Technology Vision 2014 by Accenture

From Digitally
Disrupted to
Digital Disrupter
Accenture Technology Vision 2014
Every Business Is a Digital Business

FOREWORD 3
INTRODUCTION 4
TRENDS
01
Digital–physical blur:
Extending intelligence to the edge 12
02
From workforce to crowdsource:
The rise of the borderless enterprise 28
03
Data supply chain:
Putting information into circulation 42
04
Harnessing hyperscale:
Hardware is back (and never really
went away) 56
05
The business of applications:
Software as a core competency
in a digital world 72
06
Architecting resilience:
“Built to survive failure” becomes the
mantra of the nonstop business 84
CONCLUSION 98
RESEARCH METHODOLOGY 102
END NOTES 104
CONTACTS 111
2
#techvision2014
CONTENTS

Pierre Nanterme
Chairman & CEO
Paul Daugherty
Chief Technology Officer
Foreword
When we declared “every business is a digital business”
in the Accenture Technology Vision 2013, we didn’t see
it as a trend for last year or this year. We saw it as the
future. The future of technology. The future of business.
The future of our increasingly interconnected and
interdependent world.
Last year, we saw the beginnings of business transformation
based on a digital model. Organizations looking to
reimagine themselves in a technology-driven world set
forth on their journey to becoming digital businesses.
Many organizations were experimenting, while others
were making larger investments. But all were counting
on technology to fuel their next waves of growth.
This year, we see a marked uptick in digital. The Accenture
Technology Vision 2014 lays out bold trends that are
becoming characteristic of larger enterprises, which have
been perceived by some as lagging in converting to digital
businesses. While social, mobile, analytics, and cloud still
drive these trends, the focus now is on new ways that
these technologies are being woven into the next
generation of business strategies across every industry.
Enterprises are embracing technology in the way they do
business and also as a catalyst to create something new—
new markets, new products, and new areas of growth
and revenues.
The change is revolutionary. Industrial companies are
becoming customer service companies. Consumer
products companies are becoming Internet companies.
Energy companies are becoming information companies.
And media and entertainment companies are becoming
logistics companies.
For our clients and for any organization, the Accenture
Technology Vision 2014 points toward an exciting time
of new opportunities driven by the power of technology.
We hope that you find the Accenture Technology Vision
insightful as you continue on the journey to become a
digital business.
ACCENTURE TECHNOLOGY VISION 2014
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FOREWORD

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4
INTRODUCTION

INTRODUCTION
Every Business Is a Digital Business:
From Digitally Disrupted to Digital
Disrupter
Big companies are back in the digital game. Procter & Gamble,
Tesco, Disney, GE—these are just a few of the global 2,000 that
are now in a race to become digital. Those that get there first will
be able to disrupt their existing markets and penetrate new ones.
They will be in control of their new digital destinies.
This year’s report represents the latest iteration of Accenture’s
Technology Vision, which declares that “every business is a
digital business.” In last year’s report, we laid out the imperative
for every business to reimagine itself in this digital world, and
we charted the increasing appetite of leading enterprises for
exploring the opportunities that emerging technologies provide.
5
INTRODUCTION

Big is the next big thing
This year we see something more. We see the first wave
of large traditional companies starting to use technology
as a driving force—in some situations, the driving force—
for how they grow strongly and effectively. If the last
decade has been seen as the playground of the digital
startups—overnight sensations such as Instagram and
Twitter, Zipcar and YouTube, TripAdvisor and Airbnb—
then the coming decade will see the emergence of the
traditional companies as digital giants. Backed by their
deep resources, enormous scale, and process discipline,
these new digerati are about to rewrite much of the
digital playbook.
For business leaders everywhere, the next three years
will be about determining their organizations’ pace in
this digital race—and their place in the new world of
digital. Large companies are making a push to transform
themselves from followers to leaders in digital. The first
contenders out of the gate are already poised to take
advantage of the many recent technology advances in
ways that promise to upend expectations of industry
observers and consumers alike.
Tesco, GE, and Disney
show how
Consider Tesco. In the last two years, the global
supermarket chain not only has created interactive
grocery stores in airports and subway stations but also
has expanded into new industries. Tesco now offers
movie streaming, e-books, and even its own seven-
inch tablet priced as low as $91.1
The grocery retailer
is well on its way to becoming a truly digital business.
More than 20 percent of Tesco’s online sales now come
through smartphones, and 10 percent of all orders from
Tesco Direct come through its mobile website.2
In the manufacturing arena, GE is betting on the
industrial Internet, building cloud-based services with
intelligent analytics so that it can collect and combine
vast amounts of industrial-machine data and equipment
data, extracting unique insights that it can use to set
new performance standards in major industries such as
energy and aviation.
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INTRODUCTION

In the business-to-consumer realm, Disney is introducing
a collection of tools including a wireless tracking
wristband to create an entirely new personalized and
enriched experience for visitors to its amusement parks.
For visitors wearing the MagicBand, Disney offers a
better guest experience with much less waiting. But the
technology goes beyond just giving preferential places
in queues: for example, it allows Disney park-goers to
simply “touch to pay” for food and merchandise and to
make and share plans with family and friends in a travel
group. The technology is also transforming the dining
experience, enabling patrons to preorder food, which is
then prepared and served as they walk into a restaurant.3
And of course, Disney captures a comprehensive digital
record (or storybook) of its customers’ activities.
Much more than an
investor relations game
During their years of experimentation, industrial
powerhouses such as GE, Disney, P&G, Tesco, Walmart,
and Shell have learned by doing—steadily gaining
the skills and the competencies to pull ahead of their
competitors, blunting the startups’ advantages, and
proving to their stakeholders that they absolutely have
what it takes to excel in the new digital economy.
Of course, the big players know it’s far more than an
investor relations game. They are acutely aware that
digital expertise can confer exceptional strategic
advantage. They realize that not only can they control
their own markets, but they can actually disrupt and
establish footholds in others, often creating new business
and market models in the process. For example, General
Motors is already raising anxiety in the car rental
business by partnering with RelayRides, a startup whose
use of mobile phones makes ride sharing easy. And AT&T
is entering the home security market with its Digital Life
service, allowing customers to remotely control everything
in the home, from alarms to lights to door locks.
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INTRODUCTION

When boundaries blur
A huge shift is under way. Boundaries are blurring in
many dimensions—not just between IT leaders and their
business colleagues, but between digital assets and
physical resources and between enterprises and their
customers, suppliers, and other stakeholders. IT strategy
and business strategy are no longer separate; they have
become inseparable. It’s this kind of mindset that we see
across the digital spectrum.
In many ways, digital is unlocking a renaissance for large
companies, allowing them to reconnect with what made
them industry leaders in the first place. There is a vast
variety of opportunity before them. Just as technology
leveled the field for the newcomers of the last decade, so
the incumbents can now leverage those same forces of
digital democratization to charge back. Lower barriers to
entry for one are lower barriers to entry for all. Many will
use their new digital prowess as a potent differentiator—
resetting the bar for consumer interactions, for instance,
or providing unprecedented levels of supply chain
effectiveness, or perhaps developing groundbreaking new
pricing models.
Hallmarks of tomorrow’s
digital disrupters
The concept of the “fast follower” is becoming obsolete.
In a world of nonstop change, there is no time to catch
up. Instead, we expect the emerging digital leaders to
be master orchestrators—uniquely able to strive for
convergence on a huge scale as they capitalize on a wide
array of technology breakthroughs to rapidly advance
and innovate with their systems and strategies.
In turn, this new pace will force corporate leaders to
think about new operating models that might yield
further advantage. Here too, many experiments are under
way—from new cross-functional roles for data scientists
to chief digital officers whose influence extends beyond
the four walls of the enterprise.
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INTRODUCTION

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INTRODUCTION

–
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FIGURE 1:
Every Business Is
a Digital Business:
The Evolution
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INTRODUCTION

And throughout every organization, we anticipate a
re-estimation of the skills that will be most valuable,
at all levels.
This year’s Technology Vision report highlights six
emerging themes that reflect the shifts being seen now
among the digital power brokers of tomorrow: large
enterprises such as Tesco, GE, and Disney that recognize,
as they leverage their scale to redefine digital in their
industries, that big is the next big thing.
Collectively, these themes represent the newest
expression of Accenture’s stance that “every business is
a digital business.” They provide additional components
to Accenture’s multiyear perspective on technology’s
tectonic shifts and its impact on the strategies and
operational priorities for organizations worldwide
(see Figure 1).
Individually, each theme, from each year, highlights the
evolution of a key technology, some of which are already
central to the digital explorations of many leading
enterprises. Viewed in aggregate, the themes represent
a fundamental shift in the assumptions that companies
now must make as they plan for success in the decades
to come. They provide a richly detailed view from which
business leaders in every industry can draw insight,
inspiration, and, we hope, excitement about where digital
technologies can take their organizations tomorrow.
Becoming a digital business is no longer simply about
how we incorporate technology into our organizations;
it’s about how we use technology to reinvent those
organizations to get out in front of the dramatic
changes that technology is creating. For large enterprises
especially, the opportunity to shift from disrupted to
disrupter cannot be overstated. The question these
businesses must now ask is how they will use the next
three years to redefine their places in this new world.
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INTRODUCTION

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TREND 1: DIGITAL–PHYSICAL BLUR

TREND 1
Digital–physical blur:
Extending intelligence to the edge
The physical world is coming online as objects, devices, and
machines acquire more digital intelligence. What’s emerging
is more than just an “Internet of Things”; it’s a new layer of
connected intelligence that augments the actions of individuals,
automates processes, and incorporates digitally empowered
machines into our lives, increasing our insight into and control
over the tangible world. There are benefits for consumers and
businesses. Consumers become better informed and better
equipped to influence the ways they experience everything
around them. And businesses get real-time connections to the
physical world that allow machines as well as employees to act
and react faster—and more intelligently.
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Why now?
Explosion of connected devices: The installed base of
the Internet of Things is estimated to reach approximately
212 billion in 2020. This will include 30 billion “connected
(autonomous) things” that same year.1
Increased bandwidth: Global IP traffic is expected to nearly
double between 2013 and 2016, and broadband is expected to
speed up more than twofold.2
Advanced robotics: From agriculture to oil fields, advances
in robotics are empowering human-robot collaboration
in industries beyond the factory floor. Several leading car
manufacturers have committed to bringing autonomous car
technologies to market by 2020.
Rise of real-time analytics: Data sources are growing at an
unprecedented velocity, and the ability to loop insights
immediately back into the decision process is supporting
automating responsive actions like never before. By 2017,
more than 50 percent of analytics implementations will make
use of event data streams generated from instrumented
machines, applications, and/or individuals.3
Wearing a smartwatch yet? Tracking your
workouts with your phone? Noticed a
driverless car in your neighborhood?
From wearable computers to autonomous drones, the
ways in which we experience the world are changing fast.
Intelligent interfaces are emerging that allow decisions to
be made “on the edge”—at the point where digital and
physical worlds converge—rather than in a centralized
manner. These decisions can be made exactly when they’re
needed in informed, social, easy-to-use ways, allowing
companies and governments to reimagine the possibilities
for engaging with their customers and citizens.
Smartphones have turned their owners into digitally
augmented versions of themselves—able to catalog and
quantify actions throughout the day and access, create,
and share an astonishing array of pertinent information
that can enable faster, better decisions. Several car
models can now self-park with ease—making “edge”
decisions about available space, proximity to the curb,
and more. Google and Nissan claim their driverless cars
are just five to six years away.4
And autonomous drones—
once the sole province of the military—are being used by
police precincts across the United States.
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But what does the average smartphone subscriber have
in common with the person riding in a driverless car?
They are both using “edge devices”—devices whose edges
border other devices in that they have unprecedented
capabilities to connect with other devices. These
“cyber physical” systems sense their environments and
respond—appropriately—in real time, making possible
better-informed decisions within windows of opportunity
that can create competitive advantage. The pivotal
point is that the sheer quantity of these edge devices is
increasing as dramatically as their prices are dropping.
At the same time, their ability to sense environmental
variables, share data with other edge devices via the
cloud, and have deep analytics performed by the cloud
adds up to create rich user experiences that inform much
more intelligent, real-time decision-making.
As the line between the digital and the physical
continues to blur, a vast new window of opportunity is
opening for the enterprise. By leveraging and enhancing
their physical assets, traditional companies are looking at
this opportunity as a way to leapfrog online competitors,
create immersive real-world experiences for consumers,
and gain market share. In addition, every company now
has the opportunity not just to gather insight to make
smart business decisions but to turn those decisions into
actions, in real time, in the real world. The enormous
expansion in intelligent capabilities is rapidly reshaping
established operations, paving the way for industry
disruption on a massive scale.
But to chase these new opportunities, business and
technology leaders alike must rethink how they both
engage customers and run their businesses in a digital-
physical world. For industrial Internet leaders like GE, this
means pushing sensing technologies outside of industrial
applications and further to the edge of operations.
For companies such as Cisco, which predicts that the
industrial Internet market will be worth $14.4 trillion over
the next decade, this means focusing on the “Internet of
Everything”—or, as Cisco describes it, “bringing together
people, process, data, and things to make networked
connections more relevant and valuable than ever before.”5
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A world of new user
experiences
The way people interact with the world around them is
changing. Digital technologies offer new decision-making
experiences—from selecting a restaurant in a new
neighborhood to making a critical maintenance decision
on a gas pipeline. The power of these decision spaces is
that they give users real insights, not just information;
by providing valuable insight, users are one step closer to
taking action.
Technology has been evolving to enable this for the last
decade. The ubiquity of network connectivity and the
proliferation of smart devices (such as sensors, signs,
phones, tablets, lights, and drones) have created platforms
upon which every enterprise can innovate. In terms of
creating new consumer experiences, this is perhaps most
visible in the surging popularity of the “quantified self”
movement. Consumer wearables such as Nike’s FuelBand,
Adidas’s miCoach, and Fitbit track exercise and physical
activity in ways that allow users to easily gain insight
into their performance—often in real time—giving them
the information necessary to make decisions about
picking up the pace, going for another lap, or pushing for
a personal best.
In the urban context, the Copenhagen Wheel, a
replacement bicycle wheel, is able to augment the cycling
experience by sensing the pressure and effort exerted
on the bike’s pedals and adding motorized help when the
rider needs it; in doing so, it’s able to quantify physical
activity for the rider.
These quantified measurements are not isolated to
athletes or individuals. Osakidetza, the public health
system in the Basque region of Spain, is using Microsoft
Kinect devices to enable telemedicine treatment of
chronic patients. Using the Kinect devices, patients are
given not only a more natural way to interface with
technology but also new ways to experience medical
care. Using insights from the Kinect devices, physical
therapists get access to a wealth of granular data
that can be used to offer remote consultations and to
quantifiably gauge progress. In doing so, therapy sessions
can be more frequent, more targeted, and shorter, thus
reducing costs, improving outcomes, and reducing
patients’ recovery times.6
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More and more, these experiences are expanding beyond
a user’s personal set of devices. Embedded intelligence
isn’t limited to smartphones and tablets. Everyday objects
are becoming smart and expanding the definition of what
it means to experience the real world. In London, British
Airways has unveiled two digital billboards that actively
track flights in real time, animate an image of a child
pointing to the plane, and display the flight number and
information about its destination or origin—inspiring
onlookers to dream about where they could be escaping
to on a British Airways flight.7
In San Francisco, parking
meters are smart and connected; drivers see a color-
coded map denoting varying levels of parking difficulty.
Once a car is parked, the system can alert the driver
when his meter time has nearly expired and allow him to
“feed the meter” virtually, from his smartphone. The
technology doesn’t allow drivers to reserve a parking
spot, but it does give them an interface to make a
decision on the edge.8
Similarly, Waze, a mobile phone app, allows drivers to
make decisions at the point of action. It does this by
enabling users to use their phones to share insights
on current road conditions and offering suggestions
about alternate routes around traffic obstacles. In short,
Waze users share rich, unstructured insights that create
actionable decision spaces.
These decision spaces are not the exclusive domain
of digital companies. Brick-and-mortar retailers
can differentiate themselves from their online-only
counterparts by mastering the digital–physical blur.
Retailers such as Tesco, Neiman Marcus, and Staples
are continually experimenting with new ways to deliver
unique and meaningful consumer experiences. Tesco and
Staples are transforming their in-store technology and
service offerings to better align with consumer lifestyles:
Tesco is rolling out face scanning digital signage at all
450 of its UK petrol stations to tailor engaging and
on-screen content to the audience of five million-
plus adults who pass through its stations each week;
Staples is piloting stores with less merchandise, more
kiosks (with free next-day delivery), and meeting spaces
for busy small-business owners.9
For its part, Neiman
Marcus has piloted digital-physical solutions that provide
both sales associates and customers with actionable
intelligence—in the form of store events, product arrivals,
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and even personal touches such as the knowledge of
when a favorite sales associate is working.10
With Apple’s
introduction of iBeacon indoor positioning technology
and competitors such as Estimote, brick-and-mortar
retailers will find abundant opportunities to incorporate
digital transformations on the retail floor that cascade
throughout their operations.
What all of these examples have in common are the ways
they enhance users’ experiences of the world, improving
their ability to share insights and take action. There’s a
powerful secondary effect at work here too: the more
that users have access to such amplifying technology,
the more they want access to real-time analytics to
inform their next experiences, everywhere.
Capabilities at the edge
refresh traditional
industries
Having access to instantly actionable decisions has
served the industrial world well. Over the last two
decades, industrial companies have enjoyed radical
efficiency improvements by integrating digital
technologies throughout their operations—from RFID
tags in supply chains to robotics and remote monitoring
and control in oilfield and pipeline operations.
What’s changing to put digital-physical systems on
boardroom agendas today is their infiltration into more
industries and their ability to disrupt so many sectors
of global economies. The same improvements that
manufacturers have made to drastically improve safety
and operational efficiency and, in some instances, to
augment the ability to scale are now expanding to every
industry. Today’s digital-physical systems range from
chef robots that can serve a custom gourmet burger
every 10 seconds to smart grid technologies that are
able to identify individual appliances and their discrete
energy consumption—by simply installing a single device
on a smart meter that can read, analyze, and decipher
complex electrical frequencies.11
Building owners, property managers, and industrial
equipment vendors are benefiting from the reduced cost
and increased capabilities of digital-physical systems to
drive new experiences with building operations. They
are adopting integrated solutions such as continuous
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commissioning systems that make use of sensors
throughout a building’s workspaces and mechanical
equipment to collect data with millisecond resolution on
building performance. Four years ago, Microsoft relied
on a team of reactive operations staff traversing the
enormous corporate campus in trucks responding to
hot and cold calls. Today, the company uses a software
overlay which visualizes the existing 500 million data
transactions every 24 hours and is managed by a staff of
highly skilled engineers who is harnessing big data and
using it to improve Microsoft employees’ experience and
drive down energy costs.12
Schneider Electric is going
one step further by incorporating some of the world’s
most advanced weather modeling data into its building
automation systems, allowing facilities managers to
factor external climate conditions into their decisions and
making it easier to automate many of those decisions.13
Industries from warehousing to agriculture are seeing
similar advances. With robotic systems for order
fulfillment enabling big reductions in shipment times,
warehouses can process more orders in less time with
fewer employees. Taking robots to the skies, the use cases
for autonomous drones are abundant and are disrupting
“The more that users have access to
amplifying technology, the more they
want access to real-time analytics
to inform their next experiences,
everywhere.”
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a diverse group of industries. Agricultural applications
use infrared cameras to pinpoint crops that are receiving
too much or too little water, first responders use drones
to detect survivors of accidents and natural disasters
and to deliver supplies to those emergency zones, and
road surfaces and traffic congestion are monitored
by drones. The EU has identified robotics as a high-
growth industry and is committing resources to ensure a
strategic leadership position. Together with a consortium
of ten European companies led by Shell, the European
Commission has committed €3.7 million to a €6.2 million
project to develop robots which can replace humans in
inspections of pressure vessels and storage tanks used
extensively in the oil, gas, and petrochemical industries.
When deployed, these robots will increase worker safety,
reduce exposure to hazardous conditions, and increase
economic development by creating new jobs and opening
new markets for the European robotics industry.14
Individuals are seeing the benefits of augmentation as
well. Philips is piloting the use of Google Glass to allow
physicians wearing the display to simultaneously monitor
a patient’s vital signs and react to surgical procedural
developments without having to turn away from the
patient or procedure.15
Gartner predicts that the field
service industry alone stands to save $1 billion annually
by 2017 by using smartglasses—the field now being
pioneered by Google Glass. The research firm notes
that smartglasses will enable field service technicians to
“diagnose and fix problems more quickly and without
needing to bring additional experts to remote sites.”16
Disruptions ahead
Supported by their abundant resources and their ability
to scale, large companies can now use digital-physical
systems to disrupt their industries—and other industries
too. To act disruptively, they must not simply use digital-
physical systems to improve today’s processes and
services; they have to re-imagine the end-to-end delivery
and experience of those processes and services. In doing
so, there’s ample opportunity not only to disrupt existing
industries but to define new markets.
Etihad Airways has reimagined what it means to operate
an airline in a digital world. Working with Taleris, a
provider of intelligent operations services, Etihad Airways
will tap the industrial Internet and use sophisticated
software to harvest and analyze data generated by
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hundreds of sensors working inside its planes. The tools
will allow Etihad to monitor planes in real time, reduce
fuel costs, manage plane maintenance, and even spot
problems before they happen.17
Enabling many of these advances is the concept that
data can be acquired, analyzed, and acted upon in real
time. The underlying concept is hardly novel: it applied to
the earliest anti-lock brake systems on cars, and it’s true
of many more complex systems today. The difference,
however, is that today’s digital-physical systems often
have orders of magnitude more data to help make more
informed decisions within a window of opportunity
that matters.
This “iteration capital” is a force multiplier at Ford Motor,
where 3-D printers radically reduce iteration cycles in
the design process, saving an average of one month of
production time for new engine parts, for instance.18
At
motorcycle maker Ducati, design cycle time has been
halved by leveraging 3-D printing.19
And the U.S. Army
is experimenting with 3-D printers to eliminate the need
to carry so many spare parts. The precision enabled by
today’s additive manufacturing technologies is leveraged
by GE to make parts that were simply not possible with
previous manufacturing technologies.20
In all of these
examples, companies are pushing decisions to the edge
in ways that were never before possible.
The entire transportation ecosystem is ripe for disruption
by digital-physical systems. When driverless cars
become common, not only will they change commuters’
experiences, they are expected to reduce the incidence
of traffic accidents, improve the density of road use,
smooth subsequent planning for maintenance and new
road construction, ease long-term planning for other
transportation systems such as light rail, and much
more. Overall, driverless cars will radically disrupt the
shipping and logistics industries, fleet services, public
transportation, taxicabs, rental cars, agriculture, and
mining industries. What’s more, insurance liability
markets will likely undergo dramatic changes as car
manufacturers move to self-insure, offsetting their
distributed risk via reinsurance markets.
In case there is any doubt that such technologies are
in our future, public policy—often the biggest laggard
in innovation economies—is keeping pace. In the U.S.,
California, Nevada, Michigan, and Florida have already
passed legislation allowing driverless cars on the roads.21
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The U.S. federal government has instructed its Federal
Aviation Administration to publish rules that will permit
drones to use public airspace by September 2015. Nearly
a dozen EU member states have no laws preventing small
drones from flying below 150 meters.22
Decisions on the edge are powering innovations for
consumers and businesses alike. To lead, companies need
to identify the decisions they would like to shape and the
places where they can build decision spaces to inform
those decisions. From there, companies will have new
opportunities to shape behaviors in new ways.
Shaping consumer
behavior
What’s perhaps most intriguing about digital’s
amplification effect is that it’s directly allowing
businesses and the enterprise to identify and replicate
productive behaviors. Furthermore, it’s creating the
expectation that every experience can and should be
optimized. There is significant potential to shift employee
behaviors away from preparing for every permutation of
“Organizations that understand the
potential of behavior shaping and
respect its privacy implications will
enjoy consumer loyalty and employee
engagement.”
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an experience and toward developing new and simpler
experiences altogether. These experiences prove to be
better for the end user and to be more cost-efficient for
the enterprise to implement.
Royal Caribbean International cruise line has shown its
grasp of technology’s ability to empower travelers and
optimize customer experiences. Eager to ease long lines
for shipboard restaurants—a perennial complaint from
passengers—Royal Caribbean uses sensors to relay to
passengers the real-time seating availability at each
of the restaurants on its ships. In other words, Royal
Caribbean moved dining decisions to the edge by giving
its passengers the data they need to decide where and
when to have a meal. Passengers are happier and the
cruise line was able to discard cumbersome scheduling
processes, making it a win-win situation for everyone.23
This behavior-shaping capacity can be tuned by the ways
in which information is presented to a user. For example,
if a city wants to reduce its collective carbon emissions,
it might offer a transit planning app that provides route
planning guidance on the least carbon-intense mode or
route in addition to the quickest.
Organizations that understand the potential of behavior
shaping and respect its privacy implications will enjoy
consumer loyalty and employee engagement. The key
is to notify individuals about how their activities are
being monitored, give them the choice of opting in,
and explicitly share with them the choices of actionable
information at the decision point.
These aspects are crucial. Privacy issues are likely to
keep making headlines as privacy watchdogs jump in
to defend against unauthorized tracking of citizens and
consumers. The company that can build a reputation
for providing valuable services while using consumers’
personal data in trustworthy ways will have big
advantages over competitors. Its brand will be more
valuable, it will have more opportunities to attract and
retain lifetime customers, and it can become a preferred
partner in a larger value chain of goods and services.
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Next steps for businesses
Are consumers already buying smartwatches? They are.
Is there a long waiting list for Google Glass? You bet. It’s
fair to say that there will always be individuals who are
eager to acquire technology to become better informed
and to be able to enjoy different and hopefully better
user experiences.
Businesses are likely to be more circumspect about the
migration of decisions to the edge. Accenture expects
that business-to-consumer organizations will be quite
quick to respond to consumers’ eagerness for and
openness to new experiences, offering everything from
new mobile couponing opportunities to new ways to
monitor and improve their health.
In the broader business world, there are enormous
opportunities to move employees’ decisions closer to
where they can take action. That much is apparent when
so many employees keep their mobile phones close to
them in the workplace. But businesses’ embrace of the
next generation of automation will be cautious.
Accenture anticipates three phases of uptake. The first
impact will be on making current ways of doing things
much more efficient. The second phase will see digital-
physical systems start to create industry disruptions.
Disruption will begin as it always does—by changing
users’ expectations of what is acceptable, normal. The
businesses that proactively alter users’ experiences
will be the disrupters. The third phase will be in how
organizations respond. They will need to ask questions
about how truly intelligent automation will change
interactions with and expectations of their customers
and other stakeholders. Will it open up new business
opportunities? Will it change the productivity equation
in the workplace? Will it materially change how we plan
our use of resources? Will it simplify our organization’s
structure?
The businesses that arrive at the best answers—and
that can properly leverage the strengths of machines
(precision and scale) alongside the strengths of people
(insight and decisions)—will be setting themselves up
with market-leading advantages.
#techvision2014
24

