…we used CB Insights data and analysis to dig in and see which startups have been peeling away at some of the categories served by default iOS apps… We found dozens of investor-backed private companies developing apps that would like to displace Apple’s stock apps and knock them off the home screen. In all, we identified 44 startups attacking iOS, with music, messaging, and health seeming to be the three most contested categories.
A new survey of 316 executives from large global companies, conducted by Forbes Insights and sponsored by Teradata in partnership with McKinsey, provides a fresh look at the state of big data analytics implementations. Here are the highlights.
The hype gone, big data is alive and doing well
About 90% of organizations report medium to high levels of investment in big data analytics, and about a third call their investments “very significant.” Most important, about two-thirds of respondents report that big data and analytics initiatives have had a significant, measurable impact on revenues.
59% of the executives surveyed consider big data and analytics either a top five issue or the single most important way to achieve a competitive advantage. This attitude is slightly more prevalent in financial services and much more prevalent in Asia-Pacific, where 41% of executives (compared to the survey average of 21%) consider big data and analytics the single most important way for companies to gain a competitive advantage.
The right organizational culture is key to big data success
No matter how many times you say “data-driven,” decisions are still not based on data. Sounds familiar? 51% of executives said that adapting and refining a data-driven strategy is the single biggest cultural barrier and 47% reported putting big data learning into action as an operational challenge. 43% cited fostering a culture that rewards use of data and valuing creativity and experimentation with data as key challenges.
Companies that don’t get the data-driven culture right tend to fall behind their peers. 47% of executives surveyed do not think that their companies’ big data and analytics capabilities are above par or best of breed. And the survey found that the more the respondents know about big data and analytics, the less likely they are to judge the organization as above average or best of breed. For example, among data scientists, only 8% call their organizations best of breed and 10% think they are above average.
Big data is top of mind when the CEO loves data
If you take big data analytics seriously, you get results. 51% of organizations where big data is viewed as the single most important way to gain competitive advantage are led by CEOs who personally focus on big data initiatives. In organizations where big data is viewed as a top-five issue that gets significant time and attention from top leadership, the sponsor is typically one level below top leadership. Finally, companies that have established data and analytics positions at the CxO level are more likely to have above average data analytics capabilities.
Going from the right attitude to the right action is a long big data journey
Even if you have top leadership sponsorship and the right culture, getting data to drive action and strategy is a challenge. 48% of executives surveyed regard making fact-based business decisions based on data as a key strategic challenge, and 43% cite developing a corporate strategy as a significant hurdle. Other obstacles to realizing the benefits of big data analytics are focusing resources to get the most insights from data (43%) and viewing data as a valuable asset (41%).
There’s gold in them thar brontobyte data mountains
The survey found that big data is driving opportunities for innovation in three key areas: creating new business models (54%); discovering new product offers (52%); and monetizing data to external companies (40%). To pursue these opportunities, companies that are gaining the most traction are looking beyond transactional data—exploring a wide variety of many data types.
The most-cited was location data (used to identify an electronic device’s physical location), collected by over half of the respondents, followed by text data (unstructured data like email messages, slides, Word documents, and instant messages). Social media is tracked and its unstructured data collected by 43% of companies surveyed and about a third finds golden nuggets in images, weblogs, videos, sensor data and speech files.
Big data miners still very much wanted
Realizing the business and innovation opportunities hidden in the mountains of data requires the right set of skills and experiences. 46% of the executives surveyed, however, reported that hiring the talent that can recognize innovations in data is a challenge.
Originally published on Forbes.com
Venture capital funding to education technology startups passed $1.6B last year, across 217 deals. With ed tech startup investing becoming so competitive and crowded, it’s important to know where top VCs are placing their bets…
Accel Partners, Felicis Ventures, and New Enterprise Associates are the most active smart VCs in ed tech, with more than 10 unique portfolio companies each in the area. The least active investors are Index Ventures and Battery Ventures. Two startups had the most unique smart VC investors, with 5 each: classroom-based community tool Edmodo and online learning content platform Knewton.
