RESILIENCY IN
THE COGNITIVE ERA
IN AN ALWAYS- ON WORLD, REAL-TIME DATA FLOW
AND CONTINUOUSLY CONNECTED
COGNITIVE APPLICATIONS WILL BE ESSENTIAL
IN ASSOCIATION WITH:
CONTENTS
Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2
Key points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4
What changes in the cognitive era? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7
Always on: The importance of continuous availability in the cognitive era. . . . . . .
9
The benefits will be breathtaking. So should the resiliency. . . . . . . . . . . . . . . . . . . . .
11
How cognitive capabilities can improve resiliency . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13
Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
16
EXECUTIVE SUMMARY
Cognition enables a new level of engagement with technology and a new class
of products and services that sense, reason and learn about their users and
the world around them. A cognitive system capitalizes on data from internal
and external sources for continuous learning and better forecasting for real-time
analytics in a fraction of the time it would take a human. To take full advantage
of these capabilities requires a high degree of resilience; data must be accurate,
available, accessible and auditable.
New cognitive applications are increasing expectations and raising resiliency
requirements for the overall enterprise as well as its IT and data environment. At
the same time, cognitive capabilities can help an organization maintain an alwayson environment and meet business continuity and disaster recovery goals in a
predictive and proactive way.
2 | RESILIENCY IN THE COGNITIVE ERA
KEY POINTS
Cognitive computing has arrived. It is enabling a new class of products and
services that sense, reason and learn about their users and the world around
them. This is already happening in industries including automotive, medical,
hospitality, government, media, games, manufacturing, travel, engineering,
law, pharmaceutical and science.
As cognitive computing becomes part of our everyday world, it has the
potential to radically redefine everyday life, changing how companies deliver
products and services, engage and interact with customers, learn and make
decisions.
In the cognitive era the continuous availability of data, systems, applications
and business processes is essential. It will increasingly be taken for granted
that the service is “always on.” Applying advanced analytics and automation
to predict potential issues and enable systems to be corrected proactively will
enable businesses to seize new opportunities and defend against disruption.
IBM is investing in new capabilities to help clients move from reactive business
continuity and disaster recovery planning to a cognitive, predictive and proactive resiliency program. The goal: to avoid the impact of a disaster before
it occurs.
COPYRIGHT © 2016 FORBES INSIGHTS | 3
INTRODUCTION
Five years ago, the world was introduced to Watson, IBM’s cognitive computing
system, which defeated two human champions in an exhibition match of the
American game show Jeopardy. Watson has learned a lot since then, tackling
ever more complex data sets to develop understanding, reasoning and learning
capabilities that go far beyond answering trivia questions.
Watson is helping oil and gas companies combine
seismic imaging data with analyses of papers and
reports, current events, economic data and weather
forecasts to outline risk-and-reward scenarios before
drilling. Financial institutions are employing cognitive computing for investment recommendations. In
Japan, an engaging humanoid robot named Pepper—
who will be assisting customers at bank branches and
retail outlets and providing companionship and care
in the home—will be powered with intelligence and
face recognition from Watson.
Watson’s debut on Jeopardy was played as a contest of
man versus machine—a machine designed to answer
questions with knowable answers. But Watson’s
tremendous knowledge base is now being trained
to answer complex questions and is able to present
extensively researched scenarios and probabilities
in fields such as oncology. The power of cognitive
computing is its ability to illuminate what was
previously invisible—patterns and insight from the
unstructured data of sound, pictures and movement—
allowing more-informed decisions about moreconsequential matters.Watson’s contributions are now
a matter of man plus machine.
Cognitive systems learn through experience, reason
with purpose and interact with humans naturally.
They represent a leap from the deterministic information systems that preceded them, explains John E.
4 | RESILIENCY IN THE COGNITIVE ERA
Kelly III, senior vice president, IBM Research and Solutions Portfolio. Cognitive systems are probabilistic.
“That means they can take all the data we ask them
to look at…and generate hypotheses, reasoned
arguments and recommendations, along with a
measure of the probability or confidence level of any
recommendation generated,” he says.
Unlike their science-fiction predecessors, cognitive
machines are neither able to feel emotion nor are they
autonomous. They have the potential to augment
our ability to understand—and act upon—complex
systems, such as the human genome. The success
of cognitive computing will not be measured by a
computer’s ability to mimic humans. It will be measured in more practical and essential ways, like return
on investment, more satisfied customers, new market
opportunities and—above all—lives saved.
