In the previous article in this short series we noted that in a study by the Global Center for Digital Business Transformation (GCDBT – a Cisco-IMD Lausanne cooperation), respondents expected that on average 40% of today’s top 10 incumbents in any industry would be displaced within five years and the majority believed that the risk to be put out of business altogether had substantially increased. In spite of this 45% said digitization is not a board level concern and only 25% thought their organization was actively responding. A main reason is uncertainty about sustainability of the business model, how to respond and how to assess associated risks, costs and benefits. According to the results of the study:
This lack of attention in the executive ranks is matched by inadequate strategies for coping with digital disruption. Forty-three percent of companies either do not acknowledge the risk of digital disruption, or have not addressed it sufficiently. Nearly a third are taking a “wait and see” approach, in hopes of emulating successful competitors. The velocity and high stakes of digital disruption, however, may make it unlikely that even 32 percent of companies will succeed in taking a “fast follower” approach. Only 25 percent describe their approach to digital disruption as proactive—willing to disrupt themselves in order to compete.
Whether and under what circumstances it makes sense to disrupt one’s own business in order to keep digital disruptors at bay is something that we will examine in a later post. At this point we’ll try to examine how managers can recognize and assess the level of threat. This is crucially important because, due to its particular economics – network effects and “winner-takes-all” markets -, digital disruption happens extremely fast, often much faster than managers can react. Nevertheless there are two significant clues: investment growth rates in particular technologies and demand growth rates for products / services enabled by these technologies.
In the GCDBT survey, a ranking of industries on potential for disruption through digitization was developed, based mainly on executive responses with following result:
Ranking for industry disruption potential. Source GCDBT 2015
At first glance these rankings make some intuitive sense, as more information intensive industries (in a conventional sense) and, particularly, services are seen as more prone to disruption than other products or commodities. However, a closer look reveals that this is not the whole story.
Utilities, for example, are supposedly not easily prone to disruption. This may, for the moment, be correct if one refers purely to companies managing the transmission or distribution grids, which are natural monopolies. However consider the power generation industry (in a broad sense: producing and selling electricity commodity to customers and making mainstream power generation equipment), conventionally also not thought to be an immediate candidate for digital disruption. In this industry, the big players tend to be companies building or operating large power plants, but solar PV installations (measured in GW installed) have been showing phenomenal growth rates for a number of years (albeit from very low levels). They are now starting to attract the majority of global investment in power generation, mainly due to a dramatic decline in costs.
Cost-Experience curve for solar PV 1980-2014. Price is correlated with volumes produced. Source Fraunhofer ISE 2015
Global new investment (BUSD) in renewable energy sectors 2014 and growth on 2013. Source: Bloomberg New Energy Finance
Scenarios for demand development rates solar PV to 2050. Demand is cost driven. Source Fraunhofer ISE 2015
Innovations, volumes and reducing costs trends are reinforcing each other in solar PV. Once costs (of electricity produced) reach a certain level (competitive relative to alternative forms of power generation) demand becomes independent of subsidies and grows rapidly. This is already the case in countries with medium to high insolation and is expected in northern latitudes over the next few years. As costs decrease new applications and new ways to market are developed, essentially expanding the power generation market while displacing competing technologies (fossil, nuclear and other renewable fuels, e.g. biomass) and incumbent competitors. Many energy scenarios have underestimated solar PV demand / growth over the years, including those by the International Energy Agency, though this is being rectified. Cost declines in solar PV are due to a combination of technology innovations, enhanced automation reducing material waste, production steps and labor costs, and increasing availability of symbiotic technologies (battery storage, Internet of Things), which improve performance.
Digitization provides further impetus to demand by enabling new business models, optimizing customer journeys and making a commodity (electricity) interesting. For example, roof-top solar PV installations are increasingly provided “as a Service”. The business model now usually includes integration into virtual power plants enabled through local smart (digitized) grids, designed to minimize cost on the one hand, and to maximize (wholesale or subsidized) achievable prices from the utility or the market on the other. The owner of the roof and building pays only for the electricity he uses and the cost is significantly lower than the utility retail price or what is available on the local market. In this case the service provider effectively pools roofs to create a sizable virtual solar installation, enhance market power through network effects and reduce risk. Customers are further attracted through an optimized (digitized) customer journey.
