disruption is the new normal
The Digital Economy is creating tremendous opportunities across every industry while simultaneously shifting value away from many traditional players. The speed and size of this shift is phenomenal, fueled by new industry Giants with large accumulations of stock and cash, young Unicorns with billion-dollar valuations shaping entirely new markets, and a glut of private capital lubricating the engine. More often than not, the risk for Incumbents is to be left on the sidelines using old models to understand a new world. As the headlines suggest, we are entering an age where fast-moving disruption is the new normal and the price-tag for capturing that disruption is reaching historic heights. And yet, a Giant like Facebook can now commit $21B to acquisitions in a single quarter without any immediate impact to its stock price.
Unicorns are now a class of market actors to be reckoned with...
In such a fast-paced environment, the way we used to define these things no longer keeps up with the real world - especially when so-called startups are disrupting and reconfiguring entire industries. Is a company with a $2 billion market valuation truly a “startup”? How do we fit them in the same continuum as seed-stage startups and waning Blue Chips? What does it mean when, for many companies, acquisitions are the main path to innovation?
Welcome to the world of Unicorns, where disruptors operate at scale, they spend more time in pre-exit growth stages, and their growth rates are driving multi-billion valuations for investors prescient enough to get in on the ground floor. Once thought to be rare and mysterious, billion-dollar tech Unicorns are increasingly common.
This report looks at a hand-picked basket of 60 Unicorns born in the past decade, exceeding (as of April, 2014) $375B in value. We try to understand these sky-high valuations while adding context to their impact. Combining interviews with investors and analysts, a growing ecosystem of quantitative tools to measure capital flows, and the experience and insight of our research team, we explore the dynamic world of value creation in the Digitalized Economy.
Unicorns are now a class of market actors to be reckoned with, distinct from the established Incumbents and the post-bubble web Giants from the first decade of the 21st century. Indeed, they represent new engines of innovation and the feedstock for the next generation of disruptors, posing major questions for Incumbents, Giants, and investors. How do Incumbents survive when macro changes drive them into adjacencies and entirely new markets? How do Giants strategically benefit from Unicorn disruptors? And what does it mean for founders when they must give up more control to larger amounts of private funding in order to become Unicorns? Are we seeing the emergence of what could be called the Private Economy?
Unicorns seem to be here to stay and they’re currently disrupting the very fabric of society, from hotels and taxis to employment and commerce. The technologies they play move much more quickly than the regulatory frameworks trying to keep them in check. New strategies for innovation, sustainable growth, and co-existence are clearly needed as the collateral economic value destruction by Unicorns goes along with the creation of new operating systems for the economy, which is itself able to generate new efficiencies and new wealth. Undesired and sterile friction is gradually eliminated and space opens for new competencies and new types of economic transactions.
It is likely that Unicorns are accelerating the changes that web titans have already imposed on the economy, while higher speed mobile and fixed networks are enabling even more people in the world to participate online.
With this report we explore strategies to help innovators and leaders to better prepare and respond to disruption, to anticipate new and adjacent market opportunities, and to reconfigure their businesses to learn and adapt to a fast-paced world.
CEO, Orange Silicon Valley San Francisco, CA
This document has been produced for public use and discussion by Orange Silicon Valley and may be reproduced in part or its entirety with proper attribution to Orange Silicon Valley. If you are interested in a briefing or discussion about this work please get in touch with me, Georges Nahon, at: firstname.lastname@example.org
Startups, Unicorns & Giants
In February of 2014, Facebook announced it would purchase WhatsApp for $19 billion in cash and stock. Once a heralded Unicorn itself, the mighty hunter took another as its prize. Sequoia Capital, the primary investor, declared that WhatsApp co-founders Jan Koum and Brian Acton have created the “communications backbone” of the Internet. Sequoia will likely earn a cool $3.5 billion from the exit. With less than $60 million in private funding, the 4-year old instant messaging company made its 50 employees rich, and newly-augmented with the massive resources of Facebook. Universal social messaging is now their game to lose.
How did a small mobile startup suddenly become the communications backbone of the Internet? Is there a method to the madness of these Unicorn valuations or are they just the fevered dreams of CEO’s and investors? And how can older incumbents adapt to a landscape of young giants swinging their weight around?
We live in a time of fast-moving, exponential change driven by the unprecedented ability to connect and reconfigure almost anything into novel combinatorial solutions. The result is a landscape of young, nimble Unicorns playing in disruptions and forging new markets while larger tech sector Giants work to shape the outcomes of the ecosystem - leaving Incumbents to bear the burdens of their own past while the future races ahead of them. Increasingly, new giants like Google and Facebook allow start-ups to assume the risk of innovation, using them to test new markets before buying them up just as they’re proving successful. The connected home Unicorn, Nest, illustrates this relationship. They took a tired and inefficient device – the thermostat – and rebuilt it with sophisticated new sensors, wired it into networks, and gave it cloud and mobile intelligence. The result is a combinatorial creature, a chimera of adjacencies, and a tremendously valuable source of data for their new owners at Google.