We are in an age where we are not able to efficiently
or effectively utilize the volume of information that is
produced in a single day across every single industry.
Many organizations are struggling to draw meaningful
conclusions from the unstructured data they
already have. Cognitive computing represents a giant
leap forward in addressing this challenge. Its ability to
process a vast amount of information, learn from that
information and provide conclusions is far beyond
that of any other technology available today.
Watson’s Expanding Universe
Watson began with a challenge over a decade ago: if a
computer can beat a chess master in the wordless game of
chess, would it be possible to build a system that could compete in
a game that involved language? Watson was originally designed as a
system to answer questions posed in natural language—a system
capable of breaking down language into phrases, looking for statistically related information and reasoning through possible answers.
Over the past few years, Watson has developed into something
much greater. Watson is now a cloud-based platform. The platform
is available to developers who are finding ways to pull the cognitive
power of Watson into their own organizations in new ways. There are
over 80,000 programmers in more than 500 partner companies working
with Watson. They have launched hundreds of cognitive applications in
healthcare, retail, education, travel and other fields.
Watson’s universe continues to expand. The platform now includes realtime data on weather as well as Twitter feeds and sensor data from
a growing range of connected devices—all of which can be used to
build business-relevant applications. Watson has also developed sight,
beginning with the analysis of medical images. Watson started as an IBM
initiative, but it is now a partner in medical research and practice,
professional sports, insurance and many other industries. In the near
future, Watson could be powering applications in any organization that
would benefit from cognitive computing.
COPYRIGHT © 2016 FORBES INSIGHTS | 5
This presents an opportunity for the resiliency profession—or anyone responsible for the continuous
operation of an enterprise.
As cognitive capabilities become more indispensible,
continuous availability will matter even more than
it does now. If cognitive capabilities can help save
a patient’s life, then the consequences of an outage
could mean a dangerous delay in treatment. An
enterprise that depends on a continuous flow of
data to reach accurate results with a cognitive system
might miss valuable insights or risk inaccurate forecasts if that data were disrupted.
At the same time, cognitive capabilities have tremendous potential for improving resiliency and
disaster recovery. What might Watson teach us about
preparing for something as unpredictable as an earthquake? Shirley Ann Jackson, president of Rensselaer
Polytechnic Institute and former chairman of the
U.S. Nuclear Regulatory Commission in the Clinton
Administration, suggested that Watson could be
used to identify vulnerabilities, such as those at the
Fukushima nuclear power plant in Japan, before there
is a meltdown. If Watson could help mitigate the
damage from an unavoidable disaster, imagine what
cognitive capabilities could do for the everyday
challenges of ensuring resiliency.
Pr o ac t i v e R e si l i e nc e
Business resiliency is the ability of an organization to anticipate, respond
and adapt to sudden disruption as well as opportunity. As tolerance for
downtime continues to decrease, the focus of resiliency is to ensure that
businesses are able to continue operations, no matter what happens.
With the ever-increasing reliance on technology, the impact of a failure
of technology could be catastrophic and even life-threatening in some
industries. The integration of analytical and cognitive capabilities can
improve the way companies enable resilience—moving from reactive responses to predictive and proactive alternatives to avoid the impact of
a technology disaster before it occurs.
6 | RESILIENCY IN THE COGNITIVE ERA
WHAT CHANGES IN THE COGNITIVE ERA?
The difference between cognitive computing and conventional computing is its
ability to learn, reason and rapidly present a scenario or predict an outcome with
a measurable degree of certainty.
Extracting that knowledge from any cognitive system
depends on continuously feeding it as much accurate information as possible and then asking the right
questions. In fact, knowing all the answers will no
longer distinguish someone’s intelligence, says IBM’s
Kelly. Human intelligence will be measured by the
ability to ask better questions.
will come through partnerships—partnerships to
source data and partnerships to analyze it. And most
organizations will be managing themselves within
an ecosystem that will revolve around the data they
already possess as well as specialized analytic capabilities from a range of vendors and the vast new data
resources of the Internet of Things.
The insights generated by any cognitive system will
be only as good as the data it can access. Data is
already viewed as an asset in most organizations, just
as real estate has been for millennia and intellectual
property for more than a century. In the cognitive
era, maintaining data quality and availability will
be imperative. This is where data management and
continuous availability are key.
To be effective, any cognitive system will need to
generate an analysis fast enough to make a difference,
and to provide trusted results. For example, if a city
government is going to place limits on driving within
certain areas or close factories for a day to avoid a
predicted pollution crisis, there must be a high degree
of confidence in the prediction, the data used to
create the prediction and the timeliness of the analysis.
