Patrick Schwerdtfeger is a keynote speaker who can cover technology trends and disruptive innovation at your next business event. Contact us to check availability. The full transcript of the above video is included below.
Full Video Transcript:
Technology trends. There’s a lot of prevailing trends that are coming up right now and they’re affecting all areas of our economy, and let’s just jump right into the deep end. I’m not going to share a lot of charts this morning but I will share one, and here it is, here.
So what we’re talking about is the cost of storing one petabyte of data. A thousand kilobytes is a megabyte, a thousand megabytes is a gigabyte, a thousand gigabytes is a terabyte, a thousand terabytes is a petabyte. So the cost of that in 2010 was $80,000. Does anyone want to hazard a guess on what it’s projected to cost in 2020? Just throw out a number. Yell it out if you have a guess.
I’m sorry? One thousand. Wow, that’s ambitious. Anyone else? Hundred dollars. One more… I’m sorry? One dollar. Okay. Well, we got the range. We got the range, and the right answer is four bucks. So this might be my best slide.
So seriously, just chew on this for a second. This is what’s happening. This is what’s happening in our economy and we are truly in an exponential environment. And it’s not just happening in data storage. It’s happening in data processing, it’s happening in data bandwidth, and it’s happening in data storage. So we have this really exponential environment. And when people think about exponential environments, they always think about how the curve goes up like that, which it does, right? But the inverse of that is that the cost of any one capability plummets. The cost structure in the data environment is collapsing. It’s getting cheaper and cheaper. So you get all these really—
Some of these are kind of cliché analyses of exponential, but I’m going to share one. I’m sure some of you have heard this before, but imagine if you had a pond and on that pond lily pads start to grow on the pond and every day the number of lily pads on the pond doubles. So on the 30th day, the pond is 100% covered in lily pads. So the question is, on what day is it only 50% covered?
Twenty-nine. You guys are accountants. I knew you would know that.
But the bottom line is, this is a function of exponential thinking. Guys, as human beings, we are hardwired to think in linear terms. We have to train ourselves to think ex—I do it myself. I mean, we all individually have to constantly train ourselves because our instinct, I mean, truly, our instinct is to think in linear terms. So we have to train ourselves to think in exponential terms. It’s part of what we have to do as leaders to be—a good leader in a lot of ways is to be predictive, is to be able to look into the future, and if you want to do that today where the single biggest driver in our economy right now is technology, then you need to think in exponential terms.
And there’s a lot of examples of this. [00:04:00] Here’s one that you’ve probably heard of as well, which is the Human Genome Project. So the Human Genome Project was started in 1990. That’s when they started it, and in 1997 it was 1% complete. And so all the pundits, all the doctors and scientists that were involved in this process, were like, “Oh my gosh, we’re going to need 700 years to finish this.” “It took seven years to get to 1%. We’re going to need another 700 years to get to the end.” But that’s not what happened, is it?
And some people saw it. There’s actually one guy, I’m sure some of you here follow Ray Kurzweil, really fascinating guy. He’s the guy who wrote the The Singularity. Really fascinating guy, works for Google today. Anyway, he said, “No, if we’re at 1%, we’re almost done.”
Think about that. If we’re at 1%, we’re halfway there. Because if you’re scaling at 100% a year, if you’re doubling every year like those lily pads, 1% is how many years from 100? Six and a half, right? First year – one goes to two, to four, to eight, 16, 32, 64, you got there.
And that’s exactly what happened. They finished it in 2003. We’re scaling at 100% per year. We actually came in and had a schedule. That’s what happens in an exponential environment. We are living in an exponential environment and there are things that are scaling all over the place.
Solar is a great example. Solar power today accounts for less than 1% of our global energy production, but it’s scaling too. So the global energy consumption, by the way, is growing at 1.8% a year, roughly. Right now solar is scaling—it’s not scaling at 100% per year—it’s scaling at 25% per year. But if it continues, and we don’t know if it will—we don’t know if it will—but if it continues to scale at that rate, by 2041 it accounts for our entire global energy consumption, if it continues at the same rate it’s going.
By the way, regardless of who’s in the White House. I mean, it has nothing to do—guys, this is technology. Like, I get the political chaos or however you want to discuss that—that’s fine—but this is technology. This is going to happen either way. Technology’s going to move forward either way. And you saw this slide yesterday, this is a really—Moore’s law. Moore’s law has been going on now for more than 50 years. And things are changing right now or butting up against some obstacles. You know, it’s down to 14 microns right now, so you can’t get much closer together than that, but there are other design implications which are effectively continuing the net effect in terms of processing power and the effect of this or that processing power.
But the bottom line is, you learn that innovation is a function of capabilities. Innovation comes when the capabilities can support it. So when you have these kind of environments where the cost structure in a given part of our society is plummeting like this, what it means is that everybody is going to be in the data business in the next five to 10 years. Everybody. All your clients. Think about all your clients. And the data’s coming to them from all these different angles; we’ll talk about it.