For innovators, the opportunities are tremendous. Research analytics firm, CB Insights, reports that the number of tech startups reaching a valuation of $1B or more increased 67% in 2013 versus 2012. Wild-eyed founders unencumbered by the past are emulsifying entire industries on their way to Unicorn status. For investors, ever on the hunt for the next mythical beast, their portfolios are straining at the chance to add such a wonder. CEOs and CFOs pace their towers hoping to divine the next big disruptor and draw it into their fold. Ever-growing valuations are becoming the norm. What are the patterns at play in the intersection between market sectors and deep currents? What is the science of this Unicorn alchemy? How can incumbents effectively compete in a landscape of adjacencies and emerging markets?
Ultimately, big success in the modern tech world comes from the alignment of multiple factors. The composition of the founding team, the ability to attract high-caliber investors who have the reach and influence to drive success, and a record of growth that spans many years - these are all signals that an innovation has real value and that the team has the ingredients necessary to scale. Perhaps most importantly, the product has to be a meaningful response to market opportunities and macro trends, tapping into the deep currents of our times to anticipate the greatest value before it’s obvious to everyone else. Unicorns, by their very nature, are disruptive but they also motivate the large, mature tech sector leaders to move into adjacent opportunities and recompile their organizations for greater fitness in the changing landscape.
how is valuation determined?
“…I believe there will be more unicorns per year because the markets for technology are larger today than 10 years ago. It’s not just a geographic widening, either. It’s the number of people who use technology today.”
Aileen Lee, VC at Kleiner Perkins Caufield & Byers, founder of Cowboy Ventures
We’ve examined a dataset of Unicorns scattered across multiple technology sectors to understand their core value, their impact on the marketplace, and how they play with the giants shaping the technology landscape. The main markets that these beasts play in are big data, cloud, enterprise, e-commerce, mobile, media, and social networking. It’s the blurry nature of our times that often makes it difficult to categorize businesses and technology solutions, so we’ve taken some editorial license to determine, for example, that a Unicorn corporate exit, Airwatch, is classified in the Mobile sector, even though it could also live in Cloud, or that its primary customer base is within Enterprise. As we consider how these sectors will play out over the next 5 years, keep in mind that these seven sectors have all seen significant disruption already, and that our focus here is on the next set of disruptors.
Big Data is certainly larger than the buzzword but much of the heavy-lifting has already been accomplished. Companies like MongoDB, Nutanix, Nimble, and Splunk are laying the foundation in terms of data management and storage. With more and more money pouring in, data tools like Cloudera and HortonWorks are starting to look a bit more like Giants than Unicorns. The burden now shifts towards tools likes Tableau that extract valuable insights from the mounting tsunami of information. Solutions that structure, normalize, and consolidate diverse sets of data, such as Palantir, will become more important, likely shifting from bespoke solutions towards integrated business intelligence platforms. Unicorns like Climate Corp., Marketo, RocketFuel, and Veeva Systems show that the opportunities are in the algorithms themselves, many of which are context-agnostic but will increasingly be customized, perhaps yielding a formal marketplace for machine intelligence. The upshot will be results that are much more relevant to a user’s query and soon delivered through predictive analysis based on historic data and the context of the research. For individuals and our growing set of devices and sensors, our own data shadows will grow larger and more discrete, binding individuals, data, and services into the real world, as demonstrated by Nest and Waze and the emerging Internet of Things. Innovators that can unlock data to deliver context-aware and predictive services will be well-positioned to achieve Unicorn status. In other words, the next Unicorns may come from the worlds of AI and deep learning.
Cloud infrastructure is seeking greater optimization and a lower cost profile while continuing to capture legacy toolsets. This trend has birthed numerous cloud services, like Box, Dropbox, and Evernote that are emerging as the new standard for distributed business operations. Giants like Amazon AWS and Rackspace will likely maintain their hosting dominance while extending more services across their surface. Load balancing, energy management, heat dissipation, and site location of data centers will drive bottom-line efficiency. Virtualization and dynamic network management will continue to de-couple services from infrastructure, driven by leaders like VMware, Citrix, and Palo Alto Networks. Yet, a big challenge/opportunity already underway is the management of an exponential number of requests, devices, and identities moving on and off networks, and the ever-growing surface area of vulnerability exerting evolutionary pressures on storage, security, and intrusion forensics. More security solutions are claiming Unicorn valuations, like FireEye’s purchase of Mandiant for $1.1 billion. In this context, there is huge opportunity in solving the curse of federation, identity and secure provisioning across diverse, flexible, global networks. Giants like EMC are working on this. The inexorable current, however, is flowing towards near-infinite, leasable computation serving a landscape of clients, embedded systems, and dynamic networks. This current is fundamentally re-shaping the world, displacing rigid hardware with more-nimble and adaptive soft systems while enabling fully-digital simulation of complex phenomena.
