CEO Joe Kaeser on the Next
Industrial Revolution
The
manufacturing chief describes how an industrial powerhouse founded in the 19th
century is using software, sensors, and savvy to create a digital manufacturer
that can thrive in the 21st century.
A
version of this article appeared in the Summer 2016 issue ofstrategy+business.
Very few companies have survived as many
technological and industrial revolutions as Siemens. Founded in Berlin in 1847,
Siemens AG has seen — and prospered through — the advent of steam, trains,
electricity, the internal combustion engine, steam turbines, the jet engine,
wind power, the personal computer, wireless communications, the Internet, and,
now, big data. Beyond simply managing through these consecutive industrial and
information revolutions, Siemens has helped lead them. With fiscal 2015
revenues of €75.6 billion (US$82 billion) and 348,000 employees, it is one of
the world’s largest industrial enterprises.
Today, Siemens is organized into 10 divisions,
most of which offer highly complicated products. The divisions address markets
such as power and gas, wind power and renewables, power generation, energy
management, building technologies, mobility, process industries and drives, and
healthcare. The sun never sets on this far-flung empire, which stretches from a
steel factory in Cilegon, Indonesia, to a software development center in
Bangalore, India; from an ultrasound equipment manufacturing facility in
Plymouth Meeting, Penn., to a wind turbine plant in Cuxhaven, Germany.
But Siemens is in the midst of a
transformation. Every business talks about becoming more digital. Buzzwords
like 3D printing, the Internet of Things, mass customization, and big data are
bruited at conferences and populate the fundraising decks of startups. But
these concepts — and the broader notion of digitizing manufacturing — have a
particular meaning for Siemens. The company is putting lots of time, effort,
and talent into marrying information technology to the process by which it
designs, builds, and delivers its highly sophisticated products. To a large
degree, the company is already operating digital factories.
Steering Siemens into the next industrial
revolution is the mission of Joseph Kaeser, who joined the company in 1980 and
rose through the ranks of the semiconductor divisions and then into central
management as chief financial officer. In August 2013, he was named president
and CEO.
Kaeser may not have the mien of a millennial
technology executive. He doesn’t wear hoodies, and his hair is combed carefully
in a silver coif. But he is something of a digital native, having spent time in
Silicon Valley in the 1990s. (At the time, Kaeser confesses, the locals often
confused Siemens with Simmons Bedding Company.) Today, Siemens employs more
than 17,500 software engineers. Although much of the conversation about
technology revolves around apps and websites, Siemens is providing examples of
how IT and data can add a massive amount of leverage in advanced manufacturing.
In
conversation, Kaeser is energetic and informal — one favorite word of praise
is cool — with a wide-ranging, pragmatic perspective the
issues affecting his company and his industry. Over a one-course meal (fish and
white wine) at a hotel in San Francisco in November 2015, he charted a path to
relevance for a 170-year-old advanced manufacturing conglomerate in the early
21st century. He described how Siemens’s approach to manufacturing brings
coherence to a diverse portfolio, and helps drive the culture — and he also
aired his opinion on the broader implications of the ongoing technology
revolution.
S+B: I
understand you spent several years in Silicon Valley?
KAESER: More than five years, from 1994 through 1999. I came over as CFO of what was then Siemens Components, which was the semiconductor, passive devices, and electrical components business. Then, I ended up becoming the CEO, and I left in 1999, just about at the height of the bubble. I always remember those were tough times.
KAESER: More than five years, from 1994 through 1999. I came over as CFO of what was then Siemens Components, which was the semiconductor, passive devices, and electrical components business. Then, I ended up becoming the CEO, and I left in 1999, just about at the height of the bubble. I always remember those were tough times.
S+B:
Wasn’t there a boom going on?
