As companies like Uber and AirBnB disrupt historical business models and redefine the competitive landscape of their industries, business leaders understand more than ever that harnessing disruptive technologies is critical to drive rapid innovation and maintain relevance. That’s why employers seek candidates with both business and digital acumen.
Click the recording below to hear Hult professor Olaf Groth host a webinar on the influence of disruptive innovation in the workplace. The webinar provides insight into the practical approach of Hult’s teaching model, and help you understand how forces, trends, and uncertainties in different sectors can combine to fuel unexpected innovation and success.
Olaf Groth
Professor Olaf Groth brings more than 20 years of global experience to his classroom. He has worked for pioneering startups and global enterprises such as Vodafone, Boeing, and Qualcomm. His own consultancy, Emergent Frontiers Group, advises business leaders on trends, strategies, and ventures in the global innovation economy.
Hult now offers a Master of Disruptive Innovation as part of our unique Dual Degree Program.
Transcript for Olaf Groth’s webinar:
Eriko: Thank you so much for your time today and thank you for joining us in this webinar.
Professor Groth: All right. Thank you very much, Eriko, for the kind introduction. Good morning, good afternoon, and good evening, ladies and gentlemen, from wherever you may be joining us today. I’m privileged to be speaking with you today. Eriko has given me such a nice introduction that I won’t waste much more of your time with any more information about myself, but suffice it to say that the topic that we’re going to be exploring today is of paramount importance for the global economy and for us as businesspeople. So much so in fact that the World Economic Forum has just announced that they will be setting up an office in San Francisco to assess what these types of trends mean for the fourth industrial revolution and really the future of our societies and economies at large.
So it’s a very timely topic and it will have bearing on your careers as well. And that really gets us into the first key question here, and that is why do we need to consider futures? We’re not science fiction authors, we’re not movie directors, and we’re not really on this call to entertain ourselves, much less do we consider getting an MBA and spending the time and money to be entertained per se. So why do we need them? We need them because of these implications both for societies and the global economy on a macro level because the future of employment, labor, productivity, economic development depends on them, but also because there are real implications for the shape of your career, how you lead other people, how you are productive, where you will end up in life. And of course, paramount for us as a business school, how do we best prepare you as you engage with these trends.
So we need to practice the ability to think and act strategically under uncertainty. Uncertainty is a word you hear mentioned often much in the context of other similar terms like volatility, ambiguity, and complexity. There is this wonderful acronym called VUCA: volatility, ambiguity…I’m sorry, volatility, uncertainty, complexity, and ambiguity, that wraps into an acronym the fact that we live in difficult times as businesspeople because we tend to look back to analyze our path, to recognize patterns and then make decisions for the future. Well, it turns out that the future is nothing like what we have experienced so far and that we may in fact have grown up with a number of institutions, paradigms, systems, assumptions really that we hold very dearly. Right?
So you may think that you grew up with a lot of change, especially if you are of a younger generation, for instance generation, the generation of the millennials. And yes you do have the advantage that you grew up in an era of volatility. But you, like many of us, have come to be used to some institutions in your lives. I would submit to you, for instance, the current state of the European Union, with which many of you have grown up, and the future of that is very much in question as we all know now, especially after Brexit. So we do need to ask ourselves, what are these safe assumptions that we believe to be safe but there really aren’t? Right? And let’s consider, for instance, this question here, which will be the third largest country in the world by population in 2050? I will give you a few seconds to consider.
Some of you might argue, well, that could be India and China, the largest countries in the world right now. Maybe something happens between them. We do hear about conflict, border conflict every so often. Maybe something happened that would bump one of them back to third place. Not implausible, of course, but not the right answer here. You might argue the United States, which is the obvious contender, and I’m going to have to disappoint you but the United States will grow only marginally in the next 25 or so years. Some of you might argue Indonesia for good reasons, or you might talk about Brazil, Russia, or South Africa for that matter, countries that we normally consider part of the fast-paced, emerging second tier of the economy.
But you’re unlikely, unless of course you are from the continent, to come up with this answer, Nigeria. Nigeria has in fact been found by the Pew Research Center, a global foundation, to most likely become the third most populous country by population by 2050, displacing the United States in that position. Could we foresee, could we assume, could we rightly think of circumstances that would prevent that from happening? Yes, if we assume a very large-scale pandemic or a large-scale war, or armed conflict. But really in order to derail this particular data point you would have to envision millions of people getting killed. So the Pew Foundation, of course, is experienced looking at uncertainty when it issues some of these data points, and I think it’s safe to assume that Nigeria will play a very much…a much more prominent role in the global economy over the next 25 years. And in fact, at Hult we are lucky to have many students from Nigeria as well who can educate us about the country’s workings.