e-Commerce is now more than ever about data. Rigorous analysis of sourcing and logistics, algorithmic tinkering with dynamic pricing, niche consumer channels like Etsy and Quirky, and hyper-personalized advertising and locational tools like iBeacons are advancing refinements in stoking and meeting demand at just the right time. This on-demand, mobile-first disruption is grabbing headlines with the trials – figuratively and literally – of Uber and Lyft. These Unicorns are disrupting transportation and car ownership while offering new employment opportunities to car owners. Many of these best-practices were forged by Amazon and the first wave of global e-commerce services that leveraged the web to bring the crowd together. Now, shoppers with smartphones occupy two spaces at once - a physical store and a digital storefront, comparing offerings online, introducing new pricing dynamics, leveraging brands against each other, and even seizing control of brand narratives in real-time. Data and algorithms, influencers and networks - these are driving innovations in behavioral economics and a growing array of verticals from Gilt in fashion to AirBnB’s disruption of hospitality, while simultaneously reinforcing the demand for authenticity and rapid, human response from brands. Yelp’s $5.7 billion market cap is a great example of this symbiosis. Services that help consumers find better deals on the things they actually want will leverage personalization and network analysis to drive sales. New, mobile-centric platforms like Square and Stripe are changing how we pay for them, foreshadowing a future without cash registers or checkout stands when products find us more easily than we can find them.
The enterprise faces two fundamental challenges to higher efficiency and greater innovation. First, the much-needed communication and collaboration between different functional groups and across the ecosystem of stakeholders, offered by tools such as LinkedIn and Docusign, has struggled to emerge as a new category on its own, as many startups have been acquired and folded into larger platforms before attaining Unicorn status. Microsoft acquired Yammer for $1B, Salesforce continues to explore the space, and SAP, IBM, and other enterprise solutions are making some in-roads, though more through partnerships than true utility. Solutions that align business intelligence, budgeting, performance, and collaboration across business units will enable considerable gains in productivity. Second, many businesses are still too rigid and slow-moving to adequately respond to quickening competitive pressures. They must become more lean, agile, flat, and adaptive. Like so many things, organizational structure is starting to become more sensitive and responsive to the environment in which it operates. There is an increasing need for tool-chains, like ServiceNow, that sense environmental conditions, provide probabilities of oncoming change, and, like Workday, support the modeling and reconfiguration of organizational structure to proactively capitalize on the future. As the Enterprise moves more assets into private, public, or hybrid clouds, new infrastructure needs are creating Unicorns like Fusio-io, Pure Storage, and Palo Alto Networks. This momentum is also birthing new cloud Unicorns like Box, Dropbox, and Evernote that further de-couple modular functionality from within the enterprise, enabling a lighter IT footprint.
The mobile sector is already starting to be reframed into devices – wearables, appliances, and any other networked and computational machine. And yet, there’s still tremendous opportunity to make so-called smart phones much smarter. The convergence of precise location, context-awareness, and predictive analytics offers the possibility of not only more personalized and relevant mobile applications but entirely new formulations for mobile operating systems designed to more uniquely reflect and augment their users. Recent high-profile acquisitions like VMWare’s purchase of AirWatch for almost $1.5 billion underscore the challenges in managing a fast-growing population of mobile devices, jumping on and off networks, making continuous requests for provisioning and security. It also signals the emerging role of virtual machines in making workspaces accessible everywhere from any device. Meanwhile, human behavior continues to drive disruption in the $1+ Trillion telecom sector, most recently underscored by Facebook’s purchase of WhatsApp’s universal messaging service for $19 billion, as well as Google’s declined offer of $3 billion for Snapchat. In a time of rich media and immersion, Facebook is chasing its audience into lo-fidelity, short-form communications – perhaps with an eye on the next 3 billion users in emerging markets. Looking a bit more into the future, who’s going to take advantage of all the unused computational capacity sitting in smart phones? And will peer-to-peer mesh networks like FireChat become a more popular way to communicate and share files?
Media will continue to fragment, driving both greater diversity and consolidation. Broadcast TV is slowly losing viewers to a rich marketplace of on-demand services, niche channels, and the Long Tail of user-generated content. Netflix, Amazon, and Hulu produce their own original shows, competing directly with the likes of NBC and CBS. Sports drink maker, Red Bull, has a popular extreme sports channel, and Twitch has 45 million unique viewers every month for its video game viewing service. YouTube has over 70 hours of video uploaded every minute, much of it coming from nearly-ubiquitous smart phones. Anyone can be a superstar: Jenna Marbles, a 27-year old from Rochester, NY, has 13 million YouTube subscribers and a billion and a half views. Hollywood has already started to adapt to the new MNC (Multi-Channel Networks) reality. It will be fascinating to watch how a more intimate relationship to online video consumers will inform its business of story-telling. The cost of production tools continues to go down, performance gets better, and everyone has access to global broadcast platforms. With a small, affordable, and durable camera system, GoPro has added entirely new experiences to our consumption of media, grabbing a $2.5 billion valuation in the process. Facebook’s recent acquisition of Oculus VR has made a new Unicorn that paints a future of deeper immersion than ever before, as the DNA of video-gaming in hi-res and casual formats, like Zynga, with bigger-than-Hollywood box office receipts, remixes with other genres. Behind the scenes, algorithms are getting better at tracking our viewing habits. They’re increasingly able to “look” at video and understand the contents. They’re even wielding insights from neuro-marketing to make more compelling advertising. Netflix used its viewing data to determine the best drama to produce. The result is House of Cards, which might also describe the Hollywood/Cableco establishment’s legacy model for premium content creation.
