Smartphones May Enable Smart Cities

Bernie Meyerson, The Financial Times, March 4, 2013

Connected and predictive cities will transform city living, says IBM Fellow Bernie Meyerson

People who live in cities are starting to get a lot more information to help plan their daily lives. Smarter City systems are telling residents about traffic congestion, the time the next bus will arrive, the potential for flooding on a block-by-block basis, and a host of other useful updates.

The same wealth of data enables city service leaders to proactively send crews out to mitigate future damage, such as going out to replace water lines before small leaks become catastrophic sinkholes.

This is happening because cities are harnessing the streams of information from sensors to manage municipal systems better. Cities are complex systems of systems that have always generated vast amounts of information. Information flowing in from many small subsystems, such as local flood catch-basins, is integrated with other sources to provide guidance on the overall operation of a city's storm sewer system. This integrated data, from such systems of systems, is then given to city administrators in useful formats that can transform city living for the better.

The need for cities to maximise the efficient use of infrastructure and help residents be more productive without spending vast sums on new facilities is driving this process. The more efficient use of data and predictive analytics promises to help accomplish that goal.

In some cases, cities have moved well beyond just monitoring events in real time. They have begun to accurately predict future events likely to cause damage, and take action to avoid it. Predicting and altering the future may sound like science fiction, but it is here today and represents the future for urban management.
This feat begins with gathering as much data as possible on the issues that need to be addressed. Using the "internet of things", sensors embedded in a wide array of systems serving the public (traffic signals, buses, trains, parking spaces, water systems) report the status of the system they are monitoring via the Internet.
The number of devices such as these exceeded the number of people on the internet in 2008, and will reach 50bn in 2020, according to an article in the 8th November issue of the Journal of Sensor and Actuator Networks. Cities now gather the critical data required to build the models and predictive abilities to understand and alter the future for the better.

All these devices can constantly send information to central command posts where digital streams of data can be analysed and used to alert emergency responders or divert traffic in case of trouble.

Sensors that instantly detect a broken down subway car on a busy track can give repair crews valuable extra minutes of work time to correct matters. However, a true game-changer is the use of sensors to show that a bearing on a train car is running warmer than usual, allowing analytics software to alert maintenance workers and eliminate an impending problem long before a dangerous failure occurs.

IBM, has been using predictive analytics to help cities function better for almost a decade. For example, we have helped city police in Richmond, Virginia deploy their forces to predicted trouble spots and avert crimes. We have helped schools in Mobile, Alabama identify potential dropouts and target them for additional remediation.

In Rio de Janeiro, the city has built a sophisticated central command center in preparation for the World Cup in 2014, and Rio's mayor is counting on advanced analytics to monitor the deluge of data coming in from the region and spot problems long before any one individual could.

Rio currently employs sophisticated weather prediction systems capable of forecasting weather for areas as small as one square kilometer to alert city officials to the potential for heavy rainfall to cause highly localised mud slides in a specific neighborhood located on a steep mountain side. As the predictions are very precise, public safety officials can concentrate their safety teams at key locations, alerting residents to the potential danger and moving to evacuate them if deemed appropriate.

With super-cities of tens of millions of people now emerging, at a scale and complexity never before encountered, this ability to focus resources using deep understanding of the "big picture" becomes ever more critical. In 2010, for the first time in history, more people on the planet lived in cities than lived in rural areas. More importantly, in the next 20 years, some 2bn more people will move into cities, marking one of the most significant migrations in human history.

In some countries, India and China as examples, governments are building new cities to accommodate this transformation. However, on a worldwide basis, most migrants will move to existing cities where they may have personal relationships, prospects of a job, or some other incentive.

In those existing cities, the coming population growth will challenge even the most skilled city managers, and the legacy infrastructure of many such cities is not equipped with the ability to gather the data needed to guide city operations. Despite the seeming lack of data gathering infrastructure, another option exists given the shift from desktop computing to mobile devices and tablets.