Why are we concerned with that? What are the implications of Nigeria growing that big, and getting it right in terms of its economic development? Well, just imagine a Nigeria that is economically healthy and is high growth at 440 million people. Could we imagine Nigeria becoming the entrepreneurial innovation hub for Africa? A large young population increasingly educating itself globally could be a plausible thing to assume. What about R&D activity in Nigeria? What about business model innovation for Africa that gets spawned in Nigeria? Can you imagine the Nigerian government becoming and taking a much more prominent role in the global economy, negotiating terms for trade and investment much like Indonesia…I’m sorry much like India and China are doing today? And are we familiar enough with this new paradigm, with the way Nigeria would like to set rules on the global stage?
So from multiple angles, whether you are an entrepreneur or a future executive, a consultant, or whether you look at business as a global economic development tool, the implications of Nigeria taking a prominent role are quite significant. So be concerned with the things that you fail to envision because they could prevent you then, this failure to envision could prevent you then from seeing opportunity early, ideally before other people do, or from mitigating risk before it hits you in the face. Here are some examples of people who didn’t do this.
Now when you see this slide, you might find this statement on the part of Maggie Thatcher to be morally deplorable. You might argue that it is also obviously historically wrong. You could defend her and say that she was merely trying to act in the best interest of her country, of the empire around it as it were, ensuring that its national interests are safeguarded as negotiations were going on. But whatever your feelings are about this slide, there is probably one thing that we can all agree on. She didn’t do a favor to either South Africa or her own citizens or her own business executives in preventing them from preparing for this situation actually coming true. And that is the key lesson in this, that by making these statements, whatever you might think about them, are you setting yourself up for future learning opportunity ahead of time?
Now take a look at this gentleman here, Ken Olsen, president of DEC. Ken Olsen was one of the most renowned business leaders of his time. DEC was a leading computer company of the ’70s into the early ’80s. It no longer exists. You will have seen similar statements from the likes of IBM giving you numbers that are very small compared to the reality of today’s computer world, essentially dismissing the fact that personal computers were going to take over and that we were going to migrate to a decentralized computing paradigm, away from supercomputers.
Now, Mr. Olsen was not stupid. He was very smart, very knowledgeable, very well respected. And in fact one could argue that that is exactly why some people who are so knowledgeable, so smart, and so well-respected go wrong sometimes because they know and get reaffirmed by the public frequently as being on top of their game. When you have that certainty about yourself, you stop seeing things that happen around you that might be contextual, meaning they might be adjacent to or near your core business but they’re not part of your core business. And that’s what we call the “expert trap,”
where experts are too secure in what they know to see that which they don’t know, and which could disrupt it.
It sometimes is a good thing therefore to be new to a field, to bring fresh perspectives. And in fact, we harness that here at Hult where 85%-plus of all students on a given campus are from another country and where we have a vast diversity of individual, personal and professional backgrounds. Being new to a field can in fact be an asset if it is used with a good degree of humility because you bring fresh perspectives, and because you ask questions that seem too basic or that seem irrelevant to those who know much more of a given field.
Why does this matter? It matters because we need to get around biases. When you are very good at what you do, when you have a lot of experience, your biases grow. The list that you see here is taken from Wikipedia. You can find a list of 100-plus biases there. I can’t explain all of these to you, but I can tell you that most of us, including myself and you, have quite a few of these ingrained in our brains. Why? Not because we aren’t enlightened enough, but rather because that’s how our brains are programmed. Our brains are programmed to recognize patterns, to refer to the past, to learn for the future. We make quick judgments based on these biases. Nature programmed us this way to survive, to make quick decisions and not overthink. Unfortunately in this era of complexity, ambiguity, uncertainty, and volatility, these biases more often than not harm us as we need to understand the complexity and carve through it. So we need to overcome them and mitigate them with each other’s help.
So now let’s switch gears and let’s get back to the topic at hand for this webinar. What is the future of productivity and work in light of these digital disruption trends: artificial intelligence, internet-of-things, drones and robots, and what we call the fourth industrial revolution? Why do we care, and how does it impact our company’s strategy? How do we get our arms around that? Let me show you a video that will provoke you deliberately to question your assumptions about how the future might evolve. This video is not going to come true in its entirety. You might find some of this to go far beyond future reality, to be a bit of a stretch. And so we are stimulating your brain to think critically about what you’re about to see here, and to get the engine in your brain cranking. So take a look, take a listen, and then we will discuss and I will explain to you what we do with this at Hult.
Video Narrator: Every human used to have to hunt or gather to survive. But humans are smartly lazy, so we made tools to make our work easier. From sticks to plows to tractors, we’ve gone from everyone needing to make food, to modern agriculture with almost no one needing to make food, and yet we still have abundance. Of course, it’s not just farming, it’s everything. We’ve spent the last several thousand years building tools to reduce physical labor of all kinds. These are mechanical muscles. Stronger, more reliable, and more tireless than human muscles ever could be. And that’s a good thing. Replacing human labor with mechanical muscles frees people to specialize and that leaves everyone better off, even those still doing physical labor. This is how economies grow and standards of living rise.