Social networking has birthed a narrow set of exclusive platforms, often with single players dominating regional consumer markets, such as TenCent and Weibo in China, and LINE in Japan and Korea, each of which have been led by Facebook and Twitter. Facebook is now a legitimate Giant while Twitter seems to be caught somewhere in a post-Unicorn limbo. Nevertheless, social networking has contributed a fundamental interaction model for many of the Unicorns we study. You can’t really build networked solutions without some degree of social integration. The design patterns, architectures, and best practices of social networking are working their way into all things digital, as Unicorns in other sectors adopt messaging, reputation tools, and profiles to drive everything from apartment rentals to taxi rides. As a result, huge audiences are gathering around their own content in attention markets like Pinterest and Tumblr. This tension between the growing ubiquity of social collaboration and the extraordinary value of social platforms is driving the most disruptive trend: the market leaders are trying to displace the open Internet and enclose its value within their walls. So we must ask, are the young platform elephants truly creating the commons, as their management wants us to believe, or are they just raising the walls higher around their gardens? The tilt towards social consumption on smartphones is accelerating momentum towards the latter. The top mobile applications, for example, have already displaced mobile browsers, and search is being replaced with install ads. This has profound implications for brands, agencies, and increasingly other communications providers.
how to spot a possible unicorn?
Statistically, start-ups that hit the billion-dollar mark are still quite rare but there are some commonalities – and common sense – that can help us find the ones with the best chances.
The characteristics of the founding team are quite consistent. Among recent Unicorns, founders are almost universally in their thirties, have had previous experience starting and growing companies, and have significant expertise in their domain. Unicorns typically reach maturation after 7 to 10 years, though there are often exceptions, but over that time they have shown increasingly exponential growth in accounts, revenues, or audience size. How much investment capital they’ve raised is important as well, but may not be as important as whom they’re getting the money from. Sequoia Capital, for example, has produced more Unicorns than any other VC firm, followed by New Enterprise Associates, Accell Partners, Meritech Capital Partners, and Benchmark. These firms have exceptional access to capital, talent, and marketing resources.
Ultimately, Unicorn contenders must offer a novel solution with a coherent roadmap that targets a large addressable market. Dropbox offers storage and security without the hosting overhead. Square makes retail credit card payments cheap and easy for small businesses. Uber empowers users frustrated with car ownership and slow taxi service. WhatsApp makes messaging simple and nearly-free for more than 200 million users. Identify a problem in a large market, innovate an impactful solution, and scale.
As we researched the high-speed value creation that Unicorns represent, it became clear that we are witnessing a business landscape transformation into a three-tier model: Incumbents, by which we mean legacy market players that in most cases precede the Internet revolution; Giants, meaning companies like Amazon, Google or Facebook who have built significant platforms on top of the Internet; and our current focus, Unicorns, who can be seen as the ‘natives’ born in a post-platform world where disruption is the New Normal. This three-tier model informs our discussion of how Incumbents and Giants have distinctive responses to the waves of disruption stirred up by Unicorns.
So how do we prosper in a marketplace characterized by disruptive Giants and more and more Unicorns? To frame the results of our investigation we build on previous work discussing the concept of the combinatorial enterprise, this time focusing on the notion of adjacencies.
Simply put, Adjacencies are opportunities that sit outside of the current focus of the core business. They include some of the most interesting and potentially valuable new markets. Google acquired the consumer appliance company, Nest, to gain a foothold in the home and reinforce its data access. Facebook’s purchase of Oculus VR gives the social networking Giant access to an entirely new line of immersive experiences. While much of the strategic thinking about corporate structure and efficiency has focused on what is ‘core’ and ‘non-core’, (including Hayden Shaughnessy’s idea of the ‘fluid core’), it is clear that competitive intensity and digital transformation of everything - from consumer package goods to advertising to even infrastructure - are putting tremendous pressure on executives to re-evaluate how secure the core really is, and to formulate combinatorial strategies to reshape themselves to compete more effectively. In today’s transformative business dynamics, re-evaluation of the Core should involve Adjacency.