Mobile technology has advanced dramatically in the past decade to the point where a lightweight smartphone may gather all manner of data, such as its location, velocity, local temperature and background noise levels. Furthermore, in the near future, additional capabilities are easily envisioned, where sensors could be embedded to detect both particulate and chemical pollution, local lighting conditions, vibration levels, and more.
This will enable a new era of participatory engagement by a city's population, where the very data required to optimise city operations is in part willingly provided by its citizens via smartphone apps.

It also raises complex societal issues that must be addressed as we face this new era, but similarly provides an unprecedented opportunity for the citizenry of a community to take an active role in the betterment of their community, not only in the reporting of critical environmental and transportation data, but in taking an active role in mitigating the very challenges their own data identifies.

It will be a cooperative and informed effort, with information technology enabling societal transformation, to address the growing challenges facing our cities in the coming decades.

Bernie Meyerson is an IBM fellow and vice president for innovation

OF INTEREST: Max Levchin (Former CTO of Paypal)'s keynot at DLD on Big Data

This is the approximate text of the keynote I gave at DLD13 today in Munich. I felt my delivery of this (admittedly, relatively dense) material was not the best, but the content is crucially important. To that end, I am posting the notes here. They were edited for grammar beyond the basics, so you will have to forgive the occasional fifth-grade prose.

Max Levchin, January 21, 2013
Many of today’s big data companies are trying to tackle problems that just aren’t nearly big enough. 

Most are focused on marginally improving existing, digital businesses, but I believe the next big wave of opportunities exists in centralized processing of data gathered from primarily analog systems.

At PayPal, where I was the CTO, we succeeded because we gained deep understanding of the immense quantities of behavioral data that we captured in processing millions of transactions per day. We learned so much about our customers, that we could predict their intentions, and prevent vast majority of intentional fraud. 

At HVF, the project I began in 2011, we seek to create businesses that improve the analog, real world through deep understanding of data. I will tell you more about that in a bit, but first let me expand on what I mean by “digital sensors over analog data.”

Collaborative consumption is a huge current trend. To me, it started to make sense with Über — idling black limo cars put to better use. Über (where I am now an investor) created a simple piece of software to send the idle ones to price-insensitive consumers in need of a cab with a bit of flair. 

The world of real things is very inefficient: slack resources are abundant, so are the companies trying to rationalize their use. Über, AirBnB, Exec, GetAround, PostMates, ZipCar, Cherry, Housefed, Skyara, ToolSpinner, Snapgoods, Vayable, Swifto…it’s an explosion! What enabled this? Why now? It’s not like we suddenly have a larger surplus of black cars than ever before.

Examine the DNA of these businesses: resource availability and demand requests — highly analog, as this is about cars, drivers, and passengers — is captured at the edge, automatically where possible, then transmitted and stored, then processed centrally. Requests are queued at the smart center, and a marketplace/auction is used to allocate them, matches are made and feedback is given in real time. 

Utilization per dollar goes up, because there is simply less idle time! So efficient is this new approach in fact that limo companies started hiring drivers to drive for Über only.  

I am ignoring some key details, like the need for mutual trust between participants that is at least initially enabled by the presence of a trusted third party, and the feedback loop from consumers of the service, but at its core, these business all look very similar.

A key revolutionary insight here is not that the market-based distribution of resources is a great idea — it is the digitalization of analog data, and its management in a centralized queue to create amazing new efficiencies.

Consider the cab calling experience vs Über. When dialing up a cab, you are managing your own spot in the queue. If you hang up in anger, you go back to the end. If you stay on, listening to the on-call tune, you may be an infinite loop, as there is no feedback! 

And even if you are willing to pay a hundred times more than everyone else waiting ahead of you in line to speak to dispatch, you never get to express that demand. The data exists in an analog-only format, and it moves at analog-only speeds.

With Über, the queue can be managed centrally (because the information is converted to a digital format at the edge) with nearly complete transparency to you — you know when the resources you want become available, you know how long you have to wait for them, and most importantly, you are generally assured through feedback that you have not been forgotten or ignored.

So why is all this now? Cheap digital sensors over analog resources (cars, houses, humans, etc) — AT&T pays for your GPS… so you’d consume more data of course. Mobile broadband, of course. Even more key is the critical mass of pretty smart devices that are clients for real-time participation in queue management with feedback. It’s the smart-enough terminal model. 