Your 100-day plan
In 100 days, promote decisions at the edge by completing
the following:
• Take an inventory of devices at the edge of your network;
segregate them by those used by humans and those
that act on their own, such as sensors and embedded
intelligence.
• Catalog how data is currently being collected in your
organization to drive business decisions. Understand how
having more data about daily operations could improve
business outcomes.
• Define and prioritize both the ways in which consumers
engage with your products or services and the locations
where they engage. Brainstorm ways to deliver compelling
user experiences that offer new insights into their
decision making.
• Consider how you can influence behaviors or decision
making to help consumers arrive at a favorable outcome
for your mission or business.
• Look to early adopters to learn what businesses in different
industries are doing to enhance consumer experiences,
enable field workers, and embed intelligence into their
physical assets.
• Organize a cross-functional mobility team between your IT
and business organizations. Their objective will be to pilot
relevant hardware innovations and test new consumer and
employee digital-physical experiences.
• Collaborate with your customer-facing business units
to capture the types of edge decisions they often make.
Determine how they will benefit by adding data with real
time analytics at the point of action and create a strategy
to deliver that solution.
• Reevaluate your corporate privacy policy to address the
new digital-physical interactions for your business. Data
collection, usage, transparency, and user control (opt in/opt
out) guidelines should be clearly addressed.
• Uncover the types of decisions that can alleviate oversight
obligations from middle management and start to build
decision spaces for front-line workers to take autonomous
actions.
25

sidebar
Digital augmentation makes every
worker an information worker
To-date, corporate technology investments have focused
on improving the efficiency of only certain staff: high-
cost knowledge workers. That is changing. Intelligent
devices are now sufficiently abundant, inexpensive, and
connected, empowering workers at every level to perform
their jobs with greater efficiency, productivity, and safety.
Front-line workers are becoming information workers
with some of the same augmentation technologies that
improve the performance of knowledge workers.
These new information workers are able to make
informed decisions in real time, acting in the tangible
world with the right information at the right time—often
using their own mobile devices rather than technology
supplied by the organization, yet interacting with the
organization’s back-end IT systems.
For example, paramedics in Champaign, Illinois, and
Grand Rapids, Michigan, are using their own smartphones
and tablets to increase access to medical information,
find drug dosages and interactions, and share insights
This time next year
In 365 days, you should step up your business agility by
pushing decisions to the edge:
• Develop a portfolio of pilots to deliver actionable insights to
employees and customers and that considers hardware and
software solutions. Aim for increased data resolution over
what is provided today. Monitor outcomes related to those
decisions, and consumer experiences.
• Extend your infrastructure to support enterprise mobility
for core business functions.
• Develop a real-time data analytics infrastructure to support
the data velocity and insight needs of digital–physical projects.
• Develop a governance strategy to act on real time feedback
loops to enhance decisions at the edge.
• Proactively address potential data privacy issues as new
pilots and projects are developed. Urge leaders to go
beyond compliance, giving end users transparency and
control in an effort to mitigate corporate risk and liability.
• Start planning for known technology disruptions coming
down the pipeline. Example: your business will make use of
autonomous vehicles and aerial drones. Be disruptive. Plan
on aerial drones being available for use in late 2015 and
driverless cars in 2020.
#techvision2014
26

with the destination hospital while a patient is in transit.
In the past, if this research happened at all, it would
happen when the paramedics arrived at the hospital or
returned to their depots. Now, the research can happen
in near real-time and have meaningful impact on the
course of treatment.24
The paramedics are newly enabled
by information that provides critical insights within a
narrow window of opportunity; those insights can spur a
decision “on the edge” that can possibly save a life.
In similar ways, developments with wearable technology,
such as Google Glass, may provide field-service
professionals in the oil and gas industry with access to
real-time information and deep expertise—improving
their effectiveness at fixing remote pipelines and
maintaining highly sensitive infrastructure.
As front-line workers have their capabilities augmented
by digital technologies, they are emboldened to make
more informed, real-time decisions and encouraged to
become more engaged with the organization. This drives
operating efficiency and revenue growth. Studies have
shown that companies with high employee engagement
frequently demonstrate higher levels of operating income
and growth in earnings per share than those found to
have low levels of employee engagement.
The implications of digital workforce transformations go
beyond updating bring-your-own-device (BYOD) policies.
Realizing the efficiencies from digitally augmented
workforces will require business leaders to fundamentally
rethink how employees do their jobs and reassess the
back-end systems that support them. Leaders will also
need to be comfortable with decentralized decision-
making as business decisions get pushed closer to the
edges of their business. Chief information officers
(CIOs) will need to be more cognizant of potential risks
associated with data privacy and security. Real-time
information systems will become a higher priority.
Getting information to workers as they need it will
allow businesses to uncover a workforce that is more
productive, eager for new challenges, and more effective
and efficient at making and sharing decisions by
collaborating with others. The benefits can rise above
quantity and quality of work output by contributing to
the flattening of organizations—meaning that a smaller
number of supervisors and middle managers can manage
larger and more dispersed teams.
27

#techvision2014
28
TREND 2: FROM WORKFORCE TO CROWDSOURCE

TREND 2
From workforce to crowdsource:
The rise of the borderless enterprise
Picture a workforce that extends beyond your employees: one
that consists of any user connected to the Internet. Cloud, social,
and collaboration technologies now allow organizations to tap
into vast pools of resources across the world, many of whom are
motivated to help. Channeling these efforts to drive business
goals is a challenge, but the opportunity is enormous: it can
give every business access to an immense, agile workforce that
is not only better suited to solving some of the problems that
organizations struggle with today but in many cases will do it
for free.
29

Why now?
Accelerated pace of IT change: The increasing pressure to
rapidly deploy new technology is accentuating some of an
enterprise’s biggest pain points: market insight, innovation,
and a need for highly specialized skills. These are areas for
which crowdsourcing solutions are well suited.
Maturation of crowdsourcing platforms: Communities of
shared interest have organically formed or are forming around
almost every product, service, and idea that can be imagined.
Crowdflower, Spigit, and Mechanical Turk are just a few of the
collaboration platforms that are rapidly evolving to enable
and orchestrate efficient solutions.
Strong case studies from early adopters: Some of the
biggest market disrupters, such as Facebook and large
enterprises including GE, are currently using crowdsourcing
services to solve their most complex problems, and everyone
is taking notice.
Where do leading companies like GE,
MasterCard, and Facebook go to solve
their toughest data science problems?
They don’t always turn to the professionals on their own
payrolls. Rather, they are beginning to turn to companies
like Kaggle—a global network of computer scientists,
mathematicians, and data scientists who compete to
solve problems ranging from airline flight optimization
to retail-store location optimization. This is just one
glimpse of how the concept of the corporate workforce
is changing.
Over the last decade, organizations have been using
increasingly advanced tools and processes to boost
collaboration among their employees. Videoconferencing,
instant messaging, blogs, wikis, and activity streams have
all become the norm as large companies push to connect
their employees across groups, skills, and geographic
boundaries. Outside of the enterprise, these patterns are
even more pronounced: tools such as Twitter and Yelp
and Wikipedia connect huge swaths of the population
to discuss and collaborate on everything from new-car
reviews to health care.
30
#techvision2014

Given that so much collaboration happens through
digital channels, there is the potential for almost limitless
collaboration with everyone else who is connected to the
Internet—regardless of whether they are “our” employee
or not. Which raises a crucial question for business and
IT leaders: “Are we missing out by not connecting to this
‘expanded workforce,’ everywhere and in all directions?”
The short answer is “yes.”
Digital connection
platforms
More and more digital platforms are available that make
it easier to connect to what Accenture calls the expanded
workforce. Kaggle is just one of these; others include
Amazon’s Mechanical Turk, along with services such as
Elance and oDesk. All of these can be considered online
labor markets. They help companies that have tasks that
need to be accomplished connect with resources that
have the right experience, ability, and time.
Although many organizations are experiencing the
benefits of digitally enabled forums such as innovation
exchanges and crowdsourcing platforms, few executives
yet fully grasp the idea of being able to access a truly
liquid workforce—pools of premier talent gathered in
virtual communities and coalescing around specific
business problems. This expanded workforce likely offers
not only expertise that is not immediately available in-
house but also real scale. It can be leveraged to solve
problems that may be too large or too expensive to solve
internally.
Name almost any challenge—early detection of driver
drowsiness or the predictability of drug targets or
electric-only updates to hybrid cars—and there are
often already communities of experts that companies
can leverage to competently address it. The individuals
involved may be around the corner or on the other side
of the world; what they have in common is not only the
experience and expertise to solve the problem but the
motivation—in many cases the passion—to do so.
The tasks involved may be as simple as data entry or
as complex as industrial design. The individuals—the
problem solvers—may work on a project or just part
of a project. They may be paid; they may compete for
prizes. But whatever their incentives and their spheres of
interest, the unifying feature is that their contributions
are made possible with digital tools.
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The expanded workforce
in action
Take the automotive startup Local Motors for example.
Its Rally Fighter car can’t easily be called beautiful, with
its scrawny jellybean body perched high above gangly
struts and monstrous off-road wheels. Its real beauty is
in how it came to be—not how it looks.
A harbinger of the future, Local Motors created a global
community of car enthusiasts that included engineers,
mechanics, and industrial designers and broke down
the creation of the vehicle into a set of tasks that
were widely distributed, via the cloud, to this eclectic
workforce. In just 18 months, those individuals—working
closely with the company’s employees—designed,
manufactured, and delivered a car that this user
community loves.1
Local Motors provides a provocative example of
leveraging an unconventional workforce to accomplish
something previously thought impossible. So intriguing
is Local Motors’ social-plus-collaborative take on car
making that it has attracted some blue-chip partners,
such as BMW. BMW hopes to use the startup’s expanded
workforce model to move beyond typical focus groups
and inference, developing and testing new automobile
interiors that reflect users’ true desires rather than
incomplete and veiled answers.2
Local Motors’ real innovation is conceptual. Its leaders
imagine and leverage limitless talent instead of being
boxed in by what has traditionally been a predetermined
workforce. They see talent that may already be waiting
to solve some of the challenges the organization has yet
to confront. “There are two ways to build things,” Local
Motors’ co-founder and chief executive Jay Rogers told
an industry publication. “You can hire the relevant people
to solve a problem—or you can organize in the cloud to
get better ideas faster.”3
A crucial point to make is that the use of the expanded
workforce is not another form of labor arbitrage. It is not
to be confused with employing contractors or temporary
labor or moving to an outsourcing arrangement. The
channels, structures, and transactions are entirely
different—far more fluid and versatile than any familiar
forms of accessing human resources.
#techvision2014
32

