An Ideas-Based Online Magazine of the Global Network for Advanced Management

What Do New Autonomous Technologies Mean for Global Business?

Amazon aspires to make drone deliveries for its Prime service. Uber, the dominant taxi service for the digital age, is experimenting with self-driving cars; Google, which has been testing self-driving cars for years, is also rumored to have a taxi service in mind. How will new autonomous technologies impact the lives of consumers and shape businesses, and what is the role of governments in shaping them? Global Network Perspectives asked faculty and experts to weigh in.

Photo of Topio robot
Source: Wikimedia Commons

Updated October 12.

United States

Robert J. Shiller, Sterling Professor of Economics, Yale University

How will new forms of autonomous technology—drones, self-driving cars, new forms of robotics—likely change our lives and create new business models?

In my mind, the advent of autonomous technology is best thought of as a major new true uncertainty. Frank Knight, in his 1921 book Risk, Uncertainty, and Profit distinguished true uncertainty from risk. When there is true uncertainty we cannot even frame the list of possible outcomes accurately let alone give their probabilities. With risk, possible events and probabilities are known.

With the advance of information technology and drones, we face a mixture of both true uncertainty and measurable risk. Capitalism deals with uncertainty through speculation, and speculation is a constructive response to uncertainty, even if it produces occasional speculative bubbles.

How have new autonomous technologies already impacted businesses working in your country or region? What opportunities and threats do they present?

When the Internet was invented in the mid-1990s, no one could even imagine, let alone predict, such events as the success of Wikipedia or of the social media. Those who came closest may have been science fiction writers. I was recently rereading a new book where I was one of nine economist contributors In 100 Years: Leading Economists Predict the Future. I was struck at how much the economists dwelled on the past, rather than the future they were asked to talk about. But they did speak of significant risk and uncertainty.

How are people and governments in your region responding?

Entrepreneurship, the blooming of multitudes of information technology startups, is the response of our society. These are truly exciting times for information technology entrepreneurs. The problem is that there is not a similar level of planning for the economic dislocations that might follow.

There is not a similar level of entrepreneurship in the realm of insurance, which might innovate to provide risk management for careers that are buffeted by new technology. There is not yet a similar level of innovation in public finance, where there is a potential role of government in providing risk management against technology-related future shifts in economic power between groups of people.

Insurance and finance are not just about managing risk and uncertainty. They are also about incentivizing people to take actions, so that they are not stymied by fear of the future. People need to be incentivized to take risks with their own human capital.

 As I argued in my 2009 book Finance and the Good Society, people who work in insurance and finance as innovators are solely needed. Though our mathematical models for insurance and finance may describe risk as if it were known, practitioners have always managed to deal as well with true uncertainty.  Their financial and insurance innovations are needed to deal constructively with the deep problems that rapid change in our economy may bring.


Erin L. Scott, Assistant Professor of Strategy and Policy, National University of Singapore Business School

Days before Uber launched their self-driving car in Pittsburgh, nuTonomy introduced their self-driving taxis in Singapore. Doug Parker, COO of the Cambridge, MA-based firm, noted that Singapore is an ideal location for their pilot tests given the "high demand for taxis, well-maintained roads, and clear government regulations" (Straits Times). This is indicative of the broader favorable environment for autonomous technology in the country -- a highly skilled populace with high internet and smartphone penetration rates, and clear and efficient government policy. Furthermore, many industries in the country, particularly those in the service sector, face labor shortfalls, which autonomous technology provides avenues for remedy. From the more complex driverless buses transporting students to the unique robot receptionists and drone waiters, pilot tests of autonomous technology are increasingly common across the island.

In line with many governments around the world, the Singapore Government has championed the development autonomous technology through robust investments and partnership agreements. More notably, however, the government has also supported business model experimentation by large incumbents, small businesses, and entrepreneurs alike with wide-ranging grant programs that support investment in technology. As autonomous technology fills labor shortfalls, it will also require workers to interface with more complex technologies. As such, the government has also targeted resources to allow workers to update their skills, further reducing the challenge for firms wishing to experiment with new business models. While many of these firm-level experiments may ultimately prove unsuccessful, on a larger scale these government-facilitated activities will result in faster identification and adoption of new business models that leverage autonomous technology.