Compelling adjacencies usually arise in young sectors that are showing strong growth and that offer businesses – and capital - the opportunity to expand their market position into new territory. By definition, Incumbents are heavily invested in their prior successes, and are further encumbered by management teams that are focused on maintaining that posture. The new Giants, in contrast, have a more agile platform model that allows them to move beyond their core into adjacent markets with often stunning impacts. They were also born in a time of accelerated change and exponential technologies. It is a truism that Google moved from a core Search posture to grab most of the revenues in an emergent digital advertising market in less than a decade. Amazon did the same by spinning off its internal cloud operations into Amazon Web Services.
Facebook’s purchase of WhatsApp for $19 billion is, in part, an adjacency play for the market and its audience. WhatsApp has 450 million regular users authoring almost 20 billion messages a day. The 5-year old company has shown exponential growth across global markets that are very complementary to those served by Facebook’s own instant messaging service. Facebook is also responding to macro changes as more teens and young adults are migrating into instant messaging. Likewise, the social graph of services like Facebook and Twitter are beginning to show their limitations. WhatsApp, on the other hand, has access to a person’s true rolodex of friends: their mobile contacts.
So, how do Unicorns deal with adjacencies?
They’re already there. They occupy and often define adjacencies. Before understanding the profound implications of this, we need a better model.
Defining a typology of adjacencies – Combine Adapt Share Evolve
There are numerous examples of adjacency strategies that offer pathways to move from a reactive posture towards a more proactive approach. The typologies offered below are not exhaustive nor are they mutually exclusive. Companies may pursue some or all of these in parallel, and any given strategy may be more or less complex than we’ve outlined here. The four strategies in the model are:
This is a proactive and willful posture that pursues creative opportunities where two or more components can be re-combined in a novel and meaningful way. Google’s acquisition of Nest for a whopping $3.2 billion is a study in the opportunities that arise from convergent technologies. Nest was born in adjacencies. The Nest thermostat replaced the legacy model with multifunction sensors, an IP address, and iOS/Android integration. It leverages the convergence of computation, networks, hardware, and sensing to solve a frustratingly simple problem in a much better way. By combining all these components and sticking them in the home, Google’s purchase gets at their most valuable asset: data.
Adapt to macro changes
This is a reactive response to an environment that no longer aligns with your core business. This is commonly the “adapt or die” posture but it can also be a conscious evolution. For example, VMWare has shaped the macro condition to which it’s now responding. Their recent $1.25 billion acquisition of Nicira more tightly couples virtualization with software-defined networking, reinforcing the foundation for the steady dematerialization of network functions. Similarly, their acquisition of Airwatch for $1.45 billion acknowledges that more and more devices are dynamically moving on and off networks, and they all need provisioning and management. Lenovo’s acquisition of Motorola Mobility for $2.9 billion from Google is another example. Demand has been shifting away from PC’s and towards mobile devices. As the world’s fastest growing smartphone maker, the Motorola acquisition will help Lenovo consolidate its mobile position, just as they did with ThinkPad when they bought IBM’s PC business in 2004. Facebook’s recent purchase of virtual reality start-up Oculus VR for $2 billion is the social giant’s hedge against what may be the next big emerging media platform. With a $156 billion market cap, Facebook’s interest alone may be enough to shape the success of VR.
Share best practices
This is a very forward-looking posture that aligns direct revenue opportunities embedded in internal processes with an external investment in ecosystem wellness. Founded in 1994, Amazon was not only born with the online era, they pretty much wrote the book on how to run a global e-commerce platform. In 2006, Amazon took its expertise in deploying, managing, and scaling its own cloud solution and released it to the world. Amazon Web Services (AWS) formalized their own best practices in hosting and offered the capability to the marketplace at a fraction of the cost it would take to deploy and run comparable on-premise solutions. In doing so, they created an entirely new revenue stream and fed the very marketplace they were dependent upon. More recently, Facebook shared the code it uses to measure the efficiency of water and energy consumption in its data centers. Beyond helping their business ecosystem, this move actually helps natural ecosystems as well.
Evolve into new markets
This is more of a classical adjacency that grows and adapts through market expansion, though it’s perhaps more instructive to think of it in terms of expanding into new competencies. However, this is not about consolidation which seeks to reinforce an existing position. When Google paid $1.65 billion for YouTube in 2006, it was the largest outlay of capital the company had made in its history. At the time, then-CEO Eric Schmidt remarked on the acquisition that “this is the next step in the evolution of the Internet.” Prior to the sale YouTube had reported 100 million streams a month, showing a strong market demand for its easy video sharing solution. Google’s own attempts to extend its search and advertising empire into online video were lagging. Buying YouTube allowed them to acquire the market, the segment, and the audience. The same market adjacency strategy can, in part, be seen in Facebook’s acquisition of WhatsApp for $19 billion.
How are incumbents drawn into adjacencies?
