How to Establish Startup Incubators and Ensure Successful Exits by Jerusalem Venture Partners

Gadi Tirosh, Jerusalem Venture Partners

Gadi Tirosh, Jerusalem Venture Partners

In the first quarter of 2015, 166 Israeli high-tech companies raised $994 million, a 48 percent increase year-over-year, according to research firm IVC. “We are on a positive slope right now,” Gadi Tirosh told me recently, “which is fine, as long as it’s not over-hyped. At the end of the day, what drives the numbers are significant outcomes.”

Tirosh is very familiar with the “significant outcomes” that have produced new record numbers for Israeli entrepreneurs and venture capitalists. He is Managing Partner at Jerusalem Venture Partners (JVP), one of Israel’s leading venture capital firms, established in 1991. The founder, Erel Margalit, is now a member of the Israeli Parliament; the other managing partners currently are Kobi Rozengarten and Raffi Kesten.

JVP was the lead investor in computer security startup CyberArk, one of the best-performing IPOs of 2014 and where Tirosh is serving as Chairman.

“Having an outcome like CyberArk,” says Tirosh, “creates a virtuous cycle. It makes people understand that the prize at the end might be very very significant.” This may explain why we have seen in recent years more IPOs by Israeli startups. The general tendency for years has been to sell quickly even before reaching any meaningful revenues (I found out about 10 years ago that the word “exit,” as in a successful sale of a startup, has become widely used by Israelis, including those not working in high-tech). Tirosh points out, however, that while “CyberArk gives everybody in the industry something to wish for, you have to be opportunistic and if there are good outcomes on the way, that’s a judgement call you need to make.”

“Having an outcome like CyberArk,” says Tirosh, “creates a virtuous cycle. It makes people understand that the prize at the end might be very very significant.” This may explain why we have seen in recent years more IPOs by Israeli startups. The general tendency for years has been to sell quickly even before reaching any meaningful revenues (I found out about 10 years ago that the word “exit,” as in a successful sale of a startup, has become widely used by Israelis, including those not working in high-tech). Tirosh points out, however, that while “CyberArk gives everybody in the industry something to wish for, you have to be opportunistic and if there are good outcomes on the way, that’s a judgement call you need to make.”

JVP made recently just such a judgment call when it sold CyActive, a startup fresh from JVP’s cyber security incubator (more on this later), to PayPal (for a reported $60 million). “It absolutely made sense for the founders and ourselves to integrate this very innovative technology into a bigger home,” says Tirosh.

So what’s hot in cyber security today? One way JVP knows the answer to this question is by tracking the deal flow in 17 different segments of the security market (see chart below). In addition to established areas of computer security, they track new and emerging technologies, knowing that entrepreneurs look to target security gaps created by the introduction of these technologies.

GRC=Government Relations Compliance; SIEM/DSS= Security Incidence and Events Management/ Decision Support System

GRC=Government Relations Compliance; SIEM/DSS= Security Incidence and Events Management/ Decision Support System

For example, says Tirosh, “the move to the cloud creates a whole new set of security challenges.” Your data is in the hands of a third-party and your beloved single-point-of-entry that you used to protect nicely with a firewall has just vanished. How do you protect your data when it is processed on servers located around the world that are provisioned on-the-fly? You need a new security paradigm, says Tirosh, and JVP has invested in GreenSQL, a startup offering security software that protects both traditional, on-premise databases and databases in the cloud.

New technologies create new security headaches, but they also provide new solutions. Take for example big data analytics. One of the startups in JVP’s portfolio, ThetaRay, has developed a unique approach to anomaly detection, using sophisticated algorithms to protect against unknown threats.

Traditional approaches for detecting credit fraud, for example, do not scale because they rely on pinpointing deviations from a pre-defined set of rules.  “As the system grows, you end up writing more and more rules, making it impossible to manage,” says Tirosh. “Not only that,” he adds, “once you define the set of rules, you actually define the next hack. You identify for the hackers what are the rules that they need to circumvent.”

Rule-based systems create a lot of false positives, issuing alerts for incidents that are not real fraud or threat. “The problem with dealing with so many false positives,” says Tirosh, “is that they don’t let the operators get to the true positives. It is well documented that with the Target breach, all the alarms went off. But the problem was that there were simply too many alarms.”