Broader adoption of autonomous technology will also increase the need for more robust IT security features and increased attention and investment in IT security within firms. This is no trivial feat, as indicated by the recent measure to tighten security by moving all Singapore Government computers used by public servants offline. Companies and workers with these skills will be increasingly valuable as business models that leverage autonomous technology become more common.


James McDermott, Lecturer in Business Analytics, UCD Michael Smurfit Graduate Business School

Technology is a force multiplier. That is, one worker with the right technology can carry out a task which would previously have required many. The loom is a good example. Automated technologies are like this too, but in a slightly indirect way. It's not that there is going to be a single person in Uber HQ driving the whole fleet, but between researchers and technologists, and all the people who make the business infrastructure work, we will end up with a relatively few people contributing to making a self-driving car work, and that will replace many drivers.

So there is the important implication of unemployment for large classes of workers -- not just Uber drivers, but in many areas of transport, manufacturing, agriculture, and elsewhere. In an ideal world, these jobs would be replaced by better jobs -- higher-paying, better conditions, and less drudge work. But it's not so clear that this ideal is achievable, either in terms of the number of such jobs that will be available, or the education and underlying aptitudes the employees would require. It may just be that in a world with cheap automated technology, most people's work is worth less than a living wage. Therefore, to avoid a divided and highly unequal society, we may need to accept the prospect of somehow paying workers more than the market says their work is worth. We've seen some EU governments start to talk about universal basic income, and that could be part of the solution.

To turn to an even bigger picture, we need to distinguish between automated technologies and machine intelligence. They say that intelligence is whatever a computer can't do, yet. This definition gets across a surprising trend -- that is that many of the tasks which we thought required intelligence, turned out to be amenable to "mere" brute force and signal processing. Examples include beating the world champion in chess (achieved in 1997) and recognising images as accurately as does a human (achieved, in a limited sense, around 2014). Automated technologies fit in this category.

But the world is moving towards creating machines that deserve to be called intelligent in a stronger sense. Among other things that raises the prospect of recursively self-improving machine intelligence, that is a system smart enough to make minor improvements to its own code, and then build on those to make further improvements, and so on. We all know what happens when we leave money in an account with compound interest indefinitely. Automated creation and improvement of computer programs is possible (for example, I chair the EuroGP 2017 conference which deals with these issues), although the nut certainly hasn't been cracked yet.

In response to all this, I would say that governments are doing the right thing in one respect. The EU is putting machine intelligence topics into the proposed work programmes in the next phase of the Horizon 2020 research funding programme, and this trickles down into the research priorities for national governments. These funding schemes are well-designed in that there are opportunities for academic-industry collaboration, and for interdisciplinary work, for example to explore not only the raw technologies, but also the industrial applications and the economic and social implications, in the same proposal. Many businesses who want to work in this space are already getting involved.

Watch a video of James discussing “Machines Making Decisions.” 

South Africa

Martin Hall, Emeritus Professor, UCT Graduate School of Business

While the media headlines around autonomous technology tend to focus on the cooler applications like driverless cars and drones, its real potential – at least in less developed economies – lies in its ability to overcome infrastructure constraints and facilitate more equitable urban development.

Over the next 20 years most demographic growth will be in cities in the south. The United Nations estimates that 71.3% of South Africa’s population will live in urban areas by 2030; rising to nearly 80% by 2050. South Africa’s urban population is growing larger and younger – and this is a pattern observable across Africa.

Such growth poses challenges. As resources diminish, traditional ways that cities have grown are no longer viable. Cities in the south therefore have a tremendous opportunity to leapfrog early development stages and put autonomous technology to work to solve crucial infrastructure and service delivery gaps. Access to energy, health, transport and education are all areas that could see significant advances.