This is how a couple of McKinsey consultants sing the praises of Sungevity, a solar PV company from Oakland, California, in the Harvard Busienss Review when discussing customer journeys (one of them is a Sungevity customer, a good reference by any means, who lietrally waxes lyrical):
“At first glance, Sungevity looks like a typical residential solar panel provider. But closer inspection reveals that the company’s business is to manage the end-to-end process of sales and custom installation, coordinating the work of an ecosystem of companies that supply, finance, install, and service the panels. Sungevity’s “product” is a seamless, personalized digital customer journey, based on innovative management of data about the solar potential of each home or business. Sungevity makes the journey so compelling that once customers encounter it, many never even consider competitors”.
And further:
“Starting with its initial outreach and continuing to the installation and ongoing management of the customer’s panels, Sungevity customized and automated each step of the journey, making it so simple—and so compelling—for the customer to move from one step to the next that he never actively considered alternative providers. In essence, the company reconfigured the classic model of the consumer decision journey, immediately paring the consideration set to one brand, streamlining the evaluation phase, and delivering the customer directly into a “loyalty loop,” where he remains in a monogamous and open-ended engagement with the firm.”
Sungevity’s journey strategy seems to be working. Sales have doubled in the past year to more than US $ 65 million, making Sungevity the fastest-growing player in the residential solar business. But while the Sungevity example shows how it is possible to gain competitive advantage and market share in a highly competitive market (solar PV panels) by improving the customer journey, the important thing here is to show that digitized disruption for power generators and utilities can come in unexpected ways: In this case through a combination of optimized customer journeys, exploding demand for solar power due to reducing costs and the superior economics of distributed virtual power plants, a highly digitized concept.
Full-blown digitization of sales processes and operations would not help power generation competitors peddling power from fossil power plants, as it would not help Hertz in its battle with ride-sharers. What incumbents need to do is explore how their business models can be enhanced or changed through digitization, so that they can compete more effectively. However this is not easy. Car sharing, for example, can be considered a digitized form of car rental, able perhaps to both expand the market and gain share and a disruptive threat to the traditional business. In 2013 Avis, the car rental company, acquired ZipCar, the largest car sharing provider in the US for US $ 500 million. Interestingly the rationale of the acquisition was based on cost savings and better utilization of vehicles. However, according to an interesting article in the Washington Post, this would make ZipCar like Avis, effectively destroying the business. But the model is powerful and new car sharing schemes, including by car manufacturers, are popping up all over. Life is not easy for incumbents whose business model has possibly outlived its usefulness, at least for a sufficiently large number of consumers.
Let’s consider also Consumer Packaged Goods (CPG) and Manufacturing (which rank at place 8 in the GCDBT study) and look at one specific potential disruption, namely 3D printing, which can be essentially considered a kind of ultimate digitization, because fundamental properties of a physical entity are digitized and reproduced. According to a table put together by Forbes based on a review of sales projections by research firms, the compound annual growth rates in 3D printer sales range from 20% to 106% to 2020 and is on an increasing trend. This should be combined with the fact that the price/performance ratio (features, capabilities, speed) is improving.
Source: Forbes
Based on these numbers the size of the industry in 2020 will be at least equivalent to the size of the robotics industry today, but will get there in a fraction of the time. According to a study by PwC, a consultancy, 67% of manufacturers are already using 3D printing. Of these, 24.6% are using 3D printing for prototyping and 28.9% are experimenting to determine how 3D printing can optimally be integrated into their production processes. For example GE announced that it would use 3D printing to produce 25,000 nozzles for its Leap jet engine which goes into production in 2016. According to MIT’s Technology Review:
“GE chose the additive process for manufacturing the nozzles because it uses less material than conventional techniques. That reduces GE’s production costs and, because it makes the parts lighter, yields significant fuel savings for airlines. Conventional techniques would require welding about 20 small pieces together, a labor-intensive process in which a high percentage of the material ends up being scrapped. Instead, the part will be built from a bed of cobalt-chromium powder. A computer-controlled laser shoots pinpoint beams onto the bed to melt the metal alloy in the desired areas, creating 20-micrometer-thick layers one by one. The process is a faster way to make complex shapes because the machines can run around the clock. And additive manufacturing in general conserves material because the printer can handle shapes that eliminate unnecessary bulk and create them without the typical waste”.