We identified six different ed tech markets that smart VCs are moving into.
Etay Maor, IBM
Wired recently reported that hackers posted a “data dump, 9.7 gigabytes in size… to the dark web using an Onion address accessible only through the Tor browser.” The data included names, passwords, addresses, profile descriptions and several years of credit card data for 32 million users of Ashley Madison, a social network billing itself as the premier site for married individuals seeking partners for affairs.
“I want to show you the dark side of the net,” Etay Maor told me when we met last month at the IBM offices in Cambridge, Massachusetts. He then proceeded to give me a tour of the Internet’s underground, where cyber criminals and hackers exchange data, swap tips, and offer free and for-fee services. “Information sharing is a given on the dark side,” said Maor, “but for the good guys, it’s not that easy.”
Maor is a senior fraud prevention strategist at IBM and has watched the dark side of the Web at RSA, where he led the cyber threats research lab, and later at Trusteer, a cybersecurity startup which IBM has acquired in 2013 for a reported $1 billion. His focus is cybercrime intelligence, specifically malware—understanding how it is developed and the networks over which it is distributed. Maor is an expert on how cyber criminals think and act and shares his knowledge with IBM’s customers and also with the world at large by speaking at conferences and blogging at securityintelligence.com.
The Web is like an iceberg divided into three segments, each with its own cluster of hangouts for cyber criminals and their digital breadcrumbs. The tip of the iceberg is the “Clear Web” (also called the Surface Web), indexed by Google and other search engines. The very large body of the iceberg, submerged under the virtual water, is the “Deep Web”—anything on the Web that’s not accessible to the search engines (e.g., your bank account). Within the Deep Web lies the “Dark Web,” a region of the iceberg that is difficult to access and can be reached only via specialized networks.
Maor first demonstrated to me how much cybercrime-related information is available on the Clear Web. Simply by searching for spreadsheets with the word “password” in them, you can get the default password list for many types of devices and other things and places of interest to criminals. There is easily accessible information that may have been posted to the Web innocently or by mistake. But there is also a lot of compromised information (e.g., stolen email addresses and their passwords) available on legitimate websites that provide a Web location for dumping data.
Then there are forums for criminals, some masquerading as a benign “hacking community” or “security research forum,” promoting themselves like any other business and/or community, including a Facebook page, and covering their costs or even making some money by displaying ads. One such forum had 1,200 other people accessing it when Maor showed it to me, demonstrating how, with a few clicks of the mouse, you can find lists of stolen credit card numbers including all the requisite information about the card holder.
Maor proceeded to introduce me to Tor, the most popular specialized network providing anonymity for its users, including participants in the underground economy of the Dark Web. It was developed in the 1990s with the purpose of protecting U.S. intelligence communications online by researchers at the US Naval Research Lab which released the code in 2004 under a free license. It has 2.5 million daily users, some with legitimate reasons to protect their identities, and others who are engaged in criminal activities.
Tor is based on Onion routing, where messages are encapsulated in layers of encryption. The encrypted data is transmitted through a series of network nodes called onion routers, each of which “peels” away a single layer, uncovering the data’s next destination. The sender remains anonymous because each intermediary knows only the location of the immediately preceding and following nodes. The final node in the chain, the “exit node,” decrypts the final layer and delivers the message to the recipient.
While Tor is used by people with legitimate reasons to hide their identity, it (and similar networks) also facilitates a thriving underground economy. This is where you can buy firearms, drugs, fake documents, prescription drugs or engage in pedophilia networks, human trafficking, and organ trafficking. Maor paraphrases Oscar Wilde: “Give a man a mask and he will show his true face.”
Tor is also home to rapidly growing “startups,” offering fraud-as-a-service. A decade ago, says Maor, cybercrime “was one-man operation. Today, it’s teamwork.” Furthermore, the whole process, from coding the malware to distributing it to working with money mules, can be easily outsourced. Everything a cybercriminal might need is now available on the underground forums, some components of the process as a free download, others as a for-fee service, including cloud-based services with guaranteed service level agreements (SLAs). The menu of cybercrime options has grown beyond financial fraud tools, to include advanced targeting tools, Remote Access Tools (RATs), and health care and insurance fraud tools and services.
