The insight that digitalization has the power to disrupt conventional business models is old news to us all by now. Media close-ups are full of stories about companies across sectors that are in the throes of painful metamorphosis like the tragic protagonists in a nostalgic werewolf flick of the olden days. With the continuous emergence of ever more potent technologies – such as AI, blockchains, and quantum computing – businesses will still be trying to make sense of digitalization and what it means to them for a long time to come.
The burning question on every consultant’s and analyst’s mind is which of them will grow the sharpest fangs and the fiercest growl; will it be the resourceful heavy-hitters of the industry or the nimble and fearless growth companies, commandeered by a generation of digital natives who couldn’t care less about existing lines of power? If CB Insights’ very enlightening “Disrupting” -series of analyses is to be believed, I would put my money on the latter, a hungry pack of piranhas tearing apart the raison d’être of incumbents one line of business at a time (www.cbinsights.com/blog/category/disrupting-unbundling/). In the end, it is exactly what the grand old man of innovation, Joseph A. Schumpeter, has already been proclaiming for the last 90 years, or so; there is no sheltering from the gale of creative destruction.
When asked about the topic, many still struggle to put their finger on what digital disruption really means for business and the economy. In this post, I will elaborate on a systemic approach to making sense of emerging, digital ecosystems and what they imply for both incumbent industries and the unicorns of tomorrow. It will be lengthy – apologies in advance – but I promise to provide some tangible examples to make the story worthwhile to read. For the economic developer, I promise to throw in a few actionable insights, too.
In the current discourse on the digital revolution, we have put single companies in the center of epic story-telling. The likes of Über, Airbnb, and Apple have become the Beowulfs, Lancelots, and Ramas of legends written in code. The endangered competition and the inspired entrepreneur of tomorrow look up to these superheroes, trying their best to adopt the recipes of success in their respective business contexts. And they cannot be faulted for doing so; superheroes are innately fascinating, let’s admit it. The classic epic has withstood the passage of time for a good reason. Without derailing deeper into the anatomy and allure of epics, today’s digital success stories provide for excellent learning points on how extremely fuzzy opportunities can be exploited for very tangible new business development. They give us something concrete to hold on to in a time of ubiquitous, radical transformation and very few obvious handholds to cling to.
That being said, there are serious downsides to marveling at the heroic antics of single companies too exclusively. For one, there is always the danger of not paying attention to the myriad of alternative strategies your company could catch the wave of digital transformation with. Iconic role models can stifle our own creativity by blinding us to opportunities that lie off the beaten path. The much bigger threat, however, is in failing to understand the big picture. The big picture is not about how the on-going changes are going to impact your company. It is about the impacts they have on your sector, industry and, thereby, the economy as a whole. It is indeed entire industries that are currently being pushed to the economic periphery of emerging, digitally driven ecosystems. Unless you radically pivot, your company runs danger of being flushed down the pipes with them.
What, then, do these ecosystems look like and what role do conventional industries play in them? To get something actionable out of it, let’s have a look at a tangible example: Smart grids.
As a concept, smart grid is not a recent one, by any means. Demand-side management of electricity was among the earliest applications of a limited ‘smart grid’. Since then the grid has gradually become smarter and smarter as IT-enabled technology has been integrated into the legacy infrastructure of energy production, transmission, distribution and consumption. The proliferation of new grid functionalities across time is reflected in many of the complementary definitions put forth by the various actors in the smart grid ecosystem:
According to the International Electrotechnical Commission, for instance, a smart grid “is an electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers and those that do both – to efficiently deliver sustainable, economic and secure electricity supplies. A Smart Grid employs innovative products and services together with intelligent monitoring, control, communication, and self-healing technologies to: (i) facilitate the connection and operation of generators of all sizes and technologies; (ii) allow consumers to play a part in optimizing the operation of the system; (iii) provide consumers with greater information and choice of supply; (iv) significantly reduce the environmental impact of the whole electricity supply system; and (v) deliver enhanced levels of reliability and security of supply.” The European Commission adds that: “smart grids are energy networks that can automatically monitor energy flows and adjust to changes in energy supply and demand accordingly. When coupled with smart metering systems, smart grids reach consumers and suppliers by providing information on real-time consumption. With smart meters, consumers can adapt – in time and volume – their energy usage to different energy prices throughout the day, saving money on their energy bills by consuming more energy in lower price periods. Smart grids can also help to better integrate renewable energy […].”