In contrast, ThetaRay’s algorithms do not assume anything about the domain they’re analyzing. They are derived from academic research into building a multi-dimensional, even “hyper-dimensional,” data matrix. The more data is analyzed, the better they get at detecting anomalies, knowledge that is combined with the domain expertise of the customer to identify the true positives, the real threats. By analyzing 250 million transactions, ThetaRay’s algorithms identified, in a matter of hours, fraud incidents worth 10 million euros, incidents that were not detected by the existing rules-based system, says Tirosh.

ThetaRay got its start in a JVP incubator. JVP is unique in that it’s a venture capital firm that runs two startup incubation programs. Much talked-about Silicon Valley-based incubators, such as Y Combinator (which bills itself as having “created a new model for funding early stage startups”), are just the best-known examples of some 1,250 business incubators in the U.S. and 7,000 around the world (2012 numbers from the National Association of Business Incubators). Typically, sponsors of incubators are academic institutions (about a third of U.S. business incubators) or economic development organizations (about a quarter).

JVP operates two incubators, JVP Media Labs in the areas of media and storage (in Jerusalem) and JVP Cyber Labs, in the area of cyber security (in Beer Sheva). It is not an academic institution or an economic development organization, and unlike Y Combinator, JVP does not focus only on early stage startups, so why incubate?

“We are the only VC firm running an incubator within the fund itself,” says Tirosh. One good reason to do that is that the Israeli government adds $500,000 as a risk-free loan to the first $100,000 JVP invests.  “So we have a pool of at least $600,000,”says Tirosh, “to experiment with new ideas and new teams and we can make these decisions pretty rapidly.” In that sense, it’s a unique economic development model, where the government invests and takes risks but lets private sector experts manage and nurture.

This does not explain, however, why other Israeli VC firms are not taking advantage of the State of Israel’s incubator program, sponsored by the office of the Chief Scientist. Tirosh expounds on JVP’s philosophy:  “It’s the question of what do you do with the companies that succeed and graduate out of the incubator. Having it as part of the fund allows us to fund the entrepreneurs that graduate the incubator, people we know really well. We’ve been growing the company together with them.”

Tirosh says JVP’s success in investing in all stages of the life of a startup is due to the operational background of many of the partners: “It requires a lot of involvement. You need to make sure you like it. Also, you need to be relatively good at it. Most VCs take a much more hands-off approach.”

For the entrepreneurs, JVP’s approach promises a significant follow-on investment from the main fund if and when they graduate the incubator. “It helps them build a longer-term view,” says Tirosh, “and it helps them raise money as they come out of the incubator,” having JVP’s stamp of approval.

JVP Cyber Labs was established in 2014 with the goal of identifying, nurturing and building the next wave of cyber security companies. It is located at the Beer Sheva Advanced Technologies Park, in close proximity to Ben-Gurion University (which has a leading computer science department with a special focus in computer security), the IDF’s elite computer units, and R&D centers of many multinational companies. This could be the highest concentration in the world of cyber security expertise per square foot.

“We had our Jerusalem incubator running for a while,” Tirosh told me. “It has been successful and we got quite a lot of requests to replicate it in other places around the world. None of us wanted to re-locate so we were looking to replicate it here in Israel. Since we’ve opened the Cyber incubator in early 2014, we’ve made six investments and we had our first exit when we sold CyActive to PayPal.“

And many more exits to come, no doubt.

Originally posted on Forbes.com

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Chief Digital Officers (CDOs): How Many and How Much they Make?

CDOs

CDOs_Industry

eMarketer:

The chief digital officer (CDO) role emerged alongside the digital transformation, and companies are rapidly making room for the position. In a report released in May 2015, The CDO Club estimated that the number of CDOs worldwide would double between 2014 and 2015, from 1,000 to 2,000…. Other research also suggests that more companies are relying on CDOs—or similar professionals—to navigate the digital landscape. When a January 2015 study by Accenture asked executives worldwide about their progress in leveraging digital governance and decision-making, 80% of respondents said they had a CDO or comparable role to oversee the use of digital technologies.

To this we can add research findings from Mondo, a digital marketing and technology resourcing provider. In the recent National Digital Marketing Salary Guide. Mondo reported that the Chief Digital Officer garners the highest salary among digital marketing executives, with $301,000 at the high end and $156,000 at the low end.