It will be essential that borderless enterprises work to
harness the energies and enthusiasm of the expanded
workforce. The current workforce is not going away,
of course; not every problem will be well suited to
crowdsourced solutions. However, it is no longer enough
to rely only on groups of in-house individuals to drive
market research, innovation, and product-development
activities. Digital technology has brought a global voice
to those functions. It is pushing out the boundaries that
previously defined the enterprise workforce. It’s not an
overstatement to say that business leaders now need
new perspectives on the nature of work itself.
Let’s walk through a few of the ways in which leading
businesses are starting to harness the expanded
workforce.
Marketing moves toward
perfect information
The expanded workforce is already changing the
way companies market their products and services.
Technology platforms that promote comments, user
interaction, and even consumer investment are giving
consumers a direct voice with which to communicate
with the marketing department. In doing so, these
platforms create a porous membrane between paid
employees and the expanded workforce. Consumers are
providing richly detailed information, giving companies
an unprecedented level of insight into their products,
how they’re used, and the consumers that buy them.
With the right digital tools in place, producers can
predict better than ever how the market will react to
their products and who will buy them. They can segment
markets more discretely and test premium feature sets
to see who will pay for them. The new approach trades
abstract market projections for data-driven market
decisions; consider the difference in outcomes between
33

running small focus groups city-by-city and running
a crowdsourcing contest to solicit customer input.
Responses from 125,000 real-world consumers certainly
are more statistically sound—and arguably more honest—
than responses from 125 focus-group attendees.
The benefits of expanded-workforce input go further
still. Direct consumer feedback can furnish data on
pre-order sales that enables not only sales projections
but also raising of working capital that can be used to
begin manufacture of the actual product. In this way,
the expanded workforce becomes an invaluable tool for
reducing product inventory risks. This is market insight
that is not confined by four walls or hidden behind
artificial representations of consumers’ wishes.
A few examples stand out. Walmart Labs, the digital
technology division of the world’s largest retailer, is
embracing the power of the crowd to determine which
items the company should stock in its stores and on its
website. Using a contest titled “Get on the Shelf,” which
was heavily promoted on Facebook, Google+, and Twitter,
the company offered a way to democratize the job of the
store buyer and bring shelf selections in line with shoppers’
expectations—and wants. The effort was intended only
as a “fun experiment”—which it was, but it also provided
Walmart with a clear view of the demand for products
not currently on its shelves. Consumers voted online for
the products they wanted to see sold at Walmart; winning
entries for new products won prizes and a grand-prize
winner was chosen from the top three contestants.4
Similarly, snack maker Lay’s has used consumers’ creativity
to launch new flavors. The company has run flavor
naming and defining contests in more than 15 countries
since 2008. One recent U.S. initiative that used the
slogan “Do us a flavor” drew nearly 4 million proposals.
The winning flavor—“cheesy garlic bread”—was chosen
from the votes of the company’s fans and by a panel of
experts who included a popular TV actress and several
top chefs. The new flavor is now widely available for sale.5
Of course, there is no stronger indicator of market
interest than customers’ willingness to part with their
money. These days, more and more businesses are using
“crowdfunding” platforms such as Kickstarter to help
validate product development. Kickstarter is the granddaddy
of crowdfunding sites—new businesses that use Web-
based collaboration, social media, and microfinancing
techniques to raise money for everything from new film
#techvision2014
34

projects to seed funding for small businesses. Since
Kickstarter launched, in 2009, over 5 million people have
used the platform to pledge more than $900 million,
funding more than 50,000 creative projects.6
Companies are using Kickstarter and similar platforms
not just for fundraising but to provide market insight
and product viability assessments for a fraction of
what those services typically cost. By determining what
people will actually pay for, the process influences and
validates products and pricing strategies and sometimes
leads to initial consumption and to product advocates.
Accenture has developed initial models that show that
crowdsourcing, when used correctly, leads to higher
profits for producers.
Tesla Motors is an example of a company that has taken
this idea to the next level. The maker of electric cars has
asked for advance reservation fees from customers—
$5,000 per car—not only confirming the extent of demand
but providing Tesla with working capital to the tune of
$130 million. These “funds” are willingly provided by
eager buyers for zero percent interest. Otherwise, Tesla
might have to pay 10 to 15 percent to a bank.7
“With the right digital tools in place,
producers can predict better than ever
how the market will react to their
products and who will buy them.”
35

Taking innovation
off its leash
Innovation is now at or near the top of the C-suite agenda
in every organization. But it remains difficult to execute—
difficult to scale up and to ramp up fast, and hard to
ensure that the results are of the quality expected. Yet
innovation is happening organically everywhere, whether
business leaders are aware of it or not; communities of
shared interest have formed or are forming around almost
every product, service, or idea that can be imagined.
There are new platforms, such as Spigit, that can
help to propel the innovation process quickly and
effectively. Another example is TopCoder, a mechanism
for running computer-programming competitions. Such
platforms capitalize on the very human urges to create,
solve problems, and pursue knowledge. Many people
are powerfully energized by the idea of developing
innovations that solve big, intractable problems. The zeal
of those working on the Human Genome Project, an
ambitious undertaking to fully map the human genome,
is ample evidence of that.
Organizations can’t depend solely on existing or
emerging innovation solutions. They should be willing to
create comparable platforms and communities. Roughly
a decade ago, pharmaceutical company Eli Lilly spun
off InnoCentive, an innovation exchange that now has
more than 300,000 registered problem solvers from 200
countries. Essentially, the company marries this expanded
workforce to cloud-based technology to solve problems
posed by customers. Winners receive substantial cash
prizes. To date, more than 1,500 awards have been
given, with the size of the award ranging from $5,000
to more than $1 million, based on the complexity of the
problem and nature of the challenge.8
Similarly, companies such as Facebook and Twitter are
leveraging the intellect and energy of the crowdsource by
using application-programming interfaces to open up their
platforms to the development community at large. This
open approach encourages individual developers and
companies to innovate and create products that solve
problems and issues that might never surface in the
interactions of those companies’ conventional workforces.
The open approach not only motivates the users of the
platforms; it creates substantial additional value for the
platform and subsequently for the platform owner itself.
#techvision2014
36

Fast-tracking product
development
The open-source community is the original expanded
workforce—the trailblazers, united by ideas and interests,
who helped write the rules and define the tools for
freeform ways of developing software. Collectively,
these impassioned individuals make up a global army
of developers who are creating and improving free
software, bringing worldwide benefits server by server,
device by device, for free.
This expanded workforce has touched every organization
in some way. Witness the widespread use of two outputs
of open-source projects: Hadoop and Linux. The first is
the engine that is powering the Big Data era; the second
is the kernel operating system embedded in 23 percent
of installed enterprise servers, over 80 percent of
smartphones shipped, and countless other systems
ranging from embedded sensors to supercomputers.9
It can be argued that the open-source movement has
changed the face of software development just as much
as the move from punch cards to hard disks did. Open-
source initiatives are foundational for companies such
as Yahoo and Google. Android is based on Linux; it is
projected to constitute nearly half of all mobile operating
systems (smartphones and tablets) by 2017.10
Nowadays, the largest technology players all have
significant roles in open-source development. Companies
including IBM, Microsoft, and Oracle—once strongly
opposed to all things open-source—are official, vital,
and prolific contributors to the open-source community.
The open-source paradigm has now moved to hardware
development, as seen with Facebook’s Open Compute
Project and Hewlett-Packard’s Pathfinder Innovation
Ecosystem Solutions initiatives. But it shouldn’t be
limited to just tech companies. Businesses of all kinds
should engage in these open-source communities. By
contributing ideas, time, and code, companies help set
the overall direction of product development, allowing
them to leverage not just software that is free but
software that targets their specific needs and problems.
Software is also just one example of using the expanded
workforce for product development. From smart watches
to smart vehicles, the expanded workforce is being
employed by bold companies to energize their product
37

development. The expanded workforce is becoming an
invaluable filter for reducing product development risks,
improving time to market, and determining receptivity
to new-product introductions. For example, the Pebble
watch Kickstarter campaign not only raised more than
$10 million in 2012 but allowed the company to gather
valuable product intelligence about pricing and product
demand. By interacting directly with its target customer
base, Pebble was able to determine that consumers were
willing pay $150 for one of its watches and that 85,000
watches, once funded, would be mailed in the first month.11
Using the crowd—
and its assets
Innovating, marketing, and developing products are by
no means the limit of what the expanded workforce can
help with. The concept is expanding to include people’s
assets as well as their time. Just one snapshot: Local
Motors quite literally uses its customers as free labor,
and the buyers of its Rally Fighter car actually pay for the
experience of participating in the car’s assembly.
In fact, the use of the crowd’s assets can launch new
businesses that are well positioned to attack long-
established sectors. Airbnb is a classic example. Billed as
a trusted community marketplace where people can list,
discover, and book unique accommodations around the
world, Airbnb uses the crowd as the untapped source of
places for travelers to stay. In effect, everyone can offer
their own home or apartment as a kind of hotel. Airbnb
is possible because digital tools—particularly mobile
phones—make it very easy to find, select, and obtain
accommodation. Not surprisingly, the startup—it was
founded in 2008—is seen as a significant threat by the
hotel industry.
Similarly, Uber crowdsources assets (in this case, cars)
by connecting drivers with people needing a ride, a
model that the taxicab trade views with alarm. And
RelayRides—through which car owners rent out their own
vehicles—presents competition to the established rental-
car business.
Current markets are being disrupted and new markets
are being discovered by companies that are employing
latent talents or assets made available through digital
technology. Businesses can no longer be on the sidelines
#techvision2014
38

watching and waiting to see what will happen next
and hoping to grab the coattails of the next big idea.
The enterprise needs to be out there experimenting,
discovering, and creating the next big idea.
From doing
to orchestrating
So, there is no shortage of people willing to participate
in online experiments, contests, challenges, and more.
Individuals are surprisingly ready to work for little or
no money if they get other rewards: prizes, recognition,
fame, the sense of pride in getting to create something.
But how do business leaders then effectively manage the
flow of talent and ideas? How do they effectively keep
control when their workforce moves from hundreds or
thousands to tens of thousands?
Given the relative immaturity of these crowd-based
services and platforms, there’s still much to be learned.
The strengths of these services can also be their
limitations. However, although there are no clear lines
or absolutes when employing the expanded workforce,
there are already some useful guiding principles for
planning and implementing platforms for crowdsourcing.
The use of the expanded workforce demands very diligent
planning. There must be clear, shared objectives for the
crowdsourced exercise, whether the requirement is for
new solutions to tough engineering challenges or for
funds for new-product development. And complex tasks
must be clearly and logically broken down into a series
of independent subtasks that can be parceled out to the
crowd in a way that allows the crowdsourced efforts to
be reintegrated into the overall product or project. In the
case of labor market exchanges, there can be no subtlety
in the work description; amplified across hundreds or
perhaps even thousands of “workers” in the expanded
workforce, inexactness will produce meaningless results
or work that cannot be re-aggregated.
This need for structure requires more than just planning;
typically, it will also require a technology solution to drive
users through the process. A superb example of this is the
DARPA Language Challenge, which leveraged Amazon’s
Mechanical Turk platform. The challenge was to translate,
from Arabic to English, messages that were communicated
on social platforms, where traditional grammar rules are
not used and context is paramount. Using the correct
platform, precise planning, and the expanded workforce,
39

DARPA was able to translate more than 200,000 words
per week from Arabic to English. This project required
partitioning the work up meticulously, with explicit
quality-assurance steps, and ranked incentives for those
who provided higher-quality translations. By using a
crowdsourced model, DARPA was able to shift its effort
from finding, recruiting and hiring the correct resources
to where it will do the most good, innovation around
developing the project, planning and incentives.12
It is also crucial to properly engage the expanded
workforce. With crowdsourcing, adoption is paramount;
lacking a properly motivated and incented community,
nothing gets done. InnoCentive provides a great example.
The knowledge exchange has not become a powerful
platform for innovation without paying close attention
to every aspect of its operations—from setting the
size of prizes for “solvers” to how it communicates the
challenges. One more snapshot: Quirky, a co-creation
company whose crowdsourced product innovations are
sold through mainstream retailers such as Target, has a
disciplined weekly voting process—online as well as on-
premise—to select the product ideas that it will put into
production.
It’s still early days for the use of an expanded workforce,
and being a borderless enterprise brings its own challenges.
For instance, the inherent transience and anonymity of
the expanded workforce places sharp limits on traditional
human resources activities such as job training. And
it raises many thorny questions about the security of
intellectual property.
Despite these challenges, the opportunity is immense
for enterprises that are willing to step up. The companies
that get it right will find themselves with better insight
into their customers, more-innovative products and
services, and an increased agility to retool themselves
with the skills necessary to respond to the changing
technology landscape. The question is this: how are you
going to position your enterprise to reap the rewards?
#techvision2014
40

Your 100-day plan
In 100 days, learn about the variety of options that contribute
to the borderless enterprise and begin to create a strategy for
how you can harness the crowd moving forward.
• Identify any existing enterprise connections to established
expanded workforce platforms.
• Determine how your competitors are using crowdsourcing.
• Evaluate the benefits your market research, product
development and innovation functions could reap from
using expanded workforce platforms.
• Develop an initial strategy to engage existing online
communities in support of your core functions. Where it
aligns with your core business, create a catalog of existing
online communities that are specific to market-research and
product-development functions.
• Consider assets from the open-source software community
that are usable for your core IT functions and begin
planning how to integrate them.
• Design and implement a pilot to leverage the established
expanded workforce that most aligns with the nature of
your business.
This time next year
In 365 days, you should be familiar with the various types of
crowdsourcing platforms that apply to your business and have
started an integration strategy.
• Identify which tasks are most easily broken into smaller
independent tasks and conduct pilots with existing or
custom-built expanded workforce platforms to resolve them.
• For market-research and product-development functions,
start to figure out how to engage consumer communities.
Where communities are not yet mature or specific enough,
develop a strategy to build them.
• After completing a few pilots, test your orchestration
strategies. Aim to seamlessly bring solutions, no matter how
small, back into the enterprise.
• Create and implement governance and cost-control
strategies to respond to and manage infinite capacity.
• Understand the types of specialized skills that cause surges
in demand for your organization. Determine whether
adoption of expanded workforces can resolve these surges
and reevaluate your hiring structure in response.
• Develop an authorized and trusted talent cloud with an
established expanded workforce community.
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#techvision2014
42
TREND 3: DATA SUPPLY CHAIN

TREND 3
Data supply chain:
Putting information into circulation
Yes, data technologies are evolving rapidly, but most have been
adopted in piecemeal fashion. As a result, enterprise data is
vastly underutilized. Data ecosystems are complex and littered
with data silos, limiting the value that organizations can get
out of their own data by making it difficult to access. To truly
unlock that value, companies must start treating data more as a
supply chain, enabling it to flow easily and usefully through the
entire organization—and eventually throughout each company’s
ecosystem of partners too.
43

Why now?
Corporate data silos: Data is the lifeblood of every digital
organization, but businesses are struggling to access, share,
and analyze much of the data they already have. Through
2015, 85 percent of Fortune 500 organizations will be unable
to exploit big data for competitive advantage.1
Rising data volumes: In addition to the data that
organizations already collect, new external data sources are
available, providing new opportunities for data insights. The
digital universe is doubling every two years and is expected to
grow to 40 trillion gigabytes (more than 5,200 gigabytes for
every man, woman, and child in 2020).2
Maturing data technology: The tools and technology
required to build a data platform, ensuring data access and
velocity, are available and in use. For example, a reported
20 percent of enterprises are already using NoSQL.3
With the
foundation of these technologies, the integrated, end-to-end
data supply chain is possible.
For years now, data has been talked
about as the premier strategic IT asset.
Today, it’s so much more than that.
Business leaders now view data as among their most
valuable assets too—some even call it the lifeblood of
their organization. That’s why they’re implementing the
newest big data tools, investing in advanced analytics
applications, and purchasing the latest data visualization
software.
Yet the reality is that these easily become one-off data
fixes that contribute to data silos rather than provide
an end-to-end data solution. Few companies have
mastered the concepts at the foundation of modern data
management—ideas such as the mobility and portability
of data, its structure and velocity, data as a “saleable”
product, and its valuation in open data exchanges.
Fewer still are comfortable with these concepts at scale.
Most efforts to properly manage data are ad hoc at best.
No wonder half of all companies are concerned about the
accuracy of their data and a majority of executives are
unclear about their analytics programs’ business outcomes.4
44
#techvision2014

According to research by Gartner, 85 percent of Fortune
500 organizations will be unable to exploit big data for
competitive advantage through 2015.5
The high performers, however, will embark on a journey
to ROI; they will liberate their data, generate value from
it, and operationalize insights to drive strategic decisions
through the organization. Key to their success will be
managing their data like any core product—in the context
of a supply chain. The supply chain begins when data is
created, imported, or combined with other data. The data
then moves, flows, and transforms through the supply
chain, incrementally acquiring value. And while there
may be diversions along the way, such as when a data
“product” is removed for repairs (in other words, data
cleansing), the supply chain ends with a valuable insight
as its output. Guiding this movement is a data services
platform. Analogous to the blueprint of a factory floor,
this platform provides the structure for the intelligent
transportation of data throughout the organization. It
enables the effective supply chain—fit to strategy and
designed to drive outcomes.
This means that business leaders now need to develop
an end-to-end view of data in order to achieve their
business goals. Accenture’s earlier Technology Vision
reports have dived deeply into the keystone data topics,
highlighting the value of data platforms, the importance
of industrializing data services, and the need to think in
terms of the velocity of data as well as its variety and
volume. Now, all of those themes must come together in
an end-to-end “supply chain” perspective that can help
break down the data silos—usually built and “owned” by a
single department—and enable data to flow freely for the
benefit of the whole organization.
Working in this way, however, will change how the
enterprise works with data at each stage. New sources
of data can be leveraged. How data is managed and
analyzed will evolve. And companies will begin to explore
new ways to monetize their data. Understanding the
implications at each of these stages will be critical for
business leaders if they are to capitalize on the value
of their data now and in the future and, importantly,
at scale.
45

Enabling the data
supply chain with a data
services platform
The data supply chain must enable data movement. And
in order for data to move, it must be made visible and
accessible to those who need it when they need it. As
such, the first step is to create a data services platform
or federated data access layer, which provides a standard
method of access to an organization’s curated and
trusted (albeit varied and siloed) data in a time-relevant
manner. Currently, only one out of five organizations
integrates data across the enterprise.6
But those few are
realizing great benefits. For instance, a major bank has
been able to use Palantir’s Capital Markets solution to
integrate 15 data sources into a single point of access.
This has allowed hundreds of analysts and less-technical
business users to do a variety of tasks, including
performing regression analysis, developing hedges, and
assessing investment risks.7
In order to realize their data platforms, organizations
must first make their disparate data sources accessible
through data services—ranging from Lightweight
Directory Access Protocol (LDAP) to Web services or
application-programming interfaces (APIs). Regardless
of the specific type, the power of these data services is
in their ability to mask back-end complexity and expose
data in defined ways. Once all of the data sources have
been opened up, one common solution is to make them
accessible through a virtualized data layer, which unifies
everything into a single view. Then, users can interact
with this abstracted data platform in a standardized way.
(Behind the scenes, they are actually being rerouted to
the data sources.)
Many newer data platform strategies now depend on
opening up each data source separately, but through
a common standard access protocol. Increasingly,
companies are turning to APIs to achieve this, and they’re
often aided by API management platforms. Walgreens,
for example, has opened up its prescription API to enable
third-party developers to incorporate the technology to
scan barcodes on prescription bottles, in order to make it
easier for customers to refill their prescriptions.8
#techvision2014
46