Compared to the legacy paradigm, smart grids offer multiple benefits to their various constituents, some of which are listed by the US Department of Energy. These include “more efficient transmission of electricity; quicker restoration of electricity after power disturbances; reduced operations and management costs for utilities, and ultimately lower power costs for consumers; reduced peak demand, which will also help lower electricity rates; increased integration of large-scale renewable energy systems; better integration of customer-owner power generation systems, including renewable energy systems; [and] improved security.”
To summarize, smart grids create added value in the form of enhanced cost efficiency, greatly improved reliability and unprecedented production flexibility. Because the related benefits are appropriated by both producers and consumers, the emergence of smart grids is driven by forces of both demand pull and supply push alike.
Now back to the question how emerging, digital ecosystems really look like. The definitions already imply that smart grids transcend the traditional boundaries of the energy production and transmission sectors. Monitoring, bi-directional data flows, machine-to-machine communication and electronics that enable automated optimization on the system level are not in the capability domain of traditional utilities and transmission grid operators.
A few years ago, Greentech Media Research (GTM Research) developed a plot of smart infrastructure layers on top of the traditional infrastructure value chain:
While some companies presented in the figure have been acquired, or gone out of business, the structure reveals important features of the industry ecosystem. While the incumbent energy value chain known to us all is represented in the familiar power infrastructure layer (bottom), smart grids necessitate the integration of a large number of other functional layers that build on top of the incumbent infrastructure. These include the communication infrastructure across which data is transmitted between the different stakeholders; the meter data management layer; the demand response layer which exploits multi-source data to provide services for the optimized co-ordination of energy production and demand; the grid optimization layer which translates the data-based demand-response predictions into physical control of the system infrastructure; and the storage layer, which acts as a necessary buffer between peaks and troughs introduced by both volatile demand and renewable-based production of energy.
A closer look at the respective companies in the various layers demonstrates that the structure of the system is highly cross-industrial. Indeed, it involves industry sectors and segments ranging from energy to telecommunications and software development; from machinery to industrial electronics and data analytics; and from computer hardware to home electronics and infrastructure construction. What GTM Research’s map does not reveal, however, is how these companies interact to form a new ecosystem. What does the industrial skeleton – the network of value chains – of the ecosystem look like? The direct answer is, well, like a ball of yarn. Let me explain and already apologize for the unavoidable technicalities involved.
On the quest to understand how digital ecosystems change existing business value chains, we subjected the smart grid ecosystem to a company-level financial network mapping analysis. It revealed the monetary flows between the involved industries and subindustries, and showed the intricate industrial structure of the entire system as shown in the picture below.
Source: Adriaens P. & Tahvanainen, A.-J. (2016): Financial Technology for Industrial Renewal. Taloustieto Ltd., Helsinki. Top panel by Dimitris Assanis.
Starting with the top most panel of the figure, the thickness of the lines – also called edges – between individual industry sectors symbolizes the relative financial exposure – i.e. the relative flows of money – between them. The thicker the edge, the more significant is the financial exposure – or trade relationship – between the respective industries. Another key dimension in the map is the positioning of the industries relative to each other. Those positioned closer to the core of the map display a higher connectivity – or network centrality – to all other industries than those located in the periphery of the map. The higher the centrality, the more “important” the respective industry is to the mutual connectivity of the entire ecosystem. Industries of high centrality bridge the chasms between sectors that otherwise would have very low connectivity in the smart grid ecosystem.
