Riding the Seven Waves of Change That Will Power, or Crush, Your Digital Business

Riding the Seven Waves
of Change That Will Power, or
Crush, Your Digital Business
From hyper-personalization to API-driven
ecosystems, here’s how to master tomorrow’s
technologies and business models today.

RAJ BALA
CHIEF TECHNOLOGY OFFICER
COGNIZANT TECHNOLOGY SOLUTIONS
Rajasekaran.Balasubramaniam@cognizant.com
2 KEEP CHALLENGING January 2016
Amid perpetual and accelerating technology shifts, businesses must ratchet up their
ability to see, make sense of and respond to proliferating volumes of data. This data can
yield predictive insights on everything from developing more personalized products and
services, to unsnarling complex operational logjams.
Progressive organizations are already opening their APIs to business partners and
embracing micro-services to fuel continuous innovation and build profitable e-business
platforms. Meanwhile, these forward-thinking enterprises continue to address persistent
security challenges with pervasive, layered approaches that keep mission-critical data
and networks safe from prying eyes.
What follows is our crystal ball into seven critical technology and business upheavals your
organization must navigate to succeed in the digital age.
We hope you find our perspective thought-provoking and prescriptive. Feel free to contact
me at the e-mail below to discuss how these trends relate to your business and industry.
Preface

RIDING THE SEVEN WAVES OF CHANGE THAT WILL POWER, OR CRUSH, YOUR DIGITAL BUSINESS 3
Executive Summary
Across every industry and in every corner of the globe, customers
are demanding smarter, more personalized and more secure (yet less
expensive) products and services. Meeting these imperatives will require
new technologies and information architectures, as well as new ways of
working and thinking about business and customers.
To understand these emerging business and technology mandates, look no
further than the mirror.
Whether as an individual consumer or a business customer, you are more
apt to buy from companies that don’t just meet but anticipate your needs,
as well as customize products and services around your wants and desires.
You mercilessly shop for the lowest price but expect the highest levels
of service. You demand superb, instant support anywhere and anytime
over any device, including mobiles and wearables. And any company that
compromises your personal or corporate information because of a security
breach is relegated to your blacklist.
As buyers and as sellers, the ground is shifting beneath our feet, propelled
by seven fundamental technology and business waves. These include:
1. Gaining insights from the digital data generated by the online
activities of every person, device and process. By analyzing these ever-
growing data volumes — which we call Code Halos — organizations can
uncover opportunities for revenue, savings and the development of
new markets, products and services. Read more about the emerging
insights-driven enterprise on page 6.
2. Serving “markets of one” by hyper-personalizing products and
services that meet and anticipate customers’ spoken and unspoken
needs. Business impacts include increased market share and the ability
to command premium pricing. Read more about the coming age of
hyper-personalization on page 9.

3. Establishing a smart, pervasive security strategy for a hyper-
connected world that replaces “walled gardens” with self-protecting
assets. This approach will enable businesses to securely provide
customers, employees and business partners with the digital
capabilities and information they need. Read more about over-the-
horizon developments in pervasive security on page 12.
4. Seeing, knowing and responding in real time, using just-in-time
intelligence from inside and outside the enterprise, including the
ambient information generated by the proliferating Internet of Things
(IoT). Embracing the IoT is already enabling pioneering organizations
tosenseandrespondtoeverythingfromloomingproblemsinmachines
and production processes, to subtle but important shifts in customer
behavior and sentiment. Read more about coming trends in just-in-
time intelligence on page 16.
5. Enabling enterprise control through digital code, using software-
defined automation. Doing so enables organizations to not only
slash IT and operational costs but also respond more nimbly than
competitors to changing market requirements. Read more about the
expanding software-defined enterprise made possible by “automation
everywhere” on page 19.
6. Opening application programming interfaces (API) to create
“network effects” that transform connected applications and data into
holistic business platforms (think Salesforce.com in the software-as-a-
service space). These platforms drive revenue as partners leverage
your organization’s data and systems. Read more about the evolving
API ecosystem on page 23.
7. Creatingnewskillsandtechnologysourcingmodelsthatdramatically
reduce the cost of acquiring and using information technology.
Tapping new sources of global talent and technology allows businesses
to ramp usage up or down as needed without prohibitive onboarding,
training and other overhead costs. Ultimately this will accelerate the
“gig economy” trend that has already emerged. Read more about real-
time skills sourcing on page 27.

Meeting these challenges, and exploiting these new models, requires
a keen understanding of today’s dynamic world, in which the pace of
technology change is accelerating more rapidly than ever before. All
of the drivers we have identified are tightly interrelated and cannot be
understood in isolation. The insights-driven enterprise, for example, both
drives the need for and helps deliver hyper-personalized products and
services. Just-in-time intelligence from IoT devices helps deliver real-time
intelligence to enable better business decisions, as well as the real-time
awareness required to improve security.
Understanding and responding to these transformative shifts holistically
is not an academic exercise. In just the last few years, industry giants have
been increasingly challenged and even rendered irrelevant by upstarts
that have applied new technologies and business models to win the hearts
and pocketbooks of switched-on digital consumers.
With shifts in all these areas moving at breakneck speed, the greatest
danger is failing to imagine how an unknown startup could disrupt your
business just when you think all is safe. At the same time, proactively
exploiting these trends can open new horizons in terms of careers,
business models, products, services and lifestyles that are unimaginable
by even the most digitally-savvy industry guru.
Read on to learn more about the opportunities and challenges created
by these seven interrelated trends, and see how our field-proven
recommendations can help your business gain an unfair advantage on the
competition.

Move from Raw Data to Insights, Faster
Today’s Reality
Enterprises have access to more data than ever, originating from a plethora of
sources, including consumers’ Web activity, wearable fitness monitors, smart
manufacturing equipment, social media and internal legacy systems (see Figure 1).
Translating these bits and bytes of structured and unstructured data into insights
and foresights is a concept we call Code Halo™ thinking.1
As computing and storage
costs decline yet enable ever-faster and more precise analysis of this data, enter-
prises can react more quickly, even proactively, to changing market requirements,
as if they were reading their customers’ minds.
Being first to discover and act on these insights also enables organizations to
maximize profit margins (through cost reduction or premium pricing) or gain
market share (through smarter upselling and cross-selling). Analyzing sales data
can reduce costly inventory and improve the accuracy of staff scheduling, while
the mining of network log data can uncover hidden security threats. Analyzing
past outcomes can help hospitals save lives by deciding which patients to treat first
in emergencies. Monitoring machine status (such as temperature, vibrations and
energy consumption) can prevent costly damage or failure.
Graphics
X4 >
Student
Excitement
X4 > Student
Battery Life
X4 > Student
Love
X4 > Student
4
3
ttitude
Store 1234 >
Laptops > Ted
CPU
X4 > Student
2
5 Churn Target
City > Store 1234
Churn Target
City > Store 1234
3
2
In-Store Organization
City > Store 1234
In-Store Wait Time
20 minutes > City
Store 1234 > Laptops >Ted
Training
City > Store 1234
Buying Experience
City > Store 1234 > Student
1 Website Search
X4 > Student
System removes unknown variables from
customer feedback and categorizes it.
Username: bsmith
E-mail: bsth@yahoo.com
Sex: Male
Age: 22
Location: Madison, WI
Persona: Student
Website: ACME.com
Product: X4 Ultrathin
Review Date: 05/23/2011
Overal Rating: 3.0
Display: 3.0
Performance Rating: 5.0
Convenience Rating: 3.0
Likelihood to Recommend: 8
I was so excited to get my new
laptop from ACME. It has super sick
graphics, beefy cpu and awesome
battery life. The laptop was not easy
to ebsite. When I found
it I didnt want to pay for the redicu-
lous shipping cost...so I went to the
store to pick it up. The place was a di-
saster area it made me sick. I couldn’t
anything. After waiting for 20
minutes for a yellow shirt
help. Ted was friendly, but, he had no
idea how to answer question about
the X4. Man, i loved that laptop but
this sale should have been easy and
it wasn’t. #fail ACME :( I’m going to
Target.
Combining Structured, Unstructured Data to Generate
Actionable Customer Insights
Source: “Customer Insight Command Center Speeds ‘Just-in-Time’
Marketing,” Cognizant Technology Solutions, September 2014.
Figure 1
The Insights-Driven Enterprise
SECTION 1:
Accurately linking structured data to unstructured data enables actionable customer- and store-level insights that were
previously unavailable with other methods and systems.