IDC, a market intelligence firm, estimates the amount
of data will continue to double every two years, and
the great majority of it will be unstructured. The
ability to analyze that much moving data and compute meaningful insights is outside the core mission
of most enterprises. The bulk of these capabilities
“The key for Watson-powered applications—or any
other analytics system that relies on data—is that the
data is always available, accessible, accountable and
auditable,” says Scott Ramsey, global partner, IBM
Resiliency Services.
Many organizations are struggling to draw meaningful
conclusions from the unstructured data they already have.
Cognitive computing represents a giant leap forward in
addressing this challenge.
COPYRIGHT © 2016 FORBES INSIGHTS | 7
data
and
m e d i c i ne
Medtronic, one of the largest medical technology companies, is
a pioneer in inventing and managing connected devices to improve
the health of patients with chronic diseases, such as diabetes. Diabetes
is a big disease, affecting one in 11 people around the world at a cost
of $673 billion a year globally, says Omar Ishrak, CEO of Medtronic.
Most patients measure their own blood sugar, perhaps only once a day,
and their doctors may only see average data compiled over a period of
several months. But diabetes is a complicated disease, and a patient’s
situation changes by the minute, says Ishrak. Looking at average data
would do nothing to prevent a life-threatening situation, such as a hypoglycemic event. “This is where the Internet of Things can make a
tremendous difference,” says Ishrak.
Medtronic is working with a Watson-powered system to develop a realtime, cloud-connected monitoring device that can integrate continuous
data from as many relevant sources as possible. Patients would have
access to a dashboard of their own data and would be able to ask the
system questions such as, “If I have this pasta dish, what will that do to
my carbohydrate budget for today?”
With Watson, the advisory function can be even more proactive. For
example, analyzing past data for a particular patient together with
data from patients with similar profiles, Watson might detect a pattern
that indicates a possible hypoglycemic event in three hours, even if the
patient is well within the safe zone at that moment, and then send out
a notification so the person with diabetes can take action to avoid a
serious health event. Eventually, activity data from other wearable
devices could make this application even more accurate, says Ishrak.
To achieve this level of personal trust—where someone’s safety
and well-being are at stake—will require a highly resilient technology
ecosystem.
8 | RESILIENCY IN THE COGNITIVE ERA
ALWAYS ON:
THE IMPORTANCE OF CONTINUOUS
AVAILABILITY IN THE COGNITIVE ERA
We already demand a lot of our technology. Five years ago, the idea of
controlling our homes remotely, monitoring our health with a wearable device
or dictating text would have seemed remarkable. Now we take it for granted.
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By 2020, IDC predicts there will be 30 billion
connected devices—all transmitting data and communicating with other devices—with many relying
on cloud-based operating technology to function
properly. All of these cutting-edge capabilities require
on-demand technology and the continuous flow of
reliable, real-time data.
30
In
Embedded sensors and advanced analytics are also
transforming healthcare, public safety, aviation,
urban planning and the insurance industry. Consider
the technology built into many new vehicles—not
only the autonomous variety. Some safety features are
becoming more standard, such as collision avoidance
technology that can take advantage of real-time
sensor data to automatically brake or steer clear of an
imminent collision.
Internet of Things
Billions of connected devices
In business, advanced analytics have opened a world
of insight into what customers want and need—
sometimes before customers are even aware they want
or need anything. Embedded sensors and connected
devices are telling companies how their products are
used and when they need service. IDC predicts that
by 2020, the success rate of new product introductions will improve by 70% and planning cycles for
product development will be cut by 50%, as a result
of what we will learn from the sensor data in existing products. For many enterprises, this capability
is transforming the way they interact with customers. Think of what mobile applications have done for
consumer banking and finance in the past few years.
Or how GPS allows brick-and-mortar stores to interact with customers through their devices in real
time—while they are in the store. Beyond analytics,
the youngest consumers are already interacting with
the first generation of cognitive-powered, talking toys.
Source: IDC, Worldwide and Regional Internet of Things (IoT) 2014–2020 Forecast: A Virtuous Circle of Proven Value and Demand, 2014
Denise Lund Carrie MacGillivray Vernon Turner Mario Morales
COPYRIGHT © 2016 FORBES INSIGHTS | 9
Building the data is one step to establishing a cognitive system. Building intelligence requires training
the system. As a platform, Watson has access to
vast amounts of data—and the ability to grow data
continuously in real time. Each industry and each
application will have a unique set of questions to answer, patterns to discern and phenomena to monitor.