Some people have specialized to be programmers and engineers whose job is to build mechanical minds. Just as mechanical muscles made human labor less in demand, so are mechanical minds making human brain labor less in demand. This is an economic revolution. You may think we’ve been here before, but we haven’t. This time is different.
When you think of automation, you probably think of this, giant, custom-built, expensive, efficient, but really dumb robots, blind to the world and their own work. They were a scary kind of automation, but they haven’t taken over the world because they’re only cost-effective in narrow situations. But they’re the old kind of automation. This is the new kind.
Meet Baxter. Unlike these things, which require skilled operators and technicians and millions of dollars, Baxter has vision and can learn what you want him to do by watching you do it. And he costs less than the average annual salary of the human worker. Unlike his older brothers, he isn’t pre-programmed for one specific job. He can do whatever work is within the reach of his arms. Baxter is what might be thought of as a general-purpose robot, and general-purpose is a big deal. Think computers. They too started out as highly custom and highly expensive. But when cheap-ish general-purpose computers appeared, they quickly became vital to everything. A general-purpose computer can just as easily calculate change, or assign seats on an airplane, or play a game, or do anything just by swapping its software. And this huge demand for computers of all kinds is what makes them both more powerful and cheaper every year.
Baxter today is the computer of the 1980s. He’s not the apex, but the beginning. Even if Baxter is slow, his hourly cost is pennies worth of electricity, while his meat-based competition costs minimum wage. A tenth of the speed is still cost-effective when it’s a hundredth the price. And while Baxter isn’t as smart as some of the other things people talk about, he’s smart enough to take over many low-skilled jobs. And we’ve already seen how dumber robots than Baxter can replace jobs. In new supermarkets, what used to be 30 humans is now one human overseeing 30 cashier robots. Or take the hundreds of thousands of baristas employed worldwide. There’s a barista robot coming for them. Sure, maybe your guy makes the double mocha whatever just perfect and you’d never trust anyone else, but millions of people don’t care, and just want a decent cup of coffee. Oh, and by the way, this robot is actually a giant network of robots that remembers who you are and how you like your coffee no matter where you are. Pretty convenient.
We think of technological change as the fancy new expensive stuff, but the real change comes from last decade’s stuff getting cheaper and faster. That’s what’s happening to robots now. And because their mechanical minds are capable of decision-making, they are outcompeting humans for jobs in a way no pure mechanical muscle ever could.
Imagine a pair of horses in the early 1900s talking about technology. One worries all these new mechanical muscles will make horses unnecessary. The other reminds him that everything so far has made their lives easier. Remember all that farm work? Remember running from coast to coast delivering mail? Remember riding into battle? All terrible. These new city jobs are pretty cushy, and with so many humans in the cities there will be more jobs for horses than ever. “Even if this ‘car’ thingy takes off,” they might say, “there will be new jobs for horses we can’t imagine.” But you, dear viewer, from beyond 2000, know what happened. There are still working horses, but nothing like before. The horse population peaked in 1915. From that point on, it was nothing but down.
There isn’t a rule of economics that says “Better technology makes more better jobs for horses.” It sounds shockingly dumb to even say that out loud. But swap “horses” for “humans”, and suddenly people think it sounds about right. As mechanical muscles pushed horses out of the economy, mechanical minds will do the same to humans. Not immediately, not everywhere, but in large enough numbers and soon enough that it’s going to be a huge problem if we’re not prepared. And we’re not prepared. You, like the second horse, may look at the state of technology now and think it can’t possibly replace your job. But technology gets better, cheaper, and faster at a rate biology can’t match. Just as the car was the beginning of the end for the horse, so now does the car show us the shape of things to come.
Self-driving cars aren’t the future. They’re here and they work. Self-driving cars have traveled hundreds of thousands of miles up and down the California coast, and through cities, all without human intervention. The question is not if they’ll replace cars, but how quickly. They don’t need to be perfect, they just need to be better than us. Human drivers, by the way, kill 40,000 people a year with cars just in the United States. Given that self-driving cars don’t blink, don’t text while driving, don’t get sleepy or stupid, it’s easy to see them being better than humans because they already are.
Now, to describe self-driving cars as cars at all is like calling the first cars “mechanical horses.” Cars in all their forms are so much more than horses that using the name limits your thinking about what they can even do. Let’s call self-driving cars what they really are, autos, the solution to the “transport objects from point A to point B” problem. Traditional cars happen to be human-sized to transport humans, but tiny autos can work in warehouses, and gigantic autos can work in pit mines. Moving stuff around is who knows how many jobs, but the transportation industry in the United States employs about 3 million people. Extrapolating worldwide, that’s something like 70 million jobs at minimum. These jobs are over. The usual argument is that the unions will prevent it, but history is filled with workers who fought technology that would replace them, and the workers always lose. Economics always wins.