As an aside, consumers want sexy sensors that give visual feedback to motivate action (and more data) — like the Nike Fuel band. Machines, on the other hand, just want cheap sensors to get more data from.

I sometimes imagine the low-use troughs of sinusoidal curves utilization of all these analog resources being pulled up, filling up with happy digital usage. 

Private jets spend 1h per day on average in the air. BlackJet promises to make that number closer to the commercial average — 10h/day. And not everyone in a suburban neighborhood needs their own lawn mower — they need an app to schedule one of the local kids to come by and take care of their overgrown grass. 

The defensibility of these businesses lies in their ability to build a network effect — a network effect of data. Once a business understands substantially more than any one of the resources managed in their queue, it’s effectively impossible to compete with them on price — they can always see more of the usage as it happens, and price it more efficiently, pushing any competition out. 

So what other businesses can we expect to emerge in analog-data-driven, central-intelligence queue marketplace businesses? Some interesting ones are probably already being built: a market for private neighborhood security (off-duty cops)? An auction for short-term patent licenses (litigator included)? 

Technology already enables efficient redistribution for your spare change: it’s Kickstarter and AngelList. We will definitely see dynamically-priced queues for confession-taking priests, and therapists!

How about dynamic pricing for brain cycles? We have been maximizing utilization of very high-value, very low-frequency specialists — today you can already rent the brain of a data-mining genius via Kaggle by the hour, tomorrow by brain-hour. Just like the SETI@Home screensaver “steals” CPU cycles to sift through cosmic radio noise for alien voices, your brain plug firmware will earn you a little extra cash while you sleep, by being remotely programmed to solve hard problems, like factoring products of large primes.

There is also a neat symmetry to this analog-to-digtail transformation — enabling centralization of unique analog capacities. As soon as the general public is ready for it, many things handled by a human at the edge of consumption will be controlled by the best currently available human at the center of the system, real time sensors bringing the necessary data to them in real time. The freshest, smartest pilot, most familiar with the particular complicated airport will land your plane — via remote control.   

So what’s after that? This is where it gets really interesting. These new modes of operation — remote controlled cars and planes flown by pilots you can’t see, rides in quasi-cabs with people you have never met, legal advice from lawyers whose license you cannot really check. This is going to add a huge amount of new kinds of risks. 

But as a species, we simply must take these risks, to continue advancing, to use all available resources to their maximum. Yet these risks are real, and they cannot be ignored.

The way to deal with risk is of course some form of insurance. Modeling loss from observed past events is hardly news, but dynamically changing the price of the service to reflect individual risk is a big deal. My expectation is that next decade we will see an explosion of insurance and insurance-like products and services — leveraging those very same network effects of data, providing truly dynamic resource pricing and allocation. 

This is the purpose of my new project, HVF — to bring these new products to those that will benefit from them the most. We see data-driven understanding and pricing of risk as the great opportunity to improve lives. The reason the notion of analog is so important here is because it ultimately also means “human.”

Understanding the changing risk profile of a person can deliver to them amazing opportunities they wouldn’t have in today’s world: inferring that a particular college grad is financially responsible by looking at their tweets could allow them to buy their first house on credit, at 21, without any history, and looking at someone’s heart rate monitor data could make their cardiovascular healthcare cost-free. 

These are not non-controversial topics — privacy, unfair discrimination, built-in biases are all possible, and we must be thoughtful and diligent in how we go about bringing this future. But I believe that what we can enable with data insights greatly outweighs the downsides. 

Here is what I mean, by way of a simple example.

On a Sat morning, I load my two toddlers into their respective child seats, and my car’s in-wheel strain gauges detect the weight difference and reports that the kids are with me in a moving vehicle to my insurance via a secure message through my iPhone. The insurance company duly increases today’s premium by a few dollars. 

My keepHonest app sees this too and immediately offers me up as a customer to a few competing insurance companies in the background, but nobody is willing to charge me less right now, and the phone chirps sadly to let me know I’m now paying a higher premium. Safer, but more expensive. 