Sustained very high growth rates, essentially independent of business cycles, are indicative of major shifts. Broad application of 3D printing in manufacturing will induce rapid transformative effects, first on the physical products themselves and then on production cycles, quality systems and after sales services. Finally the supply and value chains will be upended with momentous repercussions. The impact increases if/when production is shifted from the factory to end users.
Source: Deloitte
The main reason that people do not (yet) rank the disruption potential in manufacturing as high is that they expect that broad penetration of 3D printing will happen only quite far into the future. But the network effects and minimal marginal costs of digitization mean that penetration speeds of digital products can be incredibly fast.
Meanwhile the Internet has given rise to industries and companies that generate billions of transactions per day and manage and analyze data on a massive scale. For example, Google handles over 3.5 billion searches per day and Twitter over 500 million tweets. Amazon’s own account transactions are approximately 30 million per day, while Salesforce.com supports almost 1.5 billion transactions per day. The capabilities to handle massive scale transaction processing and data analytics have been increasingly applied to many other sectors upended by digitization and as deployment of both the Internet of Things and the Industrial Internet of Things unfolds they will also be required in manufacturing and related sectors as data generated to monitor, control and optimize materials, devices, products, machinery and infrastructure assets increases by orders of magnitude and potentially surpasses everything else. Few, if any, manufacturers have these capabilities today and building them is not easy, not only because technological issues need to be overcome (which they do), but mainly because of digitization economics. Digitized businesses and ecosystems create powerful network effects (the value of the network increases with each additional connection/node, both for the new user and the already existing users, – the value of a phone increases the more people have a phone) and marginal costs shrink to zero for all practical purposes (the cost of adding another connection, customer or product). This fuels rapid growth and “winner takes all markets” (markets where the top players have supersized market shares and small differences in skills can mean large differences in returns. They exist because technology has increased the size of the market that can be served by a single person or company). This implies that there will be few winners, therefore investment risk for industry incumbents in digital tranformation increases: The result is, well, digital (pun intended). You either win or you lose and there is nothing much in the middle.
For example Google’s search engine has over 66% market share, the rest is divided between 7 major players and many smaller ones. Among social media sites, Facebook has 46% market share and, excluding Youtube, all the rest have below 5%. And in on-line retailing Amazon’s market share is 60%, the next, Walmart, is barely at 10%. While the first two markets are “digital natives”, retailing is not. And according to a study by the Cetntre for Retail Research, on-line growth rates in US and Europe are 15% and 18% p.a. respectively, far higher than overall retail growth rates. As retail is rapidly digitized, incumbents find it difficult to respond, as their core competencies and earlier competitive advantages become irrelevant.The recent decision by Walmart to close down 269 stores around the world was an acknowledgement of the pressure exercised by online retailers. Whether Walmart and many others can build up digital revenues and profits as fast as they lose physical ones is unknown at this point, but it will not be easy.
In an insightful article in HBR in 2003, Nicholas Carr, the magazine’s then editor, argued that to be sustainable, competitive advantage must be proprietary, that is it must be internalized by the company and not be available to competitors. This was the time when companies were seeking competitive advantage through applications of Information Technology -a predecessor situation to the digitization Drang of today. As Carr explained, over the previous 20 years there had been a shift in senior executives’ attitudes towards information technology. While in 1983 it was considered a technical issue best left to secretaries, technicians or specialists, by 2003 it had morphed into a strategic issue, to be used for competitive advantage. But, as he noted:
“Behind the change in thinking lies a simple assumption: that as IT’s potency and ubiquity have increased, so too has its strategic value. It’s a reasonable assumption, even an intuitive one. But it’s mistaken. What makes a resource truly strategic—what gives it the capacity to be the basis for a sustained competitive advantage—is not ubiquity but scarcity. You only gain an edge over rivals by having or doing something that they can’t have or do. By now, the core functions of IT—data storage, data processing, and data transport—have become available and affordable to all. Their very power and presence have begun to transform them from potentially strategic resources into commodity factors of production. They are becoming costs of doing business that must be paid by all but provide distinction to none”.