We have seen before the benefits of early adoption of technology in the region. The poor in South Africa were ahead of the North: they were experimenting with text messaging  on cell phones when rich people in the US still depended on pagers. Mobile technology brought significant and rapid change to people in emerging markets and the new wave of autonomous technology holds similar potential – if we get it right.

Technology always has consequences – good and bad – and we have got to be aware of that, particularly in vulnerable economies. The advent of autonomous technologies will almost certainly change the nature of work, more specifically, it will put people out of work and will continue to hollow out the middle of the labour market.

South Africa is a country of extremes, with one of the largest gaps between rich and poor in the world. And while autonomous technology holds the potential to bridge that gap – equally – it might widen it.

At the UCT Graduate School of Business, our focus is on seeking novel solutions and business models that will achieve inclusive growth. And we believe that to do this we need to work closely with the communities who are most affected by these potential changes; essentially co-creating rather than imposing technology solution onto them.

The potential rewards, if we get it right, are significant. The novel solutions emerging from these regions – simple solutions that make life possible for people – have the potential to lead the world. Urban inequality is a growing feature of cities globally and not just in emerging markets, so the applications for technology solutions to bridge the inequality gap are extensive.

Right now, this innovation is being driven primarily by business and ordinary South Africans with entrepreneurial spirit who are seizing the opportunities these technologies present. Government has been slow to react to these opportunities and show leadership. This needs to change.

The next five years will be crucial in Southern Africa. Up until this point, the region has suffered from extremely high cost of data and low internet penetration. But as roll-out of fibre gains traction and the cost per unit of data drops – the region is poised to take a leap into the future.  


 Joe Peppard, Professor and Head of Information and Communications Technologies, ESMT Berlin 

How will new forms of autonomous technology—drones, self-driving cars, new forms of robotics—likely change our lives and create new business models?

These are obviously emerging technologies, with potential “use cases” being developed by both industry incumbents and new start-ups. Self-driving cars are probably getting most attention, although I believe that it will be some years yet before we actually see them on our roads. I do think, however, that some of the allied technologies associated with these cars will find their way into conventional motor vehicles, particularly those that improve safety. Computers can be better at processing information than a tired driver!

Drones have possible application as delivery vehicles (for example, Amazon’s trials) but also as a device to collect data. It is this latter application, collecting data that may be difficult or not commercially viable to collect by conventional means, which may present the greatest opportunities. Again, the challenge will be to figure out a way to monetize the data.

How have new autonomous technologies already impacted businesses working in your country or region? What opportunities and threats do they present?

As you can imagine, there is a lot of hype surrounding these technologies. Some companies are exploring them and conducting experiments; the technology is still quite immature. The challenge for the leadership teams of all organizations, as with any other technology, is to figure how to leverage the capabilities provided by autonomous technologies and, in parallel, to assess customer reaction and determine what a profitable business model might be. There will be ‘first movers’ but it widespread adoption will depend on market reaction. For public administrators and governments, these technologies may help in creating so called “smarter cities.”

“Smarter” robots are already making their way into factories, particularly those that permit humans to work in close proximity. Self-parking cars are already a reality.

However, for many applications there will be regulatory issues that will have to be overcome, for example to actually permit driverless cars on our streets. This is only to be expected as many of our laws originate from an era with little or no technology. They will have to be re-written to accommodate the new capabilities provided by technology. There are also genuine concerns cybersecurity, liability and data privacy that will have to be addressed.


Olayinka David-West, Professor, Lagos Business School

How will new forms of autonomous technology—drones, self-driving cars, new forms of robotics—likely change our lives and create new business models?

New forms of autonomous technologies will certainly have an impact on lives, society and business. As these technologies gradually reduce human-human interactions in favour of either human-machine or machine-machine interactions, we are bound to see changing business and interaction models. While these may ease existing operational and business constraints, their transformative nature also bring about disruptions in some industries and redefine the human capabilities required in others.

