaging to them is done fundamentally differently. The way that Amazon works has almost nothing in common with a traditional retailer. Their processes are embedded in software. Things like product planning or pricing or forecasting are done by algorithms. All of it rests on a foundation of data where they know enormous amounts about individual consumers, their prime customers and so on. And then can suggest, recommend products for those customers they can solve problems, they can encourage them to buy new things, basically solve a variety of problems and do so in a way that's more efficient and in many ways more effective than traditional businesses. Also, when you have a digital business like Amazon, they can scale at a rate that is much faster than the traditional retailer might have been able to scale. And because fundamentally what the scaling is driven by is software. So you have a process that's serving up all that the consumers want and running the front end and the pricing, the webpage and so on. It's running the back end, the supply chain and all that stuff. And so in some ways selling a million books is not that much harder than selling half a million books and selling a billion books is really not that much harder than selling a million books. It's in fact, in some ways the scaling process is much easier.

    Brian Kenny: Your book talks about an AI Factory. That's one of the principles that you start off with. What's an AI Factory?

    Karim Lakhani: Fundamentally, the view of the AI Factory is that we're going to be making predictions about some future state and we need data to come in and process. So we need a data system, a data pipeline that can absorb data with proprietary data internally, but also loads of external data. Put it through pretty much sort of off the shelf algorithms that will help you say what is it that's going on and then create an infrastructure to prioritize and make available those predictions so some action can be taken. So the example I will sort of say is, imagine you go to McDonald's and you are trying to order some hamburgers and other assorted happy meal types of things. Well the AI Factory in McDonald's by the way, is going to look very similar to an AI Factory at U.S. Steel. The AI Factory in the U.S. Steel plant will be the same. It will still have a data pipeline, will still have algorithms and will still have an infrastructure. And all of them will work in the same way. Our claim in the book is that all organizations will need to develop and get good at building an AI Factory so we know what are the future states that we need to be thinking about and automating those actions as towards them.

    Marco Iansiti: Think like Amazon sits on top of an AI Factory, right? So the stuff that interprets the massive amounts of data that they actually have and makes recommendations, does the forecasts, figures out what's going to happen in supply chain, it's all a bunch of data-driven processes that are enabled by this foundation of data. Take it back to 2U, it's really the same thing. I mean 2U has a bunch of data about individual students and what they're doing, what they're thinking about coming from the data they get from LinkedIn or Facebook or whatever it is. That's how they can target all those students. And in the back end they've got a marketplace of products, just like Amazon does, that is plugged in to the front end that the students come and visit and so when I go out there and see, I think I might be interested in learning about the business of AI, then 2U has got the right data to make the match or even the other way around, they can make recommendations. I think Karim based on... You might like this Harvard Business Analytics Program, which just happens to do all the things that you really want, which I know because I know a lot about Karim. Right? Based on my data factory and all of that stuff.

    Karim Lakhani: And just to build on an example of this, so we've become obsessed with Amazon recently because our book's on Amazon. So then you're always looking at, well what the sales figures are but what's interesting is like the price that Amazon is charging for a book keeps changing, right? There's a list price and then you see them discounting and there's no manager sitting there going the Iansiti-Lakhani book, well these next five minutes we're going to make it $18, then we're going to make it $24, then we'll make it $28, right? That's all algorithmically driven. They have demand data from customers. They know what other books are being bought and then they are basically changing the prices on the spot, which is incredible. So that's the AI Factory, right? The AI factory is making some prediction about the likelihood of me buying that book as the price is varying and changing.

    Brian Kenny: It sounds like the magic here is for the firm that has created the AI Factory, right? And then obviously there are many businesses that exist that don't have the capacity to build their own factory. So they have to find one to plug into. Is that the idea?