The explosion of data about us, our lives and our workplaces on the Clear Web has helped the denizens of the Dark Web circumvent traditional online defenses such as passwords. “Fifteen years ago,” says Maor, “it took a lot of work to breach a company. Today, I can go on Linkedin and find out exactly what is the structure of the company I’m interested in.” Knowledge of the reporting structure of a specific company helps criminals’ “social engineering” efforts, manipulating people into performing certain compromising actions or divulging confidential information. Once criminals get to know their targets (e.g., by connecting on Linkedin), the victims may open an email or attachment that will infect their computer and provide the desired access to the company’s IT infrastructure.
Cyber criminals are taking advantage of the abundance of data on the Web and its success at connecting and networking over 2 billion people around the world. 80% of cyber attacks are driven by highly organized crime rings in which data, tools and expertise are widely shared, according to a UN study on organized crime, generating $445 billion in illegal profits and brokering one billion-plus pieces of personally identifiable information annually.
Data and networking—aren’t they also great tools in the fight against cybercrime? Not so much. Corporations and security firms have been reluctant to share cybersecurity intelligence. Only 15% of respondents to a recent survey said that “participating in knowledge sharing” is a spending priority.
There have been some efforts to change that, such as the establishment of industry-specific Information Sharing and Analysis Centers (ISACs) and the cross-industry National Council of ISACs. The Department of Homeland Security and other government agencies are working to promote specific, standardized message and communication formats to facilitate the sharing of cyber intelligence in real time. The Cybersecurity Information Sharing Act (CISA), a bill creating a framework for companies and federal agencies to coordinate against cyberattacks, is being debated in Congress.
Alejandro Mayorkas, the Deputy Secretary of Homeland Security recently said: “Today’s threats require the engagement of our entire society. This shared responsibility means that we have to work with each other in ways that are often new for the government and the private sector. This means that we also have to trust each other and share information.”
IBM has taken a big step towards greater engagement and information sharing when it launched in April the IBM X-Force Exchange. It is a threat intelligence sharing platform where registered users can mine IBM’s data to research security threats, aggregate cyber intelligence, and collaborate with their peers. IBM says the exchange has quickly grown to 7,500 registered users, identifying in real-time sophisticated cybercrime campaigns. “I’m a fan,” security guru Bruce Schneier responded when I asked him about X-Force Exchange.
“The security industry must share information, all the time, in real time,” says Maor. “It’s a change of mindset, but it has to be done if we want to have some sort of edge against the criminals.”
Originally published on Forbes.com
It looks like most of the publications and pundits of the world had something to say about the surprise-of-the-decade: Google’s transformation into Alphabet (Techmeme provides a sample here). For me, the numerous questions they posed only triggered further questions: Is the new holding company going to be like Berkshire Hathaway, or GE, or AT&T or an early retirement playground for Page and Brin, playing God instead of golf? Is Larry Page saying he does not want to be Bill Gates or does he want to be Thomas Edison Plus? Is it just a simple “re-org,” so typical of large and lumbering companies, masquerading as an “unconventional move”?
In his post (not in a conventional press release) announcing the surprising metamorphosis, Larry Page made sure to remind us that “As Sergey and I wrote in the original founders letter 11 years ago, ‘Google is not a conventional company. We do not intend to become one.’”
Google, now Alphabet, is indeed an unconventional company in many respects, not the least of which is that the aforementioned founders hold 54% of the stock’s voting rights, giving them full control of the company. But at its core, I would argue, it’s a conventional company in a conventional business.
“Invention is not enough,” Page has said (see James Altucher’s post). “You have to combine both things: invention and innovation focus, plus the company that can commercialize things and get them to people.”
For Page and Brin, the key invention was a better search engine. But they brilliantly coupled it, with the help of the bright people they hired, with two other inventions that made that original invention a commercial success: Developing their own computing infrastructure capable of handling Brontobyte Data and a completely new approach to selling advertising.
