Cognitive Computing

How Cognitive Computing Can Get Businesses Up & Running After Disasters

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Devastation caused by natural disasters is both personal and economic.

Anyone who lives in the Northeastern United States won’t easily forget the destruction caused by back-to-back hurricanes five years ago.

Hurricane Sandy in 2012 caused more than $67 billion in damage, according to the federal National Oceanic and Atmospheric Administration, while the year-earlier Hurricane Irene caused more than $14 billion in damage. Homeowners and businesses lost power. Business operations were interrupted.

And for those in South India late last year, the intense flooding caused by a devastating mix of its annual northeast monsoons and the effects of El Nino killed more than 500. The flooding also displaced more than 1.8 million people across the Coromandel Coast region, which includes Tamil Nadu and the city of Chennai. Damages of these floods ranged from $7 billion to $15 billion.

For those of us in the services industry whose mission is to keep organizations’ information technology operations up and running, or rapidly recover when a disaster strikes, we have a new way of computing that did not exist five years ago. IBM Watson had won Jeopardy! early in 2011, but it’s full potential as a cognitive system has evolved since then.

According to a new study by IBM and Forbes Insights, cognitive computing is enabling a new class of products and services that sense, reason and learn about their users and the world around them. In other words, “think.”

Cognitive systems have the potential to radically redefine everyday life, changing how companies deliver products and services, engage and interact with customers, learn and make decisions. They are being used by governments and many industries, including automotive, medical, hospitality, government, media, manufacturing, travel, engineering, law and pharmaceutical organizations.

In the cognitive era, the continuous availability of data, systems, applications and business processes is essential. Organizations will take for granted that these services are “always on.” By applying advanced analytics and automation to predict potential issues, companies can correct systems in advance.

At IBM, we are investing in new capabilities to help clients move from reactive business continuity and disaster recovery planning to a cognitive and predictive resiliency program. The goal is to avoid the impact of a disaster before it occurs.

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 an application powered by Watson for real-time weather insights to alert clients of hazardous conditions, such as a hailstorm, and suggest alternate routes or shelter locations.

At the same time, 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.

Here are three ways that cognitive computing can help keep companies up and running:

1) Predict failure and avoid it.
Predicting weather events with more accurate probability is only one of many tools in the field of predictive failures. Cognitive systems can run analysis on different data sets, using correlation analysis and time-series analysis to predict failures. By mapping network service orders with past equipment failures, for example, organizations can see which scenarios would most likely result in a failure and avoid a full-blown breakdown.

2) Analyze best practices.
Consider two companies 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 the latest 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 practices.

3) Integrate the cognitive agent into technical support.
Every moment that equipment is down can mean lost revenue, decreased productivity and frustrated users. A cognitive agent can answer questions with precision to get systems back online faster when there is a technical issue. IBM Watson, for example, responds with an answer in less than a second, reducing the time it takes to determine the problem by up to 37 percent.

In an emergency, speed is essential. Including cognitive analytics in disaster recovery and business continuity plans helps to prioritize the best way to effectively allocate assets to notify customers, restore systems and services and assist employees. By planning in advance, for example, backup teams would be notified automatically to help out if a state of emergency was declared in one area in order to get organizations recover quickly and efficiently.


For more on this subject go to IBM Resiliency Services, and to learn more about the new era of business, visit

In addition, IBM will participate in Disaster Recovery Journal’s DRJ Spring World conference today and tomorrow in Orlando, Fla., where business continuity experts from around the world will gather to discuss best practices.

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