KAESER: Well, in 1994–95, it was still kind of a depressed environment in the Valley. House prices were still down. There were a few companies talking about Internet applications and voice over IP. And then the telecommunication networks began to bloom. Lucent was still around and telecom was very cool, and companies like Cisco and Bay Networks were thriving. You know, when Candlestick Park [the San Francisco Giants’ baseball stadium] was renamed 3Com Park in 1995, that was interesting to me. I had never thought about companies like 3Com or Cisco before. We actually were a supplier to Cisco and telecoms and datacoms, and the DRAM business was still really strong with the pull from companies like Micron. But when I introduced myself as the big shot from Siemens, people said, “Oh, is that the mattress factory?” I responded that it was kind of close, because whenever you buy products from us, you can sleep well! But this was also a time when Apple was at five bucks a share. I was working in Cupertino, and the Apple complex was just across I-280. And people were joking about Microsoft buying Apple for the price of a Snapple.
KAESER: Well, in 1994–95, it was still kind of a depressed environment in the Valley. House prices were still down. There were a few companies talking about Internet applications and voice over IP. And then the telecommunication networks began to bloom. Lucent was still around and telecom was very cool, and companies like Cisco and Bay Networks were thriving. You know, when Candlestick Park [the San Francisco Giants’ baseball stadium] was renamed 3Com Park in 1995, that was interesting to me. I had never thought about companies like 3Com or Cisco before. We actually were a supplier to Cisco and telecoms and datacoms, and the DRAM business was still really strong with the pull from companies like Micron. But when I introduced myself as the big shot from Siemens, people said, “Oh, is that the mattress factory?” I responded that it was kind of close, because whenever you buy products from us, you can sleep well! But this was also a time when Apple was at five bucks a share. I was working in Cupertino, and the Apple complex was just across I-280. And people were joking about Microsoft buying Apple for the price of a Snapple.
Siemens
Past and Future
S+B:
So you saw the beginnings of one bubble in Silicon Valley. And today we’re
sitting in San Francisco, which many people regard as the epicenter of an even
bigger tech-infused bubble.
KAESER: Well, no one can predict the future. My take would be yes, we are in the middle, if not close to the peak, of another massive bubble. But then again, the ones who survive will change the world. And that’s the fascinating thing.
KAESER: Well, no one can predict the future. My take would be yes, we are in the middle, if not close to the peak, of another massive bubble. But then again, the ones who survive will change the world. And that’s the fascinating thing.
S+B:
You’re the CEO of a massive, diversified global company. With the digitization
of information, you can have information and insight into all your different
operations on one screen. How does that affect the way you work and manage? Do
you have a dashboard of indicators on all the time? Are you texting 500
different people?
KAESER: There are two aspects to managing today. The information comes faster and is more accessible than ever before. There’s a lot of data, and the challenge is how to prioritize information. As a company leader — or as any manager, any person — you need to prioritize your tasks. It has become harder to set the priorities correctly because there’s so much information. You need to go after that information and understand what’s first and second and third [in importance].
KAESER: There are two aspects to managing today. The information comes faster and is more accessible than ever before. There’s a lot of data, and the challenge is how to prioritize information. As a company leader — or as any manager, any person — you need to prioritize your tasks. It has become harder to set the priorities correctly because there’s so much information. You need to go after that information and understand what’s first and second and third [in importance].
The second aspect to managing: How do you
manage your company using the data you collect? There’s a technocratic approach
in which you look at the numbers. But by the time you get the numbers, it’s too
late already because the numbers only reflect what happened in the past. At the
end, managing a company is still very analog, because human beings are analog,
and the way you manage your company is you deal with human beings from the top
all the way to the bottom. That value chain of human resources needs to be
intact.
S+B:
So it’s not just about the numbers?
KAESER: [At Siemens] we know our numbers, usually daily, in terms of bookings and revenues. We have built a real-time system and we know our cash flow. But in a business like ours, which has cycles from two to seven years, it’s much more important to understand the markets. How do we recognize early indicators of a changing world? That object you see — is that going to be there tomorrow? If it’s there tomorrow, is it going to be different? What’s your competitive environment? How do the customers of your customers change? That’s the type of stuff you need to understand because by the time you see by the numbers, it’s too late.
KAESER: [At Siemens] we know our numbers, usually daily, in terms of bookings and revenues. We have built a real-time system and we know our cash flow. But in a business like ours, which has cycles from two to seven years, it’s much more important to understand the markets. How do we recognize early indicators of a changing world? That object you see — is that going to be there tomorrow? If it’s there tomorrow, is it going to be different? What’s your competitive environment? How do the customers of your customers change? That’s the type of stuff you need to understand because by the time you see by the numbers, it’s too late.