By relying on advertising for its livelihood (it still accounts for over 90% of Google’s revenues), Google has become a conventional media company. It has enjoyed the growing stream of advertising dollars shifting from print and other channels to online. But it will be the victim of its own success: As online advertising becomes more dominant, growth will slow and Google’s fortunes will rise and fall with the advertising market which typically follows the rise and fall of economy (online advertising in the U.S., growing at 13%, already accounts for 28% of the overall advertising market which will grow only 3.2% this year).
In addition, relying on a segment of the advertising market which is completely dependent on ever-changing technology is a challenge in and of itself, as we have already seen in the ups and downs of display advertising and the shift from desktop to mobile. If some bright young entrepreneur (or a PhD student) finds tomorrow a way to transmit advertising to our brains without the help of devices and the Internet and we readily accept it in exchange for some new, can’t-live-without service, there will be no Google as we know it. Ditto if that proverbial kid in the garage will invent the real “disruption,” a new way to promote companies and their offerings, without what we have called “advertising” for centuries.
That may happen tomorrow or may not happen for a long time, so Page and Brin will continue to have the funds to fuel their ambitions. It’s just that now they will not have to deal at all with the day-to-day management of what has become for them a boring cash cow.
Brin has already done that for a number of years, focusing entirely on “moonshots.” But Page apparently wanted to prove to himself in 2011 (not to the world—he probably doesn’t care much about other people’s opinions) that he can also be a CEO of a large company and could make it re-invent itself. In this (the re-invention part) he completely failed. It may not be a coincidence that we learned of the final demise of Google’s grand social experiment, Page’s attempt to out-Facebook Facebook, just before the surprise Alphabet announcement. (It may also not be a coincidence that the announcement came on the 20th anniversary of When Larry Met Sergey, the first milestone in the official Google history timeline).
The failures are insignificant light of the history Page and Brin have made by giving millions of people around the world, in exchange for their data, very useful tools, at no cost. But brilliant inventions turned into commercial success, however, are not enough for the likes of Page and Brin and they never liked where the money supporting their free services came from, channeling (probably preceding) Jeff Hammerbacher’s sentiment: “The best minds of my generation are thinking about how to make people click ads.” Their version of a mid-life crisis is to remove themselves from their very successful one-trick advertising pony and immerse themselves in attempting to make very big history or Brontobyte history.
Page and Brin are sometimes mentioned—and explained—together with Amazon’s Jeff Bezos as the result of Montessori education (see here and here). But I think there is something much more important at the root of Page, Brin, and Bezos’s ambitions and successful enterprises. In the words of Harry Louis Sullivan, describing Chicago in 1875:
“Big” was the word. “Biggest” was preferred, and “the biggest in the world” was the braggart phrase on every tongue. Chicago had had the biggest conflagration “in the world.” It was the biggest grain and lumber market “in the world.” It slaughtered more hogs than any other city “in the world.” It was the greatest railroad center, the greatest this, and the greatest that… what they said was true; and had they said, in the din, we are the crudest, rawest, most savagely ambitious dreamers and would-be doers in the world, that also might be true… These men had vision. What they saw was real, they saw it as destiny.
Continuing an American tradition (how “unconventional”), Page, Brin, and Bezos saw “big” as their destiny. Page and Brin named their company after a very big number. Bezos chose the largest river in the world to stand for “the everything store.” But Bezos has taken a different route to world domination, one that is not depended on advertising and using us as the product, but on changing the way we buy and sell goods and services, inventing new ways to consume while driving down the cost of consumption. His one-trick pony, selling books online, has metamorphosed into selling everything, including computer services, serving as a platform for other sellers, creating content, designing devices, and more.
Page has said “especially in technology, we need revolutionary change, not incremental change, “and “I think as technologists we should have some safe places where we can try out new things and figure out the effect on society.” Bezos believes in incremental change and doesn’t talk much about Amazon’s impact on society. In about ten years, we should have a better idea of which approach—Alphabet’s or Amazon’s—has left a bigger and more positive impact on the world.