But one of the biggest areas of innovation right now as you’re all aware is the IoT, the Internet of Things, and more importantly perhaps is the Industrial Internet of Things, they call it. Some people call it M2M. And there are projections that we’re going to have 50 billion devices connected by 2020, and now there are people saying we’re actually going to beat that number. And so we’re getting all this innovation. There are tons of different sensors that are being produced by a million different companies for different situations and different environments, and all the latest developments and the focus of the research today is on long-range and WiFi and getting power through WiFi and low power and security and low cost and so on.. And then, so the data is being aggregated as coming to these businesses of all levels through their ERP platforms.
One of the biggest ROIs in the big data space today is in predictive maintenance. That’s kind of the lowest-hanging fruit. Again, think about your clients. We’ve only got an hour together, guys, so when we talk about these things, think about the implications. Is this relevant for your client? The whole point is, how do we expand the conversations you’re having with your clients? You guys have a seat at the table with the CFO, some of the most powerful people. CFO is usually the number two person in the company, and you’ve got access at that point. So how do we widen that conversation? That’s what this session is about, to give you some ideas of things you can talk about.
Predictive maintenance is the lowest-hanging fruit in data today. That’s where the positive ROI is coming from. And we’re seeing implications in manufacturing. We’re seeing implications in the distribution sector. We’re seeing implications in mining, of course, unbelievable implications in mining, oil and gas, refineries. We’re seeing implications in the alternative, the renewable energies, like the solar farms that are being produced, wind farms as well. It’s having huge implications in facilities management. This room probably has 200 sensors, at least, that are being aggregated somewhere.
Probably the best example of facilities management in terms of data right now is the Hudson Yards project, which is going up in New York City right now. It’s got to be the most sensored residential environment in the world when it opens, but of course that won’t last long because there are other projects coming out which will have even more. And then all this data’s being aggregated into the smart grid. Probably the best example of that today is Singapore. Unbelievable, the things they’re doing. And they’re not the only ones that’s happening right here in our country as well. So we truly are in this exponential environment.
So what I’m inviting you to do for the next, I’ve got basically 45 minutes left, is to take a step back. Now, you all have your clients, you have your goals, your milestones, your deadlines, quarterly earnings calls. The next 45 minutes, just take a step back. And it’s my job to look at these trends. It’s what I do every day. I look at the case histories, use cases, success stories. Where is the venture capital money going? Where is the private equity money going? Where is the positive ROI? That’s what I do every… I love what I do. Guys, I’m a nerd, I’m a geek, so geek out with me.
There’s this concept, it’s called institutional blindness. So when you work in a particular field giving company and industry whatever, you end up within three weeks—actually, the research is really fascinating—within three weeks you already start to have kind of tunnel vision. You have blind spots because you’re so focused on your goals. It makes sense. There’s nothing wrong with that. It’s a natural process. But the value of a session like this, what we’re doing today, is to get out of that silo and just have a look and see what the greater environment, what does it look like out there? What’s actually happening?
And let’s start with a few stories. This is a great one. Does anyone here recognize these two guys? Really? Okay, good enough.
Well, let’s start with the guy on the left. His name is Brian Acton, and Brian Acton in 2009 was looking for work and one of the places he applied to work was Facebook, and Facebook turned him down. And he’s actually a really gracious guy, if you follow me. So he’s a good guy and he wrote a tweet about this at the time. This is what the tweet said: “Facebook turned me down, the great opportunity to connect with some fantastic people. Looking forward to life’s next adventure. What might that be?” Well, he got together with a friend of his and started WhatsApp, which they grew over the course of five years and sold to none other than Facebook for a cool $19 billion. So, I’m bitter. I admit it. And I’m 46 years old. I mean, he’s a lot younger than me. Anyway.
So the pundits were out in full force, of course, when this happened. It was an unbelievable transaction. I’m sure you guys probably remember when that was announced. And they all had different viewpoints of this and different ways of looking at it, but one way is that at the time of the sale the company had 55 employees. So, by that measure, Facebook paid $345 million per employee. Imagine. Another way to look at it is at the time of the sale they had $450 million active monthly users. So by that measure, Facebook paid $42 per user. But regardless of how you look at the finance side of this, it’s an awful lot of money.
Maybe the most interesting way to look at this though is that over the course of five years—five years, it’s not that long—over the course of five years, 55 employees managed to engage a half a billion people. They built something that touched the lives of a half a billion people. How many people are in this room? Three hundred? Fifty-five people. How many people are on your teams respectively that you work with every day? In five years, 55 employees built something that touched—and it speaks to the leverage that’s in the system today. Guys, every time you hear a presentation from a speaker like me, there are always a few messages that he or she is hoping that you’ll walk away with and this is one of mine: Leverage. There is more and more leverage in the system every day, and a lot, it’s not all technology, but a lot of it is technology.
Guys, there’s a revolution taking place right in front of our eyes and most people don’t even know about it. They don’t even see it. You know all these stories about the division between rich and poor? We see these things in the evening news or on the Internet blogs, whatever? Those are things are true. The division, it’s widening. It’s incredible. The top end is exploding.