S+B:
What is the Siemens approach to the use of information technology in advanced
manufacturing?
KAESER: It’s a very powerful approach because we are industry leaders. We have a division called digital factory, where we merge the real world, which is hardware, with the virtual world, which is simulation software. We have all the elements of manufacturing automation in that division. We have hardware such as control systems and CPUs. Then, around that hardware, we have so-called PLM (product life-cycle management) software, which allows us to simulate production and robotics flows ahead of time. So today, we build manufacturing automation lines and design processes before a manufacturing plant has been built.
KAESER: It’s a very powerful approach because we are industry leaders. We have a division called digital factory, where we merge the real world, which is hardware, with the virtual world, which is simulation software. We have all the elements of manufacturing automation in that division. We have hardware such as control systems and CPUs. Then, around that hardware, we have so-called PLM (product life-cycle management) software, which allows us to simulate production and robotics flows ahead of time. So today, we build manufacturing automation lines and design processes before a manufacturing plant has been built.
Merging the real world with the virtual world
allows us to create what we call a digital twin. We copy a real-time
manufacturing process into the virtual world to optimize engineering,
processing quality, uptime, and load time — and then we copy it back into the
real world of manufacturing. That’s pretty cool. I believe we are the only
company in the world that can do it. And when we simulate processes in
manufacturing and in engineering, in R&D, we can go from destructive to
nondestructive testing. Together with Boeing, we simulate the whole development
and engineering process for new airplanes. And then, we [do simulations that
test] whether the airplane can fly or not.
Advancing
Data Analytics
S+B:
Siemens employs a huge number of software engineers. What are they doing?
KAESER: We have more than 17,500 software engineers in our company, more than many software companies in the world. And those people develop software inside the products, which is called embedded software, as well as build applications and data analytics tools that use the data we get from hardware. The importance of hardware is what people often underestimate when they talk about the Internet of Things. Have you ever thought about where data comes from?
KAESER: We have more than 17,500 software engineers in our company, more than many software companies in the world. And those people develop software inside the products, which is called embedded software, as well as build applications and data analytics tools that use the data we get from hardware. The importance of hardware is what people often underestimate when they talk about the Internet of Things. Have you ever thought about where data comes from?
S+B:
It comes from the customers, no?
KAESER: People say they are getting the data from their customers. But when I ask who and what is providing the data, they respond, “It’s the machines and stuff.” Exactly! It’s the installed base of machines. If you look at a high-performance energy turbine, like a gas turbine, our flagship, the 8000H, it’s a 600-megawatt machine — a really cool machine! There are thousands of sensors in that machine, and every sensor has a story to tell. Every moment, that sensor delivers data to software, which stores it in the cloud.
KAESER: People say they are getting the data from their customers. But when I ask who and what is providing the data, they respond, “It’s the machines and stuff.” Exactly! It’s the installed base of machines. If you look at a high-performance energy turbine, like a gas turbine, our flagship, the 8000H, it’s a 600-megawatt machine — a really cool machine! There are thousands of sensors in that machine, and every sensor has a story to tell. Every moment, that sensor delivers data to software, which stores it in the cloud.
There’s a two-step process: collecting data
and making use of it. Once I have data, how do I make meaningful analytics out
of that data so my customer has an advantage? My customer would pay me for
information that makes life easier, better, less costly, or more valuable. And
that’s what many people don’t understand when they talk about the Internet of
Things or open platforms. “I’ve got data, but why would someone pay me for that
data?”
S+B:
What does it mean to have every product you make incorporate sensors and be
connected in the cloud? Is this your way of approaching manufacturing in every
one of your diverse businesses?
KAESER: That’s exactly what it is. We’ve got energy generation. We’ve got energy management. We’ve got automation for manufacturing, and products for industries like oil and gas, food and beverage, mining, all that good stuff. And there are vertical software applications for certain industries. Those applications are all based on hardware that provides data through sensors. We look at that data, analyze it, and then make applications out of it. Think about turbines for a utility. We help the utility company analyze how much service its power plants need based on fuel consumption, the utilization rates, and the maintenance data.
