The Following article was the cover story in NACD’s monthly magazine.
Big data involves big numbers and bigger insights, and it’s time for boards to get on board. Despite big data’s proven importance to organizational success, corporate directors aren’t taking advantage of it. Conference Board and Stanford University research shows that only 7 percent of boards incorporate big data into their decision making.
Big data means big profits. The evidence: The Harvard Business Review put together a team comprising people from the Massachusetts Institute of Technology (MIT) Sloan School of Management, McKinsey & Co.’s business technology office, and the University of Pennsylvania’s Wharton School. Their conclusion: Companies that make the most of big data are fully 6 percent more profitable than those that don’t. How can your board embrace big data? Follow these six rules.
Understand Big Data
To put to rest a misconception among businesspeople, big data is not the same as analytics. It is true that both seek to glean intelligence from data and translate the findings into business advantage, but it is the volume, speed, and advanced technology involved that puts big data on a higher plane.
For example, in 2012, about 2.5 exabytes of data were created every day. For perspective, one exabyte is equal to one quintillion bytes. Put another way, the data that now flood the Internet every second is equivalent to the data stored on the entire Internet 20 years ago. And now companies are working with petabytes (i.e., one quadrillion bytes of data in a single data set). Wal-Mart alone collects more than 2.5 petabytes of data every hour from its customer transactions—or about 20 million, four-drawer filing cabinets’ worth of text.
But speed of data creation can trump volume in certain cases, as an MIT group discovered on Black Friday—the kick-off of the holiday shopping season in the United States. Using location data from mobile phones to deduce the number of people in a Macy’s parking lot, researchers estimated the retailer’s sales that day before the retailer itself knew its numbers. Accessing real or nearly real-time information can make it possible for a company to be more agile than its competitors.
It all adds up to an almost unfathomable amount of information. Learning to master and manipulate it is the defining managerial competence of the 21st century.
Incorporate Big Data Everywhere
Technological advances, coupled with changes in consumer behavior, now allow managers, marketers, and leaders to see every online step a customer takes. Add up the data from video recorders, retail checkouts, credit-card transactions, and countless other sources, and businesses everywhere are privy to a heretofore unimaginable trove of information about consumers.
Consider Wal-Mart’s effort to use radio frequency identification (RFID) tags for supply-chain optimization. RFID is another important link in the big-data chain of machine-speed-generated information that can be amassed and analyzed in a more instrumented and interconnected world. RFID technology tracks products at the stock-keeping unit level. It also keeps tabs on livestock, conference attendees, bridge structures, and luggage entrusted to an airline, among thousands of other uses. In a sixyear span, the number of RFID tags in use went from 1.3 billion to 30 billion.
It is difficult to find a product or piece of equipment these days that doesn’t contain coding. Airplanes are equipped with more than a billion lines of code that generate about 10 terabytes of data per engine during every 30 minutes of operation. To put those numbers in perspective, a flight from Heathrow Airport to John F. Kennedy Airport would generate about 650 terabytes of data.
Realize Big Data’s Big Returns
While big data has the potential to radically improve the way organizations function, it also has the potential to overwhelm them. The key is to develop processes that recognize, mine, and exploit the information that is relevant to an organization’s needs. Achieving this requires changes in management, processes, and culture. The choice is stark: master the data or drown in it.
When information was stored in analog form, data collection was expensive and time-consuming. Taking a customer-satisfaction survey, for example, required face-to-face, telephone, or mail contact with interviewees. Today, people can respond with a click of a mouse, and their responses are recorded and filtered instantly.
In 2011, managers at EMI Music spotted something interesting. A new artist was gaining a strong following among young people but had little recognition in other demographic groups. Eventually, company research showed that the artist had gained recognition among casual consumers who listen to and watch mainstream radio and television. At that point, EMI decided to launch a major marketing campaign and was subsequently rewarded with a number-one hit.