It’s a function of this leverage. That’s why it’s happening and there is a very real dynamic at play right now, around the whole world in fact, not just here, where people, some people and some businesses, are leveraging the technology and doing extremely well, and on the other side, sadly, there are a lot of people who are being leveraged by the same technology and for them it’s harder and harder to eke out a living. Diane just talked about this, right? So for them, it’s really hard to eke out a living because all this technology is essentially being used against them. They’re being replaced by it. And we’ll talk about that in a second. But it’s a function of leverage, and we all as individuals, not only as individuals but also as a company, it is our responsibility to make sure that we are always on the right side of that leverage equation, which means we can’t be afraid of the technology. We have to embrace it. We have to run towards it, which is scary. But that’s where the opportunity is.
And of course, this leverage, I mean, there’s a million examples. Software is a form of leverage. You can leverage software. The cloud is a form of leverage. You can leverage the cloud. You can leverage mobile technology. You can increasingly leverage wearable technology, fascinating technology that’s coming up right now, really interesting stuff. Virtual reality’s right around the corner and it’s coming fast right now, and everyone thinks it’s just video games but there are so many training applications, things that people can do to use VR to reduce their training costs.
And of course, robotics is coming up like crazy. The cost of the Baxter robot continues to go down and sales are going up. This is another robot that was introduced a year and a half ago, sold out immediately.
Here’s an Amazon distribution center. They have thousands of these blue shelving units, with every product you can imagine of course, and there are not people going into the aisles down into all of these blue shelving units to get what they have to get. Instead, the shelving units are picked up and brought to the front by these little navigation robots—there’s only a handful of employees right at the very front—and then the shelving units are brought right back to where they came from. It’s incredible.
This is the Tesla factory, right here in the area. It’s just a few miles down the road from where I live. Guys, this would never be possible in California. California is not a factory-friendly state. The only reason this is possible is because of robotics. There’s hardly any employees in this factory at all, although there is one. You just pointed it out to me a month ago, right there. I never even saw that myself.
Anyway, here’s another view of it. Guys, if you live here or if you visit or even on this trip if you have some spare time, get a tour of this factory – your brain will explode. Any opportunity you can to get a tour of these things, these facilities, things people are doing, take those tours. Your brain will explode. It’ll blow out your vision of what’s possible, what’s happening today. Fascinating stuff.
Tesla’s now building their Gigafactory in Nevada. You guys hear about this? Unbelievable. This one factory is going to more than double the production capacity of lithium ion batteries of the entire globe – China, India, US, all of these. Thailand is a huge producer of lithium ion batteries. This one factory—and it’s huge, this is the way it’s going to look when it’s done and they’ve only opened this top section right here and it is literally, I mean, it is an enormous facility—when they’re finished, it will be the largest building on the planet.
By the way, it’s not the largest building by volume. Does anyone know the largest building by volume? I’m sorry? Boeing. Absolutely. Absolutely, the Boeing Everett facility. So by volume that’s the largest building, but by footprint this is going to be the largest building on the planet when they’re done and it’s going to more than double the production capacity of lithium ion batteries. Guys, that is a sea change. Really, really fascinating stuff.
So, I love quotes. I literally buy books of quotes. It’s something I’m…I’m really passionate about that, actually. This is one of my favorite quotes. It goes, “The future is already here. It just isn’t evenly distributed yet.” Stuff is happening already. I mean, guys, we don’t have to reinvent the wheel. That is not our job. Our job is to look at the cutting edge, to look at the bleeding edge, what’s happening at the forefront, and learn from those—because the cost structure comes down, right? The first people pay the most, but then over time their experience, their trial and error, makes the cost structure come down more efficient. We learn from their experience. So we have to keep our eye on who’s at the leading edge.
One of the most interesting things to follow in recent years has been artificial intelligence and machine learning. Everyone wants to talk about machine learning. And it’s fun, and I’m going to go through it with you because I think it’s really important, actually – the reason this is such an interesting thing to look at is because it’s really easy to see the milestones and how those milestones are accelerating. So it’s really easy to see where we’ve come from. And you’ve heard these stories before, but again, make note of the timing from it.
So way back in 1997, that’s when Deep Blue won Kasparov at chess, right? Fourteen years later was when Watson won at Jeopardy. Big lag there. Then it was literally later that same year when Apple introduced Siri on their phones. It’s an AI, right? Absolutely. And then Google followed suit the following year with their Google Now, and then it took Microsoft a couple of years to catch up with Cortana, which they did in 2014. And then the following year, in 2015, that’s when Tesla introduced their autopilot system in their cars. That’s an AI, guys. Self-driving cars, we’re going to talk about it. It’s coming way faster than people realize. The technology’s there.