Amidst accelerating innovation and rising competitive intensity businesses will inevitably be drawn into adjacent strategies. Macro pressures change the playing field, forcing businesses to adapt or die. Competitive pressures can force the hand of leaders to act in order to defend their market share and preserve their strategic objectives. Market opportunities and internal innovations open up new fields of development. Increasingly, companies must move into adjacencies in order to attract the best talent. Otherwise, they seem old and outdated.
Having been relatively free from external competition for decades, the taxi industry – and car ownership itself - is now being aggressively disrupted by Uber and Lyft. These Unicorns built popular, on-demand, mobile-first services that have pushed the incumbents to evolve into adjacent territory. Flywheel, a mobile application for on-demand cab services, recently partnered with San Francisco’s second largest cab fleet, Luxor, to bring their taxis into the 21st century.
Most businesses will be forced into adjacent strategies sooner or later but the most proactive stance is to define them yourself. Savvy leaders can see emerging adjacencies and understand their opportunities. Sensing the flow of currents and wielding the power to guide them has driven major disruptors to move beyond responding to markets. They actively shape them.
Going forward, options for shaping adjacencies
Now that we’ve laid out the strategies, let’s summarize the options for the three types of market actors in the digital economy.
Options to shape adjacencies are not the same for all actors
Examples of strategic adjacencies
voices from the valley
On the shift away from public exits:
In the last 15 years the number of public companies in the US has dropped from 8800 to 4200. So what’s happening is the public market is collapsing. As a consequence, the new growth companies tend to stay private for longer. There’s no way to look at the number of high-profile billion-dollar-plus private companies or the amount of money going into them without looking at what’s happening in the public market.
…There are gigantic megatrends that we believe that you can’t play in public. How do you bet bitcoin on the public market? Try to make a public bet on crowd-funding. It’s impossible. Sharing economy, you can’t take a public position. With these kinds of megatrends you’re going to have capital coming over.
On flowing capital:
The really striking thing about the global economic environment right now is that there’s a lot of money on the sidelines. That’s one of the reasons I’m relatively optimistic about the next 5 or 10 years because there are just oceans of capital looking for attractive places to invest.
On the ease of capitalization and the challenges of growth:
I think you can envision having a company with 10 engineers and a billion users and a billion dollars of revenue that’s raised $10 million. Whether you can have a business like that go to $10 billion in revenue without raising billions of dollars is harder to see.
In the startup world, it is my firm opinion that the founders drive and the investors ride shotgun. I’ve never seen a great startup where this is not the case.
… VC’s can select great companies with break-out potential. People might say “how does that add value to startups?” The answer is that it doesn’t. But it does add value for LPs who invest in the fund.
What to look for in a startup:
Is the team chasing a huge potential market characterized by dynamic technology change? Is the team balanced? Will the team attract extraordinarily awesome people? Is there a “product picker”? Most great startups have someone on the team who is a product visionary perfectly suited for the opportunity ahead.
On challenges for VC’s:
The industry has to show it can deliver better returns than the public markets. There’s been good liquidity recently and a nice pipeline of private tech companies should have liquidity for the next few years. But when you look at the number of startups being created each year, you realize the probability of success is not great.
…Startups have a tremendous opportunity to build products that scale faster and address bigger markets than ever before, especially in many consumer and enterprise industries that have been relatively untouched by Internet and mobile.
On market exuberance:
Any time that people are doing something for the first time and breaking records you want to pay attention. But the markets are so much bigger than they were during the first boom.
interviewed by: Chris Arkenberg
Your work explores the impacts of what you call Digital Transformation. What does this mean for companies trying to keep up?
If you attempt to compete for the future, if you invest in new technologies to meet the needs of your market, then you will win. But there’s a more prominent part of Digital Transformation that comes from how you and I are changing as a result of technology’s impact on our lives. That’s where a lot of innovation can occur. Innovation has less to do with technology than it has to do with how you think about the opportunities to evolve or to create. I’ve found in most cases that change doesn’t start from the top down. You have to rely on the change agents to create a sense of urgency from the bottom-up and then win over executives in order to drive change from the top-down. That’s really how a culture of innovation starts.
How can older incumbents adapt to the change and disruption? Can they evolve and play on this field without getting run over?
A lot of organizations today are very stubborn. They have cultures that are more management-driven so they are optimized to scale and to grow based on the world that is and the roadmaps that exist today. It takes a culture of innovation and resilience to be able to even think you have something to learn in the first place. When you have a leadership infrastructure that’s really focused on today, they aren’t necessarily in touch with how things are changing. Until leadership leads, the culture is going to have to adapt slowly.
What’s your perspective on Unicorns and the new tier of billion-dollar-plus valuations?
When you talk about spotting a Unicorn, we tend to get caught up in trying to find the next thing based on historical performance, traction in the marketplace, investment dollars, investors, founder teams. But these factors aren’t enough to find a Unicorn. What’s going to help you find a Unicorn is digital anthropology, to recognize an opportunity based on behavior. It’s what I call the Dilemma’s Innovator. It’s solving problems and creating opportunities based on unmet needs.