Even more powerful are the new business models built around real-time, even
predictive, awareness of customer needs and trends. Examples range from auto
insurers that can price policies based on real-time driving behavior gleaned from
on-board sensors, to Amazon’s ability to predict orders from a given geography
and pre-ship them to a local warehouse for faster delivery when the actual order
is placed.2
Whatever your industry, failing to move toward an insights-driven approach will
render you progressively blind to market opportunities and risks, and at risk of
being outmaneuvered by competitors with a clearer view of near- and long-term
trends.
The following are some of the new tools businesses are using to build and extract
meaning from Code Halos:
• Cognitive computing, which uses machine learning to create systems that are
easier and more natural for humans to use.
• Machine learning, in which applications learn new patterns and responses
without being specifically programmed.
• Natural language processing that mirrors human speech and writing patterns.
• Predictive analytics that anticipate and meet the needs of customers at
ever-lower costs and greater speed.
• Prescriptive analytics that help enterprises identify the next best action for a
given scenario.
Tomorrow’s Possibilities
The dual forces of improved analytics and cost-cutting pressure will lead enter-
prises to automate more strategic decision-making. This is already happening with
routine text entry and accounts payable tasks and will spread to more sophisticated
decisions, such as audit and tax compliance. Over time, software bots (programs
that operate on behalf of a user or another program and mimic a human activity)
will optimize business processes, bringing more intelligence to both customer-
facing processes, such as real-time product recommendations and discounts, and
internal processes, such as IT security and management.
Analyzing consumer data — location, purchases, social media postings, etc. — will
enable businesses to more accurately predict customer needs and offer customized
solutions. IoT data will enable manufacturers to more completely understand
the lifecycle of the devices they produce and better support them. Recognizing
the importance of customer sentiment, businesses will also look for new ways
to measure emotions such as enthusiasm and excitement, along with customer
actions, such as downloads and clickthroughs.3
At the same time, more powerful analytics and big data tools will enable organi-
zations to move from backwards-looking dashboards to proactively addressing
customer needs, identifying market trends and creating new business models.

• Focus on providing a superior customer
experience, which is where businesses must
outshine their competitors. For example, organi-
zations can build personalized models of various
customer types through machine learning, and
apply predictive analytics to drive higher-margin
sales and improve marketing campaigns. They can
also use social, mobile and analytics tools to collab-
orate with customers, obtain their early feedback on
new products and services and adapt offerings in
real-time to best meet their needs.
• Develop expertise in, and acquire appropriate
tools for, big data analysis, modeling, analytics
and data visualization, such as in-memory
computing or stream processing.4
Put special
emphasis on modeling — choosing the proper data,
algorithms and variables and validating that they
reflect how the business actually operates. Learn
when to use deductive modeling (working from
general hypotheses to more specific predictions) vs.
inductive modeling (working from specific observa-
tions and building hypotheses from them).
>> Understand and acquire skills in managing and
analyzing the different types of structured and
unstructured data required for real-time insights
into various types of problems.
• Master the visualization and sharing tools
that enable self-service, on-demand analytics for
employees. New services such as Amazon Web
Services’ QuickSight are already coming online to
provide on-demand business intelligence.
• Plan for the move to predictive analytics by iden-
tifying key processes for which taking action “before
it happens” can result in outsized business benefit.
• Invest in the infrastructure and application tools
and skills required for agile, relatively low-cost
experimentation, quickly proposing hypotheses,
testing them and then acting on the results. If the
cost of experimentation is too high, businesses will
not be able to build a culture of sustained improve-
ment and innovation.
• Carefully choose which data to collect and
analyze based on your specific industry and
business challenges, as well as the value of the
customer, device or process involved. A health
insurer, for example, might focus data collection
on policy holders at risk of developing chronic and
costly conditions such as diabetes. Aggregating
every bit of old and new information from all sources
can drive storage, processing and data management
costs to unacceptable levels. Collecting everything
and sorting out the relationships later can lead to
higher costs and delayed business benefits. Keep in
mind the “garbage in/garbage out” rule, focusing
relentlessly on data quality.
• To make the best use of IoT data, employ abstrac-
tion layers, such as master data management and
metadata models, that allow business users, not
just IT professionals, to understand what data
is available, what the data represents and how
to quickly generate insights. Leverage existing
data from legacy industrial sensors, as well as the
analytic models used in legacy systems, to schedule
maintenance, production runs and the ordering of
raw material.
• Don’t be discouraged if existing algorithms
cannot process the amount and variety of data
generated by devices on the IoT. Employ a “divide
and conquer” approach, splitting the largest
business problems into subsets that can deliver
useful and accurate results, using current analytics
tools and real-time data.
• Remember that human input is still needed to
ensure problems are properly modeled in ways
that reflect the actual data. This is especially true
for activities in which it is unclear which variables
influence each other. Similarly, people-focused
“sanity tests” should be applied to the insights
generated. Just because an algorithm detects a
customer is pregnant doesn’t mean she would
welcome a congratulatory package of coupons
for baby gear, as one U.S. retailer found with an
underage customer living with her parents.5
Advice for the Insights-Driven Enterprise
Quick Take

Serving Markets of One
Today’s Reality
Every customer has unique wants and needs, even if he or she is the same age or in
the same income bracket or ZIP Code as countless others. Today’s most loyal and
lucrative customers expect products and experiences to reflect their ever-changing
preferences, needs and context, such as their past behavior, choice of device and
location, and forward-thinking companies are responding (see Figure 2).
By analyzing big data analytics, geolocation and historical metadata, enterprises
can customize products and services to meet, anticipate and exceed customer
needs (see Section 1 on the insight-driven enterprise, page 6). The supply chain for
physical products and digital services must support just-in-time customization, or
hyper-personalization, and technologies such as natural language processing, text-
to-speech and avatars must provide hyper-personalization capabilities in the most
user-friendly form.
More Than Half of All Marketers Use Personalization
Hyper-Personalization
SECTION 2:
Marketers were asked if they were using real-time (<1 second) personal-
ization in any of the following channels. (Multiple responses allowed.)
Website Mobile
Website
Web
Application
Mobile
App
None of the
above / NA
H E L L O
my name is
44%
17%
13%
9%
42%
Base: 242 respondents with marketing
or line-of-business titles.
Source: “Trends & Priorities in Real-Time
Personalization,” Researchscape
International, 2015
Figure 2

British Airways’ “Know Me” program, for example, combines various data sources
to create a single customer view, and uses it to give extra attention to high-value
customers or those who have recently experienced delays or other problems. It also
allows employees to search Google Images for a photo to immediately recognize
such customers.
Some retailers are already using big data analytics to build detailed records of the
behavior of their best customers and proactively push offers to them in anticipation
of their needs. These records might show, for example, that a customer submits a
clothing order every six to eight weeks at lunchtime on Wednesday. If the shopper
hasn’t purchased by Thursday morning on that cycle, the retailer can send an offer
for the customer’s favorite sweater style in a color he doesn’t yet own.
For some products, technologies such as 3-D printing (at a site near the customer
or vendor) can speed production and delivery of hyper-personalized products. An
example is Normal,6
which provides a smartphone app that allows customers to take
a photo of their ear canal, from which the company can custom-print earphones.
Another example of the hyper-personalization phenomenon comes from wireless
provider Virgin Mobile, which enables customers to build their own service plans
based on the number of users and amount of voice, data and texts they wish to
pay for, even how much data different family members can use. In India, wireless
provider Tata Docomo used Facebook Custom Audience to display customized ads
to users based on their recent Facebook activity. As a result, the company won
back more than 350,000 lapsed customers, boosted the use of services such as
paid subscriptions for songs by 26% per user, and realized more than $2 million in
incremental revenue per month.7
The first wave of personalization is well underway, with customers responding to
shopping recommendations from businesses such as Amazon and entertainment
recommendations from Netflix. Such on-the-fly customization is now spreading to
other services and mainstream markets.
In healthcare, doctors sometimes use insights into a patient’s unique biome —
the unique mix of bacteria and other organisms in their bodies — to tailor diet or
medication recommendations.8
Successful businesses are also intuiting customers’
intentions from their actions, both online and offline, in increasingly sophisticated
ways to understand the implicit requests they make.
For example, a retailer’s Web analytics might indicate a customer has conducted
three searches on the company’s site for “extra-large buffalo plaid flannel shirts”
but failed to make a purchase. The business’s CRM records might show the customer