So last year, the Olli bus started running in London. Particular neighborhood; it’s not the whole city. It’s a beta test. They’re looking for a proof of concept. Watch the proofs of concept. Where are people testing the new technologies? So the Olli bus started last year in London. They’re testing it. Later that same year is when NuTonomy started launching their autonomous taxis in Singapore. So proof of concept. They’re testing it in a particular neighborhood. They’re getting the data. They’re analyzing the data. They’re improving. And then literally the next month is when Uber started their pilot in Pittsburgh with the self-driving Uber, in Pittsburgh and other cities as well now. Later this year is when the Google autonomous vehicle is going to be launched to customers, or at least when it’s expected to. Ford has announced that they are going to have an entire fleet of cars available for the public in 2021. Guys, that’s 24 years from now. No steering wheel, no pedals. Unreal, right? So Volkswagen has shown their Sedric, their new concept car for self-driving cars, and there are all kinds of startups.
This one’s really cool, really fascinating actually. They’ve raised a ton of money. And it’s configured exactly the same way whether it’s driving forward or whether it’s driving backward. Because it’s autonomously driven, it really doesn’t matter. So inside the people actually face each other.
What happens? What happens? When sorts of technologies come, what happens? So here’s the thing: Cars. How many have a car? You guys all have cars. Where are your cars right now? They’re parked. Your cars are parked. So cars are one of the lowest utilization rates of any large individual purchase. It ranges, of course, but the average utilization rate of a vehicle is 6%. That means 94% of the time it’s parked. People aren’t going to buy cars in the future as much. It’s going to start in the urban centers, rural will lag behind, but the bottom line is you’ll have this subscription where when you need a car, maybe your subscription is a thousand miles a month or 1500 miles a month or whatever that number is, and you call a car and it shows up, it picks you up, takes you where you’re going, drops you off, and then it picks someone else up and keeps driving. It doesn’t park and it just keeps driving all day.
So what happens? Guys, 30% of urban traffic is people looking for parking. It depends on the city. Here in San Francisco it’s probably higher. Thirty percent of traffic is people looking for parking. So there are some people who are hypothesizing that in the years to come—it’s going to take a while. The fleet replaces itself on average once every 11 years, and of course the adoption rate has to go up as well. So it’ll take time, but there are people hypothesizing that the car sales are going to drop by 90%. I’m not saying that’s going to happen. So start thinking. This is exponential thinking. What happens in the future? What could happen in the future? These are the sorts of things we’re talking about. Really fascinating.
And then of course last year, I’m sure many of you heard about the AlphaGo victories? For anyone who didn’t, Go is a board game, like chess. So it’s actually infinitely more complex than chess, but people put them in the same category. But the experts in AI and so on, they thought that it would be another 10 years at least, maybe 20, before an AI figured out how to play this game because there are so many different ways the game can play out. You really can’t actually mathematically calculate all the different options and then rank them by some sort of priority scale—you have to do it a different way—and so they used machine learning as a way to do that. So what is machine learning? Guys, this is a perfect example. This is unreal. And I’m sure many of you work with these technologies already, but again, think about it your clients. Think about what’s possible because this is coming in a hurry.
So here’s what they did. This is incredible. So they built a platform and they initially gave the platform a hundred thousand human games that had been recorded from contests or whatever, and the objective for the platform was to mimic human behavior. Mimic human behavior. Then—and this is where it gets crazy—then with that knowledge that the computer had, the platform had, they allowed the computer to play itself 30 million times, way more than any human could possibly play in a lifetime, with a different objective. And the objective was to avoid past errors. The simplicity of this is deceptive: Avoid past errors. And after that, they beat the world champion, with those two steps. And they did that last year, last year in March, this guy Lee Sedol. In fact, they just beat another world champion in China literally last week.
And so then, here’s where it gets insane. So then the developers, which came from a company called DeepMind, which is based in the UK by the way, purchased by Google in 2014—brilliant, brilliant people in this organization. Anyway, the developers went into the logs to see how the computer decided on the moves that it made and they could no longer figure out what the computer was doing. So it’s just a matter of time. I mean, there’s a lot about these dystopian futures. But seriously, I mean, how crazy does it get? MIT: An AI software learns to make AI software. Fastest super-computer in the world today is in China, running 3.2 million Intel Cores. Three point two million Intel Cores.
Guys, we have to train ourselves. As leaders, as individuals, you’re leading your team, you’re heading your client discussions, you’re planning what discussions need to take place in the future, we have to think exponentially. Proof of concept, proof concept. Where are people testing the technology and what are the implications of those tests?
So last year, they tested an autonomously driven truck, Otto, which was purchased by Uber, which drove 120 miles in Colorado, down to Colorado Springs, to make a delivery autonomously driven. There was someone in the cab but he wasn’t driving. Payload was 50,000 cans of Budweiser. What happens? Last year they did a proof of concept in Europe where they drove these three trucks right across Continental Europe through a whole bunch of different countries autonomously driven. Guys, there are 3.5 million truck drivers in this country. There are 3.5 million truck drivers in this country.
