You might be forgiven for thinking Pascal Finette is talking crazy, but he has built his reputation on a seemingly impossible notion: It is easier to 10X your business than it is to increase it 10 percent.
On the surface, it seems implausible that you would have an easier time building a $1 million business into $10 million rather than bringing it to $1.1 million.
How could that be possible? Because incremental change within the structure you have is hard. You have to be able to step outside your current structure and see a whole new way of doing things.
And Pascal has made a career of riding disruptive change to ever greater heights. He was an early pioneer on the internet, before there was even a web browser. He founded a few tech startups, worked for eBay and led Mozilla’s Innovation Lab.
He now works with entrepreneurs to get them accelerated on a 10X track as the head of the Startup Program at Singularity University, a Silicon Valley think tank and educational center that bills itself as a global community using exponential technologies to tackle the world’s biggest challenges.
In this interview with Publisher Paul Feldman, Pascal tells how ordinary humans can strap exponential rockets to their business.
FELDMAN: How does somebody think 10X?
FINETTE: To be very frank, it was really hard for me for a really long time to wrap my head around the paradigm of 10X thinking. It was somewhat opaque to me how you actually practice this.
Years ago, I cofounded a venture capital firm that was focused on ecommerce. We thought about the 10X concept quite a bit, and the hack we found is the following:
When entrepreneurs pitch a company to a venture capitalist, they typically have a very clear understanding of how much money they need. So they come to you and they say, “We need a million dollars and we’ll use it for X, Y and Z.”
When we liked the entrepreneur and wanted to work with them, we would get back to them and say, “We think what you’re doing is great. We’ll give you $10 million. So it’s literally 10X. What will you do now?”
And 99 percent of entrepreneurs just have no clue. They say, “We hire more people. We go into more countries. We build a new product,” or whatever, which really never is the real answer.
The best entrepreneurs say, “That’s a really interesting question. Let me think about that.” And then a week later, they come back after rethinking their business with these new boundaries.
So instead of thinking a million, they use the boundary of 10X, $10 million, to rethink their business. And this worked really well for us.
Since then, we’ve used the same concept to work with others, such as corporations. When we look at their projects, I challenge the team behind that project to do whatever they do but with 10 times the limiting factor. That effectively creates a whole new set of boundary conditions for them. That seems to do the trick.
It’s really about tricking your brain into using new boundary conditions, which are 10 times as wide, to rethink whatever you’re doing in your business, your project, whatever it is.
FELDMAN: Dramatic 10X change can be many small changes that compound. It could even be a 1 percent improvement every day.
FINETTE: Absolutely. At Singularity University, we’re talking a lot about exponentially accelerating rate of change and technology.
This goes to figuring out your 10-, 20- or 30-year vision. Take one of these exponential thinkers like Elon Musk, who had a very clear 30-year vision when he started with Tesla — to have every single car on the road electrified. Then the question becomes, how do you break this down to something you can do in the nearer term, and how do you break that down into something you can do today?
And you’re absolutely right. The 10X expands into not just the financial means, but many other areas and processes as well.
FELDMAN: That was Elon Musk’s vision, and we can all witness it unfolding. How did he do it?
FINETTE: If you break the methodology, you need to have an exponentially accelerating technology trend supporting it. In Tesla’s case, batteries are getting better and cheaper on a truly exponential rate.
Then you break it down and you say, “So what do we need to get there?” The answer is, “We need to have at least one vehicle being mass manufactured and affordable,” which is the Tesla Model III, which just came out.
Then you break that down and you say, “First, we need a learning vehicle.” So the answer was, you take a sports car vehicle, rip the engine out, put an electric engine in and sell it to people who’ve got the money for it. Then you take that and you build a luxury vehicle, which is the Model S, and build it in small volumes and sell it.
And then you build a few more platforms, and then you eventually get to Model III. So it’s a really fascinating breakdown of a long-term goal into something tangible today.
FELDMAN: With the exponential, disruptive world that we’re living in, can you still do a five-, 10-, 20- or 30-year plan?
FINETTE: I think you can. But it’s much murkier moving forward, with the margin of error much wider as you go forward.
You can predict where technology will go in a particular time frame. Take computers, where we have Moore’s Law predicting computers get twice as fast every two years. If you project that out, I can tell you how much computing power you will have on your phone in 10 years and 20 years.
You can do the math on it, and then you can work backwards in terms of what you can do with all that computing power. That creates the long-term vision.
Then again, the art is to break that long-term vision down into concrete next steps. Mark Zuckerberg has this really wonderful quote in Facebook’s internal handbook, which they give to new employees. It says that we know exactly what our 30-year vision is, and we know precisely what we’re going to do for the next six months and everything else we need to figure out.