    Marco Iansiti: That's kind of the quandary that the Harvard Business School is saying, do we work with 2U, who has got this great data foundation, the technology, the AI Factory, all those kinds of things and they can bring us students but hey, they're going to take it a big cut of the revenues. Same thing. Are you going to sell your products on Amazon, which can dramatically increase the revenues that you have, but then goodness, they're going to take a nice cut of the profits that come out of it. This new generation of organizations is cutting across, whether it's Amazon, whether it's Google, whether it's Ant Financial in China in financial services, whether it's 2U in education have similarly kind of changed the model and offered, from the consumer's perspective, a way to solve their problem. But doing so in a fundamentally different way and the traditional companies like the Harvard Business Schools of the world or the banks in China or the merchants that are on the Amazon marketplace are trying to figure out, is it better for me to play with these guys or should I just try to do it on my own?

    Karim Lakhani: Another good example actually is we have this case on Marriott as a company and the evolution of the company. And one of the questions I ask students in the case, because of course you talk about Airbnb as well, is should Marriott list its rooms on Airbnb? Is Airbnb a competitor or in fact a complementor to you? And that's a fundamental question that even Marriott is faced up with because they're trying to create, on a high end, an Airbnb competitor. But it's like the scale of the AI Factory at Airbnb doesn't even compare to anything that Marriott has and even their investment choices of where you invest in technology versus where you invested in real estate aren't comparable. And so then the question becomes, if I'm Marriott, if I have these boutiquey hotels and funky rooms, should I actually just list them on Airbnb? And by the way, they will charge me less money than booking.com because Airbnb is like in the 5-6% versus 30% on Booking.

    Marco Iansiti: Or if I am to Harvard Business School and I have this big bunch of executive programs, should I put more of them up 2U and see if I can make the match in different ways and match their model. And you see it from industry to industry to industry. You have these hub companies or these platforms, these sort of these digital things that are built on all this data and so on. They can do a more effective process of actually aggregating the data, targeting consumers, personalizing the offerings, figuring out who the right people are and then delivering the product that are essentially providing an alternative channel for a lot of traditional organizations. And then it's almost like this Faustian thing, do play with this potential devil, I'm not saying they are at all, or do you go at it your own way without having the scale to necessarily be competitive?

    Karim Lakhani: Well, one of our beliefs though is that, I mean I think all organizations will need to sort of start to develop a strategy around their data. Develop a view of consolidation of their data. A single point of view on their data instead of the silos that have sort of persisted in the past. Even if you're not going to be a full Ninja AI Factory, you still need to be able to plug into the other factories and that will still require you to become good at those problems.

    Brian Kenny: It's so hard though, right? Where do you even begin if you're one of a large organization that's been around for a long time and you've got all these different pockets of data that are living everywhere across your enterprise, how do you even think of that?

    Marco Iansiti: Well I mean the good news is that technology is straightforward. So the technology in many ways is the easy part. It's all available on the cloud, there's a bunch of big vendors that can essentially give you an AI Factory in a box if you like. A lot of the individual pieces are easy to get. The capabilities are the next thing, and those are hard because you have to hire different kinds of people, different kinds of skill sets. But the number of analytics graduates, data scientists out there is increasing rapidly and organizations sometimes have a hard time hiring this kinds of people, but if they do it right, with rethinking incentives a little bit and rethinking compensation maybe along those lines, they can do it. And that problem is also solvable by many of the large traditional players. The thing that's the hardest part is that you kind of have to restructure the way the organization works and what is the traditional vertically oriented siloed organization where everybody's protecting their own turf, with their own individual technology, with their own individual data, all of a sudden has to behave as an integrated piece.

    Marco Iansiti: You want to have one AI Factory, you don't want to have 17 different AI Factories with data scattered in the same company, right? Where, when you go and visit one of your customers, you have to bring 17 different printouts, one from each of the different departments that tells you what you're doing with that specific customer.

    Brian Kenny: That defeats the purpose, right?

    Karim Lakhani: But it's hard because technology is asking for integration and horizontal connections. Most of our organizations are vertical silos and so we now need to do organizational change to adapt to what the technology is asking for and that's really hard. Right? And that's in many ways-

    Brian Kenny: That's the hardest thing.