These are just two of many data platform solutions
in a market of vendors offering a wide variety of
methods to create this federated access layer. Traditional
middleware providers such as Tibco Software and Red
Hat have evolved their messaging solutions to provide
that abstraction layer. Companies such as Apigee are
touting their API management software as the solution.
Additionally, Platform-as-a-Service (PaaS) providers such
as Amazon and Windows Azure are offering readymade
solutions already built into their clouds. And large
database vendors—such as Oracle and Microsoft—are
creating access layers to allow connections to data
silos in order to better manage the flow of information
throughout an organization.
In the end, there’s no one-size-fits-all solution; most
enterprises will end up with a hybrid set combining
many of these tools. But no matter what the solution,
it’s important to understand that data access and data
acceleration make the data services platform both
possible and necessary—and thus help to realize the data
supply chain at scale.
Accelerating data
through the supply chain
Data access on its own isn’t enough—velocity is needed.
Importantly, this does not mean that all data needs to
move at top speeds at all times but rather that data
needs to be prioritized on the data services platform—
such that important, time-critical data is accelerated
through the supply chain, while stale, less relevant data
moves more slowly but still meets the demands of the
business. Quick access to valuable data means that
analyses can be performed, insights can be gained, and
actions can be taken in the sometimes very small window
of opportunity available to businesses. Historically, IT
professionals have addressed this problem by giving
precedence to “hot” data—data that is accessed frequently
and saved onto high-performance systems that can store
and retrieve it very quickly. For its counterpart “cold”
data—tax records, say—they have used slower disk
hardware or even tape backups in legacy systems.
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While these strategies have worked, newer prioritization
practices improve data acceleration by adding many
more gradations of “data temperature”—or data tiers. This
makes sense when businesses consider the wide range of
how, when, and how fast users need to consume data.
The next step is to enable dynamic movement of data
through these tiers, meaning they can be “heated up”
or “cooled down” at any time. The ability to seamlessly
change priority over time based on business need
improves data velocity—but it’s also an efficient and
cost-effective capability.
Facebook shows how. Not long ago, the social network
discovered that 8 percent of all Facebook photos
accounted for 82 percent of its network traffic. It turns
out that there is a marked drop-off in accessing photos
as they age, meaning that the photos’ data may be top
priority at some point but not always. This led to
Facebook’s development of its own three-tiered data
storage solution. Its software categorizes photos and
stores them in the appropriate tier, which has dedicated
hardware to increase savings—the lower tiers (for
colder data) can store more photos and use less energy.
While the hot, tier-one data can be accessed almost
instantaneously, one of the unique aspects of Facebook’s
solution is that even cold data can be retrieved quickly
(most solutions require several hours) to better meet users’
expectations. In this way, Facebook is both increasing its
photos’ velocity and saving on storage costs.9
Tiered data solutions allow for time-critical and
commonly accessed data to be stored in data-centric
caching structures, optimized for quick transport
through the supply chain. But in all likelihood, most
data will eventually end up in the “data lake”—used to
store the vast quantities of an organization’s data that
are less time-sensitive or used less frequently. Although
historically the “data lake” was tape, technologies such as
Apache Hadoop and Amazon Redshift have been able to
keep costs low while maintaining data accessibility. With
a greater number of data tiers, more data can be stored
longer and at a lower cost, without interfering with
access to important, time-relevant data.
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More uses for
more data sources
The supply chain process starts with ingesting data.
These days, companies can use a wide variety of new
data sources—including, notably, data that they do not
control or own. For example, if a regional grocery chain
wants to analyze its daily transactions over the past
month, it should look beyond the data in its database
to supplement its findings. Many companies are already
tracking sentiment on social media sites; data can also
be analyzed in the context of weather, characteristics
of shoppers, events in the news, or virtually any new
data dimension imaginable—if the relevant data can be
located. Whether this “external” data is to be obtained
from partners, Data-as-a-Service providers, or open data
sources (free for anyone to use in any way they want),
companies should capitalize on the business value that
these new sources provide.
Collaborate.org is one example of an open data
source, containing 5 petabytes-plus of data.10
It is a
global collaboration platform (meaning that users are
encouraged to contribute data back to the platform) that
allows users to view data geospatially—such as satellite
imagery and air quality. The U.S. state of Hawaii is using
Collaborate.org to share data across organizations, and
it is the platform for the Exemplary State Initiative,
which monitors environmental efforts and enables early
identification of natural disasters.11
In similar ways, Beiersdorf, a global provider of skin
care products, is using their own internal data along
with syndicated data from research companies such
as Nielsen to provide board members with market
share development information across a variety of
products, brands, and countries. Using SAP Demand
Signal Management powered by HANA, Beiersdorf plans
to automate its data integration process, leading to
more accurate and accelerated market share insights.12
These examples demonstrate the new opportunity that
businesses have to look beyond their four walls for
data that will grant more informed data insights and,
ultimately, more value.
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Advancing data discovery
The process of discovering new insights to answer
business questions is changing fundamentally as users
get faster access to more data. Now, when data is
manipulated as it moves through the supply chain, value
can be added to and obtained from it in ways that were
previously impossible. This is because data discovery
allows businesses to discover answers to questions that
they might never have known to ask in the first place.
Previously, traditional business intelligence (BI) methods
were the only way to answer prescribed business
questions; they require multiple lengthy steps before a
solution is possible. Now, however, data discovery helps
discern the very questions that companies should be
asking by uncovering insights in a visually interactive
and rapidly iterative manner. Effectively, data discovery
empowers users to “communicate” with data at close to
the speed of thought—accelerating businesses’ time to
insight. Companies can and should be investing in this
practice today.
So that businesses can better “communicate” with and
analyze data, analytics are being embedded in data
discovery tools (as they are in applications)—effectively
enabling data scientists and less-technical business users
alike to do data discovery more easily and intuitively.
As an example, the Teradata Aster Discovery Platform
enables data scientists to do data discovery and
advanced analytics themselves, but it also allows them to
extend those capabilities to business users by leveraging
analytic functions exposed through BI or other tools.
When business users, and even business leaders, are able
to discover and answer their own business questions in
a matter of minutes, intelligent insights quickly lead to
intelligent actions.
For instance, Texas Medical Center (TMC) understands the
importance of health care data to advance patient care.
However, this data can also be extremely complex and
difficult for anyone—from medical experts to data
scientists—to analyze. Therefore, TMC is using Ayasdi’s
technology—one that specializes in the analysis of high-
volume, high-dimensional datasets—to empower users to
find insights in their data. Using a visual representation
of the data and built-in statistical tools, users can more
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50

easily perform “semi-supervised analysis” of the data. The
ability to interact with data in this quick and iterative way
allows users to identify emerging patterns and accelerate
their time to insight. This approach first proved its power
when analyzing a breast cancer dataset (one that had
been analyzed many times already); within just a few
minutes, a new subset of survivors was identified.13
TMC plans to use Ayasdi for a variety of applications,
from analyzing clinical and genomic data to drug
repurposing.14
The truth is, every organization has
unexpected insights waiting to be unearthed by data
discovery methods. Now, it’s a matter of determining
those insights and accelerating their time to insight.
The next step:
cognitive computing
As the volume and variety of data grow, so too do the
scale and complexity of the data supply chain, making it
increasingly difficult to add to and get value from data
as it is manipulated. Imagine it this way, on a standard
supply chain: everyday, more and more raw goods
(some of them new) are being delivered. Initially, this
might sound great—more supplies mean more products—
but it’s not what the machines were designed to handle,
and workers can’t keep up with the maintenance
required. The supply chain becomes clogged, hindering
the creation of valuable products. But what if, instead,
machines could be taught to leverage data, learn from
it, and, with a little guidance, figure out what to do with
it? That’s the power of machine learning—which is a
major building block of the ultimate long-term solution:
cognitive computing. Rather than being programmed for
specific tasks, machine learning systems gain knowledge
from data as “experience” and then generalize what
they’ve learned in upcoming situations. Cognitive
computing technology builds on that by incorporating
components of artificial intelligence to convey insights
in seamless, natural ways to help humans or machines
accomplish what they could not on their own. At its
most advanced, cognitive computing will be the truly
intelligent data supply chain—one that masks complexity
by harnessing the power of data to help business users
ask and answer strategic questions in a data-driven way.
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Although complex, large-scale cognitive computing may
be beyond the reach of most companies, there are some
cognitive computing capabilities that can be put to work
in practical and affordable ways. Companies should focus
on tackling well-defined problems on a smaller scale—
where machine learning techniques can be leveraged
to accomplish practical cognitive computing goals. For
example, Tempo, the calendar application found on
iPhones, uses data contained on the phone—from social
media to email, location, and more—to “learn” about
events and display relevant information to the user when
requested. This smart personal assistant application
masks the complexity behind the data supply chain as
raw data is aggregated, analyzed, and turned into an
actual event with value. Only then does the user naturally
interact with the calendar through the phone’s interface.
One interesting cognitive computing example comes
from U.S. food company McCormick. Machines are now
starting to use data to “sense” the world as humans
do, and this extends to taste—with obvious benefits for
the food industry. Using Enterra Solution’s Cognitive
Reasoning Platform, McCormick’s FlavorPrint site asks
customers to rate a variety of flavors in order to learn
taste and, from that, creates unique taste preference
profiles—or what it calls FlavorPrints. If customers
provide additional information, such as cooking
preferences, equipment, and typical pantry items,
they can receive better personal product and recipe
recommendations. As far as these customers can tell,
they’re providing just a few raw facts in return for a
great deal of personalized value about taste—something
almost everyone feels strongly about yet finds hard to
quantify or specify. From McCormick’s point of view,
learning customers’ taste preferences leads to better
insights, product decisions, and, ultimately, ability to
serve its customers.15
Cognitive computing can, and will, bring benefits to
many industries, and it will fundamentally change the
ways in which many businesses operate. It flips the
problem of data volume and variety on its head and
instead leverages it to enable the smart, interactive
data supply chain. The ultimate goal is for any business
user—from a CEO to a field worker—to be able to ask any
business question and immediately get a data-driven
answer from the masked data supply chain.
#techvision2014
52

Although this technology may seem far off, there
are already cases that prove its relevance. And by its
very definition, with more data over time, cognitive
computing technology will only learn more, adapt
quicker, and improve. It’s important for business leaders
to familiarize themselves with this technology now.
Realizing data value
By the final stages of the supply chain, a significant
investment has been made in the ingestion,
transformation, and analysis of data—and now that data
is both accessible and sharable, companies have new
opportunities to capitalize on its value. Of course, data
is important internally, but companies must now realize
that the value of data extends outside the organization
as well. From forging new partnerships to creating
new revenue streams, or even entering new markets,
businesses now have more potential than ever to realize
the true value latent in their data.
When companies open up their data for external access,
they can profit by leveraging external developer talent to
extend their platforms. It’s a win for developers, too; they
can use these platforms to add value to their products
much more easily and at a higher quality than if they
had attempted to do so on their own. For example, one
of the reasons Google Maps is so widely known and
successful is that more than 800,000 websites use its
data, accessed through its API.16
Now, companies can take advantage of the opportunities
for data monetization—to sell data insights directly, share
them through partnerships, or develop entire ecosystems
around them (see the chapter “From Workforce to
Crowdsource”). There are risks and rewards for each,
of course, and some methods will be better suited for
certain companies and industries than others, but they
are all important strategies to consider. Kabbage, for
instance, was able to find a unique use case for data
from UPS. As a partner, UPS provides transactional
shipping data to inform Kabbage’s health assessment of
the companies it finances—determining those companies’
access to capital.17
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Just as companies are finding new reasons for ingesting
external data sources, there have to be companies out
there to provide them. It’s not just about selling data; it’s
also about strengthening partnerships and developing
ecosystems around data to monetize it. Companies now
have the opportunity to think outside of the box for new
ways to realize and take advantage of the true value in
their data.
Adding one data supply
chain, and then another
Every day, as the amount of data grows, so too does
the seemingly impossible task of realizing the data
services platform and, ultimately, the data supply
chain. Unfortunately, there are no shortcuts. The path
is incredibly difficult and exceptionally long—in fact,
it never quite ends. But it is also one of the most
rewarding journeys that companies can make in their
transformation to become truly data driven.
Progress becomes possible when the transformation
process is viewed as a matter of small steps rather than
one giant leap. So, we expect that leading organizations
will start by establishing a data services platform,
followed by implementing a single data supply chain for a
specific outcome. Once that’s done, they will incorporate
another—and another. It may not be easy, but it’s doable.
The implications of enabling the data supply chain are
huge. In the first stage, organizations now have the
opportunity to ingest new sources of data. In the second,
the manipulation of data through new methods of data
discovery adds significant value. The future of this phase
is to mask its complexity and truly embed this value
through cognitive computing technologies. And finally,
businesses can now look externally to realize value from
data in new ways.
It’s time for business leaders to start thinking about the
entirety of the data supply chain—as an end-to-end
process that is outcome driven and fit to strategy.
Today, data should be more than just a premier IT asset;
it should be a premier business asset. Let’s start treating
it that way.
#techvision2014
54

Your 100-day plan
In 100 days, begin to develop a comprehensive strategy
around laying the foundation for your data supply chain.
• Start to build an inventory of your data, beginning with
your most frequently accessed and time-relevant data—
which will be given first access to your data platform and
accelerated on it.
• Identify any manual, time-consuming data curation
processes (e.g., tagging, cleansing) for potential replacement
with machine learning algorithms.
• Identify data silos within your organization (e.g., HR,
finance, engineering), along with corresponding data needs
that are currently unmet across the business.
• Begin to simplify/federate access to trusted data. Create a
strategy for standardizing data access via the data platform.
Solutions may be hybrid, utilizing a combination of traditional
middleware and API management, or even a PaaS offering.
• Prioritize your individual data supply chains to develop a
road map for implementing the data supply chain at scale.
• While building your platform, start looking outside your
company for external data sources that can be incorporated
to complement existing data and help lead to more
complete insights.
This time next year
In 365 days, begin the journey to ROI by building a supply
chain that is designed to drive outcomes.
• Pilot an initial data supply chain targeting a single business
function. Once proven, each subsequent data supply chain
will build upon this initial framework.
• Accelerate data on your data platform to enable the
practice of data discovery across your organization.
Uncover value in your data by quickly asking questions,
failing fast, and iterating to solutions.
• Empower your business users to be value creators in the
data supply chain by giving them data discovery tools and
training them to deliver insights.
• Reduce the manual effort of curating data by using
machine learning algorithms to automate the repetitive
processes in your supply chain.
• Find a specific use case that can be addressed by cognitive-
computing techniques. Use this focused issue as a chance
to experiment with and learn the ways in which cognitive
computing can be applied to your organization.
• Investigate opportunities to monetize your data. These
should include developing new partnerships or ecosystems
around data insights, in addition to directly selling them.
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#techvision2014
56
TREND 4: HARNESSING HYPERSCALE

TREND 4
Harnessing hyperscale:
Hardware is back
(and never really went away)
Eclipsed by more than a decade of innovation in software,
the hardware world is again a hotbed of new development as
demand soars for bigger, faster, lower-cost data centers. Does
your IT organization understand the new developments allowing
companies to realize the benefits of “hyperscale” systems? In this
new world, hardware matters more than ever in transforming
enterprises into digital businesses with access to unlimited
computing power that can be turned on and off as needed.
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Why now?
Rising demand for scale: Across industries, demand for
processing at scale is surging. Businesses need reliable
hardware to support the immense amounts of data processed
for predictive analytics and real-time insights.
Hardware and server architecture innovation surge: From
advances in storage to power consumption to processors
to server architecture, infrastructure innovations such as
nonvolatile memory are paving the way for faster, cheaper,
and bigger hyperscale systems.
Open source: Facebook’s Open Compute Project is
accelerating the adoption of infrastructure innovations by
sharing those breakthroughs freely. Founded in 2011, the
Open Compute Project has already grown to more than 60
official members and thousands of participants.1
Who said that everything old is new
again? He may have had a point—
especially where computing hardware
is concerned.
Not so long ago, every announcement of a new,
multicore microprocessor or personal computer met
with fanfare—lots of buzz about clock rates and cache
memory capacity. But in recent years, the prevailing
sentiment has been that hardware no longer matters—
that x86 servers are nothing more than off-the-shelf
commodities and all the important advances now happen
in software.
Fast forward to today and looking to the future, it is
becoming clear that “hardware as an afterthought” is a
blinkered view. In fact, it is now a harmful view because
it will make it more difficult for enterprises to evolve into
digital businesses.
Every industry will be touched by the technologies
being developed for the era of “hyperscale” computing
systems—the supersized, super-scalable, and resilient data
centers pioneered by heavily data-dependent companies
like Google and Facebook. Innovations in technologies
58
#techvision2014

