The Rush to Deliver Meals to Our Homes


CB Insights:

Food delivery is starting to get a little crowded. One-third of the companies in the food-delivery industry received their first round of funding in just the last year. Traditional VCs, celebrity chefs, and high-profile angel investors have all invested in these startups focused on making at-home dining as convenient as possible.

Successes like Blue Apron ($2B valuation), DoorDash ($600M), Postmates ($400M), and Munchery ($300M), have quickly reached big valuations, encouraging even more new competitors.

To date, 25 US-based companies are following the same two basic business models: delivering either prepared meals or “cooking boxes,” with ingredients and instructions. We plotted each of these companies’ first funding round on a timeline, starting with Postmates and Gobble, which each raised in May 2011, and ending with Green Chef, which raised a $15.5M round of financing in April from New Enterprise Associates and others.

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AWS, Google, Dominate New IT Landscape: Digital Accelerators vs. Digital Inhibitors


HT: @ValaAfshar

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Creative Destruction and the ‘Uber Effect’


CB Insights:

We used CB Insights’ valuation data to look at how the rise of Uber’s valuation correlates with the market capitalization of Medallion Financial Corp (NASDAQ: TAXI). Medallion Financial is a publicly-traded company that originates, acquires, and services loans used to purchase taxi medallions in several large US urban markets that Uber is also active in, including New York. We charted the stock price of TAXI versus the valuations for many of Uber’s rounds since 2010.

We found that TAXI has also been hammered by an “Uber Effect,” with its price down even more than the decline seen by New York City medallions. TAXI’s stock price is down nearly 49% since Uber raised its breakout $258M Series C at a $3.5B valuation. (The NASDAQ is up ~26% in the same time period.)

Uber’s valuation is up over 13x.

Mark J. Perry at the American Enterprise Institute:



In 1942, economist Joseph Schumpeter described “creative destruction” as a “process of industrial mutation that incessantly revolutionizes the economic structure from within, incessantly destroying the old one, incessantly creating a new one.” There probably hasn’t been a better example of Schumpeterian creative destruction in the last decade or more than the recent ascendance of app-based ride-sharing services like Uber (and Lyft, Sidecar, Gett, Via, etc.)  challenging traditional, legacy taxi cartels in cities like New York, San Francisco, Chicago and more than 160 other US cities. Market-based evidence of the gale of creative destruction in the transportation industry is displayed in the two charts above. The top chart above shows how the increasing popularity of ride-sharing apps like Uber has caused the price of New York City individual taxi medallions to collapse by at least 37%, from a peak of more than $1 million in August 2013 to only about $650,000 in recent months (based on advertised asking prices here, not actual sales).

Further evidence of the “Uber effect” is displayed in the bottom chart above, showing the collapse in the stock price of Medallion Financial Corporation, from $16.45 in November 2013 to below $7 per share in the last few days. Medallion Financial Corporation (NASDAQ: TAXI) is a NYC-based specialty finance company that originates, acquires, and services loans that finance taxicab medallions. Just as the sky-high taxi medallion prices have been significantly eroded due to competition from the upstart ride-sharing services, so has the value of Medallion Financial Corporation’s stock price been significantly dropping. After tracking the SP&500 Index closely for many decades, the share price of Medallion Financial has fallen by a whopping 58% from its November 2013 peak, during a time when the S&P 500 has increased by 7.1%.

As the traditional, legacy taxi industry continues to collapse under the Schumpeterian forces of market disruption, the taxi cartels like the one in NYC are asking for taxpayer bailouts, or at least taxpayer-supported guarantees for taxi medallion loans. Consumers are the obvious winners from the creative destruction in the transportation industry – we now have more choice, better and faster service, friendlier drivers, cleaner cars, and maybe most importantly — lower prices. Traditional taxi drivers and medallion owners, after being protected from competition by government regulations for many generations, are the obvious losers from the “Uber effect.” Medallion prices will continue to fall as the taxi cartels continue to crumble and collapse.

NPR Planet Money: Listen to Episode 643, July 31, 2015, on Gene Freidman, the “Taxi King” and how his empire is starting to crumble. Also, “Why Does A Taxi Medallion Cost $1 Million?” from 2011.

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10 Predictions for Digital and IT Transformation: Gartner


Gartner released today its top predictions for “the digital future… an algorithmic and smart machine-driven world where people and machines must define harmonious relationships”:

1)    By 2018, 20 percent of business content will be authored by machines.
Technologies with the ability to proactively assemble and deliver information through automated composition engines are fostering a movement from human- to machine-generated business content. Data-based and analytical information can be turned into natural language writing using these emerging tools. Business content, such as shareholder reports, legal documents, market reports, press releases, articles and white papers, are all candidates for automated writing tools.

2)    By 2018, six billion connected things will be requesting support.
In the era of digital business, when physical and digital lines are increasingly blurred, enterprises will need to begin viewing things as customers of services — and to treat them accordingly. Mechanisms will need to be developed for responding to significantly larger numbers of support requests communicated directly by things. Strategies will also need to be developed for responding to them that are distinctly different from traditional human-customer communication and problem-solving. Responding to service requests from things will spawn entire service industries, and innovative solutions will emerge to improve the efficiency of many types of enterprise.