initiated a chat on the issue but gave up after failing to connect with an agent. The
retailer could respond by generating a customized offer to check its remainders,
back inventory and upcoming shipments to find the best price on the specific item.
A customer receiving such proactive help is much more likely to complete that
transaction and recommend the site to others.
Businesses that generate the greatest sales and margins will explore opportunities
to push highly personalized offers to customers, based on their location in the store,
their Web search patterns or other behaviors that indicate a need for assistance
(see Figure 3). This will require the adoption of emerging technologies such as
locator beacons and “smart mirrors” that allow a customer to view how an item
would look on them, and share the image on social media.
Such on-the-fly customization can boost customer loyalty and sustain, even expand,
market share. Moreover, it can provide the opportunity to create and deliver products
and experiences that command a premium and
possibly disrupt entire industries. Think Uber and
its ability to match the needs of individual vehicle
owners (i.e., to earn money) with passengers who
need transport (and are willing to pay).
On a more tactical level, hyper-personalization
driven by analytics and machine learning can
reduce support costs and improve customer
service by providing highly customized services
without costly human intervention. Imagine the
convenience for a commercial customer, and
the associated reduction in administrative costs,
if a supplier could predict its use of various raw
materials and automatically deliver just the right
amount of the right material at the right time.
Assuming an organization has properly tweaked
its supply chain, such hyper-personalization can
also help it profitably serve niche markets with
smaller production runs.
Of course, this requires a business to enable
hyper-personalization at low enough cost levels
(or charge enough of a premium) to make the
effort worthwhile. Further, faulty execution (poor
recommendations, hard-to-use interfaces) will
hurt rather than help the brand, as will the failure to create ordering, production
and distribution systems flexible enough to deliver the customized product, services
or content.
Ensuring data quality to support such hyper-personalization can be a major
challenge, especially as data is drawn from multiple internal and external systems.
Finally, organizations need to meet increasingly stringent security demands to
protect customer data (see Section 3 on pervasive security, page 12).
Welcome, Angela! Today’s
deal: Buy this top for 50% off!
BEACON
Targeting Customers with Custom Offers
Figure 3

Deploying Layers of Self-Protecting Digital Assets
to Mitigate Cyber Risk
Today’s Reality
Every day, more applications and services move to the cloud, as businesses realize
cost savings and boost agility through highly networked, just-in-time IT and human
resources. Along with the explosion of mobile devices and applications, this
approach dramatically increases the variety and complexity of technologies that
employees, partners and customers need, when and where they choose.
Securing this hyper-connected world requires organizations to move beyond the
traditional secure perimeter they established around their business-IT infrastruc-
ture. While this may once have protected their business-critical traffic, attackers
who penetrate the organization’s “walled garden” can now compromise almost any
critical system, posing unacceptable risk. This is a no-win proposition in today’s
digital age when it’s difficult to predict which employees, business partners and
customers may need system resources at any time.
The dangers are only magnified by the rise of organized hacking for profit, and
espionage or sabotage by nation-states. One look at the rise of security breaches
in the retail space — such as the recent hacks into toymaker VTech’s website and
Mattel’s Hello Barbie algorithmically-powered doll9
— reflects the magnitude of the
problem that will only get worse over time if organizations do not plug the gaps in
today’s leaky IT environments (see Figure 4, next page).
Advice for Hyper-Personalization
• Provide intuitive tools for “self-customization” of products and services. For example, one wireless provider
already lets customers use their current bill to estimate the most suitable custom plan.
• Be clear with your customers about which of their actions are being tracked, and provide an “opt out.”
• Experiment with the proper medium and timing of personalized offers. Many businesses may begin by over-
personalizing their offers in ways that customers reject as intrusive, and then pull back in the face of resistance.
• Start small, iterate often and be prepared to “fail forward” by learning from your mistakes. Even with the most
advanced analytics, it can still be difficult to determine the context of a customer’s actions and intent.
• Put business-savvy humans in the loop for a “common-sense” review of the validity of the analysis and the
action taken based on it. For example, if an algorithm finds that lower-income home buyers in a specific age group
are a better loan risk than previously thought, human experts should review the underlying data to ensure it has
not been manipulated by, for example, unscrupulous lenders.
Quick Take
Smart, Pervasive Security for
a Hyper-Connected World
SECTION 3:

The answer lies in implementing pervasive layers of assets that are intelligent
enough to protect themselves. Such approaches include containerization —
multiple, isolated environments that enable personal and professional use of the
same system — and technologies like encryption and mobile management tools that
control what users can do with their company-supplied or personal devices.
Machine learning and artificial intelligence also help by correlating multiple security-
related events from various systems to identify the source of a breach, and
adaptively learning how to counter it.
The number and types of systems vulnerable to attack will explode with the acceler-
ating adoption of mobile technology, as well as the 50 billion smart devices expected
on the IoT by 202010
(see Figure 5, next page). Public concerns over IoT security will
only grow as more revelations emerge, such as the misuse of embedded software
to seize control of a vehicle11
and the hacking of medical equipment to change drug
dosages.12
Securing devices on the IoT will be especially challenging because some, such as
sensors, lack the computing power or memory to support security mechanisms
such as encryption and authentication. Because of their long lives, variety and
upgrading difficulties, these devices will continue to be a weak link in the security
chain. This reinforces the impossibility of physically controlling every end point,
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEPT
OCT
NOV
TARGET
40M individuals’
contact information
stolen
AARON BROTHERS
400K customers’
credit & debit card
information stolen
NEIMAN MARCUS
350K individuals’
credit card
information stolen
SALLY BEAUTY
Company admits that about
25K credit card numbers
were compromised,
but others speculate
that 280K+ records
may have been impacted
ALBERTSONS
SUPERVALU
Payment card data
compromised at
180 Supervalu
stores between
June 22 & July 17
MICHAELS
2.6M individuals’
credit card
information stolen
P.F. CHANG’S
33 P.F. Chang’s
locations affected
UPS
Customers’
personal
information
from 60
UPS stores
compromised
BARTELL HOTELS
55K customers’
information
reportedly stolen
GOODWILL
868K credit &
debit cards
reportedly stolen
HOME DEPOT
56M individuals’
credit card
information
stolen
STAPLES
113 U.S. stores
affected, 1.16M
shoppers’ debit &
credit card data
stolen
KMART
Malware stole
credit card
numbers
from 1,200
Kmart stores
for over
a month
DAIRY QUEEN
Credit & debit
card information
compromised at
395 Dairy Queen
and Orange Julius
stores
Retail Under Siege
Digital theft and fraud committed in 2014.
Source: “2015 Dell Security Annual Threat Report,” Dell Computer, 2015.
Figure 4

as well as the need for stronger authentication models (certificate revocation,
biometrics, a trusted platform module) to protect not only “dumb” devices but also
the software “bots” that will increasingly perform functions such as price negotia-
tion on behalf of people.
Meeting tomorrow’s security challenges will require a multi-layered approach and
ongoing investment in assessing, monitoring and remediating an ever-changing mix
of attack vectors, as well as ongoing cooperation from and monitoring of business
partners. Stakeholders must realize that vulnerabilities considered acceptable
when applications were seen only by employees must now be addressed now that
every breach is open to the world. Businesses should assume they have been com-
promised (because they likely have been) and reinvigorate their attempts to identify
anomalies in network traffic and application behavior that could indicate a breach.
With the right approach to security,
organizations can avoid regulatory
fines, reputational damage and sales
declines, as well as plummeting market
share and customer loyalty in the wake
of breaches. Additionally, businesses can
also use security as a competitive dif-
ferentiator that enhances their brand,
given increased consumer awareness
of cyber risks. Consistent, reliable and
easily implemented security measures,
supplied by multiple layers of self-
protecting assets, can also drive the
business by allowing it to more quickly
and easily access, analyze and share data
with employees, customers and business
partners. Building security at all levels
also gives businesses the confidence
to move quickly, innovating and experi-
menting with the knowledge that their
core assets are protected.
However, new technologies and
ongoing user education require serious
investment and effort. Correctly calibrat-
ing the cost of security with its benefits
is difficult and can lead to over- or under-spending. Security staffs must also be
careful not to reflexively deny access to corporate systems without evaluating the
business benefits of such access, so they are not seen as — or actually become — a
roadblock to innovation.
0
10
20
30
40
50
2012
8.7
11.2
14.4
18.2
22.9
28.4
34.8
42.1
2014 2015 2016 2017
Penetration of
connected objects in
total “things” expected
to reach 2.7% in
2020 from 0.6% in 2012.
Number of connected
objects expected to
reach 50 billion by 2020.
2018 2019 20202013
2%
3%
5%
Number of global connected objects
in billions
Percent of total things
in the world
50.1
The Exploding Internet of Things
Source: Cisco
Figure 5
Meeting tomorrow’s security challenges will require a
multi-layered approach and ongoing investment in
assessing, monitoring and remediating an ever-changing
mix of attack vectors, as well as ongoing cooperation from
and monitoring of business partners.