And there are huge incentives across wildly diverse industries to adopt autos. For many transportation companies, humans are about a third their total costs. That’s just the straight salaries. Humans sleeping in their long-haul trucks cost time and money. Accidents cost money. Carelessness costs money. If you think insurance companies will be against it, guess what? Their perfect driver is one who pays their small premiums and never gets into an accident. The autos are coming, and they’re the first place where most people will really see the robots changing society. But there are many other places in the economy where the same thing is happening, just less visibly. So it goes with autos, so it goes for everything.
It’s easy to look at autos and Baxters and think, “Technology has always gotten rid of low-skilled jobs we don’t want people doing anyway.” They’ll get more skilled and do better educated jobs like they’ve always done. Even ignoring the problem of pushing a hundred million additional people through higher education, white collar work is no safe haven either. If your job is sitting in front of a screen and typing and clicking, like maybe you’re supposed to be doing right now, the bots are coming for you too buddy. Software bots are both intangible and way faster and cheaper than physical robots. Given that white collar workers are, from a company’s perspective, both more expensive and more numerous, the incentive to automate their work is greater than low-skilled work.
And that’s just what automation engineers are for. These are skilled programmers whose entire job is to replace your job with a software bot. You may think even the world’s smartest automation engineer could never make a bot to do your job, and you may be right. But the cutting edge of programming isn’t super-smart programmers writing bots, it’s super-smart programmers writing bots that teach themselves how to do things the programmer could never teach them to do. How that works is well beyond the scope of this video, but the bottom line is there are limited ways to show a bot a bunch of stuff to do, show the bot a bunch of correctly done stuff, and it can figure out how to do the job to be done. Even with just a goal and no knowledge of how to do it, the bots can still learn. Take the stock market, which in many ways is no longer a human endeavor. It’s mostly bots that taught themselves to trade stocks trading stocks with other bots that taught themselves. As a result, the floor of the New York Stock Exchange isn’t filled with traders doing their day jobs any more, it’s largely a TV set.
So bots have learned the market, and bots have learned to write. If you’ve picked up a newspaper lately, you’ve probably already read a story written by a bot. There are companies that teach bots to write anything, sports stories, TPS reports, even, say, those quarterly reports that you write at work. Paperwork, decision-making, writing, a lot of human work falls into that category, and the demand for human mental labor in these areas is on the way down. But surely the professionals are still safe from bots. Yes?
When you think lawyer, it’s easy to think of trials. But the bulk of lawyering is actually drafting legal documents, predicting the likely outcome and impact of lawsuits, and something called “discovery,” which is where boxes of paperwork gets dumped on the lawyers, and they need to find the pattern or the one out-of-place transaction among it all. This can be bot work. Discovery in particular is already not a human job in many law firms. Not because there isn’t paperwork to go through, there’s more of it than ever, but because clever research bots shift through billions of emails and memos and accounts in hours, not weeks, crushing human researchers in terms of not just costs and time, but most importantly accuracy. Bots don’t get sleepy reading through a million emails.
But that’s the simple stuff. IBM has a bot named Watson. You may have seen him on TV destroy humans at “Jeopardy!” but that was just a fun side project for him. Watson’s day job is to be the best doctor in the world, to understand what people say in their own words, and give back accurate diagnoses. He’s already doing that at Sloan-Kettering, giving guidance on lung cancer treatments.
Just as autos don’t need to be perfect, they just need to make fewer mistakes than humans, the same goes for doctor bots. Human doctors are by no means perfect. The frequency and severity of misdiagnoses are terrifying, and human doctors are severely limited in dealing with a human’s complicated medical history. Understanding every drug, and every drug’s interaction with every other drug is beyond the scope of human knowability, especially when there are research robots whose whole job it is to test thousands of new drugs at a time. And human doctors can only improve through their own experiences. Doctor bots can learn from the experience of every doctor bot, can read the latest in medical research, and keep track of everything that happens to all of their patients worldwide and make correlations that would be impossible to find otherwise. Not all doctors will go away, but when the doctor bots are comparable to humans and they’re only as far away as your phone, the need for general doctors will be less.