Firstly, business processes in service-oriented industries will be challenged to better support growing digital channels and relationship management strategies for the "always" connected customers with ever-changing value propositions. As such, software platforms (and bots) will form part of organisations' critical infrastructure. Secondly, in the case of industrial businesses, hardware advancements in machinery and equipment using sensors and wireless communications networks will become standard. These will lead to the real-time aggregation and transmission of data about the machine or the context in which it is being used as we see with health data and wearables.

In both cases, the increased use of information technologies will result  in a data surge (or overload) that will require analytical capabilities to help business managers draw better insights. In order to effectively harness this data, new organisational capabilities in the field of data sciences and related partnerships will be essential. The changing customer value propositions will demand for agile organisations with flexible product design capabilities to meet customer needs. In addition, new opportunities for operational efficiency, especially in the areas of capacity utilisation and reduced downtime, will also be harnessed.

How have new autonomous technologies already impacted businesses working in your country or region? What opportunities and threats do they present?

The impact of these autonomous technologies varies from country to country in Africa, especially due to the dependence on public infrastructure; a weakness of most sub-Saharan African (SSA) countries. For example, in the Global Information Technology Report 2016, the latest iteration of the Networked Readiness Index (NRI), which ranks technology readiness in 139 countries, shows SSA countries underperforming (see figure 1 for rank performance of SSA countries). Outside of South Africa and Mauritius ranked 65th and 49th respectively, other countries ranked in the bottom half.

While access to public infrastructure delimits impact in SSA, examples of existing opportunities and threats of different technologies are highlighted across industries.

Opportunities   Threats
Logistics The use of drones for logistics has enhanced delivery capabilities in cities plagued by persistent traffic congestions. This is an opportunity for emerging e-commerce marketplaces. This function transforms the job of a delivery agent from one that requires a driver's license to one that requires navigation skills. This ability has been tested by Nigeria's e-commerce marketplace, Yudala.
  The limited range of drones is further delimited by infrastructure - network connectivity. While most urban areas are connected using wireless mobile technologies, geographic coverage and network quality may inhibit real-time communication and impact reliability and scalability. Another threat associated with the use of open networks is security, where hijack/theft of goods can be averted.
Wearables Wearables and health tracking applications and devices like FitBit open up new business opportunities for the insurance and healthcare industries. Active monitoring of high-risk patients can reduce patient emergencies that may even lead to death. While these personal monitoring tools collect the data, aggregator health analytic systems from insurance companies are lacking.
  Poor security structure may heighten privacy and security concerns.
Telematics The use of telematics in the transportation industry introduces opportunities such as enhanced transportation management, personalised insurance and management services for government, insurance providers and transport maintenance companies respectively.
  Poor security structure may heighten privacy and security concerns. The recent hacks encountered by Jeep are noteworthy.
Telecoms The telecoms industry which provides a significant portion of SSA’s infrastructure is also being revolutionised. In this sector, human data is gradually replacing human voice and messaging which is also threatened by non-human (machine-to-machine) data. Telecoms researchers, Ovum, estimate that by 2020 cellular machine-to-machine (M2M) connections will represent 3.4% of Africa’s 1.3 billion mobile connections.

How are people and governments in your region responding?

Generally, the responses are somewhat lackadaisical. However, telecom companies that are witnessing declining revenues from voice and messaging services in favour of data-oriented alternatives are being forced to review their business models and diversify investments. For example, the South-African MTN Group is a member of the African Internet Group (AIG), an internet platform company and member of the German incubator, Rocket Internet. AIG operates digital platforms across different industries and markets on the Continent.  To further enhance its digital service offerings, MTN has also established ICT startup incubators in South Africa and Nigeria.

Although several African governments are seeking to build digital jobs, governments' ability to understand and develop regulatory guidelines for emerging technologies usually occur after their adoption. 