Advice for Pervasive Security
The most important pillar in a digital security strategy is new thinking. Security is no longer only the job of the IT department,
and cannot only be focused on the perimeter. Security must now be the concern of every employee and business unit, with the
understanding that it’s not a matter of if, but when, the business will be compromised. The chief information security officer
(CISO) needs visibility into, and a reporting relationship with, the highest levels of management. CISOs must make it clear
that security is no longer a “gating” function that slows innovation but a critical enabler of the business and protector of the
brand. As organizations adopt DevOps13
to speed application deployment, they should consider adding security experts to the
scrum teams. Security must also be “industrialized” through increased automation and the auditing of not only code but also
production and test environments at all stages of the development lifecycle.
Technologies
Pervasive security requires a host of emerging and estab-
lished technologies, deployed in multiple locations, including:
• Software-defined security that allows multiple layers of
assets to protect themselves, using abstraction technolo-
gies that apply customized policies to any combination
of users, devices or assets and among multiple service
providers. Much as “software-defined networks” can be
reconfigured without touching physical devices, “software-
defined security” can easily adapt to changes in business
processes, the sensitivity of data or the needs of customers,
employees or business partners.
• Homo-morphic encryption, which enables workers to
use encrypted data without decrypting it. Data remains
protected even if the corporate firewall is breached.
• Ephemeral systems, which are built from known
components and last only as long as the business needs
them, which reduces the number of vulnerable assets.
• Micro-services that can be cost-effectively “plugged
into” applications. This approach can provide pervasive
security by enabling functions such as identity and access
management or encryption. The business owner of each
process must ensure adequate levels of security for each
corporate resource or process. (Read more about micro-
services in Section 6 on API-driven ecosystems, page 23.)
• Easier to use and more robust authentication
approaches. Such techniques include multi-factor authen-
tication, such as verification codes sent to smartphones,
and identification of a user’s unique pattern of typing or
shifting among applications.
Processes
• Robust audits and sharing of detailed post-incident
analysis across the business to reinforce that security is
everyone’s responsibility.
• Creation of detailed user- and platform-specific
baselines of normal behavior to help identify potential
threats anywhere in the enterprise.
• Use of automation to cost-effectively protect exponen-
tial increases in users, data and traffic. This includes the
use of IT forensics and related technologies and algorithms
to detect potential breaches more quickly.
• Tailoring of security to specific devices and users to
minimize cost and effort. For example, clusters of devices
with lower levels of CPU and memory might use symmetric
key pairs to manage encryption, while more capable
devices could employ a public key infrastructure (i.e., the
use of keys and digital certificates to verify identities and
allow the secure exchange of data over public networks)
with asymmetric keys.
• Rewards such as less stringent security requirements
for users who follow best practices, such as the use of
strong passwords, not downloading malware or keeping
applications patched.
• Ensuring pervasive security through automated threat
tracking to determine which vendors are safe to work with,
and what data to share with them.
• Use of DevSecOps (the integration of development,
security and operations teams) to include security in all
phases of the development lifecycle.
• Ongoing user training and education to guard against
phishing or other fraud schemes.
Security must be the concern of every employee and
business unit, with the understanding that it’s not a matter
of if, but when, the business will be compromised.
Quick Take

Sense and Respond in Real Time
for Customer Benefit
Today’s Reality
Through the IoT, businesses face an historic opportunity to use just-in-time intel-
ligence to create new business models or extend existing ones that save customers
time and money, as well as make their lives safer and easier. IoT data is well on its
way to tracking everything from the fuel consumption of a jet engine in flight, to
the temperature of a pallet of frozen food, to a shopper’s location in a mall or their
heart rate at the gym (see Figure 6). Devices ranging from drill bits to production
machinery and household appliances are, or soon will be, continuously sensing and
responding to environmental conditions, and sending updates about their health
and status.
Just-in-Time Intelligence
SECTION 4:
$
30
billion
Jet fuel
Estimated cost savings (cumulative) in five industries
over 15 years, propelled by a 1% reduction in fuel,
capital expenditures and inefficiencies.
COMMERCIAL AVIATION
Through better flight
planning and operational
changes.
OIL & GAS
By boosting availability of key
equipment sets, reduced fuel
consumption, enhanced production
rates and reduced costs.
$
66
billion
Gas generation
efficiency
POWER
Improved gas-generation
through integration of
natural gas and power grids.
$
27
billion
System
inefficiencies
RAIL TRANSPORTATION
Reduced maintenance costs through
real-time diagnostics and predictive
analytics, and eliminating waste
in fleet scheduling through fleet
instrumentation.
$
63
billion
System
inefficiencies
$
90
billion
Capital
expenditures
HEALTHCARE
Identify equipment issues and improve
resource usage and outcomes to drive down
the cost of clinical and back-office operations.
How IoT Helps Generate Value
Source: “Decomposing the Internet of Things: A $14.4 Trillion Opportunity,” Cognizant
Research Center, 2014.
Figure 6

Imagine having a complete view across the value chain, from the latest cost and
shipping time for a raw material, to the status of work in progress in the factory,
to the latest social media sentiment about your organization’s brand and product
usage statistics from the field.
Take the Nest thermostat, which learns a homeowner’s schedule and automatically
adjusts heating and cooling to match it. Manufacturers of products ranging from
commercial air conditioners to truck engines and transformers in electric grids are
reducing repair costs and improving customer service by analyzing performance
trends to identify problems early on and trigger repairs to prevent more costly
failures.
Just-in-time intelligence will expand as Web-enabled sensors become embedded
in clothing, facilitating continual remote health monitoring. Businesses can use
this data to offer products and services, including customized training regimens,
health alerts and personalized equipment, such
as an ankle brace if a sensor’s analysis of a
runner’s stance indicates he needs one. One
company already offers shoes that sync with
customers’ smartphones, track their location
and provide directions by generating vibrations
in the shoes.14
Sensors embedded under the skin could
eliminate the need to wear a separate monitor,
and even be used for authentication to log
into devices or open doors. Sensors from
cars, buildings, roads and weather monitoring
facilities will create “smart cities” that help
citizens avoid traffic jams, reduce energy use
and react more quickly to safety issues, allowing
authorities to instantly close streets and route
traffic around emergencies. The combination of
real-time information on location, weather and other elements, combined with the
instant delivery provided by drones, will provide unparalleled levels of convenience,
as well as new sales opportunities.
Just-in-time intelligence will be the next competitive battlefield, as businesses race
to meet consumer and business expectations for immediate information, enter-
tainment, help and product delivery. For businesses, timely analysis of field data
will improve the tracking of goods in transit and in the production process, reduce
inventory overhead through just-in-time delivery, and cut transportation costs
through more efficient routing. Better monitoring of equipment in remote locations
will allow proactive detection and resolution of problems, reducing downtime and
repair costs. Analyzing patient information in real time will reduce costs and enable
remote diagnostics and personalized coaching to prevent or reduce the impact of
chronic disease.
The combination of real-
time information on location,
weather and other elements,
combined with the instant
delivery provided by drones,
will provide unparalleled
levels of convenience, as well
as new sales opportunities.