What happens? Guys, this most recent election and the disruption we saw and the anger and the frustration in pockets of our society, we are just getting started. Change is coming. But of course, we’ve been through these changes before. This is not the first time. When cars came out, that was a huge innovation. Before that, we had horse-drawn carriages. So it was a huge disruption. We ended up with a lot of unemployed horses.
But people are different. People are smarter than that. They react differently to what’s possible. So let’s look at the agricultural industry where, of course, in the 1700s we had 90% of jobs were in the agricultural sector. Today, it’s less than 2% that are in the agricultural sector. So at the time, everyone’s like, “Oh my gosh, where are all these people going to work?” But nobody would have imagined that we’d have a service economy that would explode with a million different occupations like nurse practitioner and contractor and massage therapist and yoga instructor and life coach and all these thousands of things. People are creative and people want to work. As human beings, we want to be productive. We will find new things to do.
I’m not saying that the world’s going to come apart at the seams. It’s not true. Change is coming. It doesn’t necessarily mean that it’s going to fall apart. It means that we have to be ready for that change. Guys, it’s going to be winners and losers. Let’s just make sure we’re winners. I mean, let’s make sure we’re on the right side of that leverage equation.
One of the best examples is when they introduced the ATMs in the 1980s, and everyone was thinking, “Oh my gosh, all these tellers are going to lose their jobs.” Did that happen? No, it didn’t happen. In fact, the number of tellers actually increased, at a slower rate but they continued to increase. Why was that? Because when you let a lot of these basic transactions like withdrawals and deposits get handled by computers, it makes it cheaper to open a branch. And so the banks were able to open way more branches than they had before. So there might have been fewer tellers in every individual branch, but there were more tellers overall and those tellers were doing more strategic activities.
And guys, that is a perfect metaphor or a perfect example, if you will, proof of concept, of what’s going to happen to a million different service professions. A million different service professions are going to evolve where the mundane activities, the repetitive activities, are going to be replaced, allowing the service sector, the individuals themselves, to do more strategic activities. Guys, that’s what you do too. It’s one of the reasons I was so excited to come to this event, because I feel like what you do is actually very similar to what I do. You have to look for the opportunities and present those opportunities to your clients in a way where they want to engage with you to realize that future, to stay on the right side of the leverage equation. That’s what you all do. And if you’re in that side—I speak to groups that are on the other side of the leverage equation and it’s really hard to get a message that they can really, really embrace and grab onto because it’s tricky. But for you, gosh, there’s a world of opportunity out there, for people like you. People need this. These companies, most of these companies have no idea.
So let me introduce a quick model. This is really fascinating. So there are all these frameworks and predictive models that you can use to look at the trends and project into the future. That’s what I do, is I’m super-passionate about this. There are tools you can use to understand what’s coming.
So in the job market, you’ve got manual jobs and you’ve got cognitive jobs, basically two broad buckets. And then you also have, within each one of those, you have repetitive tasks and you have nonrepetitive tasks. So the repetitive manual jobs are going to eventually get replaced by robotics. That’s going to happen. The cognitive repetitive tasks are going to get replaced by algorithms at some point. You can look at your own job and think about what do you do that’s repetitive. You can look at your clients. What do they do that’s repetitive? It may not happen tomorrow, next week, next month, but you know that eventually this is going to happen. And then of course in the nonrepetitive space and manual jobs you need strong humans and you need smart humans, and that’s where the jobs are going to be. It’s people who are in the nonrepetitive space. So it’s going to be the repetitive tasks that get replaced over a period of time by technology, and then you can even map out which tasks specifically are going to get replaced and in what order because we’re working our way up a ladder of complexity with technology. So the least competitive tasks get replaced first, and then over a period of time the technology gets better and better and can handle more complex things. Guys, that’s what artificial intelligence is all about, is working our way up that ladder of complexity. We’re getting into really complex tasks that machines can now handle.
So if you look back, if you look back into the 1960s and seventies, the innovation back then was electricity, right? That was the big thing back then. So what did businesses do? They put electricity into everything. They just took one industry after another and added electricity. Well, what are we doing now? If you look into the twenties and thirties, the innovation now is AI.
So where are the opportunities? We’re going to put AI into everything. And it’s already started. [00:32:41] pretty simple AI, but it knew when I left. It knew when I left. We’re using it already, right? Our email systems are using AI already today. If you’re looking for a movie on Netflix, it’s influenced by AI; Pandora’s the same thing. Of course, there’s AI on our phones now, as I mentioned earlier. And now we’ve got the whole Amazon Alexa, which is one of the prizes that you guys have, by the way, if you get your card scanned. And Google Home.
So how many of you, seriously—and put your hands way up, not for me but for the other people in the audience—how many of you have either Amazon Alexa or Google Home in your homes? Now take a look around, guys. This is roughly, gosh, maybe 10% of the group? If you have an opportunity in the years to come, ask that question again. I promise you in the next three years, the majority, and in five to six years, virtually everyone’s going to have this. We are moving to a world of intelligent everything.