such as low-power CPUs, solid-state data storage, and
in-memory computing will benefit the performance of
all enterprises’ servers and data centers, enabling their
next generation of infrastructure to support the digital
transformation of their business.
Unilever, a consumer goods company; Pirelli, a tire
manufacturer; and the NBA, a professional basketball
league, are not companies that would typically be
associated with one another, let alone be considered
in the same context as Amazon and Google. And yet,
similar to those technology giants, these and other
traditional companies like them are faced with challenges
that hyperscale computing can help to solve: immense
amounts of data that need to be processed at speed.
However, these companies had neither the scale nor the
computing hardware to solve these challenges in-house.
So they looked to hyperscale hardware appliances to help
them perform at the speed of their nonstop businesses.
For example, Unilever, Pirelli, and the NBA are all using
SAP HANA to perform real-time analytics on huge
datasets to gain insight and competitive advantage.2
HANA gives them the capabilities of hyperscale that
Amazon and Google enjoy in a single appliance instead
of an entire data center. Others are using solutions from
Oracle, IBM, and Teradata.
These data challenges exist across every industry and
for companies of all sizes. This is why every CIO will
again be tasked with understanding the advantages and
trade-offs of hyperscale systems and big data appliances,
as well as the opportunities and risks behind choosing
which hardware will be used to inform and optimize their
digital business.
Inside hyperscale
Before we examine the hardware innovation that is being
propelled by hyperscale developments, it is important to
explain what the word hyperscale means. Accenture uses
the term to describe not just the physical infrastructure
of giant and distributed systems that support the data
centers and provide companies such as Google, Amazon,
and Facebook with the computing power to deal with
vast volumes, variety, and velocity of data, but also the
ability to scale computing tasks to achieve performance
that is orders of magnitude better than the status quo.
Hyperscale data centers consume storage, bandwidth,
memory, and computing cycles on a scale unimaginable
to most. They make pragmatic use of the latest hardware
innovations, but never at the expense of scalability.
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What does this scale actually mean? In the world of
hyperscale data centers, there are very few players.
Google is the largest with well over a million servers;
Microsoft also has more than a million. Then comes
Amazon with about half a million, and Facebook and
Yahoo with a couple hundred thousand each.3
In terms
of power consumption, Google’s global operations
continuously draw 260 million megawatts of power—
roughly a quarter of the energy generated by a nuclear
power plant.4
Not only are these companies operating on a scale
that defies most people’s imaginations, but the
services provided by these hyperscale data centers are
expected to be up 100 percent of the time—not just
99.99999 percent of the time. This is the era of “always on.”
As a case in point, note that companies such as Amazon,
Facebook, and Google are not just responsible for their
own bottom lines—they are increasingly responsible for
numerous other businesses’ survivability as well. Today,
hyperscale data centers are pivotal to an enormous
ecosystem of companies and organizations that rely on
hyperscale platforms as a necessary component of their
business models.
But the demands on hyperscale computing do not stop
with the need to be always on. It is equally critical to
be “always optimized”—application-specific computing
technologies are available to solve increasingly specialized
tasks. For example, hyperscale data centers with the
ability to horizontally scale worldwide with commodity
servers are appropriate for a website. But complex
calculations for applications such as 3D rendering, DNA
sequencing, and cryptography are more effectively and
efficiently handled by a system of servers with advanced
graphics processing units (GPUs)—specialized processors
optimized for parallel processing of very large floating-
point number calculations. GPUs are so effective at these
tasks that application-specific integrated circuits (ASICs)
are starting to become available that offer orders of
magnitude more processing capability than server farms
full of advanced GPUs with dramatically less energy
consumption and a smaller physical footprint.
There are two main reasons why this hyperscale trend is
important to the enterprise. First, hyperscale is driving
significant hardware innovation that will put businesses
at a nexus where decisions on public or private cloud, as
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well as commodity versus specialized hardware, become
significant differentiators. Second, these hyperscale
systems are no longer limited to large Internet companies.
Utilities, oil and gas, and automotive are only a few
examples of industries that are quickly approaching the
hyperscale level of interconnected devices, sensors, and
data centers. Utilities now have networks of integrated
sensors and smart meters that rival those of communication
companies. Ford, GM, and Toyota are building vehicles
with hundreds of sensors, telematics, and real-time
connectivity. As all of this information begins to be
collected every day, every hour, and, in extreme cases,
multiple times per second, the systems required to store
and analyze this data at speed will soon demand
hyperscale solutions. Take gas turbines at power plants,
for example. “We’re almost putting a data center on a
gas turbine,” GE said recently in reference to the hundreds
of sensors the company is placing on those machines to
capture data. If those sensors, combined with robust data
analysis, are able to improve efficiency by just 1 percent,
that could save nearly $6 billion a year.5
“Not only are these companies
operating on a scale that defies
most people’s imaginations, but the
services providzed by these hyperscale
data centers are expected to be up
100 percent of the time—not just
99.99999 percent of the time. This
is the era of ‘always on.’”
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The innovation behind
the hyperscale push
The rapid growth of hyperscale systems has sparked
a renaissance in hardware innovation from which all
businesses stand to benefit. While the tech-savvy reader
can jump into a bit more depth around the technology
in the “Driving innovation in hardware” sidebar in this
chapter, everyone should understand that innovations
around processors, storage, and specialized hardware
are proving to be opportunities for tangible benefits for
the business.
Putting limits on design specifications, such as energy
consumption, has driven innovation. Hewlett-Packard
(HP) drew inspiration from mobile processors for its
Moonshot servers, which operate with up to 89 percent
less energy than traditional servers.6
In a similar focus on
energy efficiency, Facebook reduced energy consumption
by 38 percent in its Prineville, Oregon, data center
compared with existing facilities by using technologies
developed as part of the Open Compute Project.7
Storage advances are providing enterprises with fresh
ways to access and manipulate data faster. Flash storage
arrays are becoming the norm for e-commerce sites
and financial services firms with trading platforms.8
E*Trade uses EMC’s XtremIO storage array to maintain
exceptional performance for customers while performing
data maintenance tasks in parallel with no performance
degradation, giving E*Trade the ability to scale operations
and support new features for users.9
And innovations in server architectures are offering
more options to match specialized infrastructure to
the applications being run, helping CIOs identify the
important requirements of each application, whether
that be performance, scale, or cost. Illustrating the
advantages that specialized hardware can provide, SAP
has 28 customers that now run analytics jobs in HANA
10,000 times faster than they did previously. Three
of these customers have experienced 100,000 times
improvement. One of those three, Yodobashi, a Japanese
electronics retailer, took a three-day batch process to
analyze loyalty customers down to two seconds, enabling
real-time couponing at the point of sale.10
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Although the details of these innovations may not need
to be completely understood outside of the IT department,
it is important to recognize their potential to transform
business processes and strategies. In doing so, it’s
paramount for companies to understand the advantages
and trade-offs of these new tools as they look to procure,
build, and use their next generation of IT systems.
Adopting an open-source
view of hardware
Facebook’s Open Compute Project is another
development that is causing significant discussion within
CIO and other technology circles. The initiative involves
openly sharing hardware innovations, following the
model associated with open-source software projects.
Members participating in this exchange of technology
innovations include Goldman Sachs and Fidelity, which,
in conjunction with AMD and Intel, have been reviewing
new motherboard designs to incorporate in their own
data centers.11
The payoff for enterprises can be significant.
For instance, Facebook designed and built its own servers
and software, claiming that it can build its data centers
at one-fifth of the cost of a traditional data center.12
Asking hard questions
about hardware
The relationship between hardware innovation and rising
demand for cloud services is raising some new questions
for IT leaders. First and foremost, over the next five
years, every IT department will consistently be faced
with the choice between leveraging external clouds
and building computing infrastructure on premise. To
make matters more complex, on-premise choices are
capital intensive and increasingly specialized. There are
computing appliances that give hyperscale capabilities
from a bevy of manufacturers—SAP HANA, Oracle
Exadata (now enhanced with Exalytics), IBM PureData
Systems (an evolution from Netezza), and Teradata are
all top-tier options. Choosing the cloud does not remove
this complexity either. Not all clouds are equal; there are
many varieties from which to choose. How CIOs make
this choice will depend significantly on the systems they
are looking to build and their demands.
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One company may need highly resilient services that
fluctuate little during the workday, but it may demand
more of those services at the end of every month.
Another may require real-time decisions on vast
quantities of data.
The array of decisions now required is reflected in the
sheer number of choices to be made when configuring
an instance on Amazon Web Services (AWS). Amazon
provides a wide range of configuration options to suit
all sorts of business needs—ranging from “compute
optimized” (with a high ratio of CPU to memory and
lowest cost per virtual CPU of all Amazon’s instance
types) to “storage optimized” (suited to applications with
specific input/output and storage capacity requirements).
So the decisions that IT leaders make about their data
centers and cloud services must consider the underlying
hardware. How will this provider’s use of low-power
CPUs in its data centers affect operational costs over the
contract term? Can our applications run on low-power
CPUs, or would GPUs be more efficient for computation?
Does the code for our critical business insights need to
be rewritten to take advantage of these new technologies?
To what extent can the data center scale up for a
pharmaceutical client, say, if the client starts putting
most of its clinical trial simulations in the cloud? Do our
business requirements mean that we are better off with
flash, in-memory, or hard-disk storage? The choice of
hardware depends very much on what the specific
application needs are, and what the usage patterns will
look like.
On this digital journey, solutions must be tailored for
individual use cases. Every organization is going to
face a set of heterogeneous requirements that will
be best served using the correct recipe of commodity
versus specialized hardware and private versus public
cloud architecture. This means that for the foreseeable
future, enterprise infrastructures will be, by necessity,
hybrid solutions—weaving hyperscale cloud, on premise,
specialized hardware, and an enterprise’s existing systems
into a computing fabric that serves more parts of the
business in more demanding, reliable, and scalable ways
than before.
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Adopting hyperscale
In a dramatic shift of IT strategy, companies are
leveraging hardware innovation on a piecemeal basis,
with some companies going so far as to build their own
hyperscale systems as a competitive differentiator. GM
is one such company that is embracing the hyperscale
concept and building out its own mega data centers. This
is not just another private cloud, according to GM: “IT
isn’t here to manage daily operations. It’s a strategic tool
to drive business forward.”13
With that in mind, the automaker is setting up its own
hyperscale environment starting with the first of two
data centers located in Michigan. Moreover, GM has
cancelled its multibillion-dollar outsourcing agreements,
believing that it needed to bring these strategic
capabilities in-house to be closer to the business
decisions needing to be made in a rapidly changing
industry.14
GM’s goal is to accelerate new product introductions,
especially when it comes to keeping up with the growth
of on-board vehicle electronics. Imagine fleets of vehicles
with thousands of sensors sending gigabytes of data
back to the data centers every second of every day from
every corner of the world—all while maintaining high
reliability levels in its data centers. Downtime at one of
its factories can cost GM $1 million per minute, given
current just-in-time inventory practices.15
And GM is not alone. By 2018, some 10 million BMWs
will be connected, asking for, and receiving more than
1 terabyte of data every day.16
More large organizations
are interested in building their own high-efficiency data
centers. Gartner estimates “large data centers”—those
with more than 500 racks—will account for 29 percent
of all data hardware revenue by 2017, up from 22 percent
in 2011.17
Even if CIOs do not have an appetite for building their
own infrastructure, companies still need to examine
their path to becoming digital enterprises and determine
whether they have the infrastructure and skills needed
to support it. There is no set path on how to grow to
meet the hyperscale challenges that businesses are going
to face. But forward-looking companies are seeing the
advantages of hyperscale technology.
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At a minimum, they are seeing an opportunity to drive
down the operational cost of running their data centers.
As such, high-performance companies are increasingly
recognizing that hyperscale systems are a vital part of
becoming a digital business. To get started, technology
leaders need to ask themselves, “What could our business
do with unlimited compute power that can be turned on
and off as needed?”
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This time next year
In 365 days, be prepared to have your IT road map include
hyperscale technologies. Have the knowledge to make the
right investments and act.
• Update models of your digital business’s most demanding
compute processes to understand the advantages, tradeoffs,
opportunities, and risks of hyperscale hardware choices.
• Create a hyperscale task force. Have it include hyperscale
hardware during infrastructure planning.
• Build the reference architectures for hyperscale workloads
and evaluate the applications that are deployed to hyperscale.
Maintain hybrid hyperscale deployment strategies that
account for improvements in offerings across SaaS, PaaS,
and hardware to support varying enterprise activities.
• Investigate how edge-device computing can make
applications more efficient and provide a vehicle for
machine-to-machine interaction.
Your 100-day plan
In 100 days, make sure your organization is informed about
the available hyperscale technology options.
• Ensure that your IT organization is aware of consortiums
and/or is testing the benefits of the latest hardware
innovations. Identify those that are most important to your
business.
• Identify your data storage needs and the magnitude of
devices producing data in your network (including sensors,
smart meters, devices, and data centers). Forecast their
expected usage based on one-year and three-year business
growth strategies.
• Create a plan that allows key data assets to be portable
across architectures.
• Explore participation in open-source communities such as
the Open Compute Project to leverage emerging hardware
innovations.
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sidebar
Driving innovation in hardware
Innovation in three corners of the hardware
world is driving hyperscale:
Processors
Historically, complex instruction set computing (CISC)–
based servers ran on high-performance x86 processors.
This helped to rein in costs and maximize compatibility
for mass-market applications. Over the last decade,
however, the massive consumer demand for mobile
phones has driven radical progress in the capabilities of
low-power processors—largely to the credit, and benefit,
of ARM Holdings. Low-power processors give data center
designers an opportunity to address data center power
costs which, in many cases, have risen to be 30 percent
or more of operational expenditures. Calculations show
that the cost of power to run a server over its lifetime
will very often eclipse the cost of the server itself.18
Innovation is not limited to power consumption. ARM
licenses its chip designs, creating a rich ecosystem
of chip manufacturers and software developers able
to pursue niche opportunities. Benefiting from this
ecosystem, HP recently announced that an upcoming
module for its Moonshot server line will use a new
version of Calxeda’s ARM-based EnergyCore chips. HP
claims that this new module will offer nearly double the
performance and four times the amount of memory per
module compared with the previous generation of low-
power processors.19
Complementing these low-power CPUs, the massively
parallel architectures of graphics processing units (GPUs)
are ideal for big data analytics. As a consequence,
x86 servers are being replaced by servers with low-
power ARM processors, using GPUs as accelerators or
coprocessors. This allows massively parallel database
(MapD) technology to realize tremendous speed gains by
storing the data in the onboard memory of GPUs instead
of CPUs, as is typical. Use of a single high-performance
GPU can make data processing as much as 70 times
faster than a conventional CPU.20
That is why 53 of the
top 500 supercomputers now use GPU accelerators or
coprocessors.21
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“Innovation at the server and data
center levels is causing a bifurcation
between the types of processing
capabilities being offered at hyperscale:
those optimized for general-purpose,
Web-scale computing and those
optimized for specialized tasks.”
Storage
Organizations must now store more data and get
more insights more quickly from the data. With data
processing capacity radically improved, the bottleneck
becomes the ability to store and retrieve large volumes of
data as rapidly as needed.
Traditionally, data has been stored either in limited
volatile memory, which provides the fastest access, or on
disk, which provides much more storage but is far slower.
Companies could have their data fast or cheap, but not
both. Now, though, innovations in flash memory are
making this trade-off unnecessary.
Vendors such as Fusion-io and Violin Memory are
providing flash memory products that address hyperscale
issues such as the need for low-latency, low-power
consumption; a smaller data center footprint; and a
high degree of resilience. These companies are providing
case studies and performance numbers that indicate the
potential for application performance to increase by at
least 25 times, and sometimes by as much as 40 times.22
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specific operational objectives and computing and
storage needs. Companies looking to build or expand
their own commodity x86 data center architectures may
find benefit in joining the Open Compute Project. For
those looking to radically improve operational costs,
low-power systems make sense. While these low-power
systems can be configured to run standard Web or
big data applications such as Hadoop, they are not
compatible with software written for x86 architectures.
However, the operational savings may be worth the
development investment; HP claims that typical data
center operational costs can be reduced by as much as
77 percent with Moonshot.23
With specialized tasks such as analytics on large
databases and computationally intense tasks such as
weather forecasting and DNA sequencing, general-
purpose hyperscale systems are insufficient to deliver
results at speed and scale. Database software companies
such as SAP and Oracle have risen to the challenge by
building in-memory computing appliances that give
orders-of-magnitude performance improvements on
big data analytic challenges. Existing customers of SAP
That means that CIOs now have new options for solving
their scalability challenges. They can start asking different
questions: Is tuning application performance a good use
of expensive developers? Will future applications run
most efficiently on commodity hardware that scales
horizontally? Does specialized hardware better serve the
business needs? What are the trade-offs? What is the
total cost of ownership?
Servers
Innovation is also occurring at the server and data center
levels. In fact, this innovation is causing a bifurcation
between the types of processing capabilities being
offered at hyperscale: those optimized for general-
purpose, Web-scale computing and those optimized for
specialized tasks.
For general-purpose computing, data center designers
now have two options to build at hyperscale: low-
power systems such as HP’s ARM-based Moonshot or
commodity x86 servers. In the most extreme cases of
the latter, Google, Amazon, and Facebook are all sourcing
custom server designs from OEMs, optimizing for their
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and Oracle will find streamlined transition paths with
HANA and Exalytics, respectively. These platforms and
others offer the benefits of hyperscale in a configuration
optimized for on-premise installations.
Moving to a greater variety of complex data processing
workloads, however, calls for supercomputing solutions.
Similar to the in-memory-computing appliances, these
individual systems do not scale, but they do provide
capabilities that go beyond what hyperscale can deliver.
Amazon understands this, which is why its Elastic
Compute Cloud (EC2) includes two of the world’s top 500
supercomputing clusters (numbers 64 and 165).24
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TREND 5: THE BUSINESS OF APPLICATIONS