Quick Take
Such real-world, real-time awareness — if communicated to the right stakeholders
and acted on properly — could also help prevent “extinction events”15
that threaten
the survival of a brand. Consider, for example, if location data from smartphones
indicated that large numbers of customers at a restaurant chain are arriving during
lunch hour but then leaving. The business could immediately investigate to see if
the problem is long lines, poor customer service or discourte-
ous wait staff. On the IT front, real-time analytics of network,
user and application behavior can uncover security breaches
while they are happening, allowing organizations to address
them before they do harm.
However, with so much data available from so many sources,
businesses can incur unnecessary costs, or fail to generate
insights in a timely manner, by storing more data than they
need. Additionally, as with other insight-driven services,
businesses will also need to respect customers’ privacy and
ensure their security. This will be especially challenging for
IoT sensors that lack the compute or memory resources to
support robust encryption or authentication (see Section
3 on pervasive security, page 12). Early movers must work
around a lack of standards that makes it more expensive and
difficult to integrate legacy or proprietary devices into modern networks, and raises
the risk of vendor lock-in. Organizations must also ensure data quality and consis-
tency between fast-changing “edge” data and historic information stored at the
core of the network for longer-term analysis.
Advice for Just-in-Time Intelligence
• Tapping the radical new possibilities created
by just-in-time intelligence requires a broader
view of customer needs and potential new
markets. Engage with stakeholders from across
the business and with external partners (legacy
and startups) to uncover the broadest range of
opportunities to add value. While cost reduction,
efficiencies and incremental sales might drive
the first round of innovation, do not overlook
the transformational potential of entirely new
business models built around the convenience,
speed and health benefits of real-time intelligence.
• Avoid “big bang” initiatives and instead
experiment with relatively quick, easy and inex-
pensive analytics projects that test and refine
hypotheses about critical business trends.
Scalable, cloud-based platforms for storing and
sharing data will help enable a fail-fast-and-learn
strategy.
• Machine learning, cognitive computing and
other advanced analytics techniques will be
essential for improving both the quality of the
insights generated, and the speed with which
they can be shared and acted on. Finding staff
with the appropriate skills in these areas may
require retraining or finding creative approaches,
such as crowdsourcing.
• While the technical challenges are formidable,
organizational and cultural issues are equally
important. Real-time edge analytics involve
activities that occur closest to the business and
the customer, whether that is at an oil wellhead,
retail store or customer smartphone. Successful
companies will effectively use the real-world
experience of savvy front-line staff to decipher
clues that emerge from sophisticated machine
learning environments.
• To be sure just-in-time insights don’t sit on
the shelf, share them not only with headquar-
ters, but also with customer-facing employees
and decentralize authority to empower front-line
decisions. For example, a local restaurant or
store manager might be given more freedom to
change hiring practices or prices or take other
remedial action, based on their knowledge of the
local market.
Real-world, real-time
awareness — if communicated
to the right stakeholders
and acted on properly — could
help prevent ‘extinction
events’ that threaten
the survival of a brand.

Enterprise Control through Code
Today’s Reality
Two related trends — virtualization and automation — are changing the face of
everything from network security to insurance underwriting.
Virtualization (the abstraction of software from hardware) is rapidly spreading
from servers and storage to other devices and services. Everything can be defined
as software, from enterprise networks (and underlying systems), to business and
IT functions such as security, in the form of abstraction layers and code that can
be easily deployed on-premise or in the cloud. eBay’s online auction service, for
example, has made infrastructure a competitive differentiator through the creation
of a software-defined data center that automates not only infrastructure but also
load balancing, object storage, databases as-a-service, configuration management
and application management.
At the same time, businesses are better able to cut costs and cycle times by
automating processes, thanks to increasing computing power, the ability to perform
faster and more predictive analytics and the development of new tools to model
and describe processes, from claims processing, to invoice entry, to x-ray analysis.
An example is drones that scan inventory in warehouses and, if Amazon has its way,
deliver packages to consumers.
Within IT, more and more tasks (from application testing to infrastructure
deployment) are performed reliably and inexpensively by rules-based scripts,
providing the IT infrastructure that produces the
insights on which the business relies.
Automation enabled by mobile devices provides
consumers with a virtual control panel to function
in an increasingly automated world, allowing them
to control everything from thermostats to security
systems through mobile applications. Robotic
vacuum cleaners and pets are already available for
the home, with automated care-givers not too far
behind.16
The common thread in this drive toward automation
is the ability to use code, rather than human interac-
tion, to perform critical everyday functions. While cost reduction is the short-term
business driver, the long-term payoff lies in greater agility and the ability to cost-
effectively experiment by developing new products, services and business models.
Software-Defined Everything/
Automation Everywhere
SECTION 5:
The common thread in this
drive toward automation
is the ability to use code,
rather than human interaction,
to perform critical everyday
functions.

Automation, currently confined to provisioning and management of the IT infra-
structure, will next expand to IT processes.
For example, developers working in multiple locations today must alert each other
when they commit code to a repository. It can then take days to compile the source
code and create a build that can be tested before it is deployed. A fully automated
process would algorithmically create new builds, test them and then return them to
developers with a list of defects or enhancements for the next build. These levels of
continuous integration and deployment are needed to deliver market-facing appli-
cations quickly enough to define and dominate new markets.
Moving beyond IT into business process automation will take longer and require
improved skills in business process modeling to accurately replicate manual
processes in software.
A further step is automating interactive repetitive services, such as answering
questions from customers and conducting routine transactions. Early versions of
this capability can be seen in the automated wealth management and robo-advisors
at some of our clients in the financial services industry. If this could be extended
to service processes in every company — providing
automated, intelligent answers to customers — the
benefits of lower prices and higher quality would be
immense.
For example, within a month of deploying an
autonomic platform, a U.S. investment bank with
which we work was able to resolve 80% of failed
trades without human involvement. It reduced
average resolution and fix time from 47 minutes to
four minutes while reducing staff costs 35%.
Another frontier is marketing automation, which
analyzes customer behavior over various channels
and automatically provides the next best offer (whether content or a product
or service promotion). The logical next step would be combining the automated
services with marketing, and automating processes such as price negotiations,
buying and reordering.
Over time, the increased use of machine learning (the use of algorithms that can
learn from experience) and predictive analytics will allow these “robots” to take
on more and more complex tasks. For instance, many news aggregation websites
use automatic authoring tools to deliver customized news updates to readers,
while programmatic direct ad buying provides advertisers a guaranteed number of
impressions from consumers on publisher sites.
Moving beyond IT into business
process automation will take
longer and require improved skills
in business process modeling
to accurately replicate manual
processes in software.

Automation enabled by hardware virtualization allows administrators to reconfig-
ure networks and change security or service policies with a mouse click rather than
visiting a server rack. It reduces management costs and errors while improving
security through automated, error-free configuration and policy-based, real-time
responses to threats.
Just as in application development, automated straight-through processing can
also deliver lower costs, shorter time to market and improved customer service for
business processes (see Figure 7). (Read more in Section 1 on the insights-driven
enterprise, page 6.) Imagine, for example, the integration of multiple automated
activities that enable customers to select a vehicle, choose financing and insurance,
and complete the purchase through a single user interface. Analysis of consumer
choices could be used to continually refine the interface, as well as the associated
products and services that can be cross-sold or up-sold to different customer
segments.
COST REDUCTION
Reduction of operational support
costs on average by 30% to 35%.
IT avoidance of unnecessary
automation software licensing costs.
SERVICE LEVEL
ENHANCEMENT
Dramatic enhancement of service
level and improvement in SLAs with
reductions in cycle times.
IMPROVED PREDICTABILITY
& AVAILABILITY
Significant improvement in application
service availability. Significant
improvement (approximately 60%)
in mean time to resolution (MTTR).
SERVICES
SCALABILITY
Unlimited scaling of virtual engineers for
automating repetitive and mundane taks;
freeing expensive and critical resources
for innovative and people-focused work.
FLEXIBILITY
Interoperability with current
support infrastructure and
investments.
Autonomics Drives Efficiency and Flexibility
Source: “Autonomics: Mastering Self-Learning and Self-Healing,” Cognizant Technology Solutions, March 2014.
Figure 7

Organizations must carefully assess whether
these software-defined capabilities will scale and
perform as promised, and sometimes wait for robust
management and security capabilities. Automation
also requires balancing the benefits of lower costs
and greater speed against the loss of human control
over business-critical infrastructure and services.
Organizations may also struggle with how to cost-
effectively and securely extend automation across
on-premise and cloud environments. Staff who built
their careers on manual configuration and fine-
tuning of infrastructure might lack the willingness or
the ability to switch to a more automated, program-
matic approach. This could require new skills or new staff, replacing single-platform
experts with those who have the big-picture view, as well as the skills to implement
best practices as scripts and algorithms.
Automation also requires
balancing the benefits of lower
costs and greater speed against
the loss of human control over
business-critical infrastructure
and services.
Advice for Software-Defined Everything/Automation Everywhere
• Automate IT infrastructure provisioning
and management first, as it is typically the
most mature organizational area, delivers
the greatest short-term cost savings and is
essential to driving business agility.
• Automate specific steps such as the creation
of user interfaces or testing, as well as
code hand-offs from requirements through
deployment.Agoodstartingpointisautomating
the creation of regression test cases, along with
continuous integration and build. Getting to
full seamless automation requires overcoming
concerns (such as security) about sending test
data and code to the cloud.
• Automation can also be aided by the use of
containers, which create secure “sandboxes”
for multiple applications sharing a common
operating system. This significantly reduces
the amount of CPU and RAM required because
each application does not need its own instance
of an operating system.
• To automate business processes, take
advantage of emerging tools, such as the
S-BPM (subject-oriented business process
management) modeling language that allows
users to describe processes in a way that is
understandable to both people and computing
systems. Focus first on processes that don’t
change too often.
• Digitize all the relevant data as early in the
process as possible and present it in a single
user interface. Doing so minimizes the delays,
errors and costs of manual re-input.
• Focus on the low-hanging fruit — those
processes in which productivity is so low or
volume is so high that even modest reductions
in effort yield significant results.
Quick Take
Automate IT infrastructure provisioning and management
first, as it is typically the most mature organizational
area, delivers the greatest short-term cost savings and is
essential to driving business agility.