Programmers, application developers and users tell the
system what they want or need, Watson analyzes the
data and learns both from the questions asked and the
history of outcomes exhibited by similar phenomena
and patterns. The more data Watson collects and the
more users interact with Watson, the more the system
will learn.
Much of what cognitive computing can accomplish
could be done by a human, given enough time, but
not as fast as an intelligent machine can do it. How
long would it take a team of oncologists to pore over
tens of millions of medical journals and papers, compare images of similar cancers and analyze the genome of a single cancer patient to help design a treat-
ment plan? By the time they finished, it might be too
late for their patient. Watson can do it in a matter
of seconds.
In the cognitive era, Big Data rules and Big Data
is time sensitive. The breadth of data relevant to a
particular activity would be irrelevant without a
means to analyze it and generate meaningful insights
fast enough to make a difference.
“Businesses will adapt to significantly increased
speed where results become available through
complex analytics and cognitive computing,” says
Mijee Walker, global strategy leader, IBM Resiliency
Services. “Once businesses have transformed to using
cognitive-enabled processes, the traditional reliance
on manual procedures during an IT outage will
no longer be able to provide the results at the speed
businesses expect and need. This drives the requirement for a resilient architecture of the end-to-end
cognitive system designed to minimize downtime and
ensure no data loss.”
l i f e -sav i ng i nsi ght s
Oncology is one of the first areas in which IBM chose to build Watson’s
capabilities as a cognitive system of insight. Working with leading cancer
institutes, Watson is being trained to play an advisory role in research and patient
treatment. For doctors at University of Texas MD Anderson Cancer Center,
the training is working both ways. While doctors and researchers help expand
the core knowledge available to all cancer treatment practitioners, Watson uses
all that structured and unstructured data to illuminate molecular anomalies,
outline treatment possibilities and even help discover new proteins for future
cancer research.
“Watson allows us to truly integrate research into everyday care,” says Lynda
Chin, associate vice chancellor and chief innovation officer for health affairs, the
University of Texas System. “It allows us to practice the art of medicine, not just
the science.”
10 | RESILIENCY IN THE COGNITIVE ERA
THE BENEFITS WILL BE BREATHTAKING.
SO SHOULD THE RESILIENCY.
IT infrastructures are already diverse—part traditional IT, part private cloud, part
public cloud and part hybrid cloud—and increasingly delivered as a service to
improve speed, flexibility and scalability.
The increased integration of different enterprise
systems makes resilience far more complex, says
Patrick J. McMahon, U.S. practice leader, IBM
Resiliency Services. “The technology being deployed
is much more heterogeneous and drives more complex solutions, and that makes it harder to maintain
resiliency,” he says. “It’s significantly more difficult to
recover an application or business process that cuts
across multiple point solutions.”
more embedded in cognitive applications in a tiered
way, says Laurence Guihard-Joly, general manager,
IBM Resiliency Services. “As more interconnected
devices are gathering information and generating
data, we will start to see more insights derived from
the analysis of data, and the need to safeguard that
data to ensure it is protected while, at the same time,
continuously available to the stakeholders who need
access to it.”
But what needs to change going forward to make this
happen? First of all, resiliency will need to become
“Businesses will adapt to significantly increased
speed where results become available through
complex analytics and cognitive computing.”
–Mijee Walker
Global Strategy Leader,
IBM Resiliency Services
COPYRIGHT © 2016 FORBES INSIGHTS | 11
The graphic below depicts the “IBM Business Resiliency Framework,” illustrating seven layers of
resiliency across the enterprise. As cognitive computing becomes more pervasive within organizations,
there will be additional considerations in each layer related to resiliency.
Strategy
and Vision
Have you considered the impact of
not being able to support cognitive
capabilities used in design of business
strategy and vision?
Organization
How will cognitive computing impact
your organization’s structure and its
ability to recover during a crisis?
processes
What will you need to do in order to
recover cognitive capabilities as they
are embedded into business processes?
applications
Have you considered the impact to
your systems development life cycle as
cognitive applications are developed
and their resiliency requirements?
data
Data is the life-blood of cognitive
computing. How will that bear on your
data replication and recovery strategies?
technology
Have you considered the requirements
for ensuring continuous availability of
cognitive platforms in your resiliency
program?
facilities
Are you thinking about the design
requirements for facilities and data
centers supporting cognitive computing?