But In a few hours, my car’s GPS duly reports to my insurer that I only drove two miles to the park, never sped and, and observed all traffic signs. My phone now chirps happily: not only has my rate been discounted, several companies are offering me a deal on insurance!

So to conclude: I believe that in the next decades we will see huge number of inherently analog processes captured digitally. Opportunities to build businesses that process this data and improve lives will abound. 

Immelt: The Future of the Internet is Intelligent Machines

Jeff Immelt, GigaOm, November 28, 2012 

Thanks to the internet, almost anything consumers might want is just a click away. But for businesses, the gains have been much less dramatic. That is about to change, with the arrival of the Industrial Internet.

As we know it today, the internet has been largely about connecting people to information, people to people, and people to business. Monetization strategies range as widely as the options available, and for all the success, there are more failures. While many of the advancements have been extraordinary – even unthinkable a short time ago – too often we’re still left asking, “to what end?”

The internet can give consumers nearly anything with just a click, but global economies remain challenged.  The internet has become the biggest library in the world, but education is just now beginning to take advantage and change.  The internet can provide businesses with unprecedented data, but true insight remains contentious and change is slow.

The real opportunity for change is still ahead of us, surpassing the magnitude of the development and adoption of the consumer internet. It is what we call the “Industrial Internet,” an open, global network that connects people, data and machines. The Industrial Internet is aimed at advancing the critical industries that power, move and treat the world.

There are now many millions of machines across the world, ranging from simple electric motors to highly advanced MRI machines. There are tens of thousands of fleets of sophisticated machinery, ranging from power plants that produce electricity to aircraft that move people and cargo around the world. There are thousands of complex networks ranging from power grids to railroad systems, which tie machines and fleets together.

This vast physical world of machines, facilities, fleets and networks can more deeply merge with the connectivity, big data and analytics of the digital world. This is what the Industrial Internet Revolution is all about.

Productivity Revolution
The Industrial Internet leverages the power of the cloud to connect machines embedded with sensors and sophisticated software to other machines (and to us) so we can extract data, make sense of it and find meaning where it did not exist before. Machines – from jet engines to gas turbines to CT scanners – will have the analytical intelligence to self-diagnose and self-correct. They will be able to deliver the right information to the right people, all in real time. When machines can sense conditions and communicate, they become instruments of understanding. They create knowledge from which we can act quickly, saving money and producing better outcomes.

As an example, we have pushed the boundaries of physical and material sciences in our aircraft engines to the point where these engines are more powerful and efficient than ever. We will continue to improve them physically, but at the same time we can use software, monitoring and big data analytics to attack the $284 billion in annual waste in the airline industry that is caused by fuel inefficiency, unscheduled aircraft maintenance, and delayed flights.

Consider that just a one percent improvement in aircraft engine maintenance efficiency can reduce related costs by $250 million annually. A similar one percent fuel savings in power generation could add more than $4 billion annually to the global economy.

Whether in terms of operations, performance or maintenance excellence, all industries are looking for their next major productivity gains. Health care is burdened by a system where doctors and caregivers have to go searching for vital information; it is inefficient at best and life threatening at worst. We need to make the data more intelligent and integrated, more predictive and proactive, so information finds the doctor instead of the other way around.

Intelligent data flows speed up care delivery and can prevent chronic conditions by getting the treatment right the very first time. Similarly, in terms of health management costs, “intelligent” hospitals are deploying systems that behave like air traffic control for medical staff and devices, and provide a full detailed view of hospital resources. Better utilization cuts capital expenses. Better asset location leaves nurses more time to focus on patients. Better management improves patient flow, cuts operating costs, and saves hospitals millions.
There are similar scenarios in every other major industry, and the economic benefit can be huge.  Assuming growth similar to what prevailed during the internet boom, the Industrial Internet revolution will add about $15 trillion to global GDP by 2030. That’s the equivalent of adding another U.S. economy to the world.

The amazing aspect of this growth is that it stems from what appears to be minor productivity improvements. At GE, we have 5,000 software engineers and another 9,000 IT engineers. We’re focused on mining for just one percent gains in productivity. The potential is irresistible.

