OPINION: Predictive analytics helps companies master the Big Data challenge

To understand how radically the nature of data is changing, consider a few facts:

• There are 200 million tweets sent each day, or roughly 12 terabytes of data.
• Every second of high-definition video creates 2,000 times as many bytes as a single page of printed text.
• In many countries, there are thousands of surveillance and video cameras in most major cities used for traffic and security monitoring.
• Banks and insurance companies are identifying fraud patterns by combining different data sources in real time to analyze transactions.
• With the intent of driving awareness of consumption and conservation, utilities are switching to electronic meters that transmit readings every 15 seconds, which results in billions of meter readings each year.

All this data presents a massive challenge, but a huge opportunity.

Organizations know they can reap huge benefits from capturing and analyzing as much data as possible. Yet at the same time, most have no idea how to do this effectively or how to efficiently share those insights with the people that are most appropriate to use the information generated.

Those that master all of this new data demonstrate just how powerful data can be. Danish energy company Vestas Wind Systems turned to analytics to crunch massive amounts of data, including weather conditions, moon and tidal phases, and satellite images to pinpoint the best places to install wind turbines and to improve efficiencies and output. Analysis that took weeks is now whittled down to less than an hour.

The challenge facing organizations isn’t simply that the amount of data is exploding. It’s also that the pace of change in business is outstripping their ability to keep up with change. A 2011 IBM survey of CEOs found that 60 per cent agreed that they have more data than they can use effectively. Yet four out of five of the business leaders IBM spoke with say that data is a vital source of competitive advantage.

"The New Intelligent Enterprise", a study conducted by IBM Institute of Business Value and MIT Sloan Management Review found that the number of enterprises using analytics to create a competitive advantage jumped almost 60 per cent in just one year (2010 to 2011). Nearly six out of 10 organizations now differentiate through analytics. The study also found that such companies were more than twice as likely to substantially outperform their industry peers who do not differentiate through analytics.

Turning information into insight means that organizations have to coordinate their business and information strategies. That means applying the right technology, creating tight partnerships between CIOs and the rest of the executive team, investing in skills, and being committed to the kind of cultural change that allows quick decision-making. These are daunting tasks, but some basic approaches can help organizations tackle them:

Spread out the analytics: Today’s society, with its smartphones, iPads, and laptops, is defined by its mobility. Employees, customers and partners are on the move and yet connected like never before. Organizations need to experiment with and develop software and applications that allow employees to analyze any data about their business, including sales, customer and financial information by using dashboards and scorecards. Whether it’s a doctor being able to see patient medical records while they’re out of the office, or bankers or insurers using the data to analyze loan and policy data to create individual products for clients, data has to be made sense of while on the run.

Rethink predictive analytics: The tech industry has talked about the promise of predictive analytics for a long time, but the ability to collect a lot of data more cheaply is creating the era of predictive analytics. The reality is that the sheer amount and complexity of today’s data means that there is no way to manually extract value from it. Advanced techniques are needed to sift through and make sense of data. An explosion of new services that showcase data warehousing and predictive analytics are emerging, ranging from new kinds of mapping tools to IBM’s Watson supercomputer, which interacts with natural-language questions.

Develop Analytical Skills: Analytics used to be the province of math or statistical specialists in an organization. But going forward, every single department of an organization will need the skills necessary to efficiently collect and make sense of these new streams of data. Not simply to process it, but to learn new ways of examining that data, be able to share it more broadly with other employees, and glean new and innovate around unexpected insights. Organizations need to make sure that a broader group of employees learn analytical skills, either through classes with outside programs or internal training. The investment that an organization makes in fundamental skills in this area will pay off quickly.

Consider one last piece of information. The performance gap between leaders and laggards is widening. Organizations that apply advanced analytics successfully have 33 per cent higher revenue growth and 12 times more profit growth than those who don’t. If there were ever a time for being smart about analytics, it’s now.