Big Data Lessons from the NSA

2013-06-bigdataOne of the biggest news stories lately has been the revelation that the National Security Agency (NSA) has been using big data from telecommunications companies to spy on people. The reaction to this story has been divided. While a portion of the American public has responded with shock, anger and fear, accusing the federal government of becoming Big Brother and ignoring citizens’ right to privacy, others have defended the surveillance as necessary to our homeland security and, ultimately, not a big deal.

The merits of whether the government should mine telecommunications data will likely be debated for many years to come, and it is probably best to have that debate in the press and at dinner tables across the nation. However, for market researchers who specialize in data sciences and big data methodology, there are important lessons to learn (or perhaps to be reminded of) from the NSA debacle.

There is Huge Value Locked Away in Your Company’s Big Data

The government is interested in understanding behavior patterns that look suspicious. They want to know who is communicating with whom, where these communications take place and how frequently they are occurring. From this, they can paint a picture of who might be a “bad guy” at risk of doing harm to the US.

Similarly, data generated from your customers’ transactions reveal a treasure trove of information. While your company might not be interested in identifying bad guys, it is likely interested in identifying brand advocates and detractors.

Utilizing big data analytics, we can learn much about how your customers use your products and services—information that could never be learned through a survey. Big data analytics also help discern behavior patterns that lead your customers to having a poor experience. Likewise, they can identify fraud, minimize waste and isolate endless opportunities for improving operational efficiency. Seemingly innocuous data that, when taken alone, would appear to be meaningless, becomes valuable and actionable when combined with other data—and data is right in front of you waiting to be harnessed.

Big Data Doesn’t Tell the Why Behind the What

If you listen carefully to how politicians and bureaucrats describe big data surveillance programs, it is clear that mining telecommunications data is just a starting point. While this data does a remarkably good job of telling the government what people are doing, it doesn’t adequately explain why people are doing it. For this, the NSA needs to go back to the Foreign Intelligence Surveillance Court to request a new court order to expand the surveillance to allow for eavesdropping, stakeouts and other “traditional” methods of police work.

The same is true with most corporate big data analysis. Big data reveals what happened but “traditional” qualitative and quantitative research reveals why it happened. The real magic happens by combining traditional and big data research in a framework that looks at the way customers interact with your company holistically. At Market Strategies, we have created such a framework. It is called the Continuous Improvement Cycle, and it systematically integrates qualitative, quantitative and big data analytics to paint a complete picture of your customers, what they are doing, and, most importantly, why they are doing it. Once you fully understand the what and the why, you will have the power to make changes that improve both your customers’ experience as well as your bottom line.

Never Forget “The Wall Street Journal Test”

The NSA and other government officials seemed surprised by the public’s outrage. Collectively, they said the program has been in place for seven years, and it is simply business as usual. The public is not convinced and, as a result, the NSA is on the defensive.

In business, as in politics, every action brings with it a certain amount of risk. In creating a surveillance program, the NSA failed to consider The Wall Street Journal test. Simply put, this means an organization should ask itself what would happen if the details of the proposed action were to become a page one headline in The Wall Street Journal. Would the fallout outweigh the benefit?

All companies should consider this test before undertaking any big data analytics project. Big data can be scary and intimidating to the public, and it is critical to consider the impact to your customers, investors, regulators and competitors. By taking The Wall Street Journal test in advance, companies can tweak their big data projects to minimize risks. Companies need an experienced partner who appreciates the inherent risks associated with big data analytics and is able to keep them safe while gaining the most value from the data. Sometimes less data is beneficial in the interest of minimizing corporate risk. For instance, a company might choose to change privacy policies, give customers the ability to opt-out or even decide to limit which data will be included in the analysis. The point is proactive measures can help avert a crisis or provide a defensible position in times of crisis.

Big Data is Here to Stay

There is no denying that big data analytics is here to stay. Data sciences allows you to learn things about your customers that were previously impossible to discern. Big data, however, does not exist in a bubble, and it does not answer all things. To succeed, you need to integrate big data analytics with the traditional methods that have served you well in the past. In combination with traditional research methods, big data analytics allows organizations to get past a sea of chaotic data to proactively isolate the few individuals that really require attention. This is just as true for the NSA trying to identify a would-be terrorist as it is for a major telecom provider trying to identify which customer is likely to churn or to spread negative word-of-mouth via social networking. The benefits to operational efficiency and the bottom line are enormous and if your organization is not harnessing this power, you can be sure your competition is.

Market Strategies is on the leading edge of market research’s big data revolution. We have created proprietary frameworks that integrate traditional research and big data analytics, and we know how to extract value from all of your data assets while proactively managing risk. Let us help you understand what is happening and why—then, and only then, can you unleash the power of your company’s big data.

Greg Mishkin is a big data market researcher who is frequently invited to share his thoughts at industry conferences. Contact him at 404.601.9561, or follow him on Twitter @GregMishkin. He will be presenting at TMRE in Nashville October 21-23.

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Greg Mishkin

About Greg Mishkin

Greg is a vice president in the Telecommunications Division but works across all divisions and is in high demand as a speaker and author in the market research and telecom fields. Greg's responsibilities include managing and growing key client relationships while maintaining a special focus on the integration of large-scale behavioral data with Market Strategies’ traditional market research solutions. He is known for turning extremely complex data into actionable insights and turning data into competitive advantages for his clients. Currently, he has four patents related to data-focused market research methodologies. Greg earned a master’s degree in business administration from Kennesaw State University in Kennesaw, GA; a master’s degree in clinical psychology from University of Hartford in Hartford, CT and a bachelor’s degree in psychology from Union College in Schenectady, NY. When not on the road for work, Greg can usually be found chasing after his 17-year-old twins to their respective musical theatre performances, symphony rehearsals, piano competitions or various other performing arts activities that are invariably too far from home.

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