An earlier version of this psot was published on Forbes.com
A number of new reports on the Internet of Things (IoT) provide a fresh look at the state of this hot market and forecasts for its future impact on the world’s economy.
IDC discussed The Internet of Things Mid-Year Review at a webinar on July 23, including findings from a survey of 3,566 companies in North America. IDC defines IoT as “a network of uniquely identifiable ‘things’ that communicate without human interaction using IP connectivity.” Tata Consulting Services (TCS) issued a report titled The Internet of Things: The Complete Reimaginative Force, based on a survey of 3,764 executives worldwide. TCS defines the IoT as “smart, connected products.” The McKinsey Global Institute (MGI) published The Internet of Things: Mapping the value beyond the hype. MGI defines IoT as “sensors and actuators connected by networks to computing systems” and excludes “systems in which all of the sensors’ primary purpose is to receive intentional human input, such as smartphone apps.” Finally, Business Insider (BI) issued The Smart City report on IoT initiatives in cities worldwide.
The economic impact of the IoT will re-shape the world’s economy
The IoT has a total potential economic impact of $3.9 trillion to $11.1 trillion a year by 2025. At the top end, that level of value—including the consumer surplus—would be equivalent to about 11 percent of the world economy (MGI). The Internet of Things (IoT) market will expand from $780 billion this year to $1.68 trillion in 2020, growing at a CAGR of 16.9%. Sensors/modules and connectivity account for more than 50% of spending on IoT, followed by IT services at more than 25% and software at 15%. Traditional IT hardware accounts for less than 5% of total spending on IoT (IDC)
Investments in IoT technologies by cities worldwide will increase by $97 billion from 2015 to 2019. The cities’ IoT deployments will create $421 billion in economic value worldwide in 2019. That economic value will be derived from revenues from IoT device installations and sales and savings from efficiency gains in city services (BI).
There will be almost 30 billion of IoT devices in 2020
In 2015, 4,800 connected end points are added every minute. This number will grow to 7,900 by 2020. The installed base of the Internet of Things devices will grow from 10.3 billion devices in 2014 to 29.5 billion in 2020. 19 billion of these devices will be installed in North America in 2020 (IDC). The number of IoT devices installed in cities will increase by more than 5 billion in the next four years (BI).
The IoT will be primarily an enterprise market
In 2018, the IoT installed base will be split 70% in the enterprise and 30% in the consumer market, but enterprises will account for 90% of the spending (IDC). Business-to-business applications will probably capture more value—nearly 70 percent of it—than consumer uses, although consumer applications, such as fitness monitors and self-driving cars, attract the most attention and can create significant value, too (MGI).
Over the next few years, North America will still be the focal point for the IoT
The IoT has a large potential in developing economies, but it will have a higher overall value impact in advanced economies because of the higher value per use. However, developing economies could generate nearly 40 percent of the IoT’s value, and nearly half in some settings (MGI). 2020 will be a tipping point year for Asia, when it will become the geographical region with the largest installed base of IoT devices (IDC). North American companies will spend 0.45% of revenue this year on IoT initiatives, while European companies will spend 0.40%. Asia-Pacific companies will invest 0.34% of revenue in the IoT, and Latin American firms will spend 0.23% of revenue. North American and European companies are more frequently selling smart, connected products than are Asia-Pacific and Latin American companies (TCS).
The telecommunication industry leads other sectors in IoT investments
The Telecommunications, banking, utilities, and securities/investment services industries are the leading sectors investing in IoT in 2015 (IDC). In gaining benefits from the IoT, industrial manufacturers reported the largest average revenue increase from their IoT initiatives last year (29%), and they forecast they’d have the largest revenue increase from the IoT by 2018 (27% over 2015). Industrial manufacturers were also in the lead for using sensors and other digital technologies to monitor the products they sold to customers (with 40% of the companies doing so) (TCS).