Think about your clients. What can they do? We need to have these conversations with our clients. I do too. Change is coming. There are going to be winners and losers. Let’s make sure we’re winners. These are disruptive technologies.
There are different types of innovation, right? There’s incremental innovation and disruptive innovation. Incremental innovation comes from the center of the field of expertise, disruptive innovation comes from the sides. So let me just give you an example of that. So obviously Apple disrupted the music business and then they also disrupted the phone business, and then Google did the same thing with Android. These are what I refer to as adjacent markets. At the time—now of course it’s a foregone conclusion, no one thinks about it—but at the time, when Apple made these announcements, it was huge. People were like, “Are you kidding? You’re going into music?” And then the phone? It seemed really crazy at the time. Now it’s a foregone conclusion. But this is how disru—disruptive innovation invalidates existing business models. Disruptive innovation invalidates existing business models. It’s not incremental innovation. It’s disruptive innovation.
So what does that actually look like? Well, if you have an industry or a series of industries where you’ve got a bunch of different industries where they’re basically autonomous but they also overlap in certain small places, where does the disruptive innovation come from? It comes from the overlap. It comes from adjacent markets. It comes from the fringe. It always comes from the fringe.
What’s the leading edge of nutritional supplements? It’s in horseracing. Horseracing is where they test the supplements. That’s where they tested creatine. That’s where they tested the impact of D3. That’s where they test all those things that are on the fringe because it’s not regulated and the desperate people who have a horse that’s not quite good enough to win will test anything to see if it might work. They beta-test at the fringe.
You can do this in every industry that you’re in as well. Online marketing. Where’s the online marketing? Honestly, it’s in online gambling. It’s in porn. That’s where they test the newest stuff, and then it infiltrates in. We always have to look at the fringe. We have to look at adjacent markets.
Facebook disrupted the SMS space, and of course that’s what Snapchat did as well. LinkedIn disrupted the recruiting space. It’s an adjacent market. Amazon disrupted the book business with their e-readers, which didn’t exist before. It’s an adjacent market. Uber is disrupting the food delivery business—are you kidding—and Amazon’s doing the same thing with groceries. And now, Google, Apple and Tesla are disrupting the automobile industry. How does that happen? They’re adjacent markets.
What are the adjacent markets to your business, to your client’s business? What are the adjacent markets? People always get in a defensive posture. They’re worried, “Who’s going to eat my lunch?” That’s the wrong approach. You got to be offensive and say, “Who else’s lunch can I eat?” Who else’s lunch can we eat?
Facebook is disrupting the ISP business with these solar-powered planes that they’re going to fly at 70,000 feet, and Google’s doing the same thing with their Project Loon. Guys, disruptive innovation comes from adjacent markets. It comes from adjacent markets. That’s where we have to keep our eye out. That’s what we do. It’s what we do.
So there are some questions that you can ask and, I’ll tell you what, they’re really interesting. So anyway, these are tools. All these things are tools. They’re mindsets. They’re frameworks. I could keep you here for four days with all this stuff. There’s so much. But let’s look at some questions that you can ask.
What’s the biggest threat to your business, to your industry? And you could think about specifically and [00:37:35] your business or your clients. I think the more powerful way to look at it obviously is your clients, but you should do both. What’s the biggest threat to your industry? Number one.
Number two—and you’ll see this again at the end, so you don’t have to write these down, by the way—who is your worst supplier? And again, not just your company, but think about your clients. Who is their worst supplier? Can you do it in-house? Can you do that in-house? Can you eat their lunch, do it better and expand vertically up the supply chain? What about if you go down the supply chain, what else do your customers want? What’s the completely unrealistic thing that the customers in that industry are asking for? One day someone’s going to do it. Someone’s going to provide it. Will it be your client or their competitor?
So disruptive innovation, right? It almost always comes from the least profitable business segment. So what are the pain-in-the-neck clients? What are the ones that are, oh, they’re such a pain, the worst clients? What do those clients want? This is incredibly strategic. You sit down with your clients and you ask that question and they know right away. I’ll bet you know. Which clients do you hate the most? You know who they are.
What do they want? Someone is going to provide what they want. So it should be you. Don’t let someone else do it. You should do it. We should stay ahead of that curve.
Number four, how can your assets be used differently? Such a powerful question. How can your assets be used differently? Not just your machinery and your capital investments, but what about the human talent? Guys, this is a room of unbelievably smart people. That’s how you got these jobs. That’s why you rose to the leadership positions that you’re in. How can your assets be used differently? How can we use that human talent more effectively, leverage it more? That’s what innovation is all about. That’s what innovation is all about.
And I’ll tell you what. Any presentation that you see about innovation, doesn’t matter who it is, where it is—it doesn’t matter—inevitably, if it’s done right, it always boils down to really one concept which you can summarize in just two words and those two words are budgeting failure. You have to be willing to budget for failure. That’s what innovation is. You have to be willing to—you have to try new things. You have to try new things that you don’t know will work.
