going to see another billion people that are going to come into the system over the next 40 years in that continent. So I think we need to spend more time there.


As a result of that, we are already seeing a far higher proportion of the most significant companies in the world are coming from the emerging markets. So the players that matter are not the Anglo-Saxon players, the European players, the German industrialists and so forth. We’re going to have almost half coming from just Asia alone and those companies exist now. We know who they are, we can see them, and a lot of them are private. A lot of them are family-owned, but they’re growing at significant rates.


So that’s the first force, just this power shift from the West to the East. I don’t think many organisations, McKinsey included, are moving fast enough in terms of what this means for their leadership profile. If you think about the top 100 people in the organisation, what proportion of them come from that part of the world.


If you think about your own experience as a leader, what is your network like, what is your experience like? Obviously you’re going to be able to build relationships, but I would also think about spending some serious time in these parts of the world to understand how they work and how they operate.


Back in 2010, I was very much into the economic power shift as being the big trend. In the last couple of years I’ve decided the technology shift is the more powerful of the four trends – and the reason is not only the range of technologies but the ones that are going to be most disruptive.


We know about the mobile internet. We saw what happened on Singles Day in China, the scale of what can happen on a system. If you want to understand how the mobile internet works, it is not the United States or Silicon Valley. It’s what’s happening in China, in India, even Saudi Arabia. The most intensive Twitter social media country in the world, it maybe surprise you, is Saudi Arabia. The average American uses one gigabyte per month. The average Saudi does three gigabytes a month. That’s partly because if you want to watch a movie, there are not very many movie theatres in Saudi Arabia, so you’ve got to use your phone and so forth, but still, consider the intensity of the interaction.


With respect to work, we think about 35% of all tasks that are done in management can be automated. 20% of what CEOs do today can be automated. It doesn’t mean the jobs will disappear. We think only about 7% of the jobs will go, but it means we’ll have to redefine how jobs work. The role of the HR leader is going to go up significantly.


I’m going to talk more about what that does for industry, the autonomous vehicles. There’s a whole slew of changes coming on the biotech side, what genomics has done. Advanced materials, renewable energy, these are some.


I say this always with a bit of caution from McKinsey, because we are the firm who in 1990 when we were advising AT&T predicted that the total global demand for mobile phones would be 90,000 phones. That’s what we said in 1990! So you might want to use your own judgement.


I think the biggest drivers of these technologies come from three areas. One is computing power. The average washing machine today has more computing power than NASA had in 1969 to send a man to the moon, and that continues with Moore’s Law.


Data – we’re creating more data as humans every two days than we had in our entirety for the last 2,000 years. Unfortunately a lot of that data is useless, but if you can use that data (we use about 1% of it) you can get very significant productivity improvements.


And then connectiveness – more and more of us are wired up, and those three factors together are leading to significant disruption.


One way to look at this on the computing power curve is to look at how close computing power is coming to the human brain. Right now we’re about at the level of an insect brain, and you may not think that’s very impressive, but I can tell you insect brains are complicated.


Some of the best research is going on at UCL. A firm I’m sure you guys have heard of is Deep Mind, Google bought them about two years ago for $1 billion. There are about 300 people there. They create no products, no services. They are some of the best neuroscientists in the world. It’s the potential of this deep neuroscience and computing power talent which is going to generate real insights into artificial intelligence.


We will get to the human brain. The sense here is that in around the 20-25 year period we will get to the human brain. I think this is going to have some pretty profound implications for how we operate. The Pope has just convened a group of technologists to talk about the ethics of what this means, how we think of what that is going to mean, in terms of how we regulate ourselves. So the computing power will continue to accelerate.


One other element I just wanted to talk about too is this Internet of Things, not just the consumer side. Some of the most profound effects on technology are going to come from how industrial companies


work. This is why GE has gone through what they’re arguing is the biggest transformation they’ve done in their history, and they’ve done quite a few of these transformations. The insight came from one of the many products they make - they make jet engines, locomotives, fridges, medical equipment. If you take a locomotive, GE spends a lot of money on R&D on figuring out what type of material to use for wheels, how to make an engine as powerful as it can be, using as less fuel as possible. There’s a lot of sophisticated engineering that goes on in making a locomotive.


But the light bulb moment, so to speak, for GE was when they did some analysis about the impact of a locomotive on a railroad company’s profitability; and it’s far, far bigger than the cost of the locomotive. One of the ways you measure the effectiveness of a locomotive is its average speed per hour per day. Over a 24 hour period the average speed of a locomotive is 22 miles an hour.


If you can take that average speed up by one mile an hour, that can have up to a $250 million impact upon a railroad company. Therefore it’s the use of that locomotive that actually matters much more than the power, the metal, or the size of it.


GE was worried that some sophisticated hoover-like person is going to come along and say “that’s great, you build the engines and we’ll provide the analytics of how you can actually use those engines more effectively, and we’ll create way more value for the company than you do by manufacturing it”. And what GE said was “forget about that, we’re going to own that ourselves. We will own and develop the data analytics”; and that’s what they’ve done.


So that’s just an example of one hard core industrial business and how the Internet of Things leads to industrial companies having a transformation.


The autonomous vehicle is a reality. We’re now seeing some cities, especially in Asia, that are going to declare that they want to have self-driving cars. That has big implications on traffic patterns. It has big implications on environmental damage.


I think one of the things we forget about when you think about some of these innovations is what I call the second bounce of the ball. When you think about innovation it’s very easy to see the direct implication, the first bounce of the ball. Obviously if you’re in Ford Motor Company, then you can start to figure out okay, what does this mean for us?


What you may not know is that probably one of the most profound effects of the driverless car will be on the cardiac surgery industry, critically in the United States. If you’re a cardiac surgeon, about 90% of hearts that we use for transplants come


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