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The Internet of Things (Infographic)

bor01

Source: Data Science Central

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The Data Market to Nearly Double in Size by 2019

DataMarket

Consisting of data platforms, data management, analytics, and data mining the Total Data Market is expected to nearly double in size, from $60bn in 2014 to $115bn in 2019. The forecast is based on 451 Research’s new Total Data Market Monitor service, which presents data, generated via a bottom-up analysis, of 202 vendors that participate across the nine Total Data segments the company tracks.  Specifically, 451 Research tracks 56 Operational Database participants, 26 in the Analytic Database market, 72 within the Reporting and Analytics segment, 41 Data Management vendors, 11 Performance Management vendors, 11 Event/Stream Processing vendors, 9 Distributed Data Grid/Cache vendors, 25 Hadoop vendors and 15 Search vendors.

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Skills for Big Data Jobs and Careers (Infographic)

Infographic - The Emerging Skillsets of the Data Revolution

Source: ObjectRocket

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The Internet of Things is Social Media for Machines (Video)

[youtube https://www.youtube.com/watch?v=qWR32v5uaI8?rel=0]

A panel discussion at the Milken Institute Global Conference 2015, moderated by Michael Schrage, Research Fellow, MIT Sloan Initiative on the Digital Economy. Panelists: Marc Goodman, Author, ?Future Crimes?; Chair for Policy, Law and Ethics, Singularity University; Alex Hawkinson, Founder and CEO, SmartThings; Bridget Karlin, Managing Director, IoT Strategy and Technology Office, Internet of Things Group, Intel Corp.; Gary Shapiro, President and CEO, Consumer Electronics Association.

Schrage: “The glib way of thinking about the Internet of Things is social media for machines.”

Marc Goodman: “The concept of my refrigerator tweeting, snapchatting, or sexting is kind of disturbing.”

Shapiro: “The Internet spreads information; the Internet of Things is actually actionable information.”

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Why The Future Is Not What It Used To Be

by alex-xs

by alex-xs

The IEEE Computer Society published in March a report titled “What Will Our World Look Like in 2022?” It identified 23 technology areas that we can expect to disrupt the state-of-the-art. These range from medical robotics to big data and analytics to photonics to 3D integrated circuits to quantum computing.

The unifying theme for all these technologies is “seamless intelligence,” where everything is connected through ubiquitous networks and interfaces. “We project that by 2022,” the authors of the report say, “society will advance so that intelligence becomes seamless and ubiquitous for those who can afford and use state-of-the-art information technology.”

The IEEE report is a bit different from similar attempts at predicting the future because it comes from technologists, some in academia but others who work at corporate research labs, and is based in part on a survey of members of the IEEE Computer Society. Typically, predictions are the stock-in-trade of think tanks and research firms. Last year, for example, the McKinsey Global Institute published “Disruptive technologies: Advances that will transform life, business, and the global economy,” identifying 12 technologies that “could drive truly massive economic transformations and disruptions in the coming years.” Earlier this year, Juniper Research published “The World in 2020: A Technology Vision,” identifying 11 key technologies that it believes “will become the most disruptive by 2020.”

Beyond the use of the word “disruptive,” there are other commonalities between the three reports. Robotics and drones, 3D printing, the Internet of Things and wearables, self-driving cars, and cloud computing appear in all or at least two of the reports. But, for the most part, there is not a whole lot of agreement on the disruptive technologies of the future. Photonics, real-time translation, and renewable energy, for example, appear in only one of the reports.

The IEEE report opens with the famous Yogi Berra quote: “It’s tough to make predictions, especially about the future.” In the rest of this post, I will discuss three reasons why.

  1. Innovations that have made a strong impact on us in recent times obscure more important recent innovations.

The first item on The New York Times’ list of greatest inventions of the 19th century, published in 1899, was friction matches, introduced in their modern form in 1827. “For somebody to whom the electric light was as recent an innovation as the VCR is to us, the instant availability of fire on demand had indeed been one of the greatest advances of the century,” wrote Frederick Schwartz in 2000 in Invention & Technology. Which invention of the last 100 years or even 10 years is overshadowing an even more important invention of recent years?

  1. The road taken is no less important than the end result.

Another difficulty in predicting what the world will look like in just 5 or 7 years from now, is that some predictions eventually become a reality but they still miss altogether exactly how we are going to get there. Often, this is the most important (and practical) part of the prediction. To paraphrase Lewis Carroll, if you know where you are going, it matters a lot which road you are taking.

