resiliency in the cognitive era

RESILIENCY IN THE COGNITIVE ERA

IN ASSOCIATION WITH:

IN AN ALWAYS-ON WORLD, REAL-TIME DATA FLOW AND CONTINUOUSLY CONNECTED COGNITIVE APPLICATIONS WILL BE ESSENTIAL

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

CONTENTS

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 always-

on environment and meet business continuity and disaster recovery goals in a

predictive and proactive way.

2 | RESILIENCY IN THE COGNITIVE ERA

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 pro-

active resiliency program. The goal: to avoid the impact of a disaster before

it occurs.

KEY POINTS

COPYRIGHT © 2016 FORBES INSIGHTS | 3


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 cogni-tive 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 !elds 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 more- consequential 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 infor-mation systems that preceded them, explains John E.

Kelly III, senior vice president, IBM Research and So-lutions 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 con!dence level of any recommendation generated,” he says.

Unlike their science-!ction 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 mea-sured in more practical and essential ways, like return on investment, more satis!ed customers, new market opportunities and—above all—lives saved.

We are in an age where we are not able to e"ciently or e#ectively 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.

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.

INTRODUCTION


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 statisti-

cally 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 real-

time 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.

Watson’s Expanding Universe


This presents an opportunity for the resiliency pro-fession—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 $ow of data to reach accurate results with a cognitive system might miss valuable insights or risk inaccurate fore-casts if that data were disrupted.

At the same time, cognitive capabilities have tre-mendous potential for improving resiliency and disaster recovery. What might Watson teach us about preparing for something as unpredictable as an earth-quake? 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.

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 re-

sponses to predictive and proactive alternatives to avoid the impact of

a technology disaster before it occurs.

Proactive Resilience

WHAT CHANGES IN THE COGNITIVE ERA?

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.


Extracting that knowledge from any cognitive system depends on continuously feeding it as much accu-rate 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.

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.

IDC, a market intelligence !rm, 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 com-pute meaningful insights is outside the core mission of most enterprises. The bulk of these capabilities

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 capabili-ties from a range of vendors and the vast new data resources of the Internet of Things.

To be e#ective, any cognitive system will need to generate an analysis fast enough to make a di#erence, 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 con!dence in the prediction, the data used to create the prediction and the timeliness of the analysis.

“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.

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.


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 hypo-

glycemic 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 real-

time, 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.

data and medicine

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2015

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2020

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9.1

11.4

13.7

16.3

19.2

22.2

25.2

28.1

ALWAYS ON: THE IMPORTANCE OF CONTINUOUS AVAILABILITY IN THE COGNITIVE ERA


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 introduc-tions 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 ex-isting products. For many enterprises, this capability is transforming the way they interact with custom-ers. Think of what mobile applications have done for consumer banking and !nance in the past few years. Or how GPS allows brick-and-mortar stores to in-teract with customers through their devices in real time—while they are in the store. Beyond analytics, the youngest consumers are already interacting with the !rst generation of cognitive-powered, talking toys.

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.

By 2020, IDC predicts there will be 30 billion connected devices—all transmitting data and com-municating 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 $ow of reliable, real-time data.

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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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

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Internet of Things


Building the data is one step to establishing a cog-nitive 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 an-swer, 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, com-pare images of similar cancers and analyze the ge-nome of a single cancer patient to help design a treat-

ment plan? By the time they !nished, 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 di#erence.

“Businesses will adapt to signi!cantly 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 require-ment for a resilient architecture of the end-to-end cognitive system designed to minimize downtime and ensure no data loss.”

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.”

life-saving insights

THE BENEFITS WILL BE BREATHTAKING. SO SHOULD THE RESILIENCY.


The increased integration of di#erent 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 com-plex solutions, and that makes it harder to maintain resiliency,” he says. “It’s signi!cantly more di"cult to recover an application or business process that cuts across multiple point solutions.”

But what needs to change going forward to make this happen? First of all, resiliency will need to become

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.”

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.

“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


Have you considered the impact of not being able to support cognitive capabilities used in design of business strategy and vision?

How will cognitive computing impact your organization’s structure and its ability to recover during a crisis?

What will you need to do in order to recover cognitive capabilities as they are embedded into business processes?

Have you considered the impact to your systems development life cycle as cognitive applications are developed and their resiliency requirements?

Data is the life-blood of cognitive computing. How will that bear on your data replication and recovery strategies?

Have you considered the requirements for ensuring continuous availability of cognitive platforms in your resiliency program?

Are you thinking about the design requirements for facilities and data centers supporting cognitive computing?

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

Organization

processes

applications

data

technology

facilities

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.

HOW COGNITIVE CAPABILITIES CAN IMPROVE RESILIENCY


According to data gathered by Munich Re, weather- related 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 dynam-ic, real-time knowledge can help companies adapt products and services that anticipate the weather, including disaster recovery and business continu-ity. “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 capabili-ties 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 refer-ence points, more than 40 million smartphones and 50,000 airplane $ights 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 !eld 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 di#erent data sets, using correlation analysis and time-series analysis to predict failures—for instance, by mapping network service orders with past equip-ment 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 di#erently? 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 de!ne 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 !le 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 best-laid resiliency plans can be undone if one small ele-

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.


ment in a process is missing,” explains BJ Klingenberg, distinguished engineer, chief technology o"cer, 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 cogni-tive 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 techni-cal 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 recov-ery and business continuity planning. Speed is of the essence in an emergency. Cognitive analytics can help prioritize the most e#ective 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, noti!ca-tions to backup teams can be generated automatically, based on the response, or lack of response, from key responders.

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.

Managing the Data Explosion


This is the true promise of cognitive computing because it allows for continuous improvement and adaptation, and for capabilities not previously imag-ined. 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 $ow 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 manage-ment approach plus a strong and proactive resiliency pro!le will allow an organization to take more busi-ness risks—all while securing employees’ engagement and taking full advantage of cutting-edge technolo-gies to create a di#erentiated customer experience. A strong resiliency program is, ultimately, a competitive advantage.

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.

Learn more about IBM Resiliency Services at

ibm.com/services/resiliency


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

ACKNOWLEDGMENTS

www.ibm.com/services/resiliency

ABOUT FORBES INSIGHTSForbes Insights is the strategic research and thought leadership practice of Forbes Media, publisher of Forbes magazine and Forbes.com, whose combined media properties reach nearly 75 million business decision makers worldwide on a monthly basis. Taking advantage of a proprietary database of senior-level executives in the Forbes community, Forbes Insights conducts research on a host of topics of interest to C-level executives, senior marketing professionals, small business owners and those who aspire to positions of leadership, as well as providing deep insights into issues and trends surrounding wealth creation and wealth management.

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FORBES INSIGHTS

Bruce RogersChief Insights O!cer

Erika MaguireDirector of Programs

EDITORIAL

Kasia Wandycz Moreno, Director Hugo S. Moreno, DirectorDeborah Orr, Report AuthorDianne Athey, DesignerPeter Goldman, Designer

RESEARCH

Ross Gagnon, DirectorKimberly Kurata, Research Analyst

SALES

North AmericaBrian McLeod, Commercial [email protected] Muszala, ManagerWilliam Thompson, Manager

EMEATibor Fuchsel, Manager

APACSerene Lee, Executive Director

resiliency in the cognitive era

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