As displayed in the lower two panels – both more clearly presented abstractions of the original map – the centrality of nodes is used to distinguish between the roles single industries have in the financial network structure of the smart grid ecosystem. Industries of high centrality – in blue – are designated catalysts. They are built on the infrastructure of anchor industries – in red – that stake the perimeter of the ecosystem.
Anchors are less well connected to the emerging ecosystem as they are still relatively contained in their incumbent industrial value chains. However, they serve an extremely important role as the providers of capital-intensive infrastructure and vital technological components. Good examples of essential smart grid infrastructure are energy production facilities and transmission grids maintained by utilities and grid companies as well as the telecommunication networks maintained by both integrated and wireless telecommunication operators. Technological components, in turn, are provided by electrical component and equipment manufacturers, industrial conglomerates, such as Siemens, Bosch and others, and communications equipment producers.
The role of catalyst industries, in turn, is the integration of the aforementioned industries to harness them for creating entirely new type of value that will be offered to users in the form of novel products and services. In the case of smart grid, this means increased efficiency, reliability and security through real-time, data-driven optimization technologies and services (smart homes, consumption timing and optimization, etc.). One could argue that, in the case of smart grids, it is the catalyst industries that make the system intelligent – an internet of things (IoT). Catalyst industries include many software-based sectors such as systems software, application software and data processing. Semiconductors as well as technology hardware and storage further corroborate the centrality of IT-related solutions in tying together the intricate web of industrial activity in the smart grid ecosystem.
Being the very nexuses of new value chain structures, it is these catalyst industries that will show fastest growth, provide for new jobs, and capture most of the new value if they play their cards right. As long as they rely on their incumbent business models, anchor industries on the other hand will be stranded in the periphery and have to content themselves with low-margined commodity businesses. This is a blunt generalization, of course. In reality the dynamics behind the division of power are a little more complex than that. Let’s have a look.
Understanding the new structures of emerging ecosystems is a necessary first step in demystifying how they impact existing industries. It does not provide the full answer quite yet, however. To go all the way, one needs to shed light on where in these structures lie the comparative strengths of the country, region, industry or company that you are interested in. Everybody wants a piece of the pie but all of them come equipped with very different tools to claim it. In our case, we looked at smart grid companies in Finland and asked how they fare on this stage.
In the infrastructure layer, Finland has a long-standing legacy in power electronics and mechanical engineering with a particularly lively, international cluster centered around the Westerly located city of Vaasa. Furthermore, Finnish power utilities had to face the open and competitive electricity market amongst the first in the world as the electricity markets were liberalized in Scandinavia as early as in the mid-1990s. In a sense, they have had a head start in designing competitive strategies and adopting smart solutions to stay at the edge in the highly commoditized market space.
Many of the same arguments apply to the Finnish telecommunications sector. With the rise of Nokia driving an explosive national and global adoption rate in mobile telephony in the same time period, the Finnish telecommunications operators faced a fast growing market place that was gagging for ever larger bandwidths and smarter services such as journey planners, digital tickets for public transportation and other flexible on-the-go solutions that helped make everyday life more efficient, less stressful and spontaneous. They, too, have had time and incentives to respond to a very demanding clientele that expected smart solutions from the start.
Our inquiries, however, show that the incumbent players in the infrastructure layer, despite their robust position to capture value from the smart grid ecosystem, have adopted a non-aggressive entry strategy. Their strong value capture position is encumbered by capital intensive, manufacturing-driven business models that are difficult to scale rapidly. Instead of strategically positioning them into the high-growth sectors of the smart grid ecosystem, Finnish enterprises have continued to provide their incumbent and highly commoditized products and services – such as electricity by the kilowatt-hour and data transfer by the megabyte – to the ecosystem. These commodities are important, no question, but the attractive margins and growth in value is in the scalable services and related products that help customers save costs through digital optimization and predictive maintenance, improve the comfort of living through home automation and user interaction, as well as improved risk management through self-healing grid technologies and intelligent security solutions. Continuing to rely on commoditized and generic product and market strategies puts enterprises in danger of becoming marginalized and being pushed to the periphery of the ecosystem. They will still remain vital as the producers of the necessary core commodities, but the value will be captured by companies in the growth sectors of the system.