So professionals, white collar workers, and low-skilled workers all have things to worry about from automation. But perhaps you are unfazed because you are a special, creative snowflake. Well, guess what? You’re not that special. Creativity may feel like magic, but it isn’t. The brain is a complicated machine, perhaps the most complicated machine in the whole universe, but that hasn’t stopped us from trying to simulate it. There is this notion that just as mechanical muscles allowed us to move into thinking jobs, that mechanical minds will allow us to move into creative work. But even if we assume the human mind is magically creative, it’s not, but just for the sake of argument, artistic creativity isn’t what the majority of jobs depend on. The number of writers and poets and directors and actors and artists who actually make a living doing their work is a tiny, tiny portion of the labor force. And given that these are professions dependent on popularity, they’ll always be a very small portion of the population. There can’t be such a thing as a poem- and painting-based economy. Oh, by the way, this music in the background that you’re listening to? It was written by a bot. Her name is Emily Howell, and she can write an infinite amount of new music all day for free, and people can’t tell the difference between her and human composers when put to a blind test.
Talking about artificial creativity gets weird fast. What does that even mean? But nonetheless it’s a developing field. People used to think that playing chess was a uniquely creative human skill that machines could never do, right up until the point they beat the best of us. And so it will go for all human talents.
Right. This may have been a lot to take in, and you might want to reject it. It’s easy to be cynical of the endless and idiotic predictions of futures that never are. So that’s why it’s important to emphasize again that this stuff isn’t science fiction. The robots are here right now. There is a terrifying amount of working automation in labs and warehouses around the world. We have been through economic revolutions before, but the robot revolution is different. Horses aren’t unemployed now because they got lazy as a species, they’re unemployable. There’s little work that a horse can do to pay for its housing and hay. And many bright, perfectly capable humans will find themselves the new horse, unemployable through no fault of their own. But if you still think new jobs will save us, here is one final point to consider.
The U.S. Census in 1776 tracked only a few kinds of jobs. Now there are hundreds of kinds of jobs, but the new ones are not a significant part of the labor force. Here’s the list of jobs ranked by the number of people who perform them. It’s a sobering list, with the transportation industry at the top. Continuing downward, all of this work existed in some form 100 years ago, and almost all of them are easy targets for automation. Only when we get to #33 on the list is there finally something new. Don’t think that every barista or white collar worker need lose their job before things are a problem. The unemployment rate during the Great Depression was 25%. The list above is 45% of the workforce. Just the stuff we’ve talked about today, the stuff that already works can push us over that number pretty soon. And given that even in our modern technological wonderland, new kinds of work aren’t a significant portion of the economy, this is a big problem. This video isn’t about how automation is bad, rather that automation is inevitable. It’s a tool to produce abundance for little effort. We need to start thinking now about what to do when large sections of the population are unemployable through no fault of their own. What to do in the future where, for most jobs, humans need not apply.
Professor Groth: Okay, so as I prefaced, this movie is intended to stimulate you and to provoke you. But it isn’t science fiction, and a lot of real research work is going into what kind of world will be emerging when digital will become ever more disruptive and pervasive in our daily lives. You may have seen this article in The Economist magazine a while ago that essentially predicted that we need to retrench into roles and occupations that are safely ours and that are safely defensible against computers. Right? So this will be a world of artists and therapists, love counselors and yoga instructors, as The Economist, tongue in cheek, pointed out. While that may be overstating the case, directionally it’s not wrong. When you look at the list of occupations here on the right, they are low in probability at the top in terms of being replaced by computers anytime soon, and very high in probability toward the bottom. You will notice that, with some exceptions of course, the ability to combine hard skills with soft skills will come at a premium and the more mechanical, the more purely structural, analytical your jobs are, the more you are at risk of being displaced over time.
Like I say, lots of work is going into this. A colleague and I are in fact writing a book about the future of artificial intelligence, and how it could solve some of the most wicked and complex problems in our world, and how it might lead to a new era of human and economic growth. But the fact remains that we need to master these challenges. Benedikt and Osborne pointed out that as much as 47% of all occupational categories today may be going away. You may have heard of Piketty in Paris who wrote a much-acclaimed book the year before last about the emerging class of supermanagers, while the rest of us will be either sitting on a couch or subject to their judgment.
There are many other scholars, renowned scholars from renowned institutions that are saying in order for us to deal with this, even if we believe that these predictions are too dystopian, too negative, is to adjust our education systems, to adjust our business models such that we become more complementary to computers, not competitive with computers. So then how do we act upon this and how do we address this in our training of future leaders, i.e. you, at Hult? We do this by combining content teaching, the hard facet, with soft skill or competency development. Let me take a look at…let us take a look at, for instance, the strategy process.
So in the course, Global Strategy, we are teaching an upgraded version of how a strategy should be conducted, and is conducted by some companies around the world. The traditional strategy process, if there is such a thing, because we obviously have to acknowledge that every company has its own version of a strategy process, if there is one, but if we were to overgeneralize, it might look something like this. If you are being tasked with a strategic question, you are likely expected to have an initial hypothesis in your mind, a mental model as we call it, to what the answer might be. You’re being expected to have that because of your experience, because of your judgment, because of the trajectory that the firm has been on, and the expectation generally to make decisions fast. Then you consider industry-specific data, and you analyze and slice and dice that until you reach some conclusions about how to refine your hypothesis and update your mental model.