Jeff Bezos, Amazon, that guy is genius. I told you I love quotes. He’s famous for saying, “If you know it’s going to work, it’s not an experiment.” If you know it’s going to work, it’s not an experiment. You got to try something new, which implies it might not work. I mean, seriously, he is such a genius.
So he also said, just recently in an interview, he said, “If you have a 10% chance to get a 100x return, you would take that bet every day. You’re still going to fail 90% of the time.” Seriously, think about that. To me, I mean, this stuff just is like revolutionary to me. You’re still going to lose 90% of the time. Even though mathematically we all know if you have a chance at a 100x return, you’ve got a 10% chance of getting it, you would go after that every single time, you’re going to lose 90% of the time.
Innovation requires failure. It requires trying new things. That’s why the gross margin is so important. Think about the areas of clients that you specialize in and you can sort all those participants in that industry segment by gross margin where some companies have a high gross margin, some companies have a low gross margin. This is known data, very easy to see. The people with the highest gross margin, they have the biggest opportunity to innovate. They do it first because they can afford to lose.
And by the way, professional services does not really apply to this because the gross margin there is different because it’s human talent that’s being sold. But in any kind of other comp—look at Google. Look at Google. Their gross margin is like 90-whatever percent, 98%, because there’s no direct cost to what they sell. It’s digital. So they have a huge gross margin. So they are the ones who innovate first. Because the bottom line is if you’re further down the pack, you don’t have that much gross margin, you can’t afford to lose that much money. So you’re better off letting the high-gross-margin players test it first. Let them spend their money and let the cost structure collapse over a period of time, and then you can see when it starts to get close to where your client is and say, “We need to do this now. Now is the time.”
Maybe today isn’t the right time. Maybe their gross margin is so tight you can’t afford that risk. That’s cool. But when do you need to pull the trigger? You could figure that out. You can see that future. You can see these things and tell them, “Okay, now we’ve got to do it. Next year or two…the time is now. We need do use these technologies. You’re going to get it cheaper than the people who did it four years earlier. That’s what innovation is all about.
So there’s that whole saying, “See the forest through the trees.” Guys, this is what I do. We all do this. Most people, they end up in the trees. They end up in the trees. Again, it’s institutional blindness. There’s nothing wrong with it. It’s natural that we end up in that space. You guys are super-busy, I know there’s a lot of pressure, I know there are deadlines, I know all those things, but spend more time out here. Have an hour a week, Friday afternoons when things slow down, allocate, put it on your calendar, give yourself two hours to go step back, and look at some of these models, some of these frameworks. Even the ones I’ve mentioned here in this presentation, you can use these to get a really clear idea of where things are going.
My message for you this morning is just to think bigger, think way bigger about what’s possible. It’s such an exciting time. I get so excited about this stuff. And there’s a lot of interesting research about this too, by the way, is the whole idea of thinking bigger. I study leadership. I read books by the dozen. I’m totally into this stuff. And there are really interesting by-products when you think bigger, and one is that you end up inspiring everyone who’s around you. All your people in your team, they get inspired by when you think bigger. Your customers get insp—your competitors get inspired when you’re thinking bigger. It inspires everybody if you think bigger.
This is the law of state transfer. When you’re talking with someone, your emotional state will tend to transfer to the other person. If you’re excited about the future, that excitement will transfer. If you’re afraid of the future, that fear will transfer. When you think bigger and have that optimistic view, it transfers to the people that you manage, the people that you work with, the people that buy your services, your clients. They need to be excited. There’s no such thing as a confused buyer. If they’re confused, they don’t buy. If they’re confused, they don’t buy. So when they talk to you, when you have those conversations, it’s got to be so simple, straightforward, obvious. They’re like, “[Snaps fingers] I get it. We need to do that.” Inspire everyone around you.
And number two, when you think bigger—and I’m not talking like a little bit bigger, I’m talking like way bigger—when you think way bigger, quite often you end up having almost no competition along the way because no one else has the courage to go after those goals. They’re afraid they’re going to fail and it might happen. So who has the courage to go after those big goals? Do you? Does your client? Are they ready to make that investment? Thinking bigger is an unbelievable thing.
So of course there are famous people we’ve all heard a thousand stories, people who are basically poster children for this type of thinking. Richard Branson is kind of a classic example. And I told you I love, I mean, I really do love, quotes, and of course he’s got a thousand of them. So this is one of my favorites: “The fastest way to become a millionaire is to start out as a billionaire and then start an airline.” Genius. Genius.
But anyway, so he started Virgin Galactic. Like, how much bigger are you going to get than that, right? Any competition? Not much. Not much.
And then you’ve got Elon Musk. This guy’s basically like a personal hero to me. I just love the way his mind works. Really incredible. Unbelievable. So he’s the guy—so for anyone who doesn’t know him, I’m sure you all do—he’s the guy who started SpaceX, the first private company to deliver cargo to the International Space Station, first private company to do it. And they’re reusing their rockets. I’m sure you guys have followed that story. They’re sending up the rockets and then bringing back the first stage so they can use it again.