TREND 5
The business of applications:
Software as a core competency in
a digital world
The way we build software is changing. Mimicking the shift in the
consumer world, organizations are rapidly moving from enterprise
applications to apps. Yes, there will always be big, complex
enterprise software systems to support large organizations, and it
will still be necessary for IT developers to keep customizing those
systems, providing updates, patches, and more. But now, as large
enterprises push for greater IT agility, there is a sharp shift toward
simpler, more modular, and more custom apps. The implications
are significant for IT leaders and business leaders alike: they must
soon decide not just who plays what application development role
in their new digital organizations but also how to transform the
nature of application development itself.
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Why now?
Digital transformation of enterprises: IT applications have
become the primary driver for growth and differentiation for
enterprises.
Accelerated pace of IT change: The increasing push to
rapidly deploy new technology is increasing the pressure on IT
to provide a faster way to develop and deploy the applications
that are driving corporate digital strategies.
Maturation of application platform providers: PaaS
players are offering ready-made data service platforms,
with sets of services already connected and instant sets
of app families available. Tibco, Apigee, and Salesforce are
already offering solutions that provide the foundation for a
customized enterprise app experience.
Rising consumer and user expectations: Customers and
employees are looking for consumer-grade experiences
everywhere. They are pressing IT to give them, in the workplace,
the kinds of low-cost, accessible, and often intelligent apps
they use every day on their own mobile devices.
A large corporation that is as agile as
its global customers need it to be?
There’s an app for that.
But there are big changes in how the application is
created. Anyone with a smartphone can see the signs.
In the consumer world, application development has
become the province of a new generation of developers
eager to strike gold by creating the next Angry Birds
or Evernote app for the mobile phone—applications
that are smaller and simpler to use. That development
approach is now moving into the enterprise, creating new
applications for mobile, Web, and desktop platforms alike.
The more quickly businesses can create and launch new
applications in today’s turbulent markets, the better they
can innovate, collaborate, improve customer experiences,
and enrich personal interactions.
The drivers of this change are not hard to find. Eager for
relief from some of their biggest pain points—especially
their systems’ lack of agility—business leaders have been
pushing for software that is far nimbler than the legacy
systems they’ve relied on for decades. They have been
pressing IT to give them, in the workplace, the kinds of
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low-cost, accessible, and often intelligent apps they use
every day on their own mobile devices.
IT is responding. Leading IT groups are building software
platforms and architectures that essentially separate the
big back-end services from the applications that users
interact with. The outcomes are a win for both the IT side
and the business side: IT gets breathing room to build
solid foundations for complex systems; the business gets
platforms that allow for an increased focus on custom
software that enables rapid iterations to tailor solutions
to fast-changing market conditions.
There’s another big consequence of the shift toward an
enterprise app world: business functions are partnering
with technology organizations to assume joint ownership
of the new agile applications. The back-end services—
from data centers to networks—still fall squarely under IT,
but in more and more organizations, the lines are blurring
as the business takes a more active role in many aspects
of front-end applications. These are not maverick activities:
they are happening with the say-so of IT in those
organizations. In fact, savvy IT leaders are deliberately
partnering with the business side not just to enable but
to encourage them to take on some of these roles.
In a sense, the building of these custom agile applications
is becoming a hallmark of the new digital enterprise. The
questions are now as much about resources as about
technology. How does IT help the business side to acquire
the necessary skills and development mind-set? How
do IT leaders manage the balance between enablement
of the business and building of a stronger technology
backbone to support a more agile enterprise? These
questions will be high on the agenda of every CIO in the
next few years.
The push toward
application ecosystems
In the consumer world, applications have the luxury of
being relatively self-contained. Shazam, for example,
excels at capturing a song heard playing in a café, but
the user doesn’t need it to manage her playlist; she has
another app for that. In the enterprise world, however,
the problems being solved are much more complex.
They often involve multiple applications to run intricate
business processes that may span multiple time zones,
several countries, and thousands of employees.
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To attack these big enterprise-level problems, then,
something more than a single, nimble app is needed.
The way forward is to think in terms of the application’s
ability to connect with other applications. In fact, the
push is toward libraries or “ecosystems” of applications
that can, while still being individually simple and agile, be
bolted together to tackle the most challenging problems.
To do this successfully, businesses require more than just
separation of the front-end applications from the back-
end services. They need software platforms to drive new
development ecosystems.
We see this trend most clearly in the movement toward
enterprise app stores. Research company Gartner predicts
that by 2017, a quarter of all business enterprises will
have an app store for managing corporate-sanctioned
apps on PCs and mobile devices.1
The top performers are
already leading the way: Accenture’s High Performance IT
research confirms that 54 percent of high-performance
IT groups have deployed a mobile-enterprise app store,
compared with just 22 percent of other IT organizations.2
China Eastern is a good case in point. In developing its
own app store in 2012, the airline wanted to drive mobile
app adoption across the company; its rationale was that
fast-growing mobile phone use in China would help drive
growth for the airline and also improve productivity and
operational efficiency, especially among the 50,000 of
its employees who use their mobiles for work. The airline
makes good use of mobile apps in areas such as aircraft
maintenance, employee feedback services, and mobile
office automation. China Eastern has also bought 2,500
iPads for in-cabin services, helping it earn a reputation as
an early adopter of the latest mobility technologies.3
But the real power of enterprise apps lies in how they
are amalgamated—combined and connected in ways that
create a customized system capable of handling larger
business tasks. To some extent, what’s old is new again:
the rise of these application ecosystems is effectively
cashing in on the appeal of service-oriented architecture
(SOA), the technology of a decade ago that promised
business process owners the ability to rapidly iterate
business processes and user experiences by reusing and
reorganizing small pieces of functionality—now known as
apps—and by providing ways to string them together.
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For example, Japan Post Co. is one of Saleforce.com’s top
five customers and has been using apps on Force.com’s
platform to streamline business planning and compete in
new markets. They created 15 custom apps to provide
business process visibility in selling services and products
from three companies as a retail outlet: Japan Post Bank,
Japan Post Insurance, and Japan Post Service. With 24,000
post offices nationwide, it efficiently serves 14 billion
mail packages annually and more than 6 million insurance
policies for upwards of 100 million clients while achieving
flexibility and a reduced total cost of ownership.4
Software platform:
middleware redux?
The proliferation of app stores speaks to the consumption
and use of small, nimble apps. But the other important
story is how IT systems are architected for this new
app world. The new direction is to separate applications
from the back-end systems that support them. Imagine
taking the look, the flow, and the experience of a
financial reporting system and disconnecting it from the
complex financial models and SEC regulation behind it.
The resulting system would allow developers to rapidly
update how users interact with it; it would be easier,
for instance, to get up-to-date cost projections without
having to touch the underlying financial models—
traditionally a burdensome effort when such updates
are required.
Software vendors and enterprises alike are already
changing how they architect their systems to enable this
separation. In essence, middleware is being resurrected as
the “software platform”—a way to present data services
that can make it easier to find modular apps that will
perform a particular business function, and to enable
modular apps to combine, like puzzle pieces, into “systems”
in order to implement more complex business activities.
Such systems are more flexible and provide a framework
to create a custom, on-demand solution faster.
Companies such as Mashery and Tibco Software—the
latter a longtime standard bearer in the middleware
world—are pushing this data services space with
their platforms to provide an integrated development
environment to rapidly create, orchestrate, and integrate
modular services and business applications. Helping USA
Today open and manage its application-programming
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interfaces (APIs), Mashery has expedited the media
company’s ability to negotiate and execute new
partnerships with distributors and device makers so that
devices from iPads to Samsung refrigerators are now
connected.5
Similarly, Tibco’s Silver Fabric cloud platform
is designed to give enterprises the ability to quickly
provision their own app stores.
Other companies such as Apigee are stepping forward
with API management tools that help make it easier for
large enterprises to extend their reach with mobile apps,
create new products with partners and developers, and
more. Live Nation Entertainment uses Apigee’s Enterprise
API Platform to grant internal developers and trusted
partners and clients the ability to extend their ticketing
functionality to mobile devices and provide additional
functions such as event calendaring and live event
applications. As a result, Live Nation’s mobile transaction
volume has more than doubled in the last year.6
And the Platform-as-a-Service (PaaS) players are
offering ready-made data services platforms, with sets
of services already connected and instant sets of app
families available. Salesforce.com’s AppExchange is a
useful case in point. Using its platform as a base for how
these applications are bought, built, and woven together,
Salesforce.com has created its own flexible ecosystem
that represents the next generation of enterprise-built
and -customized systems and solutions. Recognizing
that more than 40 percent of their transactions stem
from API calls, the Salesforce1 Platform is expanding this
ecosystem, opening up ten times more APIs and services
for developers to build upon.7
And acknowledging the
increasing value of management required to expose
APIs at scale, Microsoft recently acquired Apiphany to
integrate API management into Windows Azure.
Importantly, IT leaders should not strive for the holy grail
of software platforms; there is no such thing. It’s not
possible to use a single platform to handle every business
requirement. And don’t assume that cloud will always be
the answer either. According to Accenture’s latest High
Performance IT study, only 7 percent of applications
currently reside in the cloud, and survey respondents
expect that figure to approach 33 percent by 2020.8
In practice, companies will need to adopt a hybrid mind-
set, with different platforms, local and in the cloud,
for different sets of business needs. Abstraction of the
back-end services will have to be a step-by-step process,
starting with the highest-priority business needs. Perhaps
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the organization starts out by developing a platform
for its consumer data and then eventually creates a
platform for its ERP data. The more services that are
available, the greater the functionality that the apps will
be able to leverage and the more diverse and innovative
they can become.
Leveraging separation
to amplify impact
Of course, nobody is suggesting that ERP, CRM, or
large enterprise financial systems are about to become
obsolete. Rather, it’s important to recognize that IT has
entered a new stage in which constant change is the
new normal—one in which IT not only supports business
applications but also enables the business to play a
more active role in those front-end apps. As business
users start to embrace technology as a way to drive
their business strategies—everything from tools for
analyzing consumer sentiment on social media sites to
pilots of new pricing models—IT must start opening up
the systems, tools, and processes to allow business users
to drive these initiatives forward themselves. This lets
the enterprise move from the paradigm of a backlog
of IT requests from the business to one where IT is
empowering the business to experiment, innovate, and
drive its strategies.
Enabling the business is just the first phase; business
leaders will recognize that extending these services
to business partners has the potential to accelerate
business imperatives. For example, AT&T opened its
phone activation APIs so that its partners could leverage
them fully—building apps on top of them, for instance.
The APIs are now available as Web services, and the on-
boarding process can now be executed in a matter of
days or even hours—resulting in a 1,500 percent increase
in the usage of the APIs, not to mention a boost in
phone activations.9
Other companies have taken this “ecosystem” concept
further. Positioning their software as an open platform,
Facebook and Salesforce.com are among the companies
that are using the developer community at large as
their app innovation engine. At last count, Facebook
had more than 10 million apps on its platform, where
more than 25 percent of its annual revenue comes from
mobile app install ads.10
It’s not just tech companies that
are taking this approach; General Motors has opened
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up its OnStar APIs to the public. And, based on an
innovative application developed on top its APIs, the
company is now partnering with the start-up RelayRides
to enter the emerging ride-sharing market. In doing so,
GM is threatening to disrupt both car rental and taxi
companies—business sectors well outside of automobile
manufacturing.
This amplification effect is one of the most powerful
advantages for the new approach to enterprise apps. In
this way, the organization can be more innovative and
react more rapidly. It is not just about applications being
easier to build—it’s about the numbers of apps that can
be built rapidly and concurrently.
Adding intelligence
to applications
As more and more apps are driven by the business, they
continue to evolve: they are becoming more intelligent.
Apps will be better able to sense and respond to users’
context, their history, and the world around them. Time
Warner, for example, has embedded intelligence in its set-
top boxes so that more-relevant content can be pushed
to users based on their TV-viewing patterns.11
In another
example, a mobile app called uChek allows users to spot
potential problems such as kidney and liver issues as
well as diabetes using a picture of a chemical test strip.12
And Amazon has announced the release of an analytics
service for iOS, Android, and Kindle Fire developers that
will allow any developers to embed more intelligence into
their apps.
Far-sighted business users are also eager to make their
applications more useful and more contact-aware—which
is why there’s a growing push to embed analytics in
business applications. Analytics-rich applications can
enable users to answer many more of their own data
questions. They can effectively become their own data
scientists. Tableau Software’s simple data visualization
capability gives customers like Unilever the opportunity
to answer complex business questions very simply, thus
rekindling people’s interest in asking data questions. This
has created a resurgence in analytics and discovery of
simple solutions for previously complicated situations,
such as determining the fastest-growing products for
a very specific demographic.13
When users can extract
intelligent insights from their data in short order, they
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can take intelligent action much more quickly. At the
same time, the organization’s actual data scientists are
then freed up to dig into higher-level strategic questions.
The competencies
needed to support a
world of apps
As enterprises get more involved with the new business
of applications, corporate leaders—IT and business
executives alike—will need to re-examine the skills
and organization structures that must be in place
to support the new arrangement. Business will be
more aware of technology and its opportunities, and
IT will need a better understanding of the strategic
business imperatives that the technology will drive. As
technology and business strategies become inseparable,
multidisciplinary teams will become the norm. User
experience skill will become a necessity to drive the
adoption of every new application. And as the data
collected from these applications is dispersed across the
organization, scarce resources, such as data scientists,
will need to be built up through hiring and training.
But it’s not just tech skills that will be in demand. Unlike
many of the packaged software solutions, the business
processes are not set in stone in a world of apps. This
not only provides a big opportunity to move beyond just
technology innovation, it also enables innovation of the
underlying processes and adds emphasis to the roles of
the business process orchestrator and program manager.
Apps also have different sets of expectations in
terms of maintenance. Agility implies iteration. In a
traditional software world, deployment is the end of the
development cycle. In the app world, deployment is just
the first iteration. The expectation is that the applications
will essentially be “forever beta”—always evolving.
Crucial juncture for
IT and business
Over the next few years, we expect to see some striking
examples of business groups that are much more
engaged in the lifecycle of “their” own front-end apps.
We anticipate something of a resurgence in custom
development as leading companies view it as their best
option for pursuing the objectives of a digital business.
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And we are confident that we will observe more and
more CIOs and IT leaders sitting down with their business
colleagues to discuss how they can help facilitate the
new application development trend.
For many, though—and particularly for IT—this is a
crucial juncture. The immediate task is to fully grasp the
implications of the evolving enterprise app environment.
The second task is to understand the many benefits
that come from having the business side assume larger
roles in driving new agile applications. The next task is
to establish the boundaries of the new roles: the extent
to which IT focuses increasingly on back-end system
development or partners with the business on the front
end—or both.
And the last task? It is to dive into those roles with
relish—knowing that they will surely help the company to
become a truly digital business.
Your 100-day plan
In 100 days, begin to develop a comprehensive strategy that
will lay out the foundation for enterprise app development.
• Appoint a digital champion to coordinate development of
your app strategy across organizations in your enterprise.
• Determine your ability to enable cloud and mobile apps
against your existing SOA, API Management, and PaaS
investments. Based on this evaluation, start preparing a
strategy to separate your back-end services from front-
end apps.
• Begin the design and architecture of an enterprise apps
store for the distribution of mobile and desktop applications.
• Start creating a list of enterprise-level apps to be developed.
Work cross-functionally across business units to prioritize
the items on your list.
• Start planning a pilot for your highest priority apps that will
deploy in conjunction with the enterprise app store. Aim to
validate the readiness of your app production environment.
• Review and begin to update your app process and app
governance strategy. Prepare to shift toward a hybrid buy
and build environment, where your IT buy for front-end
functions will decrease.
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This time next year
In 365 days, begin the process of implementing the tools and
services to enable the development and distribution of smaller,
more agile applications.
• Begin the process of abstracting your front-end functions
from your back-end services. Start with the consumer
applications and services that support the applications
going through the most lifecycle iterations.
• Update your app governance strategy to support an agile
methodology.
• Re-evaluate your testing methodology to make sure you
are not disrupting it when you shift toward a continuous
testing methodology.
• Pilot the enterprise app store. Utilize the first set of high-
priority apps to test the functionality of both the app store
and the applications themselves.
• Based on your pilot results, create a multi-year road map
for partnering with the business to build and deliver the
remainder of your high-priority apps. Take into account
the expected rapid change of pace for IT. Start small but
scale fast.
• Identify potential partners to whom you can open up your
application platform and development tools.
• Pilot the deployment of a partner-developed application on
top of your application platform.
• Evaluate the possibility of opening up specific APIs, and/
or pieces of the application platform more broadly to the
developer community.
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#techvision2014
84
TREND 6: ARCHITECTING RESILIENCE

TREND 6
Architecting resilience:
“Built to survive failure” becomes the
mantra of the nonstop business
In the digital era, businesses must support wide-ranging demands
for nonstop processes, services, and systems. This has particular
resonance in the office of the CIO, where the need for “always-on”
IT infrastructure, security, and resilient practices can mean the
difference between business as usual and erosion of brand value.
The upshot: IT must adopt a new mindset to ensure that systems
are dynamic, accessible, and continuous—not just designed to
spec but designed for resilience under failure and attack.
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Why now?
Digital transformation of enterprises: Transforming to a
digital business implicitly increases a company’s exposure
to risk through IT failures. More business processes are
interconnected and automated, all of which become potential
points of failure. The average cost of data center downtime by
minute has risen by 41 percent since 2010.1
Increased cyber threats: It’s not just about gaining access to
systems; cyber criminals are also trying to bring them down.
Denial of service attacks are increasing in frequency and size.
The number of attacks has increased by 58 percent in the
last year.2
Increased IT complexity: More systems are being integrated,
and continuous improvement is becoming the IT norm.
But constant change to increasingly complex systems is
introducing more risk than ever before.
The expectation of “always on”: In a digital world, whether
your system is under attack, hit by a storm, or just being
updated, the expectation is that it always works.
Netflix loves to fail.
Not by delivering movies late, by overbilling customers
or in any of the other ways that the video streaming
company could fall short. Instead, its engineers try
to find fault with their own IT systems—deploying
automated testing tools that they refer to as a Simian
Army to deliberately wreak havoc in unpredictable but
monitored ways.3
Why? Because Netflix’s engineers know that what doesn’t
kill their company makes it stronger. Netflix is not alone;
these practices were pioneered at Amazon a decade
ago and have seen adoption at the likes of Flickr, Yahoo,
Facebook, Google, and Etsy.
Those companies’ technology chiefs understand
something that IT leaders everywhere must grasp:
failure is a normal operating condition. It must be
anticipated, accommodated, and designed into IT
systems. Practitioners of these “game day” strategies—
when days are set aside months in advance to perform
internal failure testing, with dozens of staff on hand to
respond to incidents—regularly find latent defects in
their systems, log hundreds of bugs, and continue to test
against the repaired defects in future game days.
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#techvision2014

This continuous improvement strategy involves more
than just ensuring that systems have high availability,
a condition that still allows for downtime, however
minimal. Today, the idea is no longer about designing
for “five nines” (99.999 percent) uptime; it’s about
supporting the nonstop business—literally 24 hours a day,
365 days a year. There can be no exceptions: if systems
are to be as nonstop as businesses need them to be,
they can no longer be designed just to specification or
engineered to handle only particular incidents. They must
be designed to work under failure and under attack.
The rationale is simple. As organizations migrate toward
digital, every aspect of their business is becoming
increasingly interconnected and automated. In natively
digital businesses, the digital channel may be the
only channel. In this context, resilience—the ability
of IT systems to maintain wholly acceptable levels of
operational performance during planned and unplanned
disturbances—is of growing importance. True resilience is
what will help organizations mitigate risks to revenue and
brand reputation caused by service disruptions. It’s time
to architect resilience into all dimensions of the nonstop
enterprise, including applications, business processes,
infrastructure, and security.
More vulnerable in
more ways than ever
As businesses go digital, they are far more susceptible to
disruption—vulnerable because IT systems are constantly
evolving to do things they were never designed for,
because update cycles keep shrinking, and because the
intensity and frequency of sophisticated cyber attacks
are increasing. Add the impact of natural disasters—
seemingly more frequent and more severe than before—
and it’s easy to sympathize with the challenges being
faced by brand managers and risk officers of nonstop
businesses. In an always-on world, business leaders have
to expect and accommodate the risks posed by internal
and external disruptions.
The economic risks associated with business
discontinuities can grow incredibly high, incredibly fast.
This is especially true for digital companies that rely on
Internet-based business models. Take Google’s five-
minute outage in mid-August 2013 as an example; it’s
reported to have cost the company $545,000 in revenue.4
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Not all outages are so costly; a 2013 Ponemon Institute
study found that the average cost of data center
downtime across industries is approximately $7,000 per
minute in losses.5
The cost of disruption varies by industry
and the scale of the compromised infrastructure.
Arguably, the vulnerability that CIOs feel most acutely is
from cyber attacks. As transformations to digital multiply,
so do the associated risks from cyber criminals. These
attacks are increasingly substantial, sinister, and sustained.
In 2013, for instance, charges were brought against a
group of five hackers based in Russia and Ukraine for
stealing more than 160 million credit card numbers over
the past eight years. In that same period, they also
compromised more than 300,000 accounts from a single
banking group.6
One of the myriad vulnerabilities highlighted by this group’s
crimes is the increasing sophistication of brute-force
password attacks. Contemporary password cyphers draw
from a dictionary with billions of passphrases, route them
through rule engines, and use massively parallel graphics-
processing units to test trillions of passwords against a
single login credential.7
In short, passwords—even those
stored under cryptographic hashes—are vulnerable.
Organizations that understand this insist on multifactor
authentication policies.
These days, cyber criminals are highly sophisticated and
strategic in their approaches—and rarely brought to
justice. Three of the five hackers in the aforementioned
example are still at large. Individuals are not the only
offenders: organized crime, nation states, and sometimes
unscrupulous competitors are also guilty of cyber crimes.
Cyber threats are not just about gaining access to
systems. In the case of distributed denial of service
(DDoS) attacks, it’s also about shutting down or
disabling services—or at least causing enough secondary
discomfort to damage a company’s brand. Security
company Prolexic reports that in the third quarter of
2013, its clients experienced a 58 percent increase in the
total number of DDoS attacks compared with the year-
earlier quarter.8
More advanced threats are not aimed at entire systems;
they target specific products and services that may
be beyond the protection of a conventional security
perimeter and may include physical assets. The “black
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hats” now have ready access to many helpful tools:
for example, the Shodan search engine—labeled the
“Google for hackers”—quite easily finds infrastructure
components that can be probed quickly for insecure
authentication and authorization.9
Today, a botnet that
can do millions of dollars of damage within minutes can
be rented for $7 per hour.10
A surprisingly large proportion of companies concede
that they are unprepared for the scope, severity, and
sophistication of today’s attacks. Nearly 45 percent of
CIOs surveyed in Accenture’s 2013 High Performance IT
Research admit that they have been underinvesting in
cyber security.11
Many feel overwhelmed about where
to begin; their chances of catching up seem daunting
and expensive.
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“Arguably, the vulnerability that CIOs
feel most acutely is from cyber
attacks. These attacks are increasingly
substantial, sinister, and sustained.”