I think the reality today is, you can have that North Star — where do you want to go in the long term — and you know what you need to do in the short term, but not in the middle term. You know companies in previous years still did the two-year planning or, like the Chinese, the famous five-year plan. That’s probably going away because it’s so murky and so fraught with error that it’s impossible to do.
FELDMAN: What is exponential disruption, and how does that work?
FINETTE: It works in two ways. The first way involves things that happen in your line of sight.
Let’s say you’re a car company. There’s a line of sight, which is the stuff that is clear to you. In a car, the line of sight includes the question of combustion engines versus electric engines; autonomous vehicles versus manually driven vehicles; car ownership versus shared car ownership.
In the world of things you’re seeing, you also need to figure out which of those technology trends move on an exponentially accelerated curve, and what does it mean for you as a company in that space.
The best example is Nokia being in the space of handheld mobile communication. They didn’t see, or they underestimated, the dramatic pace of Apple disrupting the industry, turning phones — which were phones, literally for voice and text communication with buttons — into minicomputers with a glass interface or a glass screen and a touch face interface.
I believe most companies are getting much better at understanding this. The Nokia example worked pretty much as a wakeup call.
Then there’s a second part to that, which is stuff that happens to the left and right of you. You typically don’t see it if you’re not very careful in scanning the landscape.
I’ll give you a very simple example. I spoke to a large airport’s management, and they’re growing really fast, particularly in the space of commercial air flights, business flights. And they were working on this 20-year project. I asked, “OK, what will this airport look like over the next 20 years?”
They expected that the business flights will continue to rise in volume. And that might be true, but what they haven’t seen and didn’t consider is technology such as virtual reality. Where today I’m getting on a plane and flying three hours across the country, I will probably do those meetings in virtual reality because it’s cheaper, quicker and easier and I don’t need to fly. That might have a pretty dramatic effect on the airport business, but it’s something they didn’t see.
What they were seeing is planes getting more efficient, different types of planes coming, consumer behavior in an airport shifting more toward shopping behavior, so airports turn more into shopping malls, etc. But they didn’t see this VR thing happening. So that’s the disruptive innovation that is happening on the corollaries, on the sides of your field of vision.
FELDMAN: The potential disrupter we’re seeing right now in our industry is robo-advising. Where do you see that going?
FINETTE: A little while ago, I worked with a very large insurance group and I was invited to speak at their leadership forum.
All the group leaders were together. And I talked about disruptive change and so on, and I asked the audience what they think their competitive advantage in the market is.
Their main answer was to say, “We understand — we can assess risk probably better than most others based on the models we build, based on all the data we have, based on us hiring the best scientists and data scientists and risk-modeling people.”
And I showed them a graph where you can predict with pretty high reliability that in year 2029, we will build computers that are computationally as smart as the human being. Then by 2050, 2060, you will have computers that are computationally as smart as every single human being on this planet.
So compute power becomes abundant. It’s already pretty abundant, but it becomes truly abundant. Then you put artificial intelligence and machine learning and big data analytics on top of that, and I guarantee you that a computer will make better risk models than a human.
So you might come into a world where the risk model you’re running on your phone in the form of a robo-advisor, for example, is better than any human. So your competitive advantage probably becomes that you have the best algorithm, but not the best humans anymore. Or your algorithm has the best access to data, so it becomes smarter than humans.
I think it will become deeply disruptive. Just to be clear, I also believe that the role of humans will shift.
The human advisor will care much more and spend much more time on really understanding the client’s needs, and then will have the computer figure out what the perfect portfolio looks like or what the perfect insurance plan looks like.
FELDMAN: But I would guess there are people, particularly younger ones, who prefer the non-human service.
FINETTE: I’ll give you an interesting example. This is minor, but was fascinating for me.
I recently set up a new account with one of the large broker firms. I used one of their internet-based tools, and they actually called me. One of their advisors said, “Hey, we’re seeing that you are opening an account and we would love to offer you this free service,” which is great. But here’s the thing, I don’t want to talk to them.
For me, I don’t like speaking on the phone. I asked the person, “Can I use chat with you, because that’s my normal way of interacting?”
And they said they don’t have chat, which was really fascinating. I thought, Wow, you’re cutting out a whole generation of people younger than I am who do everything with chat. And they didn’t offer this as a service at all, which just blew me away because it’s such a missed opportunity. It’s so easy for them to implement. It’s even cheaper for them to have chat than to call me.
I think there’s a lot that needs to be sorted out in the industry, and lots of opportunity. There’s a massive amount of opportunity.
FELDMAN: More broadly speaking, what is the future of humans in the workforce?
FINETTE: Of course, this is currently a huge debate, the idea of technological unemployment. There are a lot of questions and very murky answers at the moment.