Antti Lyrra, PhD Candidate, INFORMATION SYSTEMS AND DIGITAL INNOVATION, Department of Management, London School of Economics and Political Science 

How will new forms of autonomous technology—drones, self-driving cars, new forms of robotics—likely change our lives and create new business models?

To match the variety of jobs, tasks and social interactions, autonomous technologies come in many forms and functions. However, they converge at the aim of loosening the coupling between machines and their operators by equipping machines with interactional sense-think-act loops, which allow machines to respond to the sensory inputs according to their design and structure.

The question on how our lives are going to change cannot be answered solely in terms technology. Instead, we should expand the discussion to include contextual elements: what sort of physical and social interactions could be automated and under what principles and social conditions? Running a chatbot differs significantly from a surgical robot. New businesses and business models are bound to emerge to capture these interactional requirements as well as to design and deliver technological solutions or some parts of it. Some businesses may specialise on advising clients on specific business areas and technologies whereas others may focus on providing financial safeguards against failures. 

In his aptly titled book Our Robots, Ourselves: Robotics and the Myths of Autonomy, David Mindell illustrates how automation brings along behavioural and social implications when the locales and principles of perception, decision making and action are reconfigured. 

How have new autonomous technologies already impacted businesses working in your country or region? What opportunities and threats do they present?

Europe has a long history with industrial automation and robotics research and development. For example, car makers have used robotic technologies extensively and benefited from it. As the perception and control technologies are developing, collaborative robots are making inroads to the industrial settings where batch sizes are smaller and workers share the shop floor with robots. Should the promise of collaborative robotics realise in terms of cheaper and more flexible production lines, it could provide on opportunity to bring some of manufacturing back to Europe.  

What comes to the emerging field of service and social robotics, it is full of opportunities for designers, technology developers and users. The challenges revolve around finding the locales where interactional and behavioural requirements can be tied to some robotics technologies and methods in a commercially feasible, robust and socially acceptable way. 

How are people and governments in your region responding?

The public discourse in the English-speaking world tends to follow well-trodden paths. Media is eager to make fanciful stories that seem to be inspired more by science-fiction than the state of technological development. The trend is reinforced by technology companies that are not shy of emotionalising and anthropomorphising technologies using evocative but fluffy words such as brain, cognitive, intelligence, cloud, and amazing. This, subsequently, leads people to depict technologies more advanced, human-kind and autonomous than they really are. In general, the comments from researchers of autonomous technologies are far more qualified and cautious. 

Governments see the investment on autonomous technologies important. As an increasing amount of human labour and associated income is expected to move to the makers and owners of autonomous machines, it would be unwise to let this revenue and tax stream go. To this end, the EU as well as the UK are investing in research and innovation clusters and testing facilities. Simultaneously, they also work on legislative reviews to ensure that the public and individual interests are protected in the era of everyday automation.


Enrique Dans, Professor, IE Business School

Finally, the day has come when we see self-driving vehicles in a real city, carrying real passengers. In Pittsburgh, Uber recently unveiled the first four Ford Fusions to be used for transporting passengers, for the moment chosen from among the most loyal and satisfied of its customers: the company has right now ten vehicles, and is ready to deploy up to a hundred.

The vehicles have a driver ready to take the controls in an emergency, accompanied by a co-pilot with a laptop taking notes. The company spent the morning introducing the service to journalists and allowing them to get behind the wheel of the vehicles: read here to get an idea of the experience (Mashable, New York TimesTechCrunch, The Verge, Wired or Quartz, in addition to the official one from Uber).

Obviously, these are not fully self-driving taxis, but for most of the time they are in standalone mode. Some passengers noted the times when the driver took over, but in general everybody who took a ride seems to agree that this project is a major milestone in the future of self-driving vehicles, as well as the importance of a company deciding to launch such a test. 