Engineering to be
a nonstop business,
even under attack
The more professional and prolific cyber attacks become,
the greater the role that cyber security plays in business
continuity. CIOs must use a business-driven strategy to
managing risk across the enterprise by understanding
which assets are critical and then prioritizing resilience
and active defense measures accordingly. These
investments should be proportional to the downside risk
in the event of a disruption.
The time to start architecting for resilience is right now—
not when customers expect it or when losses in trade
secrets, revenue or brand value have reached painful
levels. After the necessary discussions about risk with
the organization’s most senior executives, IT leaders must
begin to map out the threat models specific to their
businesses. With this information in hand, they can use
business process economics to identify the services most
critical to the organization’s strategic direction and thus
those most in need of resilience. This might mean giving
different tiers of service to different users.
After that, it’s necessary to look for investments that
provide security “bang for the buck,” leveraging existing
investments and going beyond compliance. Once these
steps are complete, organizations can start to look at
advanced detection and external threat intelligence
capabilities to better orient their investments toward the
areas most in need. This process will provide the CIO with
an immense amount of data necessary to move from a
compliance-focused stance to one that is more threat-
centric and tied to strategic risk. Resilience is far ahead of
compliance and best practices.
Security experts must also architect for a diversity
of economic conditions, business risk factors, and
a multitude of entry points—including their own
security fabric. Can their own control systems trust
the information they’re receiving? Is their white
listing (identifying known entities that are trusted)
really working? Has their end-point protection been
deactivated by trojan malware?
Ensuring trust among all components of a system—
through attestation—is the next security frontier. One
of the best examples of exploits that could have been
mitigated through proper attestation was the targeted
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remote attack of Iran’s centrifuge control systems
at a uranium enrichment facility. The trojan malware
deployed against Iran’s nuclear refining capacity caused
centrifuges to spin beyond their designed operating
parameters while reporting normal operating conditions
back to the control systems.12
In response to this new class of attack, companies as
diverse as HP and Siege Technologies are innovating
attestation solutions at the hypervisor level, while others
such as Mocana are concentrating on the machine and
embedded device level.13
Putting it another way, the
former are focusing on ways to verify and trust the
operating conditions of systems while the latter are
securing end points so that they’re less likely to fall prey
to an attack.
Once an organization has the technical solutions in
place (DDoS appliances, highly skilled security personnel,
applications and infrastructure designed to detect early
warning signs, security analytics feeding into proactive
quarantining, and automated traffic swings and sink-
holing), the most effective response is coordination
among peers. This practice has been adopted by
the financial services community as a response to a
repeating pattern of prolonged, serial attacks against
its members. The victims later in the attack chain learn
from earlier victims, share architecture recommendations
and IP reputation scoring, and provide for continuity in
relationships with law enforcement. This has proven to
be an effective countermeasure and is being mimicked in
other industries and by regulatory bodies as a result of
the successes in the financial services sector.
Technologies to
improve resilience
Cyber attacks aside, businesses that are striving to
become digital are racing to keep up with always-on
expectations. It is no longer acceptable to simply post
notices about planned downtime. There is less and
less tolerance for service interruptions in any form.
Whether systems are brand-new or state-of-the-art
digital systems from the likes of Google and Facebook,
or conventional legacy systems, there are many tools
available to help systems administrators provide always-
on delivery of digital services.
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To a large extent, CIOs already understand that annual
release cycles are a thing of the past. Facebook and
Yammer are among the leading organizations showing
the way forward: they answer the call to be always
on by deploying updates in staged releases and
using quantifiable metrics and statistical modeling to
measure their effectiveness. Only if the features reach
predetermined performance metrics are they rolled out
to a broader spectrum of users.14
Technology companies are not the only ones moving
in this direction; high performers in IT are beginning to
embrace agile development practices and are adopting
related methodologies for operations—that’s six times
the rate at which other IT departments do it, according
to Accenture’s latest High Performance IT study.15
The
challenge of transitioning to agile at scale is being
met by a suite of operational tactics and technologies,
including DevOps, performance monitoring and failure
tracing, workload management, and software-defined
networking (SDN). Combined, these practices and
technologies pave the road to resilience by making it
possible to build always-on software and hardware
systems.
DevOps is the business-driven integration of software
development and IT operations. DevOps tools such as
Chef and Puppet allow for highly automated deployment
of entire systems from version control. This enables
the rapid deployment of new or extended systems
throughout the compute fabric of the enterprise without
disrupting the nonstop business.
The agile practice of automated unit testing has
transitioned to operations as well, where newly
committed code automatically goes through thousands
of test cases before being deployed; once deployed, best
practice calls for it being deployed on a “canary” server
first. If there are any issues, the canary discovers them
and stops the cascading of flawed code or configuration
to the rest of the production environment. Amazon,
Facebook, and Google all use Chef to manage the
continuous integration of new hardware and software on
their cloud infrastructures—while staying always on.16
Performance monitoring and failure tracing tools such
as Nagios and New Relic provide data center managers
with real-time insights so that they can inspect and
troubleshoot their systems, from source code to hardware
components.
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And workload management tools help to make
applications more portable across heterogeneous
infrastructure—a factor that is increasingly important
with cloud-first infrastructure strategies. With tools
such as Akka and Docker, developers can now go beyond
agile and leverage their cloud infrastructure investments
to build more distributed and concurrent applications
and services, adding resilience to the organization while
decreasing deployment timelines. Gilt, the flash sales site,
uses Akka to build a concurrent, distributed, and fault-
tolerant event-driven application that handles the daily
burst in traffic when flash sales go live.17
Traditional content delivery networks (from vendors
such as Akamai, CDNetworks, CloudFlare, Cisco, and
F5) are providing businesses with integrated workload
management technologies that allow them to stay
agile all the way to their consumer-facing activities. In
many cases, these CDNs also give businesses access to
innovation they may not have otherwise. For instance,
CloudFlare’s proprietary technology was used to reduce
the severity of the DDoS attacks on Eurovision’s annual
Song Contest that reaches 170 million viewers. By
moving to CloudFlare after the site experienced crippling
DDoS attacks during the semifinal round, service
disruptions were eliminated—something that Eurovision
could not have done on its own.18
For enterprises using private cloud solutions such as
OpenStack, CloudStack, and Eucalyptus, SDN enables
seamless bursting to public cloud infrastructure when
business demands on compute capacity overwhelm
internal capabilities. SDN is also invaluable for helping
manage the transition to agility at scale. When data
centers (or clouds) fail, SDN-enabled organizations can
instantly transfer operations to other online assets, often
in automated ways and without meaningful service
interruptions. SDN showed its ability to contribute
to resilience during Super Storm Sandy in late 2012.
CurrenEx used a Vello SDN solution to dynamically
reconfigure routes, service providers, and hybrid cloud
infrastructure. As a result, the company was the only
currency exchange in New York City that was able to
maintain connectivity throughout the storm and the
ensuing cleanup.19
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That does not simply mean putting in place the right
cyber security structures and deploying best-of-breed
highly available systems. It calls for a wholesale shift
in mind-set to the idea of 100 percent uptime. It is a
mindset rooted firmly in the context of business risk
and a deep understanding of the constant threats
of business disruptions—from hurricanes, hackers, or
internal upgrades—and the risks that those threats pose
to maintaining operational continuity and brand value.
Above all, the resilience mindset is categorically not
about compliance. Compliance means complacency; in
an always-on world, it is not enough to simply check the
Sarbanes-Oxley boxes to confirm that this or that risk
management process is being followed. To be clear, leaders
don’t follow compliance frameworks; they set them.
It’s important to know that many of the tools and
methods to engineer for resilience—to design for
always-on operation—are available and improving all
the time. It is not necessary to wait for the maturation
or proliferation of a particular technology. As noted,
agile development methodologies are already in use, and
These types of services make IT systems better able to
withstand failure, notifying administrators of dysfunction,
increasing portability, and providing self-healing
capabilities—features that circumvent the deficiencies of
the highly available, state-of-the-art systems of just a
few years ago. Those earlier systems were about hardware;
now they’re about instances and processes. Rather than
trying to design resilience into every component, it is
now best to take a systemic approach where the service
delivery architecture should be able to survive the loss
of any component—including that of entire data centers.
And when components or data centers do fail in a
resilient architecture, it’s no longer a disaster recovery
event; it is a high-availability event.
A mindset for resilience
in the digital business
Resilience is the new high ground for CIOs who take their
strategic business roles seriously.
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Your 100-day plan
In 100 days, consider where you can make the most impact in
building a more resilient company.
• Shift conversations with senior executives about security
to conversations about mitigating business risks. Talk about
the benefits of designing for failure.
• Map and prioritize security, operational, and failure scenario
threat models to existing and planned business operations.
• Develop a strategy to handle elastic business demand for IT
services.
• Reaffirm a force-ranking alignment of IT systems and
their dependent components with business-driven KPIs for
success and downside revenue risk. Evaluate the top five for
resilience.
• Test your resilience by planning a “game day” exercise for IT
operations.
• Consider hiring an outside security firm to attack your
infrastructure, monitor the events internally, and reconcile
with logs from the security firm to see where your defenses
are deficient.
• Perform a data security review. Determine from a business
risk perspective where data can reside; consider using the
public cloud as a disaster recovery solution.
• If not already doing it, plan a pilot for software-defined
networks and a software-defined data center. Start small
and scale over time.
• Create a governance model for auditing and testing the
entire ecosystem of IT system and process dependencies—
both internally and externally. Be sure it includes policies
for managing capacity utilization and using hybrid
infrastructure.
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they can be used to even greater advantage in building
resilient operations and infrastructure. Even some of the
hackers’ most useful tools, such as Shodan, can be used
by the security community as tools to actively defend
infrastructure.
The CIOs who truly get the concept of resilience have
begun transitioning their organizations to an always-
on state. Knowing that it is neither simple nor cheap
to provide real resilience, they are taking a pragmatic
approach, phasing in resilience over time as business risk
and process economics dictate. And some are already
thinking ahead to the time when their entire business is
digital, cloud-based and always on.
This time next year
In 365 days, be ready to embark on projects that will build
resilience and reduce the operational risks of your digital
business.
• During the budgeting process, look for security- and
infrastructure-related investments that maximize business
process resilience per dollar spent.
• Publish a plan to transition IT operations to a DevOps-based
agile organization.
• Mitigate business downtime risks by aiming to shift
compute loads to public cloud infrastructure—either during
peak times or while under attack.
• Consider piloting automated root-cause analysis tools in the
data center.
• Use results from game day exercises to create a prioritized
list for operational upgrades.
• Test your system against agile software outputs. Verify that
deploying faulty code leads to safe environment fallbacks.
• Create a security road map to build advanced detection and
external-threat intelligence capabilities.
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sidebar
A framework for a resilient future
How can IT leaders start to design for failure? In Michael
Mehaffy’s and Nikos A. Salingaros’ studies of resilience
in the natural world, they uncovered four key principles
that can be adapted for IT.20
Any truly resilient IT system
should demonstrate the following:
Interconnectedness. The evolution of networks, from
point-to-point, to hub-and-spoke, and now to mesh,
embodies the benefits that interconnectedness brings.
When there are more connections at the edge and
throughout a network, aggregate decision-making
improves, happens more quickly, and has a greater
tolerance for the failure of any one node. Many of these
same features appear as part of the sharing economy and
expanded workforce as well, which further underscores
the disruptive power of interconnectedness.
Diversity and redundancy. There should be no reliance
on singular data sources; embracing redundancy, IT
systems should demonstrate diversity and be designed
for failure. The Hadoop Distributed File System is a
prime example of these concepts in action; it has data
redundancy at the document, file, and system levels. This
redundancy allows analytic jobs to be broken into smaller
parts, distributed across the cluster, and run in parallel
to achieve results in a highly scalable way. Similarly, high
availability is a primary benefit.
Modular scalability. Modular systems can be replaced
easily and they enable rapid scalability. They find uses
across solution architectures and they work well in large
and small deployments. Furthermore, when modular
systems are also decentralized, each cluster of nodes
becomes less and less significant to the functioning
of the whole and more independent of centralized
control systems.
Adaptation. Sensors that are able to make localized
decisions based on quantified measurements, domain
experience, and collaboration with peer nodes can have
a significant impact on the physical world around them.
These decisions on the edge are informed by shared
knowledge and, over time, can gain decision making
characteristics akin to biological intelligence.
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CONCLUSION
The pace of technology change
is accelerating
Ten years ago, Facebook was just getting started. Eight years ago,
Twitter and Instagram didn’t exist. Six years ago, most mobile
phones were incapable of much more than phone calls and
messaging. Five years ago, tablets were a remedy for headaches—
not a means of accessing a universe of data.
Digital technologies have burst into our lives with explosive force,
and the shock waves are traveling outward at phenomenal speed.
Accenture has tracked these waves in its Technology Vision reports
over the last eight years, outlining the impacts and opportunities
that continue to lead businesses to become digital businesses.
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CONCLUSION

This year’s report continues to expand our Technology
Vision of the effects this digital surge will have—but
with one difference: this year, we see more and more
large organizations, outside of the IT industry, actively
riding the surge, even fueling it, instead of being
pressured by it. These organizations understand that it
is still early in this initial big wave, but they see just how
much opportunity it gives them. They are beginning
to leverage their vast resources and capital not just to
react to technology disruption but rather to embrace
and interweave digital technologies throughout their
companies to drive the disruptions themselves—and
to their advantage. This shift in strategies marks a
significant inflection point. The last decade of change
and opportunity was driven by digital start-ups. The
coming decade will see the traditional companies
become the next set of digital giants. Big is the next
big thing.
So it’s appropriate for all business leaders to now
start asking pointed questions. Where exactly is our
organization on its digital journey? Making a start,
perhaps by issuing tablets to the sales force?
Are we experimenting, seeing what’s working and
what isn’t? Still learning which business processes lend
themselves best to digitalization? Or, are we confidently
planning a large-scale digital transformation that will
be the most important initiative our company has
undertaken in at least a decade—a way to help us hurtle
past our competitors?
All businesses, from the global 2000 to small businesses,
are facing a pressing need to re-examine their capabilities
in light of the next stages of their digital journeys. The
pressure applies to both the IT and the business sides.
The technology imperative is absolute: it is now time for
the CIO’s organization to decide what role it plays in the
emerging digital business—reinforcing the organization’s
technology backbone while equipping the business side
with the knowledge, understanding, and partnerships
with IT to leverage it.
For the business, it is now incumbent on the leaders to
define their company’s place in the digital world. They
must redefine their relationships with their customers,
partners, and the Internet community at large;
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CONCLUSION

erase organizational silos around how organizations
collaborate and data is shared; re-examine the roles that
their enterprise plays in their industry; and lower the
boundaries barring entry to other industries as potential
areas for growth.
The opportunity at hand for each C-suite executive is
to be a digital disrupter—re-creating and redefining
their businesses to create competitive advantage. The
potential for growth is limited only by the creativity
of the enterprise itself. Now is the time to move from
disrupted to disrupter. The opportunity is here; take it.
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CONCLUSION
“The last decade of change and
opportunity was driven by digital
start-ups. The coming decade will see
the traditional companies become the
next set of digital giants. Big is the
next big thing.”

RESEARCH METHODOLOGY
About the
Technology Vision
Every year, the Technology Vision team at Accenture
Technology Labs, with the Accenture Research
organization, pinpoints the emerging IT developments
that will have the greatest impact on companies,
government agencies, and other organizations in the
years ahead.
This year’s research effort began with the collection
of over 3,000 ideas and comments on technology
trends, disruptions, and hypotheses from the architects,
engineers, and scientists across Accenture who see the
impact of technology changes every day in their work
with clients. Using Mindjet’s SpigitEngage, an enterprise
innovation platform, the ideas and examples of the
trends in action were gathered during a trends spotting
contest. Over 850 participants actively engaged in
contributing, voting and developing the vast collection
of ideas.
These crowdsourced ideas were then screened against
inputs from several other sources, including the recent
activities of commercial R&D labs, the academic
literature, the flow of venture capital funding, and
trends highlighted by IT analysts, and key themes at
industry conferences. For perspective, we also reviewed
many of the ideas with an External Advisory Board
featuring diverse perspectives from startups, venture
capitalist firms, IT ecosystem players, and public service
and enterprise technologists. In addition, we tapped
Accenture’s High Performance IT research and the
findings from our annual CIO Forum.
The ideas that surfaced during this process stood out
for their relevance to “real world” business challenges.
Specifically, the Technology Vision team sought ideas that
transcend the technologies that already drive change—
discrete categories such as social, mobile, analytics, cloud—
and concentrated on the themes that will soon start to
appear on the C-level agendas of most enterprises.
#techvision2014
102

The Technology Vision team then worked with experts
from throughout the company to add to, consolidate,
filter, and prioritize the accumulated ideas and to test
each idea against the following criteria:
• Certainty of transformational impact on enterprises
• Velocity and scale of technology change
• Impact beyond any one industry “silo”
• Ability to be more than a “one for one” replacement for
an existing solution
• Practical actionability within the next 12 months
• Transcendence of any one vendor or discrete “product”
technology
These tests produced a handful of robust hypotheses
that were synthesized into the six overarching themes
presented in this year’s report.
103

Notes
Introduction
1
“Tesco Hudl Review: Can a Supermarket Chain Put Out a Decent
Tablet?” Engadget, October 27, 2013. http://www.engadget.
com/2013/10/27/tesco-hudl-review/
2
“Tesco Profile,” PlanetRetail, November 6, 2013.
3
“Thomas Staggs at D11: Disney’s MagicBand In Action,”
AllThingsD, May 29, 2013. http://allthingsd.com/video/?video_
id=528B4FF7-C8CA-42B4-AF89-59DCE53C18F1
Digital–physical blur
1
“Worldwide Internet of Things (IoT) 2013–2020 Forecast: Billions
of Things, Trillions of Dollars,” IDC, Doc #243661, October 2013.
2
“The Zettabyte Era—Trends and Analysis,” Cisco, May 29, 2013.
http://www.cisco.com/en/US/solutions/collateral/ns341/ns525/
ns537/ns705/ns827/VNI_Hyperconnectivity_WP.html
3
“Predicts 2014: Business Intelligence and Analytics Will Remain
CIO’s Top Technology Priority,” Gartner, November 25, 2013.
4
“Self-Driving Cars More Jetsons Than Reality for Google
Designers,” Bloomberg News, February 6, 2013.
http://www.bloomberg.com/news/2013-02-06/self-driving-cars-
more-jetsons-than-reality-for-google-designers.html
“Nissan Announces Unprecedented Autonomous Drive
Benchmarks,” Nissan press release, August 27, 2013.
http://nissannews.com/en-US/nissan/usa/releases/nissan-
announces-unprecedented-autonomous-drive-benchmarks
5
Cisco website: http://www.cisco.com/web/about/ac79/innov/IoE.html;
“Embracing the Internet of Everything to Capture Your Share of
$14.4 Trillion,” Cisco, February 18, 2013. http://www.cisco.com/web/
about/ac79/docs/innov/IoE_Economy.pdf
6
“Osakidetza Teki Case Study,” Osakidetza, 2012.
http://www.youtube.com/watch?v=VkF1u7pO7zc
7
“M2M Technology Powers British Airways ‘Look Up’ Campaign,”
M2M Evolution, November 25, 2013. http://www.m2mevolution.
com/topics/m2mevolution/articles/361580-m2m-technology-
powers-british-airways-look-up-campaign.htm
8
San Francisco Municipal Transportation Agency, SFpark website:
http://sfpark.org/how-it-works/.
9
“Amscreen Introduces Digital Technology to Tesco UK Petrol
Station Network,” Amscreen press release, October 29, 2013.
http://www.amscreen.eu/en/news-1/amscreen-introduces-digital-
technology-to-tesco-uk-petrol-station-network
“Staples’ Omnichannel Stores Showcase the Future of Retail,”
Staples press release, June 20, 2013. http://investor.staples.com/
phoenix.zhtml?c=96244&p=irol-newsArticle&ID=1831576&highlight=
10
“Neiman Marcus Testing iPhone App,” Associated Press,
March 1, 2012. http://finance.yahoo.com/news/neiman-marcus-
testing-iphone-app-225258946.html
11
“Robot Serves Up 360 Hamburgers Per Hour,” Singularity Hub,
January 22, 2013. http://singularityhub.com/2013/01/22/robot-
serves-up-340-hamburgers-per-hour/
Companies offering solutions in this energy intelligence space
include Bidgely, Verlitics, Home Energy Analytics, LoadIQ, Energy
Aware, and Navetas.
#techvision2014
104
NOTES