3)    By 2020, autonomous software agents outside of human control will participate in five percent of all economic transactions.
Algorithmically driven agents are already participating in our economy. However, while these agents are automated, they are not fully autonomous, because they are directly tethered to a robust collection of mechanisms controlled by humans — in the domains of our corporate, legal, economic and fiduciary systems. New autonomous software agents will hold value themselves, and function as the fundamental underpinning of a new economic paradigm that Gartner calls the programmable economy. The programmable economy has potential for great disruption to the existing financial services industry. We will see algorithms, often developed in a transparent, open-source fashion and set free on the blockchain, capable of banking, insurance, markets, exchanges, crowdfunding — and virtually all other types of financial instruments

4)    By 2018, more than 3 million workers globally will be supervised by a “robo-boss.”
Robo-bosses will increasingly make decisions that previously could only have been made by human managers. Supervisory duties are increasingly shifting into monitoring worker accomplishment through measurements of performance that are directly tied to output and customer evaluation. Such measurements can be consumed more effectively and swiftly by smart machine managers tuned to learn based on staffing decisions and management incentives.

5)    By year-end 2018, 20 percent of smart buildings will have suffered from digital vandalism.
Inadequate perimeter security will increasingly result in smart buildings being vulnerable to attack. With exploits ranging from defacing digital signage to plunging whole buildings into prolonged darkness, digital vandalism is a nuisance, rather than a threat. There are, nonetheless, economic, health and safety, and security consequences. The severity of these consequences depend on the target. Smart building components cannot be considered independently, but must be viewed as part of the larger organizational security process. Products must be built to offer acceptable levels of protection and hooks for integration into security monitoring and management systems.

6)    By 2018, 45 percent of the fastest-growing companies will have fewer employees than instances of smart machines.
Gartner believes the initial group of companies that will leverage smart machine technologies most rapidly and effectively will be startups and other newer companies. The speed, cost savings, productivity improvements and ability to scale of smart technology for specific tasks offer dramatic advantages over the recruiting, hiring, training and growth demands of human labor. Some possible examples are a fully automated supermarket or a security firm offering drone-only surveillance services. The “old guard” (existing) companies, with large amounts of legacy technologies and processes, will not necessarily be the first movers, but the savvier companies among them will be fast followers, as they will recognize the need for competitive parity for either speed or cost.

7)    By year-end 2018, customer digital assistant will recognize individuals by face and voice across channels and partners.
The last mile for multichannel and exceptional customer experiences will be seamless two-way engagement with customers and will mimic human conversations, with both listening and speaking, a sense of history, in-the-moment context, timing and tone, and the ability to respond, add to and continue with a thought or purpose at multiple occasions and places over time. Although facial and voice recognition technologies have been largely disparate across multiple channels, customers are willing to adopt these technologies and techniques to help them sift through increasing large amounts of information, choice and purchasing decisions. This signals an emerging demand for enterprises to deploy customer digital assistants to orchestrate these techniques and to help “glue” continual company and customer conversations.

8)    By 2018, two million employees will be required to wear health and fitness tracking devices as a condition of employment.
The health and fitness of people employed in jobs that can be dangerous or physically demanding will increasingly be tracked by employers via wearable devices. Emergency responders, such as police officers, firefighters and paramedics, will likely comprise the largest group of employees required to monitor their health or fitness with wearables. The primary reason for wearing them is for their own safety. Their heart rates and respiration, and potentially their stress levels, could be remotely monitored and help could be sent immediately if needed. In addition to emergency responders, a portion of employees in other critical roles will be required to wear health and fitness monitors, including professional athletes, political leaders, airline pilots, industrial workers and remote field workers.

9)    By 2020, smart agents will facilitate 40 percent of mobile interactions, and the postapp era will begin to dominate.
Smart agent technologies, in the form of virtual personal assistants (VPAs) and other agents, will monitor user content and behavior in conjunction with cloud-hosted neural networks to build and maintain data models from which the technology will draw inferences about people, content and contexts. Based on these information-gathering and model-building efforts, VPAs can predict users’ needs, build trust and ultimately act autonomously on the user’s behalf.

10) Through 2020, 95 percent of cloud security failures will be the customer’s fault
Security concerns remain the most common reason for avoiding the use of public cloud services. However, only a small percentage of the security incidents impacting enterprises using the cloud have been due to vulnerabilities that were the provider’s fault. This does not mean that organizations should assume that using a cloud means that whatever they do within that cloud will necessarily be secure. The characteristics of the parts of the cloud stack under customer control can make cloud computing a highly efficient way for naive users to leverage poor practices, which can easily result in widespread security or compliance failures. The growing recognition of the enterprise’s responsibility for the appropriate use of the public cloud is reflected in the growing market for cloud control tools. By 2018, 50 percent of enterprises with more than 1,000 users will use cloud access security broker products to monitor and manage their use of SaaS and other forms of public cloud, reflecting the growing recognition that although clouds are usually secure, the secure use of public clouds requires explicit effort on the part of the cloud customer.