In addition to the publicity from being a groundbreaker — Google’s tests have not been open to the general public — the company aims to benefit from the data and insights gained from passengers themselves, which will be very different from that provided by its engineers. In Spain so far, the only experience we have seen related to autonomous vehicles has been a Citröen - traveling from Vigo (SW of Spain), where the Citröen factory is located, to Madrid, with a couple of politicians and a journalist. Not much. Can we expect any particular city to champion the movement and incentivize any company to come up with real tests? Spain is notable for being socially hyperactive, and one of the most important European countries in car manufacturing: anyone sees the opportunity? 

In an autonomous vehicle, when there is a problem, the algorithm is corrected, and the problem does not reoccur in any other vehicle, something completely impossible to imagine in the case of human conduct. Hence the real importance of these deployments, which makes them much more than just advertising.

The Ford Fusion adapted by Uber is a first attempt, and one that will continue through the collaboration with Volvo to incorporate more vehicles. A LiDAR spins continuously atop the vehicle, with sensors front, back and on the sides to detect objects in close proximity. In addition, 20 cameras collect information about what is going on around the car: braking vehicles, pedestrians crossing, traffic lights, signs, etc. There are also two antennas on the roof and on the back for GPS data and wireless connectivity. The vehicles shown this morning have a tablet in the back seat with a series of frequently asked questions, which the sensors, informs you when the vehicle is driving autonomously and when not, as well as the speed and route being taken. The lower two thirds of the screen show the vehicle and its surroundings as perceived by the LiDAR located on the roof, to give passengers an idea about what the vehicle sees, all in a bid to make the experience as transparent as possible. Also, you can use the tablet to take a selfie and share it, a brilliant marketing element. Everything is designed so that passengers will not only feel at ease and get used to the idea of using a self-driving vehicle driven autonomously, but also to get them to share their experiences.

Volvo, the other brand Uber is working with (the relationship with Ford, according to Ford themselves, is not a collaboration, but Uber’s own choice to use their vehicles), was not decided by chance. Besides having a reputation for safety obtained over a long time, it is adopting a similar communication strategy: a few days ago it launched the Drive Me project in Gothenburg, lending its SUV XC90 to families gather data: users see things differently than engineers do. 

Again, the idea is to familiarize the general public with the idea of self-driving vehicles, clearly part of a wider automobile industry response to the challenge from technology companies. Volvo intends to market its autonomous vehicles to the public in 2021, the same year as Ford. For its part, GM last month unveiled the Chevrolet Bolt EV with greater autonomy to the Tesla Model 3 at a similar price, obviously building on its decades of experience in the industry, playing up the delays that have hampered Elon Musk’s projects, but who looks like achieving his dream of a truly competitive market that should make electric-powered cars a reality in the short term.

The future is still not clear and there are many questions: who will carry out the multi-billion dollar investments required to put together the fleets of vehicles required to meet the transport needs of entire cities? How will they be maintained, and how will competition be guaranteed? Who will take responsibility when there are accidents, and of course what will people employed as drivers until now do?

These are not problems that will be resolved overnight, but neither can we sit on our hands waiting for them to answer themselves. alone.

But as of today, in a city in the United States, you can now call Uber and be taken to your destination for most of the time in a self-driving vehicle that is constantly generating data to feed a constantly self-learning algorithm to improve driveability. And the interesting thing about Pittsburgh is that the city has committed to become a testbed for experimentation in autonomous vehicles, hoping to become one of the first cities to change their layout and redistribute urban space between cars and people. 

All those who, for whatever reason, refuse to accept that technology is more than just advertising for the future, should take a trip to Pittsburgh. What they’ll see is just the beginning. In Spain, I guess, we will have to wait a little bit more... 


Howard Yu, Professor, Strategic Managment and Innovation, IMD Business School

How will new forms of autonomous technology—drones, self-driving cars, new forms of robotics—likely change our lives and create new business models?