IBM BUSINESS RESILIENCY FRAMEWORK
In the cognitive era, the collaboration between man and machine will create significant dependencies
between them. The loss of data or infrastructure will have severe impacts and consequences. This requires
resiliency strategies to ensure data and infrastructure are always there and available on demand.
12 | RESILIENCY IN THE COGNITIVE ERA
HOW COGNITIVE CAPABILITIES
CAN IMPROVE RESILIENCY
The same cognitive capabilities that are expanding knowledge and redefining
analytics can be deployed to make any enterprise more resilient. Consider a
factor as fundamental and uncontrollable as the weather.
According to data gathered by Munich Re, weatherrelated natural catastrophes in the United States
caused more than $1 trillion in losses and 30,000
deaths between 1980 and 2011. What if we could
crunch weather data to predict the potential impact of
severe weather and prompt appropriate action? Using
Weather Company data and Twitter feeds, insurance
companies are now able to use a Watson-powered
application for real-time weather insights to alert
clients to hazardous conditions, such as a hailstorm,
and suggest alternate routes or shelter locations.
Airlines have the opportunity to combine real-time
and historical data to reduce delays and optimize
fuel consumption. Utilities could be able to better
predict outages and respond more quickly when bad
weather strikes.
IBM’s Guihard-Joly believes this kind of dynamic, real-time knowledge can help companies adapt
products and services that anticipate the weather,
including disaster recovery and business continuity. “We have a crisis team in every country, tracking
storms and making sure the locations and teams are
ready, business units are informed, and their business
continuity leaders are aware of what’s coming,” she
says. “They will use all the help of cognitive capabilities to support critical decision making, such as do I
evacuate a site and send people home, or do I need to
move data to another location?”
Of course, humans have attempted to predict
the weather for millennia. What has changed is the
volume of data available to analyze and the cognitive
capabilities to use that data to customize, hypothesize
and learn continuously. Watson now ingests Weather
Company data from 3 billion weather forecast reference points, more than 40 million smartphones and
50,000 airplane flights per day. Those data points
will grow exponentially as more and more devices
are connected. “You can really learn and increase the
accuracy of what you are doing and actually create
new data points, new learning and new services,” says
Guihard-Joly.
What else can cognitive computing capabilities do for
resiliency? Here are a few examples:
Predicting failure—and avoiding it. For resiliency
professionals, predicting weather events with more
accurate probability is only one of many tools in the
field of predictive failures. If there is a high probability
of a hurricane, for example, a system in its path could
fail ahead of time. Cognitive systems can run analysis
on different data sets, using correlation analysis and
time-series analysis to predict failures—for instance,
by mapping network service orders with past equipment failures to understand which scenarios are most
likely to result in a failure and avoid a full-blown
breakdown.
Analyzing best practices. Consider two com-
panies with state-of-the-art resiliency plans. One
company is experiencing outages, and the other
company is not. What are they doing differently? The
answer might not be obvious. Perhaps one company
is using bleeding-edge technology and the other is
waiting at least six months. A cognitive system can
compare multiple variables across multiple companies
to look for correlations that define the most successful
resiliency practices, and even do it by industry.
Relying on a virtual engineer. Dynamic automa-
tion can address repetitive and routine incidents, such
as adding storage if a file system is reaching capacity.
IBM’s virtual engineer is addressing 64% of incidents
automatically, reducing time to resolve a situation by
80 minutes on average.
Orchestrating process resiliency. Cognitive
computing can be deployed for resiliency planning as
well as predicting. “We can have multiple data copies,
we can have redundant systems, but even the bestlaid resiliency plans can be undone if one small ele-
COPYRIGHT © 2016 FORBES INSIGHTS | 13
ment in a process is missing,” explains BJ Klingenberg,
distinguished engineer, chief technology officer, IBM
Resiliency Services. Process orchestration is the key.
“When a process is executed, whether a claim for an
insurance company or a banking transaction, if we
fail to recover a dependent technology component,
the process fails,” he says. “We can have the cognitive system analyze any process to make sure we don’t
miss anything from a resiliency perspective,” he adds.
A Watson-powered application can learn every step of
a mission-critical process to help with planning and
in case of disaster recovery. A cognitive approach can
illuminate obscure dependencies that tend to develop
as systems grow in complexity.
Integrating the cognitive agent into technical support. Every moment equipment is down
can mean lost revenue, decreased productivity and
frustrated end-users. A cognitive agent can answer
questions with precision for faster uptime when
there is a technical issue. For IBM Power Systems™,
System x® and System Storage™, IBM Technical
Support Services use Watson to respond with an
answer in less than a second, reducing problem
determination time by up to 37%.