IoT adoption is gaining momentum worldwide
36% of companies in North America have IoT initiatives in 2015 (IDC). 79% of companies worldwide already use IoT technologies, investing 0.4% of revenue on average. They expect their IoT budgets to rise by 20% by 2018 to $103 million (TCS).
Costs and customers are the key drivers of IoT investments
Lower operational costs and better customer service and support lead the list of significant drivers of current IoT initiatives. In large companies, business process efficiency/operations optimization and customer acquisition and/or retention also top the list (IDC). Companies with IoT programs in place reported an average revenue increase of 16% in 2014, in the areas of business where IoT initiatives were deployed. In addition, about 9% of firms had an average revenue increase of more than 60%.The biggest product and process improvements reported by companies were more customized offerings and tailored marketing campaigns, faster product improvements, and more effective customer service (TCS). Cities are adopting IoT technologies because they deliver a broad range of benefits for cities including reducing traffic congestion and air pollution, improving public safety, and providing new ways for governments to interact with their citizens (BI).
Security, culture change, determining priorities, and optimizing ROI are key IoT concerns
Security issues top the list of current barriers to IoT adoption (especially with larger companies), followed by funding the initial investment at the scale needed, determining the highest priority use cases, and changing business processes (IDC). identifying and pursuing new business and/or revenue opportunities that the IoT makes possible, and determining what data to collect, are key issues. Also important are getting managers and workers to change the way they think about customers, products, and processes, and having top executives who believe the IoT will have a profound impact and are willing to invest in it (TCS). Currently, most IoT data are not used. For example, on an oil rig that has 30,000 sensors, only 1 percent of the data are examined. That’s because this information is used mostly to detect and control anomalies—not for optimization and prediction, which provide the greatest value (MGI).
Microsoft leads the IoT market
The top 5 vendors mentioned as the IoT provider companies “plan to work with within the next 2 years” are: Microsoft, AT&T, Verizon, Cisco, and IBM. For large companies (more than 1000 employees), Microsoft and Cisco lead the list (IDC).
Originally published on Forbes.com
[youtube https://www.youtube.com/watch?v=y8zvkWWcUdA?rel=0]
Joi Ito: It gets back to open standards, interoperability, and a focus on non-IP-encumbered technology.
Jon Bruner: Everyone is looking for clarification on the rules on drones.
Renee DiResta: I don’t know that I feel that policy is really impeding anything right now. Maybe I’m wrong about that. I read through the FCC1 report and didn’t get the sense that there was anything [holding back the IoT] on a fundamental policy level.
Mark Hatch: Maybe it’s bandwidth-related: How do we handle the frequency and the radio waves and all the telecommunication requirements? This is a Qualcomm Technologies question maybe, along with the FCC. I may be completely wrong on that, but it’s one of the things I am curious about. How do you handle all of the communication data flow that’s going on and keep things from running into one another?
Mike Olson: The globe doesn’t have a data-privacy policy. Europe does broadly, but not in detail. In the United States, we have precisely two data-privacy laws: HIPAA,2 which protects your healthcare data, and the Fair Credit Reporting Act. Those are the only things that happen nationwide in terms of data privacy. Everything else is left to the states, and the states are pretty clueless about it. If we could elucidate policies and create laws that were uniform, it would be a lot easier for us to build and deploy these systems.
Dan Kaufman: If I had to guess, it’s the ability of people to protect their information. The Internet of Things is based on this fundamental ability to share information, and if we can’t do that in a safe and secure way, we’re going to need policies and laws so that everybody understands what’s within reason.
Cory Doctorow: I would reform the Digital Millennium Copyright Act, the 1998 statute whose language prohibits the circumvention of digital locks. I think with one step, we could make the future a better place. Ironically, the US Trade Representative has actually gone to all of America’s trading partners and gotten them to pass their own version of the Digital Millennium Copyright Act. So, every country in the world is liable to this problem. Now, the great news is that if the US stops enforcing it here, then all of those other countries will very quickly follow suit, because there’s money to be made in circumvention. The only reason to put a digital lock on is to extract maximum profits from your platform.