To begin with, transaction costs will shrink dramatically (if not go away entirely). When logistic coordination among industry players becomes automated, moreover, it is easy to see how redundancy in production facilities and waste will plummet, and the need for direct communication with managers will become less necessary. And once market coordination becomes easier, the argument for bringing activities in-house will weaken significantly: whatever advantages large companies had for being vertically integrated will dissipate. This, in turn, will permit smaller players with far fewer resources to specialize in best-in-class services and deliver highly customized solutions to meet specific demands. Traditional companies must therefore prepare for a new economic reality that’s radically different from the one they’ve known.

How have new autonomous technologies already impacted businesses working in your country or region? What opportunities and threats do they present?

Machine algorithms already predict how we click and buy. Companies have automated how they mail, call, offer discounts, recommend products, show ads, inspect for flaws, and approve loans. Credit card companies detect which transactions are likely to be fraudulent. Insurers anticipate which customers are likely to file claims.

Malcolm Gladwell’s bestseller Blink celebrates the human ability of a medical specialist to make a diagnosis almost as soon as a patient walks in or an art expert to “sense” when a work is a forgery. However, machine learning, as demonstrated recently by both AlphaGo and IBM Watson, is seriously challenging such dominance by human experts. For example, based on information from millions of pages of medical journals, IBM Watson can offer physicians recommendations suggestions on additional blood tests and updates on the latest clinical trials. To receive a diagnosis from Watson, all a cancer doctor with an iPad app has to do is describe the patient’s symptoms in plain English.

In Switzerland, such changes will directly impact the banking industry especially. From private banking to wealth management, from international money transfer to high frequency trading, autonomous technologies have already made big impacts on back-end processes, turning them more efficiency and accurate. Going forward, however, the front-end customer experience will also be revolutionized.  

How are people and governments in your region responding?

Like most countries, the biggest debates surround the prospect of job security as many occupations are under threats because of automation. At the same time however, local government, think-tanks, big companies, universities, incubators, startups, and science parks are racing to bring ever more technologies online. We are in the race of global competitiveness. Resisting and denying technologies will be a catastrophic stand for any nation. For this reason, the pursuit of autonomous technologies has actually accelerated, rather than slowing down.  


Knut Haanaes, Professor, IMD Business School

Henry Ford famously introduced his “automation program” in 1947. Since then we have seen continuous innovation in automation within manufacturing, mainly ways to improve the value chain through processes (such as lean manufacturing) and machines (such as industrial robots). Most of the business improvements driven by automation have in fact been in manufacturing value chains.

As automation technologies are multiplying (such as advanced robotics, self-driving vehicles and drones) we will continue to see effects in manufacturing value chains, for sure. But we will also for the first time see huge effects of automation in more service based business models. Especially two types of services business models will be dramatically enabled by automation; network services and resource sharing platforms.

Let us start with how network services will be enabled by new automation technologies. Networking services are linked to embracing new technologies that allow for new ways of delivering network value. Think about Uber and Amazon. We already see that Uber will enrich their connectivity through self-driving cars and that Amazon wants to use drones to improve their delivery capabilities. They both run “clubs” that grew to become huge because of network effects, connecting more people, companies, products and places. The customers simply want to be part of the largest network because it provided the best connectivity – the richest offerings, access to the most people and places. Automation for networking services companies allow them to deliver faster and at lower cost, and it allows them to handle flows more efficiently.

Next, let’s look at resource sharing platforms, i.e., companies insourcing use of physical, informational, and human resources. Classical examples include shared facilities or labour pools, but this is a current fast growing set of services covering all business functions ranging from IT and HR to facility management and contract manufacturing. The logic of resource sharing is compelling – by leveraging the total scale in the delivery of a given process across clients, the provider can drive up value through reliability, development and quality at the same time as they can drive down costs through shared technology platforms. Automation will be a major enabler because it allows firms such as IBM and ISS to build more efficient global delivery at scale, whilst using relevant data to continuously improve delivery quality. Services through resource sharing is a scale and platform game where the winner is the one to drive scale in customers and to utilize technology platforms to deliver. Automation will be a major enabler to develop more scalable platforms.

Global Network for Advanced Management