Delivering the Network Effect for Enterprises
Today’s Reality
As software “eats the world,”17
APIs are becoming
a core corporate resource, as they allow applica-
tions to communicate with other systems.
The power of APIs lies in their speed and ease of
use, compared with the brittle system-to-system
interfaces that businesses have historically used to
connect applications to each other or to back-end
systems.
On a tactical level, businesses tap APIs from business partners and vendors to
enable rapid, easily maintained connectivity among an ever-changing mix of data,
services and devices (see Figure 8). They also publish their own APIs to create
interoperable ecosystems with customers, and to enable business partners and
other third-parties to connect with their systems and applications. A leading
discount drug retailer, for example, uses APIs to allow users of third-party mobile
applications to print photos directly from their smartphones at their local store.
This not only drives revenue from photo printing services but also draws customers
into stores for possible additional purchases.18
On a more strategic level, easy-to-use APIs can turn a
business into a “platform” from which it — as well as third-
party developers — can generate revenue (see Figure 9,
next page). The platform economy spans organizational
boundaries, fueling innovation from internal business
groups and trusted partners. APIs from Salesforce.com,
for example, allow third-party developers to write appli-
cations that increase the value of its namesake customer
relationship management system. Google’s APIs allow
developers to tap into Google services such as its maps,
resulting in the funneling of users and ad revenue to
Google. APIs generate nearly half of the annual $3 billion
in income at Salesforce.com, and close to 90% for the
Expedia travel website.19
The importance of APIs increases with the sale of
every smartphone, wearable fitness tracker and smart
appliance or industrial device. Each of these devices
instantly generates data about its status, communicat-
ing its owner’s wants, needs and behavior. The metadata
generated enables organizations, or their partners, to
derive and apply insights (see Section 1 on the insights-
driven enterprise, page 6). This may be as straightforward
as offering homeowner’s insurance to an auto insurance
policy holder who just changed addresses, or as complex
API-Driven Ecosystems
SECTION 6:
Application
Programming
Interface
Partner Apps
Company’s App
Users benefit from
a robust, streamlined
experience.
The platform economy spans
organizational boundaries, fueling
innovation from internal business
groups and trusted partners.
The Art and Science of APIs
Figure 8

as tweaking the fuel flow in a jet engine running too hot for peak efficiency. APIs
can deliver anything from the seemingly simple “Log in with Facebook” button that
makes it easier for new customers to register at your site, to more complex services,
such as receiving a real-time video security feed from home.
Almost any business with data or expertise (including business rules embedded
within legacy applications) must master the disciplines required to develop, secure,
share, use and monetize APIs. They will become even more essential and strategic
tools in organizations’ push for market share and revenue as the number and
variety of applications, devices and data types grow.
APIs also ease the move to micro-services architectures by replacing monolithic Web
applications with services that can be deployed and changed as needed. They slash
the time required to integrate organizational systems with those from a business
service provider to drive joint revenue. An example is the applications interoper-
ability that allows United Airlines passengers to book a ride with Uber from within
United’s mobile app.20
In a survey of 300 IT decision-makers:
75%
50%
said their
company has
an API strategy
said they are
generating revenue
via an API or will
within a year.
OVER
of whom
APIAPI
33%
50%
OF FINANCIAL
SERVICES
ORGANIZATIONS
OF MEDIA/
TELECOM
COMPANIES
are deriving revenue from
APIs, making over $10 million
through the channel.
70% of organizations are
integrating about 20 apps.
OF THOSE MAKING
$10 BILLION OR
MORE IN REVENUE:
are integrating
100 or more apps.50%
APIs by the Numbers
Source: “Mulesoft 2015 Connectivity Benchmark Report,” Mulesoft, May 2015.
Figure 9

APIs also make it relatively easy to enhance
an application, such as adding support for
a new mobile payments platform or a new
trading partner, because each micro-service
is operationally encapsulated. Developers
seeking to make use of the service only need
to understand the API, not the inner workings
of the application or service to which they are
connecting. This agility is enhanced when the
use of APIs is leveraged by DevOps, which
combines development and operations to
speed app deployment.
API-driven ecosystems also allow enterprises to sell selected internal systems
or data as profit-making products. One leading bank worked with us to offer an
internal training platform to its partner banks, turning what was an internal cost
center into a revenue source. Other financial services firms with which we work
offer APIs that make it easier for new applications such as mobile payment systems
to work with their legacy platforms. This prevents the loss of revenue and market
share from customers defecting to newer “direct” banks, or allows existing banks
to sell back-end processing services to such new entrants.
We assisted a U.S.-based bank holding company to develop a micro-services archi-
tecture that allows outside developers to create mobile applications that help
customers apply for auto and home loans. Our work began with a functional analysis
of 150 existing loan-related services that suffered from a lack of governance,
support and evaluation of the business requirements for the mobile applications.
Based on this, we published and documented a set of core services through APIs,
and defined an orchestration layer to handle specific channels such as Web and
embedded software for devices on the IoT. We also developed requirements and
implemented DevOps to build, deploy, configure and monitor the services.
The failure to deliver secure, easy-to-use APIs (or choose the right APIs from a
partner) can isolate systems and data from customers and partners, depriving orga-
nizations of potential revenue and market share. Businesses should also consider
the costs of delivering, maintaining and managing APIs, realizing that every micro-
service requires ongoing support and enhancement.
Developers seeking to make
use of the service only need
to understand the API, not
the inner workings of the
application or service to which
they are connecting.

• Build APIs with the end customer and the
data to be transferred in mind, which includes
thorough documentation and ease of use. A
retailer that sells product sales data through
an API, for example, should include granular
access controls over which manufacturers can
see what data and for how long, while ensuring
that competitors cannot see each other’s infor-
mation, and that the data access does not slow
the retailer’s own systems.
• The use of pre-fetching or caching can help
improve performance on the recipient’s end.
• Consider platforms that help companies
develop, secure, share, monitor and monetize
their APIs, such as Apigee and Mashery.
• The use of the 12-Factor App methodology21
can help enforce best practices. Examples
include explicitly declaring dependencies. (i.e.,
the databases or other systems on which an
application relies so they can be accessed when
needed) and keeping the development environ-
ment as close to the production environment
as possible to reduce the risk of code failing
when put into production.
• To avoid the creation of too many expensive
services, we recommend designing them to
support specific business capabilities, such as
price look-up or inventory check, rather than
technical functions, such as data access. Design
each service to be as small as possible while
still delivering its required function. Service
creation and deployment can be aided by
useful open source tools, as well as emerging
integration platform as-a-service offerings.
• A successful API-powered micro-services
strategy requires DevOps, continuous integra-
tion, testing, logging and tracing, monitoring,
messaging, service registration and discovery.
Service design reviews help avoid duplicate
services, while service structure reviews ensure
that services follow approved designs. Use of
JSON22
or a similar language makes it easier for
other developers to understand and work with
the services offered by the business.
Quick Take
To avoid the creation of too many expensive
services, we recommend designing them to
support specific business capabilities, such as
price look-up or inventory check, rather than
technical functions, such as data access.
Advice for API-Driven Ecosystems