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GE’s Internet of Things (IoT): The software platform, Predix, and new business model, GE Digital (Video)

On September 14, 2015, GE announced the creation of GE Digital, “a transformative move that brings together all of the digital capabilities from across the company into one organization.” It integrates GE’s Software Center, the expertise of GE’s global IT and commercial software teams, and the industrial security strength of Wurldtech. This “new model” (not a business unit, apparently) is led by Bill Ruh, chief digital officer.

In the video above, Ruh talked briefly about GE Digital, preceded by GE Digital’s CTO Harel Kodesh talking about Predix, GE’s software platform for the “Industrial Internet” or IoT.

See also Internet Of Things (IoT) News Roundup

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What is Hadoop?


HT: @KirkDBourne

See also:

5 Highlights Of The First And Largest Hadoop Maturity Survey

Hadoop Bubble Watch: The Bubble Quivers As Hortonworks Misses

The End Of The Hadoop Bubble?

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Hadoop Maturity Survey: Key Findings

Results of the largest worldwide survey to date of Hadoop users were released recently by AtScale, which was assisted in this project by Cloudera, MapR and Tableau. The answers from more than 2,100 participants provide insights into the current and future use of Hadoop and where and how it brings business value to the companies investing in this foundational big data technology.

“Enterprises today have reached a new stage where they are worried about providing access to Hadoop to business users,” says Bruno Aziza, AtScale’s Chief Marketing Officer. “Self-service is the next big thing for Hadoop and the companies that understand how to deliver on the promise of democratizing access to the Data Lake will win.”

So what’s up with Hadoop?

Focusing on revenues, providing self-service, and an executive mandate are key to getting value from Hadoop

Hadoop DriversCompanies that deploy Hadoop to drive revenues are about 30% more likely to achieve value from Hadoop than those who are looking to cut costs. Those that provide business users with self-service access to Hadoop are nearly 50% more likely to realize a tangible value. The presence of an “executive mandate” (i.e., telling people they are going to do Hadoop rather than just “sponsoring” it) boosts an enterprise’s chances of deriving value from Hadoop by 20%.


Hadoop_Exec Mandate

The more you invest in Hadoop, the likelier you are to get value out of it

72% of the enterprises surveyed that have deployed over 500 nodes are getting value out of Hadoop, but only 33% of those with up to 10 nodes say they got value out of their investment. 49% of all survey participants say they are already deriving tangible value from Hadoop and 94% think they will continue or start to get value from Hadoop.

Hadoop is moving to the mainstream of enterprise IT

In its early days, Hadoop was talked about (or dismissed) as “replacement for tape,” a better-performing data archiving solution. As its capabilities and ecosystem have evolved, it is now maturing into a mainstream enterprise data management tool.

76% of current Hadoop users plan on doing more with it over the next 3 months and almost half of those who haven’t yet deployed Hadoop say they will do so in the next 12 months. While 26% describe Hadoop as “experimental,” 47% regard it as “strategic” and 15% say it is “game changing.”


Business intelligence is rising again

When big data and data science took over the airwaves five years ago, Hadoop rose as a technology of choice for two specialized workloads: The traditional Extract-Transform-Load (ETL, the process by which data is taken from different sources, formatted, and uploaded to a data warehouse or database) for the folks in IT dealing with unstructured data, and the new data science process used by the new breed of data scientists to find new insights in the data, somewhat overshadowing the business analysts performing traditional business intelligence tasks.

This is reflected in where Hadoop has been deployed so far. 74% of the companies participating in the survey that have already deployed Hadoop are using it for ETL, 62% for data science and 65% for business intelligence.

In another indication of the mainstreaming of Hadoop, however, business intelligence may rise again to take advantage of the new new thing.  The picture is somewhat different for those that have not yet deployed Hadoop, with 69% intending to use it for business intelligence, 56% for data science and only 51% for ETL.

Hadoop_Tipping Point

Online companies are Hadoop-savvy, financial firms not so much

As could be expected, the companies that make their living on that vast repository of unstructured data, the World Wide Web, are ahead of other sectors in Hadoop maturity.  Surprisingly, the financial services sector which is typically the first to invest in and learn new enterprise IT tools and applications did not do well in terms of Hadoop maturity in this survey. It may well be that financial services companies hold themselves to very high standards or that the survey captured many small financial services firms that do not have the same resources as their larger brethren.


As ones and zeros are eating the world and enterprises worldwide are analyzing private and public data to find new sources of revenues and new ways to streamline operations, time-to-access (for data) and time-to-value (for analysis) are shrinking rapidly. Hadoop and similar big data tools are graduating into an enterprise IT environment where the underlying technologies merge to collectively provide more data and better analytical tools to more employees.

Originally published on

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