EMI typically uses a data-driven process to make decisions about how to market new artists, according to David Boyle, the company’s senior vice president for consumer insight. Such decisions used to be made by managers with deep knowledge of the industry but little information to draw on. Now, those managers can dive into EMI’s sizable database composed of results from more than a million online interviews, bolstered by data that flow in from Spotify, a music-streaming service with a library of 15 million tracks and three million paying users. Spotify supplies EMI with anonymous data on every track a user listens to, providing the kind of fine-grained insight into listening habits that would have been unimaginable before the Internet.
If an artist shows signs of attracting attention among an untapped group of consumers, managers may try to place him or her on radio and television shows popular with the demographic. Or they might develop a full-fledged advertising campaign. “In the last few years, EMI has gone from a business where this kind of approach was slightly feared to one where data are used to help do almost everything we do,” Boyle says.
Focus on the What Over the Why
There is another core difference with the way information was treated in the past. Traditionally, the goal was to work backward from the data to figure out the “why” of what the information showed. If, for example, data revealed that there was more employee absenteeism on Monday than on any other day of the week, the goal would be to find the reasons behind the behavior. With big data, the “what” becomes more important than the “why.” The primary goal is to allow organizations to prepare for events, to minimize any negative impact, or seize any opportunity they may present—in this case, change staffing patterns on Mondays.
The change from why to what has profound implications for all organizations. It creates a practical, proactive, forward-thinking mind-set. Not surprisingly, it is business that is leading the charge. UPS is a case in point. The delivery giant wanted to lower the number of costly breakdowns its trucks suffered. The company knew which parts were most likely to give out, so it has placed heat or vibration sensors on those parts. When the sensors detect a certain measure, the part is replaced before it fails—in the shop, not on the road. The data doesn’t tell UPS why the parts are failing, just that they are. But it does achieve the goal of minimizing delayed deliveries and idled drivers. With the immediate mission accomplished, the company can explore the reasons for the breakdowns.
Let Data Trump Instincts
As the acceptance of the big data’s efficacy spreads, traditional thinking about decision making and the value of experience must be recalibrated. Leaders have to be open to having their instincts overruled by data. This can be difficult for those people prized for their ability to make decisions that ultimately rely on gut instinct. It means letting go of some of their authority because changing an organization’s decision-making culture requires starting at the top.
Venture capital firms have embraced big data. Atlanta-based Kabbage supplies capital to online startups. It asks businesses that come to it for funding to share proprietary real-time data, such as sales, customer feedback, purchase and shipping records, and social media presence. By analyzing companies on the basis of this data it gains relevant information, learns how well organized a company is, and sees its skill at maneuvering online. Kabbage has been named a Red Herring 100 North American winner, which recognizes companies that have developed sustainable innovations and are poised for long-term growth, and as one of the Top 10 Most Innovative Companies in Finance by Fast Company.
Use Big Data for Big Decisions
In the past, the résumé and personal interview were the most important factors in a hiring decision. Big data is changing that. In the words of Dan Shapero, LinkedIn’s vice president of talent solutions and insights, “Recruiting has always been an art, but it’s becoming a science.”
Big data opens up new streams of verifiable information about potential hires that dwarfs those provided by résumés and interviews. But perhaps big data’s greatest human-resources value comes as a predictive tool. By analyzing information on established high performers, it allows organizations to determine which attributes have proven valuable in the workplace. It can then evaluate potential hires for those characteristics.
In the days before big data, recruiting was often contracted out to headhunting firms, which would seek out candidates that weren’t actively looking to change jobs. With big-data tools, many human-resources departments can turn to networking and data-aggregating sites such as LinkedIn in addition to using outside headhunters.
The Cost of Not Knowing
The risks—and missed opportunities—to boards ignoring big data are significant. The question is this: What is the cost of not knowing? Hint: It’s high. Big data is as important as financial and operating information. Jack Welch’s gut instinct may have sufficed in an age when these technologies didn’t exist, but relying on gut instinct doesn’t work anymore. It’s time for boards to join the big data revolution and use big data to make decisions in every aspect of corporate governance.
Barry Libert is the CEO of OpenMatters, an investor in social, mobile, and big-data companies. He is also an advisor to larger organizations, their boards, and leaders seeking to benefit from today’s digital technologies.
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