KAESER: That’s exactly what it is. We’ve got energy generation. We’ve got energy management. We’ve got automation for manufacturing, and products for industries like oil and gas, food and beverage, mining, all that good stuff. And there are vertical software applications for certain industries. Those applications are all based on hardware that provides data through sensors. We look at that data, analyze it, and then make applications out of it. Think about turbines for a utility. We help the utility company analyze how much service its power plants need based on fuel consumption, the utilization rates, and the maintenance data.
S+B:
Is this a vertically integrated process in the sense that you’re manufacturing
the machines that produce the data, you’re collecting and analyzing the data,
and then you’re writing software? And are you also making the sensors?
KAESER: We manufacture products that generate power, that automate manufacturing processes, that scan people (like CT and MRI machines), and that move people and goods from place A to place B. That’s a lot of products, and all those products have sensors. But we don’t manufacture sensors. However, once we get the data, we have the data analytics platform and the cloud. We have a proprietary cloud, for example, an on-site cloud. Our customers care about manufacturing and engineering data and intellectual property rights because [this type of data] is the holy grail of innovation.
KAESER: We manufacture products that generate power, that automate manufacturing processes, that scan people (like CT and MRI machines), and that move people and goods from place A to place B. That’s a lot of products, and all those products have sensors. But we don’t manufacture sensors. However, once we get the data, we have the data analytics platform and the cloud. We have a proprietary cloud, for example, an on-site cloud. Our customers care about manufacturing and engineering data and intellectual property rights because [this type of data] is the holy grail of innovation.
S+B:
How does this approach change your relationship with your customers and the
value proposition Siemens offers?
KAESER: It changes the relationship massively because data analytics gives a company a lot of information [it can use] to optimize and shorten the value chain. The value chain consists of the supplier of your supplier, your supplier, your company, your customer, and the customer of your customer. The information you get from data can shorten that value chain. You can make products faster, more cost-efficiently, more flexibly. You can produce in lot sizes of one. You can cut out different links of the value chain. And the links that get cut out provide the least value in the value chain. And that’s what you need to understand. “Where am I in the value chain? How can I remain a strong link by providing more value than anyone else in there?” You’d better know what you can do with your data and cut someone else out rather than get cut out yourself. The issue isn’t just that your suppliers might try to cut you out. Your customers might try to cut you out because they say, “I’ve got the data, so why do I need you?” That’s the paradigm shift…. The telecom space is a good example. Now why would you pay a lot of money for making a phone call if you’ve got Skype?
KAESER: It changes the relationship massively because data analytics gives a company a lot of information [it can use] to optimize and shorten the value chain. The value chain consists of the supplier of your supplier, your supplier, your company, your customer, and the customer of your customer. The information you get from data can shorten that value chain. You can make products faster, more cost-efficiently, more flexibly. You can produce in lot sizes of one. You can cut out different links of the value chain. And the links that get cut out provide the least value in the value chain. And that’s what you need to understand. “Where am I in the value chain? How can I remain a strong link by providing more value than anyone else in there?” You’d better know what you can do with your data and cut someone else out rather than get cut out yourself. The issue isn’t just that your suppliers might try to cut you out. Your customers might try to cut you out because they say, “I’ve got the data, so why do I need you?” That’s the paradigm shift…. The telecom space is a good example. Now why would you pay a lot of money for making a phone call if you’ve got Skype?
The
Industrie 4.0 Difference
S+B:
It seems like this approach would require a substantial shift in the culture —
as well as how you train people and present yourself to customers.
KAESER: If you look at a company culture and what it takes to stay alive for the next generation or two, or maybe even longer, you need to look at the purpose of the company. Why is it that I’m going to get up in the morning and go to work at that company? Why do I believe it is worth going the extra mile and giving my extra five cents? The way we’ve been defining the purpose at Siemens is that we are a “business to society” enterprise.
KAESER: If you look at a company culture and what it takes to stay alive for the next generation or two, or maybe even longer, you need to look at the purpose of the company. Why is it that I’m going to get up in the morning and go to work at that company? Why do I believe it is worth going the extra mile and giving my extra five cents? The way we’ve been defining the purpose at Siemens is that we are a “business to society” enterprise.