But I think in very broad brushstrokes, at a very high level, what we will see is that machines, both artificial intelligence as well as robotics, will take over a lot of the more mechanical tasks when machines are better at doing them.
And with mechanical tasks, I also mean stuff like picking a stock or picking an insurance portfolio, or when you go to a doctor, having a machine look at your X-ray and telling you if you have pneumonia based on machine learning algorithms.
IBM has a working product that looks at X-rays and predicts cancers and things you can see on X-rays on behalf of doctors. And it’s better than any human in detecting those. So we’re already in a world where, if your hospital or your doctor says, “Do you want to have an AI look at this, or do you want me to look at this?” you actually want to say, “Please have the computer look at this.”
But that doesn’t mean that the role of the doctor goes away. I think the doctor then becomes much more what the doctor really should be, which is this human interface to me and working with me on my health and advising me and helping me. And I think the same is true for the insurance industry and the financial industry.
FELDMAN: With all of this stuff happening, is there a way to future-proof yourself?
FINETTE: Yes, absolutely. We’re already in an age where constant learning is the norm. So, this old idea, which is that you go to college and then you get your job and you work in your job for 20 years or longer —that’s over.
I think it’s really about constantly learning and doing these micro-credentials, probably. You want to get credentialed and stay on top of stuff. What this does to you as a human is move you higher up in the service hierarchy.
It’s a little bit like, if you remember, Maslow’s hierarchy or pyramid of needs. We’re moving higher and higher up.
Take the financial advisor, for example. Understanding that role is probably less about knowing everything there is about a specific basket of financial products, because the machine will know that. It’s being much better at sitting down with clients and really understanding their interests and goals — where do they want to be in the world — so that you can fine-tune the machine to get the best result for your clients.
It’s about moving up that stack to stay on top. There’s a lot of stuff humans are inherently better at, and it’s about empathy and creativity and connecting.
And I think that will stay with us for a long time.
FELDMAN: How does somebody spot change that’s going to be a disruptor or a real market shifter?
FINETTE: That’s tricky. It requires a few ingredients. First, you need to be open to seeing it. You need to have a mindset that even allows you to recognize and see it.
With that mindset, you need to spend time regularly scanning the horizon to figure out what’s actually happening in the world. And luckily, because we’re living in such a connected world today and most of the information is free or very cheap, it’s actually fairly easy.
In my case, I scan the horizon and I ingest a lot of data sources such as MIT Tech Review so I can know what’s happening and what’s in the ether. That requires some work and some dedication to it.
I think it really becomes part of your job to say, “There’s half an hour a day or an hour a day I’m spending on scanning the horizon and figuring out what’s happening.”
FELDMAN: So one thing that you do is work with a lot of startups. What are some characteristics of a good startup?
FINETTE: It’s a good question. So, I think most people in Silicon Valley will agree on is that the two factors of a good startup are typically people and timing.
There’s this age-old saying in venture capital, which is that good people can’t fix a bad product. But a good product with bad people — well, with not particularly good entrepreneurs — just doesn’t fly. It doesn’t work. So you look at people who have the experience, who ideally have worked together before, because building a startup is super stressful and the more experience people have with each other over longer periods of time, the better it is.
A friend of mine said the magic ingredient is them being irrepressible. So there’s this burning fire in them. So that’s one factor.
Timing is the other one. You need to figure out what the market timing is. There’s some science behind it, but it really has a lot of art in there.
And then there’s a whole bunch of hygiene factors, where the product needs to make sense, the market needs to be big enough and they need to know how to build the product. But those factors are typically fixable if you have the first two ingredients.
FELDMAN: Interesting. With all the disruption that’s happening in the world today, does an existing business need to think like a startup and always think like a startup, or do you get out of that mode?
FINETTE: I think if you look at an existing business, part of that business needs to think like a startup. I have observed this now, and I’ve got this theory that when a business is a young fledgling business, it gets to a product market fit.
Once it finds this magic moment where they’re producing something the market wants, what the business then does is start to protect that status quo, which is perfectly reasonable and the right thing for it to do. So once they find something that works and figure out the right pricing and the right product, and it starts to fly off the shelves, that business turns to protecting that status quo. They start to fight off competitors. They will flood the market with advertising, all this kind of stuff, and that’s great. The challenge with that is, the people who are doing status quo thinking are different from the people who are doing startup.
I think what you need to do, as an established business, is both. The core of your business is protecting the status quo, and that’s great. But protecting the status quo makes you vulnerable to being disrupted. So at your core, you need to have this other part of your company that is constantly scanning the horizon, figuring out how do I disrupt myself? How do I create new product offerings in a world that is rapidly changing? The short answer is, if you turn an existing business purely into startup mode, they will lose their core business, which is their lifeblood. So that doesn’t work.