That usually get codified, as it were, built into business plants, quantitative business plans. This is where 30, 40 page spreadsheet calculations come in. And at the end of the calculation, you will usually be expected to have a number, or a narrow range of numbers, whether that’s NPB or ROI or market share, whatever your key metric is. However, we have just seen that the world is uncertain. So how do we now embrace these diverse perspectives to catch that uncertainty, to hear from people who can tell us what the future might hold, to get these what we call “orthogonal” inputs? Meaning these are inputs from fields that are not your field, that may be adjacent to your field, or that may have some impact on your field of business. Well, one thing we have to do is we have to look beyond the immediate areas of expertise that we hold.
Necessarily, most of us grew up in a very economic, business paradigm. Many of you will be engineers. Some of you might be social scientists. But the prevailing paradigm is such that we are driven by economics and by technology. We need to look much broader. It’s become apparent that we need to understand our mental forces much more, because they will drive regulation, social and political, legal and ethical, forces are increasingly determining our business environment. We can no longer escape this. We need to become responsible global business citizens. We need to also take a long view. That means we need to look beyond the quarter. We need to look beyond the fiscal year. We need to look at the future beyond even the duration of our business plans, whether they are one year, three years, or five years.
Taking the long view does not mean that we engage in science fiction. It means that we are opening our brains to the plausible things that could be happening in the future to then bring those back and understand what they might mean for our business today. Because, and I quote a renowned scholar, “the future is actually already here, it is just unevenly distributed.” Meaning we can see indicators of the future today. It is evolving as we speak. But it isn’t quite yet manifested at scale.
So then this is the process that we pursue in this course. We open up our aperture, to use a photography term, our lens to explore these STEEP/STEEPLE trends, and then we make hypotheses about how the market environment might evolve. So, we might have three different scenarios on the market that are all very divergent, all very different. We hold those in our minds at the same time. Then crafting decisions, strategic moves, for each one of these futures and across to make our strategy more robust. That may seem counterintuitive to you, but it can be done, and it is being done by very well-known companies like General Electric and UPS. This is the process. I will not step through this here, but we arrive at these four market futures through a structured, rigorous process that combines both creativity and analysis.
Now, coming back to that main topic then, as we explore these trends which is step number one, that might determine the future of work and productivity. You can come up with lists of 80, 100, 120 drivers in these STEEPLE categories, and many of these will seem familiar, such as the ones here in green. Economic resources for IT investments, scientific advances on AI and brain neuroscience, digital natives. Many of you are digitally native and are driving innovation and disruption today. But then there are those in orange that you may not have readily expected such as education reforms, faith-based initiatives, zero marginal cost on energy and connectivity. All of these have implications for the future of work and productivity and how artificial intelligence will evolve.
Next we then construct alternative futures, we understand how our industry ecosystem will evolve in each future, and then we say we craft decision portfolios against the backdrop of these changes. This is an image that signifies how we craft market narratives, how the market will evolve over time, and it doesn’t really matter whether your horizon is 2020, ’25, or ’30, or even ’35, what matters is that each one of these trajectories is plausible. That it is rich in data, that it follows a logic that we know today or at least leads us into understanding a new market logic. But none of these are so far out and so unbelievable that they are no longer plausible to business decision-maker.
Then we place established strategy tools into each scenario such as the Porter Five Forces that help us analyze the industry look at the connections and relationships between the forces, and we say, “How will these evolve to meet the emerging customer needs of the future?” We then craft options, slates that are organized in paths or trajectories that we can execute. So we will tell each other how we will start to create early optionality, how we will build our business in the future. The different colors signify different types of moves. The purple ones here are moves, they are actions or investments that are robust across all emerging market futures, whereas the big red one for instance is a bet that we are placing for any one given market future to evolve. Much higher risk, potentially much higher payoffs.
So finally then let me tell you that we have a program here at Hult that will address this combination of hard and soft skills. You will get the methodologies, the frameworks, the analysis, and you will get the soft skills. How to formulate purpose in a team. How to coach and teach each other. How to advocate for ideas, how to dialogue with each other so that different people are heard. How to elevate each other’s imagination and ideation. We have heard from about a hundred executives around the world, all with MBAs, that we need to increase the degree to which we play on creativity and imagination as the future evolves. We need to teach you how to conduct cross-cultural navigation and negotiation. How to be a commercial diplomat, integrating the various interests on the part of not just business decision-makers but civil society out there, and we need to increase your capacity for emotional intelligence. All of this is in fact being addressed by the Hult MBA. And especially the soft skills track that runs in parallel to the hard skills track. And it has gotten attention out there. One of the major accrediting bodies, the Association of MBAs, AMBA, has awarded us with an innovation award recently for this combination.