Adding cognitive analytics to disaster recovery and business continuity planning. Speed is
of the essence in an emergency. Cognitive analytics
can help prioritize the most effective allocation of
assets to restore systems and services, assist employees
and notify customers. This analysis can help in the
planning stage—and it can be ready to kick in with
the most up-to-date information if disaster strikes. For
example, if the roads are blocked and communication
lines are down for certain key employees, notifications to backup teams can be generated automatically,
based on the response, or lack of response, from
key responders.
M anag i ng t he D ata E xplosi on
Cognitive systems are already adding new analytic capabilities to resiliency
planning and disaster recovery. But the explosion in data from connected devices
and the enterprise-transforming power of analytics will test the limits of feasibility
for system resiliency going forward. “Data growth is the biggest issue I see with
every client,” says BJ Klingenberg, distinguished engineer, chief technology
officer, IBM Resiliency Services. The amount of new enterprise data doubles
every 18 months, according to IDC estimates. Data from sensors, devices and
social media is growing even faster. “Will we be able to build datacenters fast
enough to keep up?” he asks.
That raises an important question: When is it okay to throw data away? Or to stop
saving redundant data? How can an enterprise optimize its storage environment?
At some point, software-defined resiliency will help manage the data explosion,
predicts Klingenberg. “At IBM, we are applying cognitive techniques to determine
when you don’t need copies of the same data in storage, on the server and in
the application, because the costs are going to skyrocket,” he says. Data storage
optimization in the future will be a matter of orchestrating across these layers to
decide what really matters and tier storage intelligently.
14 | RESILIENCY IN THE COGNITIVE ERA
CONCLUSION
The future of technology is cognitive, and the future is here. Cognition is already
enabling a new class of products and services that sense, reason and learn about
their users and the world around them.
This is the true promise of cognitive computing
because it allows for continuous improvement and
adaptation, and for capabilities not previously imagined. This is already happening with cars, medical
devices, appliances and even toys. Cognition transforms
how a company operates. Business processes infused
with cognitive capabilities capitalize on the surge of
data from internal and external sources.
Is your organization ready? Is your resiliency program
able to support cognitive products and services? Can
you protect the flow of real-time data from connected
devices used by your customers? Will you be able to
support the deeper engagement that your customers
will come to expect from cognitive-enabled apps? Are
you ready to manage data availability when your data
is growing exponentially?
To succeed in the cognitive era, every organization
needs the right plan and the right tools to ensure
resilience and data quality. The time is now to make
sure your cognitive business processes are truly
resilient. Cognitive solutions can take your resiliency
program into the next era.
With cognitive infused into your resiliency program,
you will be able to:
• Provide the right level of data availability
and protection across your business
• Become more proactive than reactive in your
resiliency program
• Improve your resiliency profile
There is a strong business case for adding cognitive
to your resiliency program. A holistic risk management approach plus a strong and proactive resiliency
profile will allow an organization to take more business risks—all while securing employees’ engagement
and taking full advantage of cutting-edge technologies to create a differentiated customer experience. A
strong resiliency program is, ultimately, a competitive
advantage.
COPYRIGHT © 2016 FORBES INSIGHTS | 15
ACKNOWLEDGMENTS
Forbes Insights and IBM would like to thank the following individuals
for their time and expertise:
Dr. Lynda Chin, Associate Vice Chancellor and Chief Innovation Officer for Health Affairs,
the University of Texas System
Laurence Guihard-Joly, General Manager, IBM Resiliency Services
Omar Ishrak, CEO, Medtronic
John E. Kelly III, Senior Vice President, IBM Research and Solutions Portfolio
BJ Klingenberg, Distinguished Engineer, Chief Technology Officer, IBM Resiliency Services
Patrick J. McMahon, U.S. Practice Leader, IBM Resiliency Services
Scott Ramsey, Global Partner, IBM Resiliency Services
Mijee Walker, Global Strategy Leader, IBM Resiliency Services
Learn more about IBM Resiliency Services at
ibm.com/services/resiliency
16 | RESILIENCY IN THE COGNITIVE ERA
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Matthew Muszala, Manager
William Thompson, Manager
Erika Maguire
Director of Programs
EDITORIAL
Kasia Wandycz Moreno, Director
Hugo S. Moreno, Director
Deborah Orr, Report Author
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Peter Goldman, Designer
EMEA
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APAC
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RESEARCH
Ross Gagnon, Director
Kimberly Kurata, Research Analyst
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