Roadmap to the Revolution
In the near future, I expect nothing short of an open, global fabric of highly intelligent machines that connect, communicate and cooperate with us. This Industrial Internet is not about a world run by robots, it is about combining the world’s best technologies to solve our biggest challenges. It’s about economically and environmentally sustainable energy, curing the incurable diseases, and preparing our infrastructure and cities for the next 100 years.

To do this industry and government need to work together on two critical areas: standardization and security.  We need to establish common standards so that innovative minds can develop the best solutions for the machines and systems that move our world. Just as the advancement of mobile devices and operating systems have brought forth a prosperous  “app” economy, a standard language for machines will unleash waves of innovation that will truly change how the world works. This is a critical step and needs government policies that favor advancement.

Attaining the vision set forth for the Industrial Internet will also require an effective internet security regime. Cyber security should be considered in terms of both network security (a defense strategy specific to the Cloud) and the security of devices that are connected to the network. We need industry to effectively secure facilities and networks and governments to enforce a regulatory regime that promotes innovative solutions and international standards.

The Industrial Internet era has already begun. And during a time when the global economy is recovering but remains volatile and where resources are constrained for people, governments, and companies, what we need most is to not lose sight of a real opportunity to create meaningful change around the world.
After all, this is what revolutions are all about.

Jeff Immelt is the chairman and CEO of GE. 

WSJ - CEO Council on Big Data

Big Data: Opportunities and Risks Co-Chairs
Tim Armstrong, Chairman and CEO, AOL Inc.
Dominic Barton, Global Managing Director, McKinsey & Co.
R. Marcelo Claure, Chairman, President and CEO, Brightstar Corp.
Subject Expert
David J. Rothkopf, President and CEO, Garten Rothkopf

Big Data: The Top Four Recommendations
1. Big Data Is Opportunity
Industry already recognizes that the advent of Big Data is a potential engine of significant economic growth. Policy makers must address issues such as security and privacy but not restrict this opportunity. Consumers, government and companies all have a role to play in defining policy. Countries need to recognize that the treatment of data is ultimately an issue of national competitiveness.

2. Create Rules of the Road
The government should define which activities concerning data are legal or illegal. For activities that are legal, consumers should then define what is public or private in their own cases through opting in or out in terms of what they choose to reveal about themselves.

3. Enact Cybersecurity Standards
The private sector, government, the military and consumers should jointly develop detailed standards and incidence-reporting practices for cybersecurity, building on existing industry best practices.

4. Create a Global Data Treaty
The U.S. should play a leadership role in coordinating with international bodies to pass a treaty to establish clear, universal standards on data privacy and ownership.

It's a phenomenon commonly referred to as Big Data, and it has generated widespread debate over a host of issues. What should companies do with such data? How can it be used profitably? How should it be treated? Should there be laws governing its use? Internationally recognized safeguards for consumer privacy? And how do U.S. companies stay competitive as more countries learn how to process and interpret such data?

The Wall Street Journal's John Bussey moderated a task-force discussion about just such issues. Here are edited excerpts of their presentations to the CEO Council:

Opportunity First
JOHN BUSSEY: Our group ended up with essentially two principles and two action items. Dominic, if you could take our first, please?

DOMINIC BARTON: Our group felt very strongly that this is a huge opportunity, and we shouldn't focus on how to protect or regulate Big Data before we recognize how important it is. Companies that use Big Data effectively get about a 6% productivity improvement versus others.

We're at the early stages. It's in every sector. And we all felt it can be the next wave of productivity growth if we use this data effectively.

Depending on how you protect or use data, it can actually lead to a country's competitive advantage. We've got small city-states like Singapore and Abu Dhabi that are allowing, for example, consumer medical information to be publicly available to get innovation.
So let's not lose sight of how important it can be for productivity improvement as we think about the protection.

MR. BUSSEY: Marcelo, our second principle.
MARCELO CLAURE: First of all, we had a fascinating group. We had a tremendous amount of interaction. And we quickly realized that all of us live in a hyper-connected world. By that I mean we're passing a huge amount of data every day through a connected car, a connected cellphone, a connected tablet, a connected home.