What can power utilities, component manufacturers and telcos then do to reposition them for improved value capture and growth? In the US, some telcos have been particularly aggressive. Verizon, for instance, has invested into its own energy production capacity, and now powers its own facilities. Verizon hardly intends to go head-to-head with energy utilities for a share in a low-margin, regulated commodity business, but uses these investments to learn about the dynamics and technologies of renewable energy generation, grid integration, micro- and off-grid technology, power distribution, demand response optimization and consumption prediction. It is a test laboratory in Verizon’s own backyard that enables the company to develop and adopt an entirely new skillset for providing cutting-edge telecommunications-related solutions without the historical baggage of legacy companies that are too slow to capture value in the smart grid ecosystem. At the same time, the company benefits from the goodwill their sustainable and independent energy setup imparts on the Verizon brand.
Less aggressive strategies build on acquisitions. Again, US contenders are more courageous in the adoption of this strategy than their European peers. There is an acquisition frenzy sweeping across the smart grid landscape as companies across industry boundaries compete for the largest share of the still growing smart grid market.
But why would companies make such risky commitments in face of the still somewhat vague economic promises made by smart grids? Isn’t partnering, for instance, a more flexible and less risky option to probe the emerging space? An acquisition strategy has one major advantage over pure partnering strategies, the least aggressive of options: the buyer internalizes the value the acquiree would otherwise capture from the growing ecosystem. In our company analyses we often encountered enterprises that claimed to have committed to becoming a key provider of smart grid solutions. On a closer inspection of their respective business models, however, it turned out that the enterprises’ role in these solutions remained that of the conventional commodity provider. At the same time, a number of their partners – sometimes tens of them – contributed all the smart elements and captured the respective value.
Sure, large incumbent enterprises can charge a certain margin for their role as an integrator of these elements and for providing a market channel to the often much smaller partners but the dependency on a partner’s specialized capabilities in the emerging smart grid space compromises this advantage. A lot of potential synergies are left on the table. Furthermore, the appropriation of relevant capabilities, a prerequisite to long-term success in any environment new to a company, is difficult in an arms-length, contractual relationship, in which partners are understandably reluctant to disclose their core capabilities.
That being said, partnering is a justified first step in entering into the smart grid ecosystem. It provides consortia of companies with the possibility to capture an increasing share of a fast growing market space. Sometimes speed is crucial to the establishment of a competitive position. The objective for corporate consortium partners, then, is to exploit the partnerships to validate potential market opportunities, acquire the required core capabilities for long-term success and aggressively leverage their superior resources to establish their presence in the new market.
According to our results, start-ups and SMEs are quicker to tap into the smart grid market potential than their large corporate counterparts. Their business models are more scalable and, most decisively, exhibit a much higher capital efficiency. This gives them the capability to capture opportunities faster. This is a strength worth preserving. The make-and-sell business model, the stalwart of the traditional CleanTech economy, is being eroded by service models with recurring revenue streams and low capital intensity. CleanTech 3.0 has been defined by business models that have been built on top of legacy infrastructure, and has given rise to the cleanweb. ICT and network-based technologies are at the core of the transition from cleantech to cleanweb. A decade after cleantech was defined as an innovation space, the convergence between ICT and cleantech holds the key to scale and profitability. Our current results imply that SMEs in the smart grid space are well positioned to do just that, given their fairly scalable business models and excellent capital efficiency.
However, both start-ups and SMEs suffer from the same weakness that seems to be characteristic of the entire ecosystem: poor leverageability of industry capabilities needed to gain access to markets. There is a need for building out a growing smart grid industry cluster and market. As a first step, start-ups and SMEs could work with large enterprises to address their energy needs. Small firms can leverage the market infrastructure of large enterprises to gain access to the global market place. Therefore, in the short term, a partnering strategy offers a synergetic opportunity that both small and large firms could benefit from. Indeed corporate strategic investors have increasingly turned to the development of corporate incubators with small companies. The objective is to align innovative product offerings with corporate lines of business. In the long term, however, once the necessary capabilities have been acquired, large enterprises have the incentive to use their asymmetric market power to capture most of the value generated in consortia.