For Your Next App or Next Employee,
Look to the Cloud
Today’s Reality
Between the rise of global services and open source software, enterprise sourcing
models have changed more in the last decade than in all of the previous decades of
the information age.
However, those changes pale beside the shifts that businesses
will make to meet tomorrow’s demands for low-cost, high-
quality and agile delivery to accommodate, if not exceed, the
needs of digital business. Fewer organizations can afford the
massive internal IT staffs or proprietary hardware that sits on
the balance sheet whether they’re used or not. Nor can they
watch competitors grab market share while HR seeks special-
ized skills with the latest data query language or IT deploys
the servers needed to deliver responses to real-time queries.
On the skills front, new cloud and Web-based sourcing
provides IT with high levels of flexibility and efficiency — with
the additional benefit that customer and provider need not be
in the same town, time zone or even continent. Many of these
collaborators inside and outside the organizational firewall will
leverage open source software for everything from research
and development applications to software testing. Increasingly,
talent will come and go on an as-needed basis, in what has
increasingly been termed the “gig economy.”23
On the technology front, everything from open source develop-
ment platforms and applications to security will be available as
a service from the cloud (see Figure 10). This will save massive
investments in in-house data centers, but decimate sales and
margins at legacy vendors. As a result, the shift is already
on to small, innovative software vendors, many of which sell
products based on lower-cost (and often more feature-rich)
open source software (OSS) that customers can tweak to meet
their needs (see Figure 11, next page).
Amid these changes, enterprises must balance the drive for
efficiency and agility with their need for security and reliabil-
ity. Legacy systems that would be too difficult, expensive or
sensitive to move to the cloud must co-exist with cloud-based services. To help
Digital Sourcing
SECTION 7:
In a recent survey of 930 IT professionals,
93%
are using the cloud.
The public cloud makes up 88% of users, and
63% of users employ the private cloud, while
over half use both.
Cloud, the New Normal
Source: “2015 State of the Cloud Survey,” Rightscale,
Feb. 18, 2015.
Figure 10

manage this mix, many IT organizations are struggling to become “honest brokers”
of internal and external services, expert at assessing their own capabilities and pro-
actively looking outside for faster, less expensive or more effective solutions.
With growing levels of education and broadband penetration, the global pool of
independent, highly skilled workers will grow rapidly. According to McKinsey & Co.,
up to 540 million people worldwide could benefit from online talent platforms by
2025, boosting global GDP by $2.7 trillion.24
Advances in analytics and machine
learning will provide businesses with increasingly rich real-time insights into the
skills and qualifications of this talent pool. Declining costs for cloud-based services
(Amazon Web services cut its price 8% from Oct. 2013 to Dec. 2014, while Google
and Microsoft dropped prices 5% to 6%25
) and new business models such as crowd-
funding26
will help collapse barriers to entry for new competitors.
Organizations should look for:
• The provision of more IT and business services over the cloud, with increased
automation through software-defined services and improvements in machine
learning and predictive analytics (see Section 5 on the software-defined
everything/automation everywhere, page 19).
39%
plan to start
own external
OSS project
47%
will release
internal tools
and projects as
open source
expect to
reduce barriers
to employee
participation in
OSS
53%
In the next 2-3 years, corporate participation
in open source solutions will increase.
Open Source Takes Off
Source: “2015: The Future of Open Source,” Blackduck Software, April 15, 2015.
Figure 11

• The spread of open-source software, forcing reliance on a distributed “volunteer”
global support system that is not accountable through traditional contracts.
• The explosion of “shadow IT” as business units bypass central IT to meet urgent
needs. This will drive adoption of software-defined infrastructures and pervasive
security that is flexible enough to manage and protect decentralized infrastruc-
tures.
Tapping global talent reduces costs and improves quality. Walmart’s use of the
Kaggle crowdsourced platform to analyze pricing strategies led not only to useful
insights but also the hiring of specialists that the retailer might otherwise have
overlooked.27
We used our “Crowd-on-Cloud” crowdsourcing solution to field-test
a mobile financial education application for global financial services giant UBS.
Seasoned staff in different locations tested the
application on a variety of devices for performance,
functionality, security, content and user interface
parameters. This helped boost the application’s
performance while speeding turnaround and
reducing costs.28
Skilled local workers can help organizations
tailor their products, marketing and business
practices to a new market, and quickly ramp staff
up or down without committing to full-time staff.
Crowdsourcing is also an opportunity to apprentice
or audition staff before hiring them.
The smaller data center footprints found in this new
model do not have to mean reduced clout for IT.
CIOs that can change their skill sets and mindsets
can gain influence by becoming “trusted brokers”
that monitor the market for needed technologies and skills, and help manage the
risks and benefits of working with new providers. By protecting core data and
systems while meeting rising needs for data and services, they also can become
trusted guardians of the enterprise’s core assets.
Many IT organizations are struggling to become “honest
brokers” of internal and external services, expert at
assessing their own capabilities and proactively looking
outside for faster, less expensive or more effective
solutions.
CIOs that can change their skill
sets and mindsets can gain
influence by becoming “trusted
brokers” that monitor the
market for needed technologies
and skills, and help manage the
risks and benefits of working
with new providers.

Advice for Digital Sourcing
• Technologies such as semantic search and
machine learning can help find and rank
workers, while new collaboration tools will make
it easier for them to share their work, be eval-
uated and get paid. Technology vendors such
as Textkernel offer software that provides
multi-lingual parsing of resumes and semantic
search that understands when employers and
job seekers use different terms or phrases to
describe the same assignment or skill. Wazoku’s
Idea Spotlight allows
access management, can ease the use of dis-
tributed systems through single sign-on, as well
as enabling logging and analytics. A loosely-
coupled architecture, in which applications
and services are not tied to specific hardware,
makes it easier to switch suppliers of either
IT or business process services (see Section
5 on software-defined everything/automation
everywhere, page 19).
• As IT struggles to weigh the security and
reliability risks of purchasing from smaller,
lesser-known vendors against the cost and
agility benefits, effective due diligence will
become more important than ever. Businesses
should work closely with their organization’s
legal department to understand the licensing
and intellectual property issues around open
source software, and how use of the cloud
could be affected by the latest rulings and
regulations around data privacy (particularly
in regions such as the European Union, where
privacy regulations are particularly restrictive).
• The gig economy is an opportunity to work
more closely with business heads, legal and
project management offices to minimize the
risk of working with new providers. This might
include terms, conditions and contracts for
trial runs that allow businesses to end the rela-
tionship without loss once short-term goals are
attained, or if the vendor can’t deliver.
• Organizations should assign an individual
or group to monitor sources of alternative
technology, such as crowdfunding sites and
universities. Furthermore, decision-makers
should seek out the most innovative individuals
or groups within their organizations to discover
best practices and sources of technology.
• Internal crowdfunding programs should be
considered that allow employees to “vote”
(with company dollars) for the projects they
believe would deliver the most business value.
Quick Take
A loosely-coupled
architecture, in
which applications
and services are
not tied to specific
hardware, makes
it easier to switch
suppliers of either IT
or business process
services
users to capture, evaluate,
prioritize and select ideas,
and provides analytics to
track activity on crowd-
sourced projects.29
• Organizations must
understand local labor
laws and how they
affect how this distrib-
uted workforce is paid,
the benefits they receive,
and who owns the code
and other intellectual
property they generate.
• Creative organizations
should tap the power
of social platforms to
allow peers to rank each
other’s skills, much as
renters (and guests) rate
each other on Airbnb. The tools to automati-
cally, and accurately, assess and verify such
skills are not yet widely available, but this is
an area IT organizations should monitor.
• Business and IT leaders should work
together to understand the specific levels of
skill and experience required, in which specific
areas, for each potentially crowdsourced task.
This will make it easier to create rules for the
predictive analytics required to accurately
rank potential collaborators.
• Using cloud services across the enterprise
reduces capital and operating costs for the
distributed workforce by allowing the provi-
sioning of virtual devices as needed, as well
as automating their management. The use
of API-enabled systems, such as identity and