$19 B is an exorbitant amount of money to pay for WhatsApp, for example. It’s going to create an unfair bar because people are going to look at the users, the potential revenue, and the valuation instead of the reasons why WhatsApp is what it is and why Facebook bought it. WhatsApp is special because it addresses a market need that was unaddressed. Text messaging and iMessage weren’t meeting the needs of the younger generation.
Facebook famously said that “we want to be the dial tone for the internet”. That’s a really big statement. That means that they want to change how people communicate. If you really extrapolate what $19B means, maybe at some point you’re not going to have a phone number. You’re going to have an IP address. You’re going to have something that’s unique to you regardless of the device or the platform. That’s a powerful future to consider. It’s a $19B bet on that.
Looking forward to the 2020 horizon, we can develop a sense of how technology sectors will form around the deeper currents of behavior and adaptation. Like all forecasts, this is about likelihoods, not prediction. Given our focus on Unicorns, these scenarios offer a radar for adjacencies and strategic opportunities available to all players: Incumbents, Giants, and Unicorns present and future.
Ubiquitous computation emerges when chips become so small and affordable that they can be used anywhere. They can be poured with concrete, woven into clothing, and embedded in surfaces. Intel predicts that this point will arrive around 2020 and the current landscape (as well as their own efforts to build smaller chipsets like Edison) suggests they may be correct. The nascent explosion in smart, connected hardware – the Internet of Things – is enabled by this condition. The power of computation is spreading everywhere, from discrete and localized objects to vast distributed cloud resources, all of it networked by default and increasingly accessed through virtualized, on-demand interface layers. We are approaching a time of near-infinite, leasable computational capacity. Autodesk is helping build this future so that architects, engineers, and scientists can accurately simulate kinetics, heat envelopes, and the very processes of human physiology and biological life. Ubiquitous, networked computation has the potential to radically reshape much of our world.
By 2020, the built environment and biological systems will see increasing disruption from computational Giants and more adaptive Incumbents.
Hardware proliferation is reaching an inflection point as the barriers to production become ever smaller. On-demand, just-in-time, powerful and personalized design and manufacturing is driving a Cambrian explosion of devices, tools, materials, and data. It’s being enabled by precision tooling from vendors like 3D Systems and Stratasys, powerful design tools from Autodesk and Dassault Systems, and easy access to manufacturing resources like Ali Baba, Ponoko, and Shapeways. Jawbone, Basis, and Fitbit have each benefited from this environment. The likely trend is towards tools that offer more precision and power for less money, coupled to niche services and communities that birth exceptional innovations. Byproducts include the combinatorial amplification of smart, connected hardware as things beget more things and templates are shared and iterated through interest communities like Instructables and DIY Drones. This current has the potential to redraw the creation of goods, handing more power to individuals and collaborators while applying greater competitive pressure to established manufacturers. We’re already seeing the impacts, for example, with the GE-Quirky partnership for crowd-designed solutions coupled to the distribution and marketing weight of an appliance giant. This rising tide is lifting all boats so it’s important to watch how such broad empowerment of individuals is refracted through diverse motivations and power structures. There is a strong likelihood that algorithmic governance will move into this space in an attempt to contain and direct the explosion.
In 2020, algorithmically-powered predictive supply chains anticipate demand from distributed design and manufacturing communities.
Virtualization offers a highly-flexible, customizable interface layer for distributed computation. The cloud distributes computing resources across networks and into the hands of core infrastructure providers like Rackspace and Amazon AWS. Virtualization reconciles that abstraction by separating the interface layer from the CPU. The result is trending towards smart, dynamic, and adaptive networks coupled to distributed and fluid computation resources. The impact will likely further commoditize computation as a basic utility while fostering innovation in custom virtual machines and task-based interfaces, as well as much more fluid access to personal desktops from any screen anywhere. This shift will also impact middleware solutions for federation, provisioning, and security that will need to follow users across numerous entry points and interfaces. Emerging services like FireChat that enable messaging on smartphone mesh networks suggest not only a future that disintermediates service carriers, but also one that’s able to assemble computational clusters from numerous mobile devices and then assign virtual machine layers to them. Imagine being able to lease CPU cycles – or sensor arrays - on meshes of under-utilized smart phones.
By 2020, Virtualization will extend from the compute layer to networks and devices, creating new combinatorial opportunities for Giants and Unicorns.
Communication is a core competency of the human species. It will continue to shape our tools and drive the way we innovate and collaborate. Like talking itself, digital communication is trending towards being essentially free, finding ways to route around any economic, geographic, or political barriers. Both WhatsApp and Snapchat are examples of this trend, enabling easy and cheap messaging across the world. Indeed, information itself is flowing more than ever, from knowledge stores to tacit experiences. This current has already been deeply disruptive and we should expect more challenges and conflicts to arise from the ease with which we can communicate, share, collaborate, and execute. Growth sectors like cyber-security and intrusion forensics will meet obfuscators and algorithmic agents on a playing field that will soon include the Internet of Things. It’s notable that more than half of network communications are from machines, suggesting a future where protocols for M2M interactions outweigh human systems.