Small and medium –sized companies, therefore, are advised to develop parallel value chain strategies independent of large industry connections. Progress in generic, digital market platforms is a promising venue that helps small companies scale their offering onto global markets without having to lock into market channels controlled by dominant enterprises or having to invest heavily into building costly proprietary market infrastructure.
Our findings give rise to a number of policy recommendations. First, the smart grid ecosystem seems to have gathered industrial momentum to grow in a sustainable manner. However, a closer look has revealed a weak connectivity of the companies to appropriate market channels that would allow them to exploit the momentum.
To accelerate the formation of partnerships, economic developers are advised to favor development vehicles that promote collaboration between enterprises and growth companies. Innovative pioneers in this area already exist. The Nordic Innovation Accelerator (NIA), for instance, runs a technology and business brokerage program that “invites corporations to bring their innovation needs to be served by a number of startup solutions.” For startups, in turn, NIA’s program provides “validation for their ideas and products and provides opportunities for funding and acquiring ready clientele.” NIA has already successfully brokered partnerships between a number of Finnish start-ups and global enterprises such as Fortum and Veolia. A similar concept is applied by Vertical Accelerator , a broker of partnerships for growing healthtech companies and large, multinational enterprises such as Samsung, Sonera and Ingram.
Another useful vehicle for the promotion of cross-industrial partnerships is the support of world-class industrial and economic pilots that demonstrate the viability of emerging ecosystems on a believable scale. A great example of an ecosystem-wide demonstration is the Smart Energy Platform as currently launched in Åland. As the consortium behind the pilot states, “the target [of the pilot] is to create the world’s most advanced flexible energy system of the future as a cleantech showcase in Åland, where a fossil free energy system and the whole value chain enabling different flexibilities simultaneously can be demonstrated.” The power of ecosystem-wide pilots is in that they already assemble viable consortia – representative of the underlying industrial value chain – that can carry the momentum forward after the completion of the pilot.
Finally, we argued that the fastest growing businesses in smart grid revolve around IT- and data-enabled service models (XaaS) that, given the progress in digitalization and machine-to-machine communication, are now available even to more conventional, engineering-driven component and systems manufacturers. The biggest drag on the proliferation of the XaaS model is the lack of a universal governance model for the ubiquitous network of the vast array of diverse and inherently incompatible IT-systems that digitally-enabled services run on. Most of the systems have been developed for a specific, stand-alone purpose and service. Interconnectivity between the systems has not been an integral nor desired feature at the time of their inception. In XaaS models, integration of IT-systems across entire value chains becomes key, as data needs to flow along the chain of suppliers, clients and partners. Lacking a universal governance model, integration between systems today is a tedious undertaking, as connectivity needs to be established in a customized, non-scalable, case-by-case fashion.
Scaling of digitally-enabled businesses would see unprecedented rates if a unified governance standard for a network of systems could be established. History has shown that it is possible to introduce standards in a de facto, industry-induced fashion. It is a long, evolutionary road that is usually dominated by the large and often entails unproductive battles over who will set the standard that is adopted widely. On the other hand, history has also shown examples of active, centrally-lead standardization projects. These are a lot faster to set in place and, when designed properly, will not introduce market distortions that favor single stakeholders. Policymakers and economic developers could take decisive action in promoting digital governance standards to pave the way for the quick emergence of cross-industrial service models.
Based on Adriaens P. & Tahvanainen, A.-J. (2016): Financial Technology for Industrial Renewal. Taloustieto Ltd., Helsinki.
Dr.Sc. (Ind. eng. & mgmt.), M.Sc. (econ. & bus. adm.) Antti-Jussi Tahvanainen is Chief Research Scientist at The Research Insitute of Finnish Economy Etla.