So even that alone, guys, think about this stuff. So just one more question here, right? The cost of sending a rocket to the ISS, International Space Station, the cost of doing that is about 60 million bucks, ballpark. Depends on the cargo. It’s about 60 million. How much does the fuel cost? How much does the fuel cost? Any ideas? Let’s draw it out. Sixty million is the total price tag. How much does the fuel cost?
10 million? Anyone else? Twenty-five? Twenty-five million? The answer is $200,000, 1/300 of the total cost. One-three-hundredth of the total cost, which means if you can reuse the hardware, you can bring down the cost function by a hundredfold or more.
Disruptive innovation. Unbelievable. Thinking in first principles. What’s the cost of the inputs? That’s what they’re doing in the Gigafactory in Nevada. What are the costs of lithium ion batteries, just the straight raw materials? Think in first principles. How do you completely turn an industry upside down? That’s what they’re doing.
And the first time they pulled it off was just right at the end of 2015, just before Christmas 2015, and when they did it their employees partied like it was 1999. I’ll tell you what, the average age of these folks are 27 years old on average. That makes them millennials.
Let me tell you something. It’s true what we heard earlier. They get a bad rap. People say they’re lazy, apathetic and entitled. It’s not true. Those millennials will work harder than anyone you’ve ever seen if you give them something inspiring to work towards.
So thinking bigger, guys, it’s not just a cliché. You inspire everyone around you by thinking bigger. It’s true. There are examples of this everywhere. You want to get those people engaged? Do something bigger. They all want to change the world. They want to be part of something bigger. These people who work at SpaceX and Tesla, they’re working 14 hours a day and they’re doing it with a smile on their face because they’re changing the world. How do you bring that message to your clients? Say, “We have an opportunity, we’ve got an asset we’re already paying for. Let’s get them engaged. Let’s get them fired up.”
So Elon Musk started Tesla. So any competition with any of this stuff? With the SpaceX, not much. With Tesla, not when they launched. No one thought to produce a high-performance electric car. They all wanted to produce slow ugly electric cars, right? But Tesla said, “No, we’re going to give the customer what they want. We’re going to do it the big way. We’re going to do it the fantasy way.” So last year they introduced their Model 3 and got 400,000 preorders, way bigger than any car launch in history. Why? Because people were inspired by what they’re doing, right?
And then they introduced the Powerwall. I don’t know if you guys have seen this. For anyone who’s not familiar, this is basically an attractive battery. It looks pretty. It’s like a work of art. You put it on your wall. It’s a battery and you connect it to the solar panels that are on the roof of your house so that the battery can charge during the day. You can use it at night and disconnect from the power grid entirely. Any competition? Nope. This is their 2.0, their new version.
All these stories—you’ve heard a million of these stories—they’re all the same. These people, these leaders that we have in our world that inspire us, that drive us forward, what are they all doing? They’re thinking bigger. They’re taking those risks. They’re inspiring everyone around them. Those two things happen as a result of each other.
So at the end of the day, it’s a conversation about leadership. My presentation isn’t a presentation about technology trends or disruptive innovation. It’s about leadership. It’s about leadership. It’s about the extent to which we’re willing to step up and say, “Yeah, we’ll do it,” and in order to do that you have to get out of that institutional blindness from time to time. Plan for it. Friday afternoons, whatever it is, do a meeting once a month with your leadership team or with your client’s leadership team and blow their brains out so that they think differently. Tell them some of these case histories. Get that dialogue going. You can do more than just compliance. You can do so much more. There are so many opportunities to make sure that your clients are on the right side of that leverage equation.
My presentation’s all about leadership and about thinking way bigger. And I truly am, like what I said before, one of the things I love about…I speak to the most insane, you wouldn’t believe the diversity of audiences that I have an opportunity to…and I love what I do, I truly do. But there’s a unique opportunity here because I view what you do in your businesses, it’s not that dissimilar to what I do, but we have to have the courage to step out and introduce those concepts to our clients.
So these are those four questions again. You’re going to be having, after the break—we’re going to a break here in just the next five minutes—but after that you’re going to have some breakout sessions and people are going to be referring to these questions again in those breakout sessions. So start thinking about these things.
And there’s one that I didn’t include here, but it’s, “What’s the least profitable market segment of your client?” So your primary client, what’s their least profitable market segment? There’s an opportunity with that group.
So think about these questions because these questions can inspire. The ideas are going to come from all of you.
And I’m super-grateful to be here. Thank you very much for your time this morning. I’m going to be here in the break. My favorite part of my job is talking to people afterwards. People always have incredible stories and ideas. I love hearing them. So I’ll be here at the break. I’m also going to be here at lunch. Unfortunately, in the afternoon I have to run because I have to catch a flight, but I’m thrilled to be here and thank you so much for your time this morning. Thank you.
Patrick Schwerdtfeger is a keynote speaker who has spoken at business conferences in North America, South America, Europe, Africa, the Middle East and Asia.