by Klaus Schwab
In addition to maintenance, the ability to predict the performance of an asset enables new business models to be established. Asset performance can be measured and monitored over time – analytics provide insights on operational tolerances and provide the basis for outsourcing products that are not core or strategic to the needs of the business. SAP is an example of a company that is leveraging data from physical products embedded in agriculture to increase uptime and utilization.
The ability to predict the performance of an asset also offers new opportunities to price services. Assets with high throughput such as lifts or walkways can be priced by asset performance, and service providers can be paid on the basis of actual performance against a threshold of 99.5% uptime over a given period. Take the example of truck fleets. Long-distance haulers are interested in propositions where they pay tire manufacturers by the 1,000 kilometres of road use rather than periodically buying new tires. This is because the combination of sensors and analytics enables tire companies to monitor driver performance, fuel consumption and tire wear to offer a complete end-to-end service.
3.2.3 Collaborative Innovation
A world of customer experiences, data-based services and asset performance through analytics requires new forms of collaboration, particularly given the speed at which innovation and disruption are taking place. This is true for incumbents and established businesses but also for young, dynamic firms. The former often lack specific skills and have lower sensitivity to evolving customer needs, while the latter are capital poor and lack the rich data generated by mature operations.
As a the Forum’s Collaborative Innovation: Transforming Business, Driving Growth report outlines, when firms share resources through collaborative innovation, significant value can be created for both parties as well as for the economies in which such collaborations take place. One such example is the recent collaboration between the industrial giant Siemens, which spends around $4 billion a year in research and development, and Ayasdi, an innovative machine-learning company and Forum Technology Pioneer founded at Stanford University in 2008. This partnership gives Siemens access to a partner that can help solve complex challenges of extracting insights from vast data, while Ayasdi can validate its topological data analysis approach with real-world data, while expanding market presence.
Such collaborations, however, are often far from straightforward. They require significant investment from both parties to develop firm strategy, search for appropriate partners, establish communication channels, align processes, and flexibly respond to changing conditions, both inside and outside the partnership. Sometimes, such collaborations spawn entirely new business models such as city car-sharing schemes, which bring together businesses from multiple industries to provide an integrated customer experience. This is only as good as the weakest link in the partnership chain. Companies need to go well beyond marketing and sales agreements to understand how to adopt comprehensive collaborative approaches. The fourth industrial revolution forces companies to think about how offline and online worlds work together in practice.
3.2.4 New Operating Models
All these different impacts require companies to rethink their operating models. Accordingly, strategic planning is being challenged by the need for companies to operate faster and with greater agility.
As mentioned earlier, an important operating model enabled by the network effects of digitization is the platform. While the third industrial revolution saw the emergence of purely digital platforms, a hallmark of the fourth industrial revolution is the appearance of global platforms intimately connected to the physical world. The platform strategy is both profitable and disruptive. Research by the MIT Sloan School of Management shows that 14 out of the top 30 brands by market capitalization in 2013 were platform-oriented companies.37
Platform strategies, combined with the need to be more customer-centric and to enhance products with data, are shifting many industries from a focus on selling products to delivering services. An increasing number of consumers no longer purchase and own physical objects, but rather pay for the delivery of the underlying service which they access via a digital platform. It is possible, for example, to get digital access to billions of books via Amazon’s Kindle Store, to play almost any song in the world via Spotify, or to join a car-sharing enterprise that provides mobility services without the need to own the vehicle. This shift is a powerful one and allows for more transparent, sustainable models of exchanging value in the economy. But it also creates challenges in how we define ownership, how we curate and engage with unlimited content, and how we interact with the increasingly-powerful platforms that provide these services at scale.
The World Economic Forum’s work in its Digital Transformation of Industry initiative highlights a number of other business and operating models designed to capitalize on the fourth industrial revolution. The previously mentioned “customer-centricity” is one of these, with proponents such as Nespresso focusing their efforts on front-line processes and empowering staff to put the client first. Frugal business models use the opportunities afforded by the interaction of digital, physical and human realms to open up new forms of optimization such as efforts by Michelin to provide high-quality services at low cost.
Data-powered business models create new revenue sources from their access to valuable information on customers in a broader context and increasingly rely on analytics and software intelligence to unlock insights. “Open and liquid” companies position themselves as part of a fluid ecosystem of value creation, while “Skynet” firms focus on automation, becoming more prevalent in hazardous industries and locations. And there are many examples of businesses pivoting towards business models that focus on employing new technologies to make more efficient use of energy and material flows, thereby preserving resources, lowering costs, and having a positive impact on the environment (see Box B: Environmental Renewal and Preservation).