Big Data: The Top Four Recommendations
1. Big Data Is Opportunity
Industry already recognizes that the advent of Big Data is a potential engine of significant economic growth. Policy makers must address issues such as security and privacy but not restrict this opportunity. Consumers, government and companies all have a role to play in defining policy. Countries need to recognize that the treatment of data is ultimately an issue of national competitiveness.

2. Create Rules of the Road
The government should define which activities concerning data are legal or illegal. For activities that are legal, consumers should then define what is public or private in their own cases through opting in or out in terms of what they choose to reveal about themselves.

3. Enact Cybersecurity Standards
The private sector, government, the military and consumers should jointly develop detailed standards and incidence-reporting practices for cybersecurity, building on existing industry best practices.

4. Create a Global Data Treaty
The U.S. should play a leadership role in coordinating with international bodies to pass a treaty to establish clear, universal standards on data privacy and ownership.

Companies around the world increasingly collect and process vast amounts of customer data, particularly data tracking consumer behavior on the Web.

 We see it as a tremendous opportunity, but what is the government role?

Some members of our group argued that government shouldn't be allowed to regulate or do anything related to Big Data. But the rest of the group agreed that we've got to define the basics of what the government is going to do.

And where we came out at the end was, government should have the role of defining what is legal and what is illegal in the use of Big Data. And that's where the government should stop. We think it should be left up to the consumer to define what he or she wants to share and doesn't want to share, what is public and what is private.

Limiting government control to what's legal and illegal will allow the consumer to make more choices. As a consumer, you should be able to determine how much of your Facebook profile you want to share, or whether you want to share information about where you shopped last.

Security and Treaty
MR. BUSSEY: And Tim has our two action items.

TIM ARMSTRONG: The first one is probably more important than it seems on the surface, especially for private companies. I think we started this as kind of a government conversation, but mostly it's private companies that actually own the infrastructure that makes the company or the country work.

So cybersecurity is something that really needs to be dealt with. And specifically, having standards around this is important in two different directions.

One is standards of what happens when something gets attacked. How do you report it, and what is the infrastructure to help companies with that?

The second piece which is important and which came up in our discussion is when your data lives outside the country, or when you're going to do things with data in other countries. There are groups like CFIUS [the U.S. government's Committee on Foreign Investment in the U.S., which reviews foreign investment deemed to have an effect on national security] which are inside the government, which, if you haven't dealt with them, you will, over these type of data assets. Cybersecurity is really important.

The last action item is coming up with a global data treaty. The U.S. is probably the largest economy involved in Big Data right now, and we think it's important for the U.S. to take a leading role in defining what some of the Big Data policies and standards should be in such a treaty. We would hope that we, the U.S., could define a basic treaty to start off, and then other countries could either adopt or augment the treaty over time.

Gartner Says Big Data Creates Big Jobs: 4.4 Million IT Jobs Globally to Support Big Data By 2015

Analysts Discuss Key Issues Facing the IT Industry During Gartner Symposium/ITxpo 2012, October 21-25, in Orlando

ORLANDO, Fla.--(BUSINESS WIRE)-- Worldwide IT spending is forecast to surpass $3.7 trillion in 2013, a 3.8 percent increase from 2012 projected spending of $3.6 trillion, but it's the outlook for big data that is creating much excitement, according to Gartner, Inc.

"By 2015, 4.4 million IT jobs globally will be created to support big data, generating 1.9 million IT jobs in the United States," said Peter Sondergaard, senior vice president at Gartner and global head of Research. "In addition, every big data-related role in the U.S. will create employment for three people outside of IT, so over the next four years a total of 6 million jobs in the U.S. will be generated by the information economy."

"But there is a challenge. There is not enough talent in the industry. Our public and private education systems are failing us. Therefore, only one-third of the IT jobs will be filled. Data experts will be a scarce, valuable commodity," Mr. Sondergaard said. "IT leaders will need immediate focus on how their organization develops and attracts the skills required. These jobs will be needed to grow your business. These jobs are the future of the new information economy."

Mr. Sondergaard provided the latest outlook for the IT industry today to an audience of more than 8,000 CIOs and IT leaders at Gartner Symposium/ITxpo, which is taking place here through October 25. He said the IT industry is entering the Nexus of Forces, which includes a confluence and integration of cloud, social collaboration, mobile and information.