Many commentators writing this month about the 50th anniversary of Gordon Moore’s article charting a future course for the semiconductor industry (what became to be known as “Moore’s Law”), mentioned his predictions regarding home computers and “personal portable communications equipment.” But they ignored Moore’s prediction that “the biggest potential lies in the production of large systems. In telephone communications, integrated circuits in digital filters will separate channels on multiplex equipment. Integrated circuits will also switch telephone circuits and perform data processing.”

Moore was right that integrated circuits will have an impact on large systems but failed to see that “the biggest potential” of the constant and predictable miniaturization he forecasted will be in smaller and smaller devices, in ubiquitous computing. In 1965, it was difficult to see that centralized systems will be replaced by distributed, anywhere computing. Which is why Moore added to his use of the term “home computers”—“or at least terminals connected to a central computer.”

  1. We extrapolate from the present and ignore or misunderstand non-technological factors.

Many predictions are what the forecasters want the future to be or simply an extension of what they are familiar and comfortable with. I have in my files a great example of the genre, a report published in 1976 by the Long Range Planning Service of the Stanford Research Institute (SRI), titled “Office of the Future.”

The author of the report was a Senior Industrial Economist at SRI’s Electronics Industries Research Group, and a “recognized authority on the subject of business automation.” His bio blurb indicates that he “also worked closely with two of the Institute’s engineering laboratories in developing his thinking for this study. The Augmentation Research Center has been putting the office of the future to practical test for almost ten years… Several Information Science Laboratory personnel have been working with state-of-the-art equipment and systems that are the forerunners of tomorrow’s products. The author was able to tap this expertise to gain a balanced picture of the problems and opportunities facing office automation.”

And what was the result of all this research and analysis? The manager of 1985, the report predicted, will not have a personal secretary. Instead he (decidedly not she) will be assisted, along with other managers, by a centralized pool of assistants (decidedly and exclusively, according to the report, of the female persuasion). He will contact the “administrative support center” whenever he needs to dictate a memo to a “word processing specialist,” find a document (helped by an “information storage/retrieval specialist”), or rely on an “administrative support specialist” to help him make decisions.

Of particular interest is the report’s discussion of the sociological factors driving the transition to the “office of the future.” Forecasters often leave out of their analysis the annoying and uncooperative (with their forecast) motivations and aspirations of the humans involved. But this report does consider sociological factors, in addition to organizational, economic, and technological trends. And it’s worth quoting at length what it says on the subject:

“The major sociological factor contributing to change in the business office is ‘women’s liberation.’ Working women are demanding and receiving increased responsibility, fulfillment, and opportunities for advancement. The secretarial position as it exists today is under fire because it usually lacks responsibility and advancement potential. The normal (and intellectually unchallenging) requirements of taking dictation, typing, filing, photocopying, and telephone handling leave little time for the secretary to take on new and more demanding tasks. The responsibility level of many secretaries remains fixed throughout their working careers. These factors can negatively affect the secretary’s motivation and hence productivity. In the automated office of the future, repetitious and dull work is expected to be handled by personnel with minimal education and training. Secretaries will, in effect, become administrative specialists, relieving the manager they support of a considerable volume of work.”

Regardless of the women’s liberation movement of his day, the author could not see beyond the creation of a 2-tier system in which some women would continue to perform dull and unchallenging tasks, while other women would be “liberated” into a fulfilling new job category of “administrative support specialist.”  In this 1976 forecast, there are no women managers.

But this is not the only sociological factor the report missed. The most interesting sociological revolution of the office in the 1980s – and one missing from most (all?) accounts of the PC revolution – is what managers (male and female) did with their new word processing, communicating, calculating machine. They took over some of the “dull” secretarial tasks that no self-respecting manager would deign to perform before the 1980s.

This was the real revolution: The typing of memos (later emails), the filing of documents, the recording, tabulating, and calculating. In short, a large part of the management of office information, previously exclusively in the hands of secretaries, became in the 1980s (and progressively more so in the 1990s and beyond) an integral part of managerial work.