These transformations mean that businesses will need to invest heavily in cyber- and data-security systems to avoid direct disruption by criminals, activists or unintentional failures in digital infrastructure. Estimates of the total annual cost to business of cyber-attacks are of the order of magnitude of $500 billion. The experiences of companies such as Sony Pictures, TalkTalk, Target and Barclays indicate that losing control of sensitive corporate and customer data has a material negative effect on share prices. This accounts for why Bank of America Merrill Lynch estimates that the cyber-security market will more than double from around $75 billion in 2015 to $170 billion by 2020, implying an annual growth rate of more than 15% for the industry in the coming five years.38
Emerging operating models also mean that talent and culture have to be rethought in light of new skill requirements and the need to attract and retain the right sort of human capital. As data become central to both decision-making and operating models across industries, workforces require new skills, while processes need to be upgraded (for example, to take advantage of the availability of real-time information) and cultures need to evolve.
As I mentioned, companies need to adapt to the concept of “talentism”. This is one of the most important, emerging drivers of competitiveness. In a world where talent is the dominant form of strategic advantage, the nature of organizational structures will have to be rethought. Flexible hierarchies, new ways of measuring and rewarding performance, new strategies for attracting and retaining skilled talent will all become key for organizational success. A capacity for agility will be as much about employee motivation and communication as it will be about setting business priorities and managing physical assets.
My sense is that successful organizations will increasingly shift from hierarchical structures to more networked and collaborative models. Motivation will be increasingly intrinsic, driven by the collaborative desire of employees and management for mastery, independence and meaning. This suggests that businesses will become increasingly organized around distributed teams, remote workers and dynamic collectives,
with a continuous exchange of data and insights about the things or tasks being worked on.
An emerging workplace scenario that reflects this change builds on the rapid rise of wearable technology when combined with the internet of things, which is progressively enabling companies to blend digital and physical experiences to benefit workers as well as consumers. For example, workers operating with highly complex equipment or in difficult situations can use wearables to help design and repair components. Downloads and updates to connected machinery ensure that both workers in the field and the capital equipment they use are kept up to date with the latest developments. In the world of the fourth industrial revolution, where it is standard practice to upgrade cloud-based software and refresh data assets through the cloud, it will be even more important to ensure that humans and their skills keep pace.
Combining the digital, physical and biological worlds
Companies able to combine multiple dimensions – digital, physical and biological – often succeed in disrupting an entire industry and their related systems of production, distribution and consumption.
Uber’s popularity in many cities starts with an improved customer experience – tracking of the car location via a mobile device, a description of the car standards and a seamless payment process, thus avoiding delays at the destination. The experience has been enhanced and bundled with the physical product (transportation of a person from A to B) by optimizing the utilization of the asset (the car owned by the driver). In such cases, the digital opportunities are often not translated into just a higher price or lower cost but also into a fundamental change of the business model. This is driven by an end-to-end approach, from service acquisition to delivery.
These combination-based business models illustrate the extent of the disruption that occurs when digital assets and interesting combinations of existing digital platforms are used to reorganize relationships with physical assets (marking a notable shift from ownership to access). In their markets, neither company owns the assets: a car driver owns the car and makes it available; a homeowner makes his room available. In both cases, the competitive advantage is built on a superior experience, combined with reduced transaction and friction costs. Also, these companies match demand and supply in a rapid and convenient manner, which side steps the business models of the incumbents.
This marketplace approach progressively erodes the long established position of incumbents and dismantles the boundaries between industries. Many senior executives expect industry convergence to be the primary force impacting their business in the next three to five years.39 Once a customer has established a track record of trust and confidence on the platform, it becomes easy for the digital provider to offer other products and services.
Fast-moving competitors provoke a disaggregation of the more traditional industry silos and value chains, and also disintermediate the existing relationship between businesses and their customers. New disruptors can rapidly scale at a much lower cost than the incumbents, generating in the process a rapid growth in their financial returns through network effects. Amazon’s evolution from a bookseller to a $100 billion a year retail conglomerate shows how customer loyalty, combined with insights on preferences and solid execution can lead to selling across multiple industries. It also demonstrates the benefits of scale.