"This is a time of accelerating change, where your current IT architecture will be rendered obsolete," Mr. Sondergaard said. "You must lead through this change, selectively destroy low impact systems, and aggressively change your IT cost structure. This is the New World of the Nexus, the next age of computing."

Cloud
The cloud is the carrier for the three other Forces: mobile is personal cloud, social media is only possible via the cloud, and big data is the killer app for the cloud. Cloud will be the permanent fixture, the foundation.

"Cloud is not merely about cost-cutting, the end game is not just cheap on-demand services. In fact, 90 percent of these services are still subscription based, not pay-as-you-go," Mr. Sondergaard said. "We are just at the beginning of realizing the cost benefits of cloud, but organizations moving to the cloud are also attracted by the new capabilities they do not get today. It is bringing new approaches to designing applications, specifically for the cloud, and providing more resilience by architecturing failure as a design concept. Cloud also teaches us about services and service levels, and the contrast between what the business wants for outcomes versus IT's old methods of getting there."

Mobile
In 2016, more than 1.6 billion smart mobile devices will be purchased globally. Two-thirds of the mobile workforce will own a smartphone, and 40 percent of the workforce will be mobile. The challenge for IT leaders is determining what to do with this new channel to their customers and employees.

"Mobile is about computing at the right time, in the moment. It is the point of entry for all applications, delivering personalized, contextual experiences," Mr. Sondergaard said. "It means: marketing gets more time with the customer; employees become more productive; and process flows get dramatically cut."

In less than two years, iPads will be more common in business than Blackberries. Mr. Sondergaard said some CIOs are now placing orders for tens of thousands of iPads at a time. Productivity is the driver. Two years from now, 20 percent of sales organizations will use tablets as the primary mobile platform for their field sales force. As a result, by 2018, 70 percent of mobile workers will use a tablet or a hybrid device that has tablet-like characteristics.

Gartner forecasts that in 2016, half of all non-PC devices will be purchased by employees. By the end of the decade, half of all devices in business will be purchased by employees.

Social Computing
In the next three years, the dominant consumer social networks will the limits of their growth. However, social computing will become even more important. Companies are establishing social media as a discipline. Gartner predicts that in three years, 10 organizations will each spend more than $1 billion on social media.

"Social computing is moving from being just on the outside of the organization to being at the core of business operations," Mr. Sondergaard said. "It is changing the fundamentals of management: how you establish a sense of purpose and motivate people to act. Social computing will move organizations from hierarchical structures and defined teams to communities that can cross any organizational boundary."

Big Data
By tapping a continual stream of information from internal and external sources, businesses today have an endless array of new opportunities for: transforming decision-making; discovering new insights; optimizing the business; and innovating their industries.

Big data creates a new layer in the economy which is all about information, turning information, or data, into revenue. This will accelerate growth in the global economy and create jobs.

"Big data is about looking ahead, beyond what everybody else sees," Mr. Sondergaard said. "You need to understand how to deal with hybrid data, meaning the combination of structured and unstructured data, and how you shine a light on 'dark data.' Dark data is the data being collected, but going unused despite its value. Leading organizations of the future will be distinguished by the quality of their predictive algorithms. This is the CIO challenge, and opportunity."

About Gartner Symposium/ITxpo
Gartner Symposium/ITxpo is the world's most important gathering of CIOs and senior IT executives. This event delivers independent and objective content with the authority and weight of the world's leading IT research and advisory organization, and provides access to the latest solutions from key technology providers. Gartner's annual Symposium/ITxpo events are key components of attendees' annual planning efforts. IT executives rely on Gartner Symposium/ITxpo to gain insight into how their organizations can use IT to address business challenges and improve operational efficiency.

Additional information about Gartner Symposium/ITxpo in Orlando, is available at www.gartner.com/symposium/us. Video replays of keynotes and sessions are available on Gartner Events on Demand at www.gartnerondemand.com. Follow news, photos and video coming from Gartner Symposium/ITxpo on Facebook at http://www.facebook.com/GartnerSymposium, and on Twitter at http://twitter.com/Gartner_inc and using #GartnerSym.