Tim O’Reilly: To me, policy makers need to not be trying to prevent the future from happening. They should be just policing bad actors. A good example is in healthcare. We are already producing vast reams of health data. HIPAA, the health-information privacy act, is a real obstacle. If you have a serious illness, you want to share your data with anybody who can help. You want to put your data together with other people’s data, because this collective amassing of data is one of the great keys to the future. And yet here we have these overreaching privacy laws that are going to make it difficult. So, punish bad actors—don’t prevent good actors.
Gartner just released its 2015 Hype Cycle for Emerging Technologies report. It’s our most reliable buzz bellwether, annually defining what’s in and what’s out. At the peak of inflated expectations just two years ago, Big Data was dethroned by the Internet of Things last year (but it was still estimated to be five to ten years from the Plateau of Productivity), only to completely disappear from Gartner’s hype radar this year (the 2010-2014 hype cycles are at the bottom of this post). Big data is out. So what’s in?
Gartner, August 2015
The Internet of Things is still at the top of the list, with self-driving cars (“autonomous vehicles”) ascending from pre-peak to the peak of the hype cycle. But there is an intriguing new category—“advanced analytics with self-service delivery”—sharing with them top billing. I guess one could hype all three in one emerging technology package of “The Internet of Autonomous Vehicles Delivering Advanced Analytics“ as the solution to all our transportation problems.
These technologies at the peak of the hype cycle also highlighted for me what’s missing from this year’s report. Given that the most hyped news out of Black Hat and Defcon conferences earlier this month were demonstrations of how to hack into cars (self-driving or not) and take control of them remotely, it is interesting that Gartner does not list any specific cybersecurity-related emerging technologies. It does mention, however, two general categories—“digital security” and “software-defined security” —both described as pre-peak, 5 to 10 years to the Plateau of Productivity. This may simply reflect the hype-less status of cybersecurity technologies. Given the daily news about data breaches, one could only hope that next year’s report will include some specific emerging solutions to what is promising to be a growing economic burden.
Another emerging technology showing promise last year—data science—has disappeared from this year’s report. It is replaced by “citizen data science” which Gartner thinks, as it did regarding data science last year, is only 2 to 5 years from the plateau. This could turn out to be the most optimistic prediction in this year’s report. A related category—machine learning—is making its first appearance on the chart this year, but already past the peak of inflated expectations. A glaring omission here is “deep learning,” the new label for and the new generation of machine learning, and one of the most hyped emerging technologies of the past couple of years.
It all boils down to what Gartner calls digital humanism: “New to the Hype Cycle this year is the emergence of technologies that support what Gartner defines as digital humanism—the notion that people are the central focus in the manifestation of digital businesses and digital workplaces.”
For the last 21 years Gartner has published the Hype Cycle report, of which Lee Rainie of the Pew Research Center has said: “There are sometimes disputes about where on the curve any individual innovation might rest, but there have been few challenges to the general trends it outlines.” I remember attending a Gartner Conference just before it started publishing this report and listening to a presentation by the analyst responsible at the time for Gartner’s emerging technologies research. He started his presentation by declaring: “Those who live by the crystal ball, die eating broken glass.”
The charts below show the evolution of Gartner’s crystal ball over the last five years and allow us to track the hype around Big Data over that period. It made its first appearance in August of 2011 as “‘Big data’ and extreme information processing and management” with 2 to 5 years to the Plateau of Productivity,then just made it into the Peak of Inflated Expectations in 2012, then rose to the top of most hyped technologies (together with consumer 3D printing and Gamification) in 2013, then started to descend into the Trough of Disillusionment in 2014, only to completely vanish in 2015. I guess Big Data is no longer an emerging technology.
Gartner Hype Cycle 2014
Gartner, August 2014
Gartner Hype Cycle 2013
Gartner, August 2013
Gartner Hype Cycle 2012
Gartner, August 2012
Gartner Hype Cycle 2011
Gartner, August 2011
Gartner Hype Cycle 2010
Gartner, August 2010
An earlier version of this post was published on Forbes.com
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