In almost all industries, digital technologies have created new, disruptive ways of combining products and services – and in the process, have dissolved the traditional boundaries between industries. In the automotive realm, a car is now a computer on wheels, with electronics representing roughly 40% of the cost of a car. The decision by Apple and Google to enter the automotive market shows that a tech company can now transform into a car company. In the future, as the value shifts towards the electronics, the technology and licensing software may prove more strategically beneficial than manufacturing the car per se.
The finance industry is going through a similar period of disruptive change. P2P (peer-to-peer) platforms are now dismantling barriers to entry and lowering costs. In the investment business, new “robo-advisory” algorithms and their corresponding apps provide advisory services and portfolio tools at a fraction of the old transaction cost – 0.5% instead of the traditional 2%, thereby threatening a whole segment of the current financial industry. The industry is also aware that blockchain will soon revolutionize the way it operates because its possible applications in finance have the opportunity to reduce settlement and transaction costs by up to $20 billion and transform the way the industry works. The shared database technology can streamline such varied activities as the storage of clients’ accounts, cross-border payments, and the clearing and settling of trades, as well as products and services that do not exist yet, such as smart futures contracts that self-execute without a trader (e.g. a credit derivative that pays out automatically when a country or company defaults).
The healthcare industry is also faced with the challenge of incorporating simultaneous advances in physical, biological and digital technologies, as the development of new diagnostic approaches and therapies coincide with a push to digitize patient records and capitalize on the wealth of information able to be gathered from wearable devices and implantable technologies.
Not all industries are at the same point of disruption, but all are being pushed up a curve of transformation by the forces driving the fourth industrial revolution. There are differences according to industry and demographic profile of the customer base. But in a world characterized by uncertainty, the ability to adapt is critical – if a company is unable to move up the curve, it may be pushed off it.
The companies that survive or thrive will need to maintain and continually sharpen their innovative edge. Businesses, industries and corporations will face continuous Darwinian pressures and as such, the philosophy of “always in beta” (always evolving) will become more prevalent. This suggests that the global number of entrepreneurs and intrapreneurs (enterprising company managers) will increase. Small and medium-sized enterprises will have the advantages of speed and the agility needed to deal with disruption and innovation.
Large organizations, by contrast, will survive by leveraging their scale advantages and investing in their ecosystem of start-ups and SMEs by acquiring and partnering with smaller and more innovative businesses. This will enable them to maintain autonomy in their respective businesses while also allowing for more efficient and agile operations. Google’s recent decision to reorganize into a holding company called Alphabet is a vivid example of this trend, driven by the need to sustain its innovative character and maintain its agility.
Finally, as the next sections detail, the regulatory and legislative landscapes will significantly shape how researchers, businesses and citizens develop, invest in and adopt both emerging technologies and the operating models that enable them to create value for users. While new technologies and innovative businesses offer new products and services that can improve the lives of many, those same technologies and the systems that support them could also create impacts we wish to avoid. These range from widespread unemployment and increased inequality, which was discussed previously, to the dangers of automated weapons systems and new cyber risks.
While perspectives on what constitutes the right mix of regulation may vary, my conversations with government, business and civil society leaders indicate that they share the same overarching goal: to create agile, responsible regulatory and legislative ecosystems that will allow innovation to thrive while minimizing its risks to ensure the stability and prosperity of society.
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Box B: Environmental Renewal and Preservation
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The convergence of the physical, digital and biological worlds that is at the heart of the fourth industrial revolution offers significant opportunities for the world to achieve huge gains in resource use and efficiency. As Project MainStream, the World Economic Forum’s initiative to accelerate the transition to the circular economy, has shown, the promise is
not just that individuals, organizations and governments can have less impact on the natural world but also that there is great potential to restore and regenerate our natural environment through the use of technologies and intelligent systems design.
At the heart of this promise is the opportunity to shift businesses and consumers away from the linear take-make-dispose model of resource use, which relies on large quantities of easily accessible resources, and towards a new industrial model where effective flows of materials, energy, labour and now information interact with each other and promote by design a restorative, regenerative and more productive economic system.
There are four pathways that help take us there. First, thanks to the internet of things (IoT) and intelligent assets, it is now possible to track materials and energy flows so as to achieve huge new efficiencies all the way along value chains. Of the $14.4 trillion in economic benefits that Cisco estimates will be realized from the IoT in the next decade, $2.7 trillion in value can be gained from elimination of waste and improved processes in supply chains and logistics. IoT-enabled solutions could reduce greenhouse gas emissions by 9.1 billion tonnes by 2020, representing 16.5% of the projected total in that year.40