12
Interview with Darrell Smith, Director of Facilities and Energy at
Microsoft; “88 Acres: How Microsoft Quietly Built the City of the
Future,” Microsoft, 2013. http://www.microsoft.com/en-us/news/
stories/88acres/88-acres-how-microsoft-quietly-built-the-city-of-
the-future-chapter-1.aspx
13
“Weather Services for Energy Load Forecasting,” Schneider
Electric. http://www.schneider-electric.com/products/ww/en/5100-
software/5190-weather-decision-support-solutions/61688-
weather-services-for-energy-load-forecasting/?BUSINESS=9
14
“Digital Agenda: EU-funded Project Uses Robots, Not Humans,
to Inspect Petrochemical Containers,” European Commission press
release, September 3, 2013. http://europa.eu/rapid/press-release_IP-
13-810_en.htm
15
“Philips Collaborates with Accenture to Create First Proof of
Concept for Delivering Vital Patient Data via Google Glass,”
Accenture, October 3, 2013. http://newsroom.accenture.com/news/
philips-collaborates-with-accenture-to-create-first-proof-of-
concept-for-delivering-vital-patient-data-via-google-glass.htm
16
“Gartner Says Smartglasses Will Bring Innovation to Workplace
Efficiency,” Gartner, November 6, 2013. http://www.gartner.com/
newsroom/id/2618415
17
“Brains for Planes: Etihad Taps Big Data to Keep Planes on Time,”
GE Reports, June 18, 2013. http://www.gereports.com/brains-for-
planes/
18
“Printing Out Barbies and Ford Cylinders,” Wall Street Journal,
June 5, 2013. http://online.wsj.com/news/articles/SB1000142412788
7323372504578469560282127852
19
“Ducati: Motorcycle Maker Accelerates Engine Design with FDM
Prototyping,” Stratasys, 2013. http://www.stratasys.com/resources/
case-studies/automotive/ducati
20
“Printing Out Barbies and Ford Cylinders,” Wall Street Journal,
June 5, 2013. http://online.wsj.com/news/articles/SB1000142412788
7323372504578469560282127852
21
“Automated Driving: Legislative and Regulatory Action,” The Center
for Internet and Society, 2013. http://cyberlaw.stanford.edu/wiki/
index.php/Automated_Driving:_Legislative_and_Regulatory_Action
22
“Ashton Calls for Military-Grade Drones in EU Airspace,” EU
Observer, October 22, 2013. http://euobserver.com/defence/121854
23
“Digital Strategy Does Not Equal IT Strategy,” HBR Blog,
November 19, 2012. http://blogs.hbr.org/2012/11/digital-strategy-
does-not-equa/
24
“Smartphone Apps Could Be Life-Saving Link for First Responders,”
Nexstar, November 13, 2013. http://www.illinoishomepage.net/
story/smartphone-apps-could-be-life-saving-link-for-first-
responders/d/story/Lcd5zTg0uUawXEVYhX7Nlg
“More Paramedics Tap Smartphones for Emergency Information”
Capital News Services, April 19, 2013. http://news.jrn.msu.
edu/capitalnewsservice/2013/04/19/more-paramedics-tap-
smartphones-for-emergency-information/
From workforce to crowdsource
1
“Rally Fighter,” Local Motors, 2013. http://localmotors.com/
rallyfighter/wp-content/uploads/2013/01/RFBROCHURE2013.pdf
2
“BMW and Local Motors announce Winners of ‘Urban Driving
Experience Challenge,’” BMW Blog, November 6, 2012.
http://www.bmwblog.com/2012/11/06/bmw-and-local-motors-
announce-winners-of-urban-driving-experience-challenge/
3
“Group Think: Online Collectives Solve Creative Challenges,”
Compass, Autumn 2013. http://compassmag.3ds.com/Society/
GROUP-THINK
105
NOTES

4
“@WalmartLabs Crowdsources Walmart’s Product Selection with
New ‘Get on the Shelf’ Contest,” TechCrunch, January 18, 2012.
http://techcrunch.com/2012/01/18/walmartlabs-crowdsources-
retailers-product-selection-with-new-get-on-the-shelf-contest/
5
“How Lay’s Is Tapping Its Audience for Its Next Big Chip Idea,” Fast
Company, August 1, 2012. http://www.fastcocreate.com/1681333/
how-lays-is-tapping-its-audience-for-its-next-big-chip-idea
“Lay’s Cheesy Garlic Bread Potato Chips Win ‘Do Us a Flavor’
Contest,” ABC News, May 8, 2013. http://abcnews.go.com/blogs/
lifestyle/2013/05/lays-cheesy-garlic-bread-potato-chips-win-do-
us-a-flavor-contest/
6
Kickstarter website: http://www.kickstarter.com/help/stats.
7
“Motor Industry and Crowdfunding,” Megafounder Blog,
January 29, 2013. http://blog.megafounder.com/blog/nuevas-
formas-de-financiar-la-industria-del-motor/
8
InnoCentive website: http://www.innocentive.com/about-
innocentive/facts-stats.
9
“Worldwide and U.S. Enterprise Server Shipments and Installed
Base Forecast, 1996–2016,” IDC, December 2012.
“Android Pushes Past 80% Market Share While Windows Phone
Shipments Leap 156.0% Year Over Year in the Third Quarter,
According to IDC,” IDC, November 12, 2013.
10
“Forecast: Devices by Operating System and User Type,
Worldwide, 2010-2017, 3Q13 Update,” Gartner, September 25, 2013.
11
“Pebble Smartwatch Tops $10 Million in Kickstarter Pledges, Sells
All 85,000 Watches,” TNW News, May 10, 2012. http://thenextweb.
com/gadgets/2012/05/10/pebble-smartwatch-tops-10-million-in-
pledges-sells-all-85000-watches/
12
“DARPA Language Challenge,” Amazon Mechanical Turk case
study. https://requestersandbox.mturk.com/case_studies/cs/darpa
Data supply chain
1
“Big Data Business Benefits Are Hampered by ‘Culture Clash’,”
Gartner, September 12, 2013.
2
“IDC Digital Universe Study,” IDC sponsored by EMC, December
2012.
3
“The Steadily Growing Database Market Is Increasing Enterprises’
Choices,” Forrester Research, Inc., June 7, 2013.
4
“Journey Toward Analytics ROI,” Accenture, February 27, 2013.
http://www.accenture.com/us-en/Pages/insight-analytics-action-
infographic.aspx
5
“Big Data Business Benefits Are Hampered by ‘Culture Clash,’”
Gartner, September 12, 2013.
6
“Journey Toward Analytics ROI,” Accenture, February 27, 2013.
http://www.accenture.com/us-en/Pages/insight-analytics-action-
infographic.aspx
7
“Powering Capital Markets Divisions at Major Banks,” Palantir,
2012. http://www.palantir.com/_ptwp_live_ect0/wp-content/
uploads/2012/06/ImpactStudy_CapitalMarkets.pdf
8
“Walgreens Opens API for Mobile Prescription Scanning to
Developers,” eWeek, February 13, 2013. http://www.eweek.com/
developer/walgreens-opens-api-for-mobile-prescription-scanning-
to-developers/
9
“Facebook Comes up with Exabyte Data Centers for Cold Storage,”
StorageServers.com, January 23, 2013. http://storageservers.
wordpress.com/2013/01/23/facebook-comes-up-with-exabyte-
data-centers-for-cold-storage/
10
Collaborate.org.
#techvision2014
106
NOTES

11
“Hawaii Uses Collaborate.org as its Data Sharing Backbone,”
Government Technology, June 3, 2013. http://www.govtech.com/
geospatial/Hawaii-Uses-Collaborate-org-as-its-Data-Sharing-
Backbone.html
“Collaborate.org: A Global Intelligence Dashboard that Visualizes
the World’s Data,” GeekWire, May 22, 2013. http://www.geekwire.
com/2013/collaborateorg-global-intelligence-dashboard-wanted/
12
“Beiersdorf Leverages HANA and SAP Demand Signal
Management to ‘Tell Stories from Their Data That Marketers Love
to Read,’“ SAP, November 27, 2013. http://www.saphana.com/
community/blogs/blog/2013/11/27/beiersdorf-leverages-hana-and-
sap-demand-signal-management-to-tell-stories-from-their-data-
that-marketers-love-to-read
13
“Using the Power of Math to Solve Medical Mysteries,” Ayasdi,
June 20, 2013. http://www.ayasdi.com/blog/topology/using-the-
power-of-math-to-solve-medical-mysteries
14
“Texas Medical Center and Ayasdi to Create a World-Class
Center for Complex Data Research and Innovation,” Ayasdi,
November 13, 2013. http://www.ayasdi.com/connect/pr-ayasdi-
and-texas-medical-center-to-create-world-class-center-for-
complex-data-research-and-innovation.html
15
“Enterra’s Cognitive Reasoning Platform Brings Era of Big Data to
Consumer Packaging Industry,” Enterra Solutions, October 28, 2013.
http://www.enterrasolutions.com/media/Enterra_McCormick_Big-
Data_10-29-13_FINAL.pdf
16
Google website: http://www.google.com/enterprise/mapsearth/
products/mapsapi.html.
17
“UPS Partners with and Backs Online Merchant Lender Kabbage;
Will Provide Data for Underwriting,” TechCrunch, February 15, 2012.
http://techcrunch.com/2012/02/15/ups-partners-with-and-backs-
online-merchant-lender-kabbage-will-provide-data-for-underwriting/
Harnessing hyperscale
1
“Calxeda Adds Frank Frankovsky, Chairman of the Open Compute
Foundation, to its Board of Directors,” Calxeda press release,
October 17, 2013. http://www.calxeda.com/news-item/calxeda-
adds-frank-frankovsky-chairman-of-the-open-compute-
foundation-to-its-board-of-directors/
2
“Unilever: SAP HANA,” Accenture, 2013. http://www.accenture.
com/us-en/Pages/service-unilever-sap-hana.aspx
“Pirelli Analyzes Tire Information with SAP HANA,” SAP customer
success story, September 25, 2013. http://www.youtube.com/
watch?v=v5kr9hxC8D8
“The NBA Utilized SAP HANA to Build an Interactive, Real-Time
Game Experience,” SAP customer success stories, July 30, 2013.
http://www.youtube.com/watch?v=gjXYEFYI36o
3
“Datacenter Disruption—Servers,” Evercore Partners,
May 27, 2013.
“Steve Ballmer: Worldwide Partner Conference 2013 Keynote,”
Microsoft, July 8, 2013. http://www.microsoft.com/en-us/news/
speeches/2013/07-08wpcballmer.aspx
4
“Google Details, and Defends, Its Use of Electricity,” New York
Times, September 8, 2011. http://www.nytimes.com/2011/09/09/
technology/google-details-and-defends-its-use-of-electricity.html
5
“Putting Data Centers on Turbines to Save Billions of Dollars,”
Gigaom, October 16, 2013. http://gigaom.com/2013/10/16/putting-
data-centers-on-turbines-to-save-billions-of-dollars/
6
HP website: http://www.hp.com/moonshot.
7
“Building Efficient Data Centers with the Open Compute Project,”
Facebook, April 7, 2011. https://www.facebook.com/note.php?note_
id=10150144039563920
107
NOTES

8
“Build Your Business Case for All-Flash Storage Arrays,” Forrester
Research, Inc., August 21, 2013; updated September 4, 2013.
9
“XtremIO Customer Case Study: E*TRADE Financial,” EMC,
November 14, 2013. http://www.youtube.com/watch?v=VsL1PzZA4SY
10
“SAP AG Presents at Deutsche Bank Access Technology
Conference,” SAP, September 12, 2013.
11
“Facebook Shatters the Computer Server Into Tiny Pieces,” Wired,
January 16, 2013. http://www.wired.com/wiredenterprise/2013/01/
facebook-server-pieces/
12
“How the Mega Data Center Is Changing the Hardware and Data
Center Markets,” Gigaom Research, March 18, 2013.
13
“What the Enterprise Can Learn from GM’s Mega Data Center,”
Gigaom Research, September 25, 2013.
14
“GM’s $130M Data Center Takes After Facebook, Runs Hadoop,”
Silicon Angle, May 15, 2013. http://siliconangle.com/
blog/2013/05/15/gms-130m-data-center-takes-after-facebook-
runs-hadoop/
15
“What the Enterprise Can Learn from GM’s Mega Data Center,”
Gigaom Research, September 25, 2013.
16
“BMW’s Connected Cars Force New Data Center,” Slashdot,
September 13, 2012. http://slashdot.org/topic/datacenter/bmws-
connected-cars-force-new-data-center/
17
“Forecast: Data Centers, Worldwide, 2010-2017, 2Q13 Update,”
Gartner, August 19, 2013.
18
“Disruptive Technologies in the Datacenter,” 451 Research, May 2013.
19
“Calxeda Updates Its ARM Server Platform, Targeting Private
Clouds,” Data Center Knowledge, October 29, 2013.
http://www.datacenterknowledge.com/archives/2013/10/29/
calxeda-updates-arm-server-platform-targeting-public-clouds/
20
“Graphics Chips Help Process Big Data Sets in Milliseconds,” MIT
Technology Review, October 18, 2013. http://www.technologyreview.
com/news/520021/graphics-chips-help-process-big-data-sets-in-
milliseconds/
21
“Nvidia, AMD Bulk Up Their GPU Accelerators,” eWeek,
November 18, 2013. http://www.eweek.com/servers/nvidia-amd-
bulk-up-their-gpu-accelerators.html
22
Fusion-io and Violin Memory customer case studies.
23
HP website: http://www.hp.com/moonshot.
24
“Amazon Puts 26,496 CPU Cores Together, Builds a Top 100
Supercomputer,” Ars Technica, November 18, 2013.
http://arstechnica.com/information-technology/2013/11/amazon-
built-one-of-the-worlds-fastest-supercomputers-in-its-cloud/
The business of applications
1
“Enterprise App Stores Can Increase the ROI of the App Portfolio,”
Gartner, February 4, 2013.
2
“High Performers in IT: Defined by Digital,” Accenture, 2013.
http://www.accenture.com/highperformanceit
3
“Case Study: China Eastern Airlines’ Corporate App Store Boosts
Enterprise Mobility,” Forrester Research, Inc., July 12, 2013.
#techvision2014
108
NOTES

4
“Salesforce.com, Inc. Earnings Call Transcript,” Salesforce.com,
May 23, 2013.
“Japan Post Network Builds 15 Custom Apps for 75,000 Users at
24,000 Post Offices on Force.com,” Salesforce.com case study.
http://www.salesforce.com/showcase/stories/japanpost.jsp
5
“How USA Today’s API Powers Partnerships,” Mashery blog,
August 6, 2013. http://www.mashery.com/blog/how-usa-todays-
api-powers-partnerships
6
“Innovator Spotlight: Live Nation—Industrializing API
Infrastructure for Management and Growth,” Apigee, June 5, 2013.
https://blog.apigee.com/detail/innovator_spotlight_live_nation_
industrializing_api_infrastructure_for_management_and_growth
7
“The $10 Billion Playbook,” Salesforce.com, November 19, 2013.
http://www.sfdcstatic.com/assets/pdf/investors/df13-ics-financial-
overview.pdf
“Salesforce.com Introduces Salesforce1,” Salesforce.com,
November 19, 2013. http://www.salesforce.com/company/news-
press/press-releases/2013/11/131119.jsp
8
9
“AT&T: Using APIs to Help Developers Build Great Apps Quickly,”
Apigee case study. http://apigee.com/about/customers/att-using-
apis-help-developers-build-great-apps-quickly
10
“Facebook Annual Report 2012,” Facebook, February 1, 2013.
http://files.shareholder.com/downloads/AMDA-NJ5DZ/2832440778
x0x658233/46826077-D2FD-4E84-9BBE-C3F844B547A0/
FB_2012_10K.pdf
“Twitter is Testing a Mobile Ad Product that Will Give Facebook
a Huge Headache,” Business Insider, November 4, 2013.
http://www.businessinsider.com/twitter-testing-mobile-app-install-
ads-2013-11#ixzz2mvx8fHjo
11
“Time Warner Cable Customer Case Study,” Alteryx, 2013.
http://www.alteryx.com/customer-case-studies-and-video-
testimonials
12
Biosense Technologies’ uChek website: http://www.uchek.in.
13
“Data Tells Consumer Stories at Unilever,” Tableau Software case
study. http://www.tableausoftware.com/learn/stories/data-tells-
consumer-stories-unilever
Architecting resilience
1
“2013 Cost of Data Center Outages,” Ponemon Institute sponsored
by Emerson, December 2013: http://www.emersonnetworkpower.
com/documents/en-us/brands/liebert/documents/white%20
papers/2013_emerson_data_center_cost_downtime_sl-24680.pdf
2
“Q3 2013 Saw Significant Changes in Attack Methodologies,”
Prolexic, October 23, 2013. http://www.prolexic.com/knowledge-
center-ddos-attack-report-2013-q3.html
3
“Chaos Monkey Released into the Wild,” Netflix Tech Blog, July 30,
2012. http://techblog.netflix.com/2011/07/netflix-simian-army.html
4
“5-Minute Outage Costs Google $545,000 in Revenue,”
VentureBeat, August 16, 2013. http://venturebeat.com/2013/08/16/3-
minute-outage-costs-google-545000-in-revenue/
5
“2013 Cost of Data Center Outages,” Ponemon Institute sponsored
by Emerson, December 2013. http://www.emersonnetworkpower.
com/documents/en-us/brands/liebert/documents/white
papers/2013_emerson_data_center_cost_downtime_sl-24680.pdf
6
“Russian Hackers Stole More Than 160 Million Credit Cards,” NPR,
July 25, 2013. http://www.npr.org/2013/07/25/205548308/russian-
hackers-stole-more-than-160-million-credit-cards
109
NOTES

7
“How the Bible and YouTube are Fueling the Next Frontier
of Password Cracking,” Ars Technica, October 8, 2013.
http://arstechnica.com/security/2013/10/how-the-bible-and-
youtube-are-fueling-the-next-frontier-of-password-cracking
8
“Q3 2013 Saw Significant Changes in Attack Methodologies,”
Prolexic, October 23, 2013. http://www.prolexic.com/knowledge-
center-ddos-attack-report-2013-q3.html
9
“Shodan Search Exposes Insecure SCADA Systems,” ZDnet.com,
November 2, 2010. http://www.zdnet.com/blog/security/shodan-
search-exposes-insecure-scada-systems/7611
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“Cybersecurity Pioneer Barrett Lyon Unveils Defense.net to
Combat the Newest DDoS Attacks on Large Enterprise Critical
Infrastructure,” Defense.net Press Release, August 6, 2013.
http://defense.net/index.php/company/press-releases/
cybersecurity-pioneer-barrett-lyon-unveils-defense-net-to-
combat-the-newest-ddos-attacks-on-large-enterprise-critical-
infrastructure/index.html
11
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Washington Post, June 1, 2012. http://articles.washingtonpost.
com/2012-06-01/world/35459494_1_nuclear-program-stuxnet-
senior-iranian-officials
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York Times, June 1, 2012. http://www.nytimes.com/2012/06/01/
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iran.html?_r=0
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2013. http://downloads.hpmediasolutions.com.edgesuite.net/
managed/36185-1-InnovationInsight0813_Security_2020.pdf
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14
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15
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The Register, February 13, 2013. http://www.theregister.co.
uk/2013/02/04/opscode_chef_11_control_freak/
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CloudFlare,” CloudFlare case study, 2013. http://www.cloudflare.
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Chad Parris, Managing Director at State Street Global Markets,
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20
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#techvision2014
110
NOTES

contacts
For more information
Paul Daugherty
Chief Technology Officer
paul.r.daugherty@accenture.com
Michael J. Biltz
Director, Accenture Technology Vision
michael.j.biltz@accenture.com
Prith Banerjee
Managing Director, Accenture Technology
R&D
prithviraj.banerjee@accenture.com
www.accenture.com/technologyvision
111
CONTACTS

About the Accenture
Technology Labs
The Technology Vision is published each year by
the Accenture Technology Labs, the research and
development (R&D) organization within Accenture. For
more than 20 years, the Technology Labs have helped
Accenture and its clients convert technology innovation
into business results. Our R&D team explores new
and emerging technologies to create a vision of how
technology will shape the future and shape the next
wave of cutting edge business solutions.
The Accenture Technology Labs offers seminars on the
Technology Vision, which provide a forum to discuss the
trends in greater depth and explore the implications for
your organization’s business.
To learn more about the Accenture Technology Labs,
or our seminars, contact a member of the Technology
Vision team.
About Accenture
Accenture is a global management consulting,
technology services and outsourcing company, with
approximately 281,000 people serving clients in more
than 120 countries. Combining unparalleled experience,
comprehensive capabilities across all industries and
business functions, and extensive research on the world’s
most successful companies, Accenture collaborates
with clients to help them become high-performance
businesses and governments. The company generated
net revenues of US$28.6 billion for the fiscal year ended
Aug. 31, 2013. Its home page is www.accenture.com.
Copyright © 2014 Accenture
All rights reserved.
Accenture, its logo, and
High Performance Delivered
are trademarks of Accenture.

Technology Vision 2014 by Accenture

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