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How to make real-world use of big data

Lee Sung-youl
Lee Sung-youl
What is so new about big data, the tech buzzword that is attracting so much attention these days?

After all, plenty of organizations, from global telecommunications companies to stock exchanges, have been handling and sifting though massive amounts of data for years. But in fact, three important trends are converging to usher in a new era of big data, one that will fundamentally transform how businesses operate and how they engage with customers, suppliers, partners and employees.

The first seismic change is in the area of mass digitization. Today, through the use of instrumentation, such as RFID technology, companies and individuals can monitor in real time everything from the status of a bullet train racing across the countryside to hourly energy usage in their homes and even individual appliances.

The second trend is social media. People around the world are communicating and interacting via social networks in ways that were unimaginable only a few years ago.

And the final trend is the advancement that we have seen in the area of technology that enables organizations to store, access and analyze these huge new streams of data.

The convergence of these three trends is enabling organizations to efficiently use massive amounts of new kinds of data to make more informed decisions and deliver tremendous value throughout the enterprise.

Leading organizations who are taking advantage of big data are deriving real results, according to the “Big Data @ Work Study,” conducted by IBM’s Institute of Business Value and the Sad Business School at the University of Oxford. The study findings show that 63 percent of those surveyed report that the use of information and analytics, including big data, is creating a competitive advantage for their organizations, up from 37 percent just two years ago ― a 70 percent increase.

For instance, the New York Stock Exchange uses big-data technology to detect suspicious trading activity, among other analytics tasks. With IBM technology, the NYSE can do in minutes what used to take hours or days. Pharmaceutical multinational company GlaxoSmithKline is using IBM’s machine-based discovery technology to mine millions of published papers, literature, patents and material properties. Then, by incorporating human-aided discovery, advanced analytics, modeling and simulation, it was able to save years of research with more precise, and sometimes unexpected, insight while saving billions of dollars invested per drug and shortening the span of the drug discovery process, which takes an average of 12 to 15 years.

Meanwhile, ING Netherlands is using IBM analytics software (Unica) to improve the customer experience. ING started collecting data on what customers felt at different times of their journey and with different transactions. They also used Web analytics to monitor its online customer application process. ING soon discovered that people were dropping out at the final stage since they were required to print out the form, sign it, and send it to ING. Now if a customer drops out of the application process, a message is sent automatically to the call center. An agent then calls to offer assistance, such as printing out the form and sending it to the client with a free-of-charge return envelope. As a result of this move, ING is moving to a culture where it solves problems from a customer’s perspective.

The survey highlighted a few consistent approaches that successful companies are taking as they progress their big-data initiatives:

― Focus initially on customers: For many organizations, the greatest value associated with big data is in the area of customer analytics. By using big data to truly understand customer preferences and anticipate future behavior, companies can significantly improve customer service and loyalty. In the era of the digitally empowered consumer, this is crucial. Customer information and analytics can help companies connect with customers in new, more effective and relevant ways that enhance and personalize customer interactions and satisfaction.

― Start with existing data: To achieve results, while building momentum for longer-term projects, companies are taking a pragmatic approach by taking advantage of existing information and technology. These organizations are gaining new insights from existing internal data, and then extending into new sources of data over time. In many organizations, the size and scope of this internal data, such as detailed point-of-sale transactions for retailers or call records for a telecom is extremely large and clearly represents big data. By applying advanced analytical models and methods, this data is delivering valuable new insights into customers, suppliers, marketing campaigns, pricing programs and employee leadership potential, among other things.

― Develop analytics skills based on business priorities: As reflected in the study, one of the major inhibitors of big data success is the lack of requisite analytical and technical big data skills. The success of big data projects will hinge on closing this gap. Organizations have to invest in not only the tools, but also the combination of business, technical and analytical skills required to deliver on the promise of big data.

― Craft business cases with clear goals: Another challenge highlighted in the study is the need for organizations to develop a quantifiable business case necessary to advance their big data initiatives. To this end, successful organizations are deriving significant economic benefits in areas such as customer retention, marketing effectiveness, supply chain optimization, real-time pricing, employee productivity, while at the same time reducing the costs associated with maintaining existing information management environments.

Another key lesson learned from leading organizations is that to achieve success with big data, it is imperative that business and IT collaborate and work closely together. Big data means nothing as a technological advancement if it does not help organizations derive true business value by becoming smarter, more efficient, more responsive to customers, suppliers and employees and ultimately more profitable.

By Lee Sung-youl

The writer is managing partner, Global Business Services, IBM Korea. The opinions reflected in the article are his own. ― Ed.
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