In 2020, conversations with non-human parties will be common, raising issues of trust, and openings for new disruptors.
Identity is becoming a primary organizational structure of the connected life. The data shadow cast by our online identities is being leveraged to better understand our interests, map our affinities, deliver contextual services that specifically meet our needs, and even to predict our behaviors before we act. We each have a data object around our digital selves. When networks interpenetrate more of the physical world our location can be used to provision or revoke services. Geofencing can be as simple as turning off the lights when you step out your front door, or it could bar you from accessing public transit or passing through toll gates. While our digital identities are fragmented today – Facebook, Google, Yahoo, and the government all try to own us, in a sense, as do our enterprise employers - there will be efforts to consolidate them into a single universal ID that sees little difference between walled gardens, virtuality, and the physical world. This will also renew public discussion and practical implementation of data ownership and user rights, perhaps leading to greater literacy about who controls our data.
Between now and 2020, we will better see how Facebook and others occupy Identity adjacencies beyond the web and into the physical world.
Context awareness is the convergence of data, location, and algorithmic sense-making. So-called smart phones start to become aware of who we are, where we are, and what is valuable to us and what we blacklist. Our personal devices and the digital services we commission begin to act as agents on our behalf. Amazon Recommendations are a simple example of this, matching related items to what we’re currently observing, but this capability is beginning to reach into the physical world. Today, smart traffic lights watch flows and automatically adjust their timing to manage congestion while Google driverless vehicles use machine vision to navigate roadways and correct against collisions. In this context, the Internet of Things becomes a distributed sensory apparatus emerging all around us like mushrooms from an unseen mycelial mat. The boom in sensor-based data is enabling advanced cybernetics and embedded governance – the essential elements for both smart cities and strong enforcement. Helping us better navigate the world is only one facet of a surface that is steadily creating more points of control – and vulnerability - for machines and governors alike. It’s also building the framework for increasingly intelligent computation. Artificial intelligence start-up, Vicarious, has received $60 million from a suite of A-list tech CEO’s to bankroll its efforts towards the world’s first intelligent machines. Among its many curious acquisitions, Google spent $500 million to buy Deep Mind, a startup using machine learning and systems neuroscience to build “general-purpose learning algorithms”. Google has also been buying up robotics companies hungry for greater context awareness.
By 2020, we fully expect a perceptive built environment to push AI and Machine/Deep Learning to Unicorn status.
about Orange Silicon Valley
Orange Silicon Valley is the Bay Area division of Orange - one of the world’s leading telecommunications operators, serving 231 million customers. Orange Silicon Valley actively participates in the disruptive innovations that are changing the way we communicate, which is the core business of Orange in the 220 countries where we operate. We contribute to and engage with the Silicon Valley ecosystem in a variety of ways.
At Orange Silicon Valley, we thrive on collaboration, seek out disruption, and anticipate that the future is closer than we think. Orange Silicon Valley fosters innovation through our Orange Fab accelerator program, and promotes discussion around the key issues and trends within the tech sphere through our network.
The services and activities executed by the Orange Silicon Valley team are constantly evolving. What remains constant in all our iterations is our commitment to be objective, insightful, and inclusive of the ecosystem in everything we design and do.
This report began with very timely insights from our CEO, Georges Nahon, in response to Facebook’s unprecedented $19 billion acquisition of WhatsApp. Our analysis of Unicorn valuations soon led us to re-frame our work within the context of Haydn Shaugnessy’s “Radical Adjacencies” in an attempt to surface the strategic importance of these entities and show how they fit into the broader ecosystem of technology and capital. We’d also like to make a special acknowledgement of Aileen Lee and Cowboy Ventures for inspiration and insights into the Unicorn phenomena. We want to thank Brian Solis for speaking with us about Digital Transformation and the pathways of disruption and innovation; Marc Andreesen and Andreesen Horowitz / a16z.com for insights into the private economy; Mike Maples for comments on founding teams; and Don Dodge for thoughts on exit strategies. Data for this report has been drawn from multiple sources but we want to especially acknowledge CB Insights for their thought-provoking visualizations, as well as Capital IQ for extensive data sets. And of course, where would we be without Crunchbase?
Georges Nahon, CEO, Orange Silicon Valley
Mark Plakias, VP Strategy
Gabriel Sidhom, VP Technology Development
Chris Arkenberg, Lead Researcher
Wale Ayeni, Senior Technology Analyst
Derek Au, Technology Analyst
Ken Yeung, Strategy and Research Content Lead
Anca Ranta, Research Assistant
This work wouldn’t have been possible without continued support from our Graphic Design Lead, Marielle Atanacio.
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