We
created that term — business to society — because we have B2C
(business to consumer) and B2B (business to business) offerings. But we are a
business that contributes to society’s development in the world, through
becoming carbon neutral by 2025 (we’re the biggest company in the world that
has committed to doing that); or saving lives; or providing people with
reliable, safe power; or giving people a more livable life in cities. Our
employees think that’s pretty great. That’s how we start changing the culture.
Next, everyone in this company, from the
receptionists all the way up to the CEO, needs to have an understanding of what
we call our ownership culture. I say to them, “Whatever you do, whoever you
are, wherever you work in the Siemens world, just act as if this were your own
company.” That approach is how we do business and how we manage our business.
S+B:
That’s mostly inward-facing. What about external-facing efforts?
KAESER: You need to change the way you go to market. The world is all about competencies. Never let the hardware guys sell software, never, ever! Just don’t even let them get close to it. Our perspective is that we now sell solutions, applications, and comprehensive systems as opposed to just selling the product. We sell value instead of selling functionality. It’s a complicated go-to-market method.
KAESER: You need to change the way you go to market. The world is all about competencies. Never let the hardware guys sell software, never, ever! Just don’t even let them get close to it. Our perspective is that we now sell solutions, applications, and comprehensive systems as opposed to just selling the product. We sell value instead of selling functionality. It’s a complicated go-to-market method.
S+B:
What is Industrie 4.0, and what role is Siemens playing in that?
KAESER: Industrie 4.0 is the German version of the first generation of manufacturing automation. It basically combines engineering and manufacturing. We call it a digital twin. We’ve built Industrie 4.0–type manufacturing plants in Germany. And the first one outside Germany is in Chengdu, China. Thousands of people are visiting this plant.
KAESER: Industrie 4.0 is the German version of the first generation of manufacturing automation. It basically combines engineering and manufacturing. We call it a digital twin. We’ve built Industrie 4.0–type manufacturing plants in Germany. And the first one outside Germany is in Chengdu, China. Thousands of people are visiting this plant.
S+B:
If I were to show up there, would I notice a difference between it and any
other factory?
KAESER: Oh, yeah. You will see a highly automated manufacturing flow, like what the automotive industry uses. But what you see is sometimes the flow is like this [he moves one hand off to the side]. Sometimes the flow is like this [he shifts it again], and all of a sudden, the flow is like this [he moves both hands]. And you say, “What the hell is going on here?” Well, what happens is that there’s a customer request such as, “I want this product in that size, in that lot size, with that blue color, with that dot on the bottom.” So the software steers the manufacturing process into lots as small as one item. And then sometimes all of a sudden, you see that certain products are being sorted out into a queue, because the plant received information about a quality defect in that product. So the simulation fixes the defect and gets approval from quality management to put it into the production process. And then off we go.
KAESER: Oh, yeah. You will see a highly automated manufacturing flow, like what the automotive industry uses. But what you see is sometimes the flow is like this [he moves one hand off to the side]. Sometimes the flow is like this [he shifts it again], and all of a sudden, the flow is like this [he moves both hands]. And you say, “What the hell is going on here?” Well, what happens is that there’s a customer request such as, “I want this product in that size, in that lot size, with that blue color, with that dot on the bottom.” So the software steers the manufacturing process into lots as small as one item. And then sometimes all of a sudden, you see that certain products are being sorted out into a queue, because the plant received information about a quality defect in that product. So the simulation fixes the defect and gets approval from quality management to put it into the production process. And then off we go.
The production process is being changed. It’s
machines talking to machines in a self-optimizing manufacturing and engineering
process. Using this approach, we have attained a production quality rate of
99.9988%. That is getting pretty close to Six Sigma. In the last five years, we
have increased productivity eightfold. It’s really something.
S+B:
When you go back to the origins of the assembly line in the U.S., Henry Ford
said it could work only if you had a standardized product. For 100 years,
customization has been the enemy of manufacturing efficiency. But you’re saying
this approach resolves that contradiction?