How "Big-Data-as-a-Service" Can Help Smaller Companies Compete

Brian Proffitt, Read Write Web, September 26, 2012

The common perception of how big data is used centers around giant multi-national enterprises spending millions trying to fine tune their business strategies to eke out every last penny from their customers. But in reality, big data is worming its way into businesses large and small, often as a service instead of on-premises software.


The Evolution Of The Comment Card
Visit a bustling diner in a small town and you may see them tucked in among the bottles of ketchup and sugar packets on the linoleum counter: 3 X 5 comment cards. How was your meal? How was your service? Fill it out and tuck it in the little wooden box by the cash register, please.

Regulars might make their concerns known directly to the staff, but diners such as this - like nearly every other business in the world - need to attract and keep new customers in order to grow. That's the point behind comment cards: get as much feedback as you can so you to improve what needs fixing and keep doing what's working well.

Moving the comment card into the 21st Century is essentially what big data is all about.

The most common form of big data in busines today was created as a technological response to tracking all of the data that was generated by commercial websites. Once marketers and other business execs saw that they could monitor an online customer's responses all the way down to the mouse click, software engineers started figuring out a way to keep that data and mine it for ever more useful information.

The combination of speed and volume needed to catch all of this information is what makes big data tools and technology really necessary. But for the vast majority of businesses that do not have big ecommerce sites, is big data even worth the attempt?

It turns out, yes.

Big Data Tools Work For Small Data, Too
One of the easier ways smaller businesses are taking on big data is seeing the general value of data analytics no matter how big or small the data set is. That message is practically a non-brainer: business owners are scanning the headlines every day and getting excited about applying data to their decision-making process.
Social media is one quick way to implement big data within a smaller business. Used and analyzed properly, the information from social media can give any business instant feedback that's far more robust and immediate than those old-fashioned comment cards.

"Every time we perform a search, tweet, send an email, post a blog, comment on one, use a cell phone, shop online, update our profile on a social networking site, use a credit card, or even go to the gym, we leave behind a mountain of data, a digital footprint, that provides a treasure trove of information about our lifestyles, financial activities, health habits, social interactions, and much more," wrote former Tivoli CEO Frank Moss in his 2011 book The Sorcerers and Their Apprentices.

Big-Data-as-a-Service (BDaaS)
Using big data can go beyond mining social media as a juiced-up form of the comment card. Big data can also be integrated with existing business practices to improve and expand day-to-day operations.

It's becoming pretty well-known that big data and fast data analysis are being used by large hotels and chains to improve their yield management processes. This kind of infrastructure is typically beyond the reach of smaller hotels, inns and bed and breakfasts. It's probably overkill anyway: while a big hotel near Orlando, Fla., area might see 75 room pricing changes per day, a small independent lodging in a less-volatile market might only see a couple of price moves daily.

But that doesn't make the need for a smaller inn to adjust to local market changes any less important, says Erik Hovanec, CEO of LeisureLink, which specializes in providing yield-management as a service to smaller hospitality locations.

One of LeisureLink's clients is a 120-room property outside Myrtle Beach, SC, that "is great at hospitality, not necessarily at IT." Hovanec described. Using his company's service, the property is able to tap into information about local Myrtle Beach hotels and see real-time pricing information on other properties and make adjustments accordingly.

This is exactly what the larger hotels and chains have been doing for a while. But now this service is available to smaller, mid-market establishments. Typically, a large hotel or chain might invest $30-$40 million just to increase their yield management from 90% to 95%. Hovanec boasts that since LeisureLink's service is often the first real step into automated yield management for smaller hotels, their efficiency in yield management can rocket from 20% to 80%.

Can Big Data Work For Every Business?
At some point, any company considering a big-data approach needs to consider the one basic question: is there information out there that will help improve the business? If there's a yes in there, then a search for a big data solution might be worth the effort.

It's not that we really need another another "as-a-Service" acronym, but thanks to the use of Internet-based Big-Data-as-a-Service (BDaaS), you don't have to be a giant enteprise to play any more. These days, there's a good chance that someone out there will have the information you need or can help you find it.