    Karim Lakhani: Yeah, and that's the barrier. So I mean our view is that the technology, there are plenty of templates and roadmaps on how to do this, but I think the big challenge is actually the org change and to change the architecture of the organization to match the architecture of the technology.

    Brian Kenny: One of the things your book talks about is the competition collision. And I thought that was an interesting concept too and we've touched a little bit on it here, but I'd love to hear more about how do you define what that is?

    Marco Iansiti: I think all of these examples that we've talked about 2U and HBS or Amazon and the local merchant or Ant financial and one of the more traditional banks in China, is an example of what we call a collision event. And collision as we define it is when you have essentially the same use case. I want to take a machine learning course or I want to buy a book. That use case can be solved now by two fundamentally different kinds of organizations that work in fundamentally different ways. If you look at a traditional bank is a siloed, structured, organized in a certain way as they have been organized literally for hundreds of years as the Harvard Business School. They can solve a problem for the consumer, a very different kind of organization, whether it's Ant financial or 2U or Amazon can solve that same problem, but will do so in a fundamentally different way. More scalable, is able to generate much greater scope, this organizations can serve all kinds of different services to all kinds of people and also is able to change and innovate more rapidly than traditional organizations are able to do. The old model has been around for hundreds of years. Organizations have been built in silos for hundreds of years. Organizations have-

    Brian Kenny: For good reason.

    Marco Iansiti: For good reason because you try to manage human complexity and try to focus efforts into smaller groups and so on. If your organization is run by networks and algorithms, you want to organize it differently to make it work well.

    Brian Kenny: I'm going to project what I think listeners might be thinking right now, which is they're hearing that you can take people out of this equation and it's much more efficient and scalable and it learns by itself and what does that mean for jobs and the things that people do.

    Karim Lakhani: Just thinking about this in the first case, right? Which is a company like Ant financial has 1.2 billion customers. They have processes where if you want to open up a bank account, they say it takes you three minutes to fill out the application, one minute for approval, zero human interaction. Because there's no way you can think about offering loans to 1.4 billion people with a human based system or you think about Amazon, I think their SKU count is somewhere in the billions, right? There's no way you're going to have enough managers to sit there and think about the pricing structure. So the scale, the ambition of scale that these organizations have is such that you have no choice but to go to the algorithms.

    Marco Iansiti: You still have people in the organization, they're designing the systems and they're also doing all the tasks that the algorithms and robots aren't able to do yet. The center of the organization essentially is a bunch of algorithms and it's a bunch of data. That's a little bit our predicament right now because I mean the natural thing is that there is a bunch of different things that software and algorithms are just better at doing than having a bunch of individual workers. The organizations in this generation are colliding against traditional ones. Essentially taking over many of the traditional roles, business opportunities and use cases. The role of humans in the management and in the execution of tasks changes. The next question is what is going to happen to jobs? And the estimates that I've seen is that virtually every job is going to change. We're all going to be transformed by this. There is going to be a lot of dislocation. There's going to be a lot of transformation and a lot of people thinking and learning hopefully how to do their jobs in a different way.

    Karim Lakhani: I think what we know for sure that there will be dislocation. I think we're fooling ourselves to think dislocation won't happen. I think then it's a question of our companies and our societies on how we handle dislocation, how we think about worker retraining because the types of jobs that will exist will be different. I think that's both a research question, but also a really important policy and social question for us. What are the support systems we'll provide to our workers in terms of retraining and reeducation and reallocation when these things start to happen across the board.

    Marco Iansiti: These kind of issues sort of the job transformation, replacement, retraining and so on is just one of the issues that is emerging out of this massive change that we're seen across the economy. There's many other things that this new generation of companies bringing along. Sitting on top of a data factory-

    Brian Kenny: Yeah. I was going to raise that one.

    Marco Iansiti: Exactly.

    Brian Kenny: It's a lot of information to have about people.