KAESER: Exactly. Industrie 4.0 basically takes the cost of scale close to zero. No matter what lot size you need, the unit cost is about the same. At some point, what will happen is this: You are a consumer and you want to buy a car. You go to the Internet, put your specs together, and send that order to BMW. Someone will check your credit history and your funds. Then, your car will go straight to production and the factory will build it to order. Four weeks from now, you will have a car. No more waiting six months, or compromising at the dealership, where they have 50 cars but not the one you want.
KAESER: Exactly. Industrie 4.0 basically takes the cost of scale close to zero. No matter what lot size you need, the unit cost is about the same. At some point, what will happen is this: You are a consumer and you want to buy a car. You go to the Internet, put your specs together, and send that order to BMW. Someone will check your credit history and your funds. Then, your car will go straight to production and the factory will build it to order. Four weeks from now, you will have a car. No more waiting six months, or compromising at the dealership, where they have 50 cars but not the one you want.
S+B:
There’s been a lot of talk about the ability to do mass customization through
technologies such as 3D printing. But so far it seems like more of a hobbyist’s
endeavor.
KAESER: No, no, no! We use a lot of 3D printing already. We print small-volume prototypes, and that’s a very important method of speeding up innovation. In the old days, it took ages to design a high-efficiency, high-temperature blade. Today, we simulate it, thanks to our digital factory PLM simulation system. We simulate the airflow, the cooling system, and the coating, which is important because the temperature at the edges of that turbine blade goes up 1,600 degrees Celsius when it’s in use, so we’ve got to really understand what the cooling system is all about and how we minimize the gaps in efficiency. Once we’ve done the simulation, we print the blade. 3D printing is also a huge help in bridging the gap between scale and scope. Scale used to mean that if you did 5,000 blades, it was cheap, and if you did only five blades, it was very expensive. Today, it doesn’t matter because those five blades can be produced by 3D printing. If you take the scalability out of the equation, you can expand your scope — and have a lot size of one. That’s the approach. It’s interesting. This is real, and it’s not a bad thing to have.
KAESER: No, no, no! We use a lot of 3D printing already. We print small-volume prototypes, and that’s a very important method of speeding up innovation. In the old days, it took ages to design a high-efficiency, high-temperature blade. Today, we simulate it, thanks to our digital factory PLM simulation system. We simulate the airflow, the cooling system, and the coating, which is important because the temperature at the edges of that turbine blade goes up 1,600 degrees Celsius when it’s in use, so we’ve got to really understand what the cooling system is all about and how we minimize the gaps in efficiency. Once we’ve done the simulation, we print the blade. 3D printing is also a huge help in bridging the gap between scale and scope. Scale used to mean that if you did 5,000 blades, it was cheap, and if you did only five blades, it was very expensive. Today, it doesn’t matter because those five blades can be produced by 3D printing. If you take the scalability out of the equation, you can expand your scope — and have a lot size of one. That’s the approach. It’s interesting. This is real, and it’s not a bad thing to have.
Labor
and Society
S+B:
There’s a lot of concern about the impact of technology on jobs and employment.
If manufacturing becomes substantially more automated, what effect will that
have on employment throughout the supply chain?
KAESER: If you shorten the value chain by cutting out links, as we discussed earlier, it results in lower cost, and that means fewer resources are being used. Fewer material resources will be needed, and fewer human resources will be needed. This is just the way it works. Furthermore, the remaining human resources will need different skills than blue-collar workers used to have. Workers need to deal with machines that are quicker to understand what needs to be done than the workers themselves are. Their experience is dwarfed by the computer’s “experience,” because the computer stores all the knowledge and calibrates all the data. People will still be in the factory, but they will doing different work than they used to. Reskilling workers is a lot of hassle. That’s not great news, right?
KAESER: If you shorten the value chain by cutting out links, as we discussed earlier, it results in lower cost, and that means fewer resources are being used. Fewer material resources will be needed, and fewer human resources will be needed. This is just the way it works. Furthermore, the remaining human resources will need different skills than blue-collar workers used to have. Workers need to deal with machines that are quicker to understand what needs to be done than the workers themselves are. Their experience is dwarfed by the computer’s “experience,” because the computer stores all the knowledge and calibrates all the data. People will still be in the factory, but they will doing different work than they used to. Reskilling workers is a lot of hassle. That’s not great news, right?
