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Have You Hired A Star Data Analyst Today? Here's Why You Should

Some 97 percent of companies with revenue of more than $100 million are pursuing expertise in business analytics. But the data analytics field is projected to come up short of professionals by 2018. You do the math.

Have You Hired A Star Data Analyst Today? Here's Why You Should

If you’ve ever wanted to see what the fate of your personal information will look like in five years, then open to the senior class of any 2013 yearbook. There you will see, among the hundreds of portraits of graduating teens, the faces of those who will be managing your data.

From the places where you spend your money to what you buy to how you buy it, the details of your activities will be captured and managed, largely, by the college-bound freshman of today. And there may not be enough of them.

Consider that 97 percent of companies with revenue of more than $100 million are pursuing expertise in business analytics, according to Forrester Research. Yet the data analytics field is projected to come up short of professionals by 2018—almost 200,000 qualified data scientist positions are projected to be vacant by that time.

With more than 2 quintillion bytes of new data every day, who should be surprised? My own quick, informal search recently revealed 1,950 available data analyst and scientist positions.

The loyalty industry is approaching a critical juncture: The need for jobs in data analysis is mounting, so who do we want at the wheel? To fill this mounting demand for what Harvard Business Review called "the sexiest job of the 21st century," dozens of programs have been developed at major universities, including Columbia, Stanford, New York University, Northwestern, Syracuse, University of California at Irvine and Indiana University. My alma mater, Ontario-based Queen's University, recently launched a master’s program in management analytics and easily filled the class in the program’s first year.

But for the industry to thrive its leaders need to have more than a good education, they also need a principled conscience. This may not sound sexy, but consider the power data yields. Mishandled, personal data can affect a person’s credit ratings, personal insurance coverage and job prospects. It can really turn our lives upside down.

So how do our institutions build the models that balance these considerations while sorting out those who want to solely let the data speak for itself? Many offer ethics courses, which I believe should be a requirement in freshman year. No one should have access to data without understanding the rationale for having it, the need to care for it, and the implications of mismanaging it.

But what else? I’d also suggest these points on the responsible use of customer information in the wake of Big Data:

Put yourself in the customers’ shoes: Data analysis may require a curious, scientific mind, but it needs to be viewed from a personal perspective as well. The student (and later, employee) has to put the customer at the center of his or her purpose from the start, and then base every decision on what is meaningful to that consumer, based on what the shared data reveals. Responsible data use is an important part of this task.

Respect the data: Once a person agrees to share his or her personal information, a company, by way of its employees, is responsible for treating that data with respect and care. To me, this means being transparent—explaining your intentions for the data and what’s to be gained by the customer. It also means using the data as promised and retaining it only as long as needed. And always destroy data with care.

Use the data to benefit the customer: Smart companies focus on creating real value for the consumer as well as themselves. For a lot of brands, this task has been oversimplified through the deliverance of incentives such as cash, points or coupons. But such offers are so commonplace to today’s savvy consumer that the significance is diluted. The experiences people value are those that are relevant to personal needs and aspirations. Communications, offers, merchandise and service all should reflect the information revealed in the data.

Learn to share: Once the data analyst or scientist graduates and gets to manage actual data, he or she should share its substance with others within the organization. To do less would be to limit its possibilities. By sharing the insights across the organization, from marketing to merchandising to store planning, the data wizards are empowering the organization to reconfigure every aspect of its operations around its ideal customers. These insights can help decision making on price, promotions, the products stocked and communications. Maximizing insights in this way will help a company stand above its competitors.

There are tremendous opportunities for both companies and customers that arise from sharing information and improving the way we create meaningful interactions. But the industry is simply expanding too fast to cut corners, and our brands, reputations and balance sheets are at risk if we don't ensure balance between what is possible and what is right.

Only then can we make the move from Big Data toward good data.

Bryan Pearson is president and CEO of LoyaltyOne and author of The Loyalty Leap: Turning Customer Information Into Customer Intimacy. Follow Bryan at

[Image: Flickr user Bruce Guenter]