This was very difficult, maybe impossible, to predict. It was a question of status. No manager would type before the 1980s because it was perceived as work that was not commensurate with his status. Many managers started to type in the 1980s because now they could do it with a new “cool” tool, the PC, which conferred on them the leading-edge, high-status image of this new technology. What mattered was that you were important enough to have one of these cool things, not that you performed with it tasks that were considered beneath you just a few years before.

What was easier to predict was the advent of the PC itself. And the SRI report missed this one, too, even though it was aware of the technological trajectory: “Computer technology that in 1955 cost $1 million, was only marginally reliable, and filled a room, is now available for under $25,000 and the size of a desk. By 1985, the same computer capability will cost less than $1000 and fit into a briefcase.”

But the author of the report (just like Gordon Moore in 1965) could only see a continuation of the centralized computing of his day. The report’s 1985 fictional manager views documents on his “video display terminal” and the centralized (and specialized) word processing system of 1976 continues to rule the office ten years later.

This was a failure to predict how the computer that will “fit into a briefcase” will become personal, i.e., will take the place of the “video display terminal” and then augment it as a personal information management tool. And the report also failed to predict the ensuing organizational development in which distributed computing replaced or was added to centralized computing.

Yes, predicting is hard to do. But compare forecasters and “analysts” with another human subspecies: Entrepreneurs.  Entrepreneurs don’t predict the future; they make it happen.

A year before the SRI report was published, in January 1975, Popular Electronics published a cover story on the first do-it-yourself PC or what they called  “first minicomputer kit,” the Altair 8800. Paul Allen and Bill Gates, Steve Jobs and Steve Wozniak, founded their companies around the time the SRI report was published not because they read reports about the office of the future. They simply imagined it.

Update: Gordon Moore quoted in VentureBeat “Once I made a successful prediction, I avoided making another.” and “I wish I had seen the applications earlier. To me the development of the Internet was a surprise. I didn’t realize it would open up a new world of opportunities.”

Originally published on Forbes.com

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ABI Research: 7.7 Million Autonomous Truck Fleets to Ship by 2025

AutoamtedTrucks

ADAS=Advanced Driver Assistance Systems

Truck platoons are the most imminently anticipated application of highly automated driving in commercial vehicles. A fusion of forward-looking radar and V2V communication enable fleets of trucks to safely maneuver with a short distance between vehicles. The reduction in aerodynamic drag for following vehicles, and buildup of pressure behind the lead vehicle yields impressive fuel efficiencies, with various tests reporting convoy savings of between 5% and 10%. “With most fleet operators attributing some 30 to 40% of their operating costs to fuel expenditure, the savings presented by platooning are significant,” comments James Hodgson, Research Analyst, ABI Research.

As technology progresses and regulations adapt to accommodate greater vehicle automation, further benefits to fleet operators will come in the shape of labor productivity gains and better asset utilization. Currently, solutions from pioneers such as Peloton Technology require active intervention from the following driver to keep the vehicle within the lane of travel, but in the future the driver of the lead vehicle could be in sole control of all vehicles in the convoy; allowing following drivers to rest, or eliminating the need for them altogether.

Free ADAS and Active Safety Webinar on May 21, 2015 at 11 am ET for a deeper look at ABI Research’s commercial trucking coverage and the convergence of ADAS, telematics, autonomous driving, and big data,

These findings are part of ADAS and Autonomous Driving Technology in Trucks and Commercial Vehicles, a report from ABI Research’s Automotive Safety and Autonomous Driving and Commercial Vehicle Telematics Market Research.

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Data Science on Cloud Foundry (Video)

[youtube https://www.youtube.com/watch?v=n95hCVvuPKQ?rel=0]

Data Scientists frequently need to create applications that enable interactive data exploration, deliver predictive analytics APIs or simply publish results. Cloud Foundry provides an ideal platform for data scientists by making it easy to quickly deploy data driven apps backed by a variety of data stores.

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Big Data Market 2011-2026, From $7.6 to $84.69 Billion

BigData_Wikibon2015

Wikibon: For the calendar year 2014, the Big Data market – as measured by revenue associated with the sale of Big Data-related hardware, software and professional services – reached $27.36 billion, up from $19.6 billion in 2013. While growing significantly faster than other enterprise IT markets, the Big Data market’s overall growth rate slowed year-over-year from 60% in 2013 to 40% in 2014. This is to be expected in an emerging but quickly maturing market such as Big Data, and Wikibon does not believe this slightly slower growth rate indicates any structural market issues.

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