S+B:
Certainly not for labor. How do we get around this?
KAESER: Making up the difference is possible only through growth. If you can massively lower the costs of a product, people who were unable to afford that product will become able to afford it. We have 7 billion people on this planet. Of those, maybe 4 billion would be able to drive. But only 2 billion can afford a car. By making the cars cheaper, you have maybe another 200 million who can afford a car. By tearing down the cost barrier, you enable more people to afford it and thus you secure growth.
KAESER: Making up the difference is possible only through growth. If you can massively lower the costs of a product, people who were unable to afford that product will become able to afford it. We have 7 billion people on this planet. Of those, maybe 4 billion would be able to drive. But only 2 billion can afford a car. By making the cars cheaper, you have maybe another 200 million who can afford a car. By tearing down the cost barrier, you enable more people to afford it and thus you secure growth.
S+B:
Do you see barriers to the rollout of ever more efficient manufacturing
technology?
KAESER: We were just having quite a debate and discussion with Andy McAfee [coauthor of The Second Machine Age, which argues that revolutions in technology will sharply reduce the need for labor]. And I said, “There is one thing we really never had a look at. Will the majority of the society be willing and able to deal with the fact that the few smartest, the few brainiest, are going to conquer the world?”
KAESER: We were just having quite a debate and discussion with Andy McAfee [coauthor of The Second Machine Age, which argues that revolutions in technology will sharply reduce the need for labor]. And I said, “There is one thing we really never had a look at. Will the majority of the society be willing and able to deal with the fact that the few smartest, the few brainiest, are going to conquer the world?”
He said: “Why not?” I responded that democracies
[are run] by the majority vote and not so much by who is the smartest, the
fastest, and the brightest.
And the reality is that we don’t know the
outcome [of these technological advances]. There is going to be a regulatory
catalyst. And there is going to be a societal catalyst. The unions, the
churches, those social types of nonprofit organizations say to businesses, “You
think you’re pretty cool. You’re going to cut out all the middlemen, but you’re
also going to cut out social justice, so you just go to hell. We don’t want to
deal with you.” That societal impact has always been a massive topic that we, I
think, also are trying to understand. How can you as a business contribute to
society? Because if you don’t provide a value to society, society will just not
accept you.
S+B:
This would seem to require a different type of leadership from technology and
industrial companies.
KAESER: Think about the whole matter of air pollution. We said, we’ve got to get the CO2 emissions down. Of course we need to. Then, we talk to China and to India and to Indonesia and say, “You are going to have to stop the coal-fired power plants and you’re going to have to stop the pollution of your cities.” And they say, “You know, you [in the West] screwed the whole world. You are developed now. You are rich. You’ve got a lot of money and you are driving nice cars and you are telling us now we cannot do that because you have already produced all the allowable CO2 emissions?” That’s not going to work. So, [if you’re a business in the West,] you’d better make sure that your emissions go down.
KAESER: Think about the whole matter of air pollution. We said, we’ve got to get the CO2 emissions down. Of course we need to. Then, we talk to China and to India and to Indonesia and say, “You are going to have to stop the coal-fired power plants and you’re going to have to stop the pollution of your cities.” And they say, “You know, you [in the West] screwed the whole world. You are developed now. You are rich. You’ve got a lot of money and you are driving nice cars and you are telling us now we cannot do that because you have already produced all the allowable CO2 emissions?” That’s not going to work. So, [if you’re a business in the West,] you’d better make sure that your emissions go down.
If you don’t bridge the societal divide,
you’re going to go nowhere with Industrie 4.0 or the Internet of Things or
anything else a lot of techies and companies are talking about. That’s something
that leaders of companies had better think about. They need to ask themselves,
“How do I deal with the digital divide, the societal divide? How do I make sure
that I bring people along and make a meaningful contribution to society?”
by Daniel Gross
http://www.strategy-business.com/article/Siemens-CEO-Joe-Kaeser-on-the-Next-Industrial-Revolution
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