    Marco Iansiti: There's a lot of information. There's a lot of risk and so, you have cybersecurity, it's been a problem for many years, but it's becoming an increasing problem. We have privacy issues that are becoming front and center. There are issues around algorithmic bias, for example, when you make a pricing decision or it's a matching decision in the Airbnb marketplace, you can apply bias. There's a whole range of consequences out of this. As the economy changes and becomes structured in a fundamentally different way that we're going to have to pay attention to.

    Brian Kenny: What I hear there is that there's an opportunity here that people may not even have thought of yet. I think about the program that we're doing with 2U, which is in some ways a reaction to this. We're offering a certificate in business analytics right in sort of the heart of thing, right?

    Karim Lakhani: Absolutely. The program is designed for mid-career executives to learn the technical stack. So you understand statistics and you learn R, you understand programming and systems, you learn Python and then also machine learning. But also those elements aren't in a vacuum. It's about how they help you create opportunities in digital strategy, in marketing, in operations, in people analytics and it's a dialogue between what the technology enables you to do and also what the business side is as well. So we've been fortunate to have amazing participants. Average age in our program is 42, two thirds have a master's degree already. Most of them are retooling because they see this as happening in their industries and so they want to retool and get ready for this.

    Marco Iansiti: It's a great example really of the more general response you get on the one hand there are challenges, but there's also opportunities even for an all style organization like the Harvard Business School, we can create this program and all of a sudden we have access to all of these great students and doing all of this really cool stuff.

    Karim Lakhani: It's incredible. The case study in the classroom is so sacrosanct at HBS. We run cases in our program on Zoom, with 60 people doing a case method. And none of us thought that would ever work. We were like, we're going to try it. We're going to try it. We're going to try it. And some of our most gifted case teachers come in and say, " Wow, this is a totally different experience than the classroom. But it's different but good as well." And they love it as well. So it's been quite a learning experience for all of our faculty that are used to teaching in the HBS classrooms to now be on this online approach. They've shot videos, they get questions. The funniest was, I thought, was there's a chat box in the Zoom interface and we told everybody else no chatting. Right? We have a no device rule in the classroom. No chatting. Of course our students didn't listen to it. They started chatting. For me what it did though was, Oh I can see your thought bubbles because you were chatting about the topic I'm saying so that I can say, Hey Melissa, you mentioned this thing. Can you... So I can do a lot of cold calls, based on the chats because they have one way to express it and I can bring that in. In the classroom, I don't get access to the thought bubbles.

    Brian Kenny: So what I'm hearing there too, Oh and I'm thinking as a brand manager now, which is my main job, we were trying to export an experience into a different environment in the same way that people experience it here. And by doing that may have missed out on an opportunity to actually enhance the experience.

    Karim Lakhani: Yeah, it's been quite fascinating. So I think we've learned tremendously in this interaction.

    Marco Iansiti: As you're saying it's part of the more general problem is we all think about how our old style organization is going to evolve. I think it's much better to go out there and embrace the change, work with it, learn how to work with it and play with it well, take some risks, learn a little more, do some more things, and evolve the older organization into the new environment and figure out how it's done.

    Brian Kenny: That's a great way to end our conversation. Thanks guys.

    Karim Lakhani: Thank you.

    Marco Iansiti: Thank you so much.

    Brian Kenny: If you enjoy Cold Call, you might like other podcasts on the HBR Presents Network. Whether you're looking for advice on navigating your career, you want the latest thinking in business and management, or you just want to hear what's on the minds of Harvard Business School professors, the HBR Presents network has a podcast for you. Find them on Apple podcasts or wherever you listen. I'm your host, Brian Kenny, and you've been listening to Cold Call, an official podcast of Harvard Business School on the HBR Presents network.

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    Marco Iansiti
    Marco Iansiti
    David Sarnoff Professor of Business Administration
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    Karim R. Lakhani
    Karim R. Lakhani
    Dorothy and Michael Hintze Professor of Business Administration
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