So then all of this is obviously only as good as the lifelong learning agenda that it develops for you. We want to be there for you longer-term. We want to have that impact on you. We want you to continue to monitor the trends that you learned about here at school. We want you to track indicators, we want you to continue to have a “Hult reading list” for the rest of your career. We want you to develop techniques that allow you to manage others, to build networks of customers and stakeholders, that enable you to foresee plausible futures and to manage your businesses in a more sustainable and robust way.
So as with all of my students I would encourage you to keep in touch now, during your degree, or after your degree, and let us know how what you heard here or what you might be experiencing on one of our six campuses around the world, how that helped you. How we could help you in the future, how we can continue to improve our programs to be relevant to you, and to equip you to be robust and successful in a volatile VUCA future. Because it is that learning, and it is that impact we want to have, and we want to be that most relevant business school that helps you do this. So with that, I open up to Q&A, and thank you for your attention.
Eriko: Thank you Professor Olaf. I’m sure it was a lot of good information to take, and everybody’s… something, it’s a topic that makes you think a lot. We do have a couple of questions. This question is from Ipal [SP]. “Is the STEEPLE the most appropriate tool for strategic planning?”
Professor Groth: It’s a good question. There are many tools for strategic planning. This one is particularly valuable because it forces you to think in dimensions that you are maybe to this date not trained in, and that you haven’t been rewarded for. And so we need you to open up your personal point of view to these other fields. And so it is merely a prompt to think more multi-dimensionally. And it is beautifully flexible because it connects very well with most other strategy tools that I know.
Eriko: Is there any other questions? Please feel free to type the questions in the chat box. Okay, there was another question here, from Anna. “First, I’ll be incredibly honest and tell you that this job is pretty…” Let me just check. Hold on. I lost the question. Okay, the question is here. “It is easy to overestimate futuristic tendencies. How do you adequately adjust for this?”
Professor Groth: Yes. So, all of us like a good thought provocation, and we have been to the movies, and those movies are inspiring, sometimes they’re scary. And in reality the future is much less either utopian or dystopian. The point is not to try to envision the extreme. The point is to envision a path that is likely going to be a much more moderated path. Why will it be moderated? It is because we will take influence. Human beings like to shape their environment. We like to have a say in our future, and so the way to moderate and to shape is to get involved and dialogue, to design businesses that can actually shape these trends so that they are not unnecessarily dystopian.
Eriko: Okay, we have the question again from Anna. She’s basically a graphic designer, and one of the key questions she asks herself in each campaign in the advertisement is “Who is my target audience?” But in a conclusion from the talk, it seems that population is increasing, but they’re highly going to be unemployable, so who do you think the largest target audience for her would be?”
Professor Groth: The largest, I’m sorry Eriko, the largest target audience for a designer?
Eriko: Yes.
Professor Groth: Yes. So, design thinking, and of course I would have to know more about what is meant by “design,” but design thinking is a tremendously important skill and competency to have. In fact, this strategy framework combines hard analytics with an anthropological or an ethnographic design thinking capability, about how people will live each other…will live their lives, and what their emerging needs might be that we can address as business people. As such, design thinking is of key importance to decision-makers to design solutions, and I have seen this skill set apply to many different sectors out there that are both B2B, business to business, and business to consumer. So my answer to you is, it’s a limitless array of potential audiences out there.
Eriko: Okay, the next question is from Yaya [SP]. “What are your views about innovations like Uber? In this case, robots not replacing humans.”
Professor Groth: Yeah, so I think honestly there is much resistance to Uber in a number of countries around the world. Uber is not available in a lot of countries both developed and developing. And Uber has also not been successful in a few places around the world, but overall we’re seeing a sustained trend towards the sharing economy and toward a more automated sharing economy. So I believe that there will be a backlash, because people will in fact lose jobs. Uber has been testing driverless autonomous vehicles at Carnegie Mellon. These are Volvos that are driving around. They will still have a person in them, but it’s merely to assure us that the vehicle is safe. So we are already looking at a future where automated driving will replace labor, and we need to as business leaders proactively work with government, with nonprofits, to make sure that these individuals get retrained and find better jobs. And as the speaker in the video said, this change will happen quicker than we think, and society’s systems are usually working much more slowly. So this is where we as entrepreneurial executives are really challenged to help mitigate this now.
Eriko: Okay, the next question is: “Based on the current scenario and your statement ‘the future is already here,’ what and how do you see human and technology partnership to be like?”