As far as technology goes, 13 years later this is still valid. The key elements of digitization (connectivity, sensing, algorithms, analytics, cloud, even processes) are non-proprietary “infrastructural” technologies and cannot provide advantage per se, other than temporary advantage during a change phase. As Carr continues:
“Proprietary technologies can be owned, actually or effectively, by a single company. A pharmaceutical firm, for example, may hold a patent on a particular compound that serves as the basis for a family of drugs. An industrial manufacturer may discover an innovative way to employ a process technology that competitors find hard to replicate. A company that produces consumer goods may acquire exclusive rights to a new packaging material that gives its product a longer shelf life than competing brands. As long as they remain protected, proprietary technologies can be the foundations for long-term strategic advantages, enabling companies to reap higher profits than their rivals.
Infrastructural technologies, in contrast, offer far more value when shared than when used in isolation. Imagine yourself in the early nineteenth century, and suppose that one manufacturing company held the rights to all the technology required to create a railroad. If it wanted to, that company could just build proprietary lines between its suppliers, its factories, and its distributors and run its own locomotives and railcars on the tracks. And it might well operate more efficiently as a result. But, for the broader economy, the value produced by such an arrangement would be trivial compared with the value that would be produced by building an open rail network connecting many companies and many buyers. The characteristics and economics of infrastructural technologies, whether railroads or telegraph lines or power generators, make it inevitable that they will be broadly shared—that they will become part of the general business infrastructure”.
Companies however inevitably fall into technology traps where they mistake infrastructural technologies as having proprietary character and that competitive advantage through them will be available indefinitely. In fact what happens is that once the technology’s potential is widely understood and recognized it attracts huge amounts of investment rapidly, costs decline and its buildup proceeds very fast. Affordablity increases leading to further increases in demand. Usage is standardized, best practice is widely emulated and quickly built into the technology infrastructure itself, which in turn becomes available “off-the-shelf” and even assumes commodity characteristics.
The flip-side of this of course is the fact that infrastructural technologies become indispensable, without them the game cannot be played at all. And in the process of acquiring them many things change and inevitably many fall by the wayside, in particular those whose product, service, business or operating model are not sufficiently compatible or cannot sufficiently profit from the new technologies relative to competitors and alternatives.
There is a difference however now to 2003:
i) the technological ability, driven by ubiquitous digitization, to create many “markets” with network effects and winner take all economics, which in the past had been confined largely to “natural monopolies”, such as the railroads or the telecommunications network (social networks emerged mainly after 2003. Nevertheless network effects could already be detected in some markets, where the biggest players became de facto standards). This is compounded by the fact that digitization enables the emergence of platforms and ecosystems with thousands of players around giant vendors operating as central hubs. The hub provides the infrastructure through which business is conducted, goods and services exchanged. Therefore while the infrastructure in itself may be largely off-the shelf, competitive advantage is conferred to fast movers through location, much in the same way that location confers an advantage in physical retail. In this case however it is much more powerful.
ii) the emergence of data as a major asset class. Today online companies of different types with large numbers of users utilize data to both adjust and market offerings more effectively (location, time, features –even in real time), optimize supply chains and, significantly, generate revenues from third parties who want access to that data to develop insights, create and tailor offerings.
Consequently demand for data access (in different forms) increases strongly. While it is very difficult to find reliable estimates for this type of demand, data traffic may serve as a proxy. In the below example of cellular machine-2-machine traffic (associated with the IoT), the CAGR is expected to be 32% over the period and is driven by overall number of connections and intensity of use. This type of data traffic currently accounts for approximately 2% of total, where CAGR is projected to be 23%. Data traffic is however limited by network carrying capacity which generally lags behind demand. Data generation growth rates are significantly higher -for example it is estimated that over 90% of extant data was generated in the past 2 years or less.
Global cellular M2M data traffic 2014-2024. Source: Machina Research 2015
Currently over 90% of data (on average) generated in companies is not utilized to produce insights, knowledge or action. This has been mainly due to technology limitations, suppressing the value of data. As these limitations are overcome and utilization increases, the value of data will increase, while the marginal cost of preparation, replication and distribution remains close to zero. This will have significant implications for the structure of markets and industries.
Digital disruption is underway when sustained very high growth rates in investment in particular technologies are observed coupled with explosions in demand for resulting products and services. The growth rates are driven by network effects and winner-take-all markets causing disruptions and transformations to happen very rapidly, frequently before incumbents have time to react.
In the next posts we will deal response strategies by incumbents and the special case of manufacturers and to what extent servitization can be a winning strategy for a digital world.
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A great article, which provides some good insights by quoting actual industry related initiatives rather than simply throwing some glossy hollow jargon.