What’s the Big Deal About Big Data?
Virtually everyone spends time online these days, but few think about the invisible trail of data they are generating with their everyday digital activity. With every phone call, text, Tweet, Facebook post, product view, purchase, “like,” app download, browser search and online bill payment, we leave behind a stream of digital exhaust. The combination of these digital footprints of millions of users is called “Big Data”—a massive amount of information revealing people’s preferences and interests, which companies can use to learn more about current and potential customers.
This information can be used to effectively market products, services and processes that appeal to customers. For example, Amazon tracks what products you buy and then tailors its marketing emails and the content you see on its website to your interests. In their seminal book “The Human Face of Big Data”, authors Rick Smolan and Jennifer Erwitt note that all of humanity until 1993 generated about 5 exabytes of data (five billion gigabytes.) Today we generate that much data every two days, and the pace is accelerating.1
Distilling this enormous amount of information down to usable facts requires specialized expertise and great care. Pearson Partners’ Q1 2013 Spotlight Series Breakfast discussed the burgeoning business of Big Data, and how companies are learning to aggregate, analyze and leverage it to their advantage.
Our esteemed panel members included:
- Stephen Holland, Chief Technology and Digital Officer, 7-Eleven, Inc.
- Kevin Jones, Vice President, Dell Services, Dell, Inc.
- Keith Morrow, Chief Information Officer and Executive Vice President, Shared Services, Epsilon Inc.
- Steve Vandehey, Vice President, Hitachi Consulting
A Big Focus on Big Data in Most Industries
Because Big Data is a disruptive new phenomenon, virtually every industry is exploring how it can be leveraged. Consumer packaged goods manufacturers, retailers and telecommunications companies are leading the Big Data revolution, as they already store and manage a wealth of information about customer transactions and patterns. Many Big Data projects are also kicking off in the health care, government, financial and insurance sectors.
Although Washington is taking interest, regulations to protect privacy have yet to catch up with these new technologies, which can be controversial. There’s a fine line between Big Data and Big Brother. For example, an increasing number of retailers are integrating wireless technologies such as sensors, RFID tags and GPS locators in their stores that allow them to sense every message or ping from visitors’ mobile phones. With this data they can track how long people stay in the store, what interests them, in what parts of the store they spend the most time and what purchases they make even after they leave the store. Although this micro-targeting can ultimately provide a better experience for the consumer, companies are wise to continually update their privacy and security regulations to ensure transparency and allow customers to “opt out” or remain anonymous.
Putting Data to Work
Big Data is about much more than the habits of Internet and mobile phone users. Although social media and digital device users tend to skew younger—and young people tend to be less concerned about privacy—there are many ways to capture data about the habits of customers of all ages, including sensors in cars, toll stations, trains and stores. Through analytics, companies can segregate customer data by age and other demographics, then through micro-targeting of marketing efforts, communicate with different customer segments in different ways to influence their purchasing behavior.
Big Data is not for every company. Before a company invests in a Big Data initiative, it’s wise to first step back and decide what the company wishes to accomplish, and how realistic it is to achieve that goal using Big Data. Some businesses tend to rely more on experience when making decisions. For companies with a culture that embraces data in decision-making, these initiatives can be tied to company goals and objectives and provide a big advantage over competitors.
Big Data projects may require adopting a different enterprise architecture than was needed for legacy data warehousing projects. This can create the need for new and different skills among the current team. Mathematicians and statisticians are in demand because they are capable of thinking differently and finding patterns in enormous amounts of data. In addition, Big Data teams must implement adequate security and controls, create quality algorithms, run experiments to test hypotheses, identify flawed data and know how to whittle down vast amounts of data into valuable data sets. Projects will be most successful when the data is applied to solve a business problem like creating demand for a new product or bridging a competitive gap.
The more data points you have, the more you can learn, so data are rarely deleted. Growing data storage requirements place tremendous pressure on traditional data archiving systems, as well as companies’ IT budgets. IT companies are working to make data storage more efficient and economically viable, making Big Data more accessible to any company interested in influencing customers to buy.
As Smolan and Erwitt summarized, “Big Data carries the potential for unintended consequences. But if we are careful and wise, in the not too distant future this new set of technologies may have an impact on humanity as great as those of language and art.”2
1Eric Schmidt, Executive Chairman, Google, as cited in The Human Face of Big Data, Smolan, Rick, and Erwitt, Jennifer. Against All Odds Productions, 2012. 19-21.