Professor Groth: I believe that we need to be complementary to each other. There are things that machines just do a lot better with a lot higher degree of reliability and much fewer mistakes. And so I think what we need to do is, we need to develop the governance systems that includes values-based judgments. Computers don’t have values unless they are programmed into them. We need to tell computers what the value systems are that we want to see in place, how to treat human beings, how to optimize decisions in favor of human beings’ well-being. Those types of formulations of purpose, of human spirit, of human values, of ethics, and then the optimization of that against economic growth and gain. So the human growth combined with the economic growth, that is our formative challenge. So we have to be the masters of that.
Eriko: Okay, the next question is from Valeria [SP]. “Would you please give us a practical example of what kind of jobs we will be preparing…we should be preparing ourselves for in the future?”
Professor Groth: This world is increasingly global, and most of you have been born into the global world, but there is lots and lots of tension and conflict. People have jobs that require you to have the core business skills of analysis and good business judgment, economics, management techniques, but then beyond that you will have jobs that will manage this conflict hopefully towards good creative tension. So, being able to manage people well, understand them, probe for their interests, and integrate that will be a paramount business skill. I think increasingly leaders, global business leaders will be prized and valued for that skill.
Eriko: Thank you. We have a question from Frederick, she has two questions, or he has two questions. “In what way would you see Nigeria having a great economic role?”
Professor Groth: I believe that the future of Africa is bright. Yes there are problems, but there are problems everywhere we look today. And I believe that there is much innovation potential in Africa to design African solutions for Africans. So the era of us just exporting industrialized country solutions to these countries…to these developing countries or emerging markets, that era is over. We need to engage locally, and I believe that Nigeria with its talent pool, with its resources, if it is able to deploy the resources away from oil and gas into higher value-added resources, that innovation-centric resources, training and education, advanced infrastructure, I believe then that Nigeria would be ideally placed to help lead the innovation economy of Africa.
Eriko: Okay, and the other question from Frederick. She asks: “Do you have an example to clarify exactly what design thinking means?”
Professor Groth: Design thinking means that we need to understand that a human being, whether that is a businessperson or a consumer, or somebody who has very little to do with either, but is an influencer in society, how people like that tick. How they work, how they function. What their daily pain points are. What kinds of problems they’re trying to solve. What kinds of aspirational challenges they’re trying to meet. What are their desires and dreams? And to then say, “How does their life work? What are the forces at play? And how do we integrate into that?”
Rather than designing a solution that, in my head, as a businessperson or as a product engineer or product developer, is a great product, rather than pushing that out and hoping that it will stick, take a very human-centric approach, and design solutions that fit into people’s lives. That’s in a nutshell the essence of what design thinking helps to do. And it’s very, very multifaceted. Looking at economics, looking at marketing, looking at anthropology, looking at life patterns. Looking at both emotional and hardware content in a product.
Eriko: Okay, I think we have one more question from Sandra. She asks, “Emotional intelligence is a big factor at work. How do you see the auto industry, for example, mimicking humans emotionally?”
Professor Groth: So the automobile industry is currently… most auto makers have understood that. I work with a number of them. Their pace of decision-making is slower than the internet companies that are driving the disruption for the most part. But there are auto makers who are quite advanced in integrating a human being and integrating emotional intelligence aspects into their products. And so you will see car environments that integrate the human being’s, the driver’s life pattern data, meaning what is going on in their lives outside of the car, into the actual car experience such that they will be able to enjoy the drive better, make the drive safer, or be productive or entertained in the car.
Understanding the essence of that human being is done through, of course this life pattern data, but also sensors in the car. And auto makers are very much investing in that now, working with startups who are working on these solutions. The car will be able to sense your state of emotion, whether you are agitated or relaxed, your state of energy, whether you are tired or whether you are very much present. And it will contextualize that with everything else that’s going on around you, including the traffic situation, to help you steer that car and drive that car better. So that’s very much underway, and it’s a very, very exciting domain to work in.
Eriko: Okay, we have time only for a small question. Regarding… what is your view [inaudible 00:56:21]
Professor Groth: I apologize, Eriko, but you were dropping. Could you please repeat the question?
Eriko: Sure. The question is, “What is your view on some political forces recognizing potential in protecting human labor against disruptive innovation?”
Professor Groth: Oh, the political forces are very significant. They always have been through human history, and they serve to slow disruptive change down. And there’s good reason for them, and I have a great deal of empathy for them. Large-scale layoffs putting people into poverty and personal distress does not serve anybody very well. A poor out-of-work worker does not make for a very good customer, and it also triggers my empathy on a purely human level. So I have great understanding for the political forces at work. However we need to recognize that slowing down, buying time, and retraining this labor is valid, but trying to prevent the disruption from happening, trying to defeat the technology has never worked. And so to me it’s a matter of adapting and buying time, but not about avoiding or defeating the technology.
Eriko: Okay. Thank you, professor. There have been some other questions, but what we’re going to do, we will forward these questions that were not answered in the webinar via email to the professor and we will send you the answers after the call in the next few days. I wanted to say thank you for…
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