These new staffing models can fail if IT cannot properly evaluate and verify the
identities, skills and experience of contributors, or find the required gig economy
skills. Lapses in these areas can cause waste, delay and even security risks.
Businesses must educate just-in-time staff on their priorities, cultures and goals,
and battle reluctance to trust unknown outsiders with corporate data or code. This
is where a micro-services architecture can help by providing standalone test envi-
ronments that do not expose core systems to vulnerabilities, while pervasive and
self-protecting assets defend against attacks that penetrate the corporate core.
(Learn more in Section 3 on pervasive security, page 12.)
On the infrastructure front, use of the cloud — especially combined with traditional
on-premise IT — may trigger complex licensing, access management, data privacy
and security issues. Some legacy systems will be too difficult or expensive to move
to the cloud, requiring costly integration or the movement of large amounts of data
to and from the cloud. Local privacy and security regulations may make it impossible
or cost-prohibitive to move some operations or data among cloud providers.
Footnotes
1
Code Halo thinking describes the art and science of distilling and applying
meaning from the digital code that surrounds people, process, organizations and
devices, or things. To learn more, read “Code Rules: A Playbook for Managing at
the Crossroads,” Cognizant Technology Solutions, June 2013, http://www.cognizant.
com/Futureofwork/Documents/code-rules.pdf, and the book, Code Halos: How
the Digital Lives of People, Things, and Organizations are Changing the Rules of
Business, by Malcolm Frank, Paul Roehrig and Ben Pring, published by John Wiley &
Sons. April 2014, http://www.wiley.com/WileyCDA/WileyTitle/productCd-1118862074.
html.
2
Greg Bensinger, “Amazon Wants to Ship Your Package Before You Buy It,” Wall
Street Journal, Jan. 17, 2014, http://blogs.wsj.com/digits/2014/01/17/amazon-
wants-to-ship-your-package-before-you-buy-it/.
3
Laurie Sullivan, “Disney Finds Emotion Next Targeting Metric For Advertising,
Marketing,” MediaPost, Oct. 2015, http://www.mediapost.com/publications/
article/259739/disney-finds-emotion-next-targeting-metric-for-adv.html.
4
Stream processing allows some applications to exploit a limited form of parallel
processing. Source: https://en.wikipedia.org/wiki/Stream_processing.
5
Kashmir Hill, “How Target Figured Out A Teen Girl Was Pregnant Before Her Father
Did,” Forbes, Feb. 6, 2012, http://www.forbes.com/sites/kashmirhill/2012/02/16/
how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/.
6
Normal website, https://nrml.com/.

7
“Tata Docomo: ‘Hyperpersonalization’ Direct Marketing by Interface Business
Solutions,” Coloribus, Jan. 2013, http://www.coloribus.com/adsarchive/direct-
marketing/tata-docomo-hyperpersonalization-18372455/.
8
Melissa Dahl, “The Future of Dieting Is Personalized Algorithms Based on Your
Gut Bacteria,” New York Magazine, Oct. 2, 2015, http://nymag.com/scienceo-
fus/2015/10/future-of-dieting-is-personalized-algorithms.html.
9
Chris Morris, “More than 20,000 Kids Just Got Hacked,” Fortune, Nov. 30, 2015,
http://fortune.com/2015/11/30/vtech-hacking-children-data/; Whitney Meers, “Hello
Barbie, Goodbye Privacy? Hacker Raises Security Concerns,” Huffington Post, Nov.
30, 2015, http://www.huffingtonpost.com/entry/hello-barbie-security-concerns_565
c4921e4b072e9d1c24d22.
10
“Gartner Says 4.9 Billion Connected ‘Things’ Will Be in Use in 2015,” Gartner press
release, Nov. 11, 2014, http://www.gartner.com/newsroom/id/2905717.
11
Andy Greenberg, “Hackers Remotely Kill a Jeep on the Highway—With Me in It,”
Wired Magazine, July 21, 2015, http://www.wired.com/2015/07/hackers-remotely-
kill-jeep-highway/.
12
Kim Zetter, “Hacker Can Send Fatal Dose to Hospital Drug Pump,” Wired Magazine,
June, 2015, http://www.wired.com/2015/06/hackers-can-send-fatal-doses-hospi-
tal-drug-pumps/.
13
DevOps is an approach to software development that is focused on streamlined
communication, collaboration, integration and automation (of testing as well as
coding), as well as measurement of cooperation between software developers and
other IT functions. The term was popularized through a series of “DevOps Days”
starting in 2009 in Belgium. Since then, DevOps Days conferences have been
held in many countries worldwide. Source: https://en.wikipedia.org/wiki/DevOps.
For more on DevOps, read our white papers “How DevOps Drives Real-Time
Business Growth,” http://www.cognizant.ch/InsightsWhitepapers/How-DevOps-
Drives-Real-Time-Business-Growth.pdf, and “DevOps Best Practices: Combine
Coding with Collaboration,” http://www.cognizant.ch/InsightsWhitepapers/
DevOps-Best-Practices-Combine-Coding-with-Collaboration_nn.pdf.
14
Amanda Kooser, “Smart Shoes Vibrate You in the Right Direction,” CNet, July
29, 2014, http://www.cnet.com/news/bluetooth-smart-shoes-vibrate-you-in-the-
right-direction/.
15
To learn about extinction events caused by the inability by companies to
compete on code, read Code Halos: How the Digital Lives of People, Things,
and Organizations are Changing the Rules of Business, by Malcolm Frank, Paul
Roehrig and Ben Pring, published by John Wiley & Sons, April 2014, http://www.
wiley.com/WileyCDA/WileyTitle/productCd-1118862074.html.
16
Timothy Torres, “Are You Satisfied With Your Care?’ New ‘Gentle’ Caregiver Robot
from Japan Enters Experimental Stage,” Tech Times, March 2015, http://www.
techtimes.com/articles/36950/20150303/satisfied-care-caregiver-robots-japan.
htm.
17
An expression coined by Netscape inventor and venture capitalist Marc
Andreessen to explain how software pervades today’s products and services.
Source: http://forwardthinking.pcmag.com/none/300368-marc-andreessen-
explains-why-software-is-eating-the-world.
18
“Walgreens: Putting an API around their Stores,” Apigee, http://apigee.com/
about/customer-story/walgreens-putting-api-around-their-stores.

19
Pratap Ranade, Devin Scannell, Brian Stafford, “Ready for APIs? Three Steps
to Unlock the Data Economy’s Most Promising Channel,” Forbes, Jan. 7, 2014,
http://www.forbes.com/sites/mckinsey/2014/01/07/ready-for-apis-three-steps-
to-unlock-the-data-economys-most-promising-channel/.
20
Dennis Schaal, “Uber Secures a Top Spot in United’s Mobile Apps in Business
Travel Push,” SKift, Aug. 20, 2014, http://skift.com/2014/08/20/uber-secures-a-
spot-in-uniteds-mobile-apps-in-business-travel-push/.
21
The Twelve Factor App website, http://12factor.net/.
22
JavaScript Object Notation is an open standard format that uses human-read-
able text to transmit data objects consisting of attribute–value pairs. Source:
https://en.wikipedia.org/wiki/JSON.
23
Arun Sundararajan, “The Gig Economy Is Coming. What Will It Mean for Work?”
The Guardian, July 25, 2015, http://www.theguardian.com/commentisfree/2015/
jul/26/will-we-get-by-gig-economy.
24
“Connecting Talent with Opportunity in the Digital Age,” McKinsey Global
Institute, June 2015, http://www.mckinsey.com/insights/employment_and_
growth/connecting_talent_with_opportunity_in_the_digital_age.
25
“Cloud Computing Price War, Only the Beginning,” Cloud Tweaks, January 2015,
http://cloudtweaks.com/2015/01/cloud-computing-price-war-beginning/.
26
“2015CF: The Crowdfunding Industry Report,” Crowdsourcing.org, April 7, 2015,
http://www.crowdsourcing.org/editorial/global-crowdfunding-market-to-reach-
344b-in-2015-predicts-massolutions-2015cf-industry-report/45376.
27
“Walmart: The Big Data Skills Crisis and Recruiting Analytics Talent,” Forbes, July
6, 2015, http://www.forbes.com/sites/bernardmarr/2015/07/06/walmart-the-big-
data-skills-crisis-and-recruiting-analytics-talent/#2715e4857a0b153185cd247d.
28
“Cognizant 2014 Annual Report,” Cognizant Technology Solutions, 2014, http://
www.cognizant.com/SiteDocuments/Cognizant_Annual_Report_2014L.pdf.
29
More information on Textkernel and Wazoku can be found at http://www.
textkernel.com/ and http://www.wazoku.com/.
Credits
This white paper was researched and written by the Cognizant Global Technology Office (GTO).
Providing key technology trend insights and analyses were Joseph Tobolski, GTO Vice-President and
U.S. Chief Technology Officer, as well as Gerhard Koch, Prabhakaran Sabhapathy, Uma Ramachandran,
M. Murali and Mahesh Balaji, who function as business unit CTOs and play key roles within the
Cognizant Technology Labs organization.

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Riding the Seven Waves of Change That Will Power, or Crush, Your Digital Business

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