Over the previous generation, successive waves of new information technology – from the introduction of personal computers to the Internet to wireless broadband and diverse mobile devices – have enabled dramatic gains in workplace productivity. Today, in a period of widespread economic uncertainty and diminished expectations of the future, skeptics wonder if the tech-driven productivity gains of recent decades have run their course.
Far from it. The explosive growth of digital data foretells the dawn of a new technological era that will be marked by utilizing both the data we have accumulated and the huge volumes of new data being created from sensors to personalize information experiences. The use of this massive and expanding data set will shift from historical understanding to predictive data analytics that deliver insights in real time to create new value that help shape our forward looking interactions. This idea of using information systems to shape future outcomes is unlocking a fountain of economic opportunity.
According to the latest “census” of the digital universe conducted by the research firm IDC, the amount of new information in the world is doubling every two years, growing at a rate of more than 7.6 billion gigabytes per day.
IDC claims that nearly one-quarter of this data holds potential economic value once it becomes tagged and analyzed. Yet, less than one percent of it is being analyzed today.
Innovative companies and entrepreneurs have already seized this opportunity. Firms that integrate advanced data analytics into their operations are now realizing productivity gains of five to six percent higher than their peers, say Andrew McAfee and Erik Brynjolfsson of the Center for Digital Business at the Massachusetts Institute of Technology.
For example, GE now embeds its jet engines with sensors to communicate terabytes of in-flight telemetry data per day, so mechanics on the ground can predict costly problems and perform less costly preventive maintenance. As CEO Jeff Immelt has said, the smarter use of data to achieve just one percent more of improvement in jet engine fuel efficiency can mean $2 billion in additional profits.
In a similar vein, electric utilities are equipping customers with “smart meters” that transmit nearly 3,000 times more data per month about electricity usage patterns on their grids. The ability of these so-called “smart grids” to identify and predict transmission problems enables utilities to prevent more power outages before they occur.
These early adopters in the innovative use of data are the exception rather than the rule, however. Fewer than 10 percent of the large companies we see actively use real-time, predictive data analytics to build a competitive edge. Over time, gains in productivity will be felt more broadly as these techniques become more widely adopted and routine.
For years, organizations have used data mining to extract business intelligence from their internal databases. The next generation of smarter decision making will incorporate insights drawn from less structured data formats derived from social networking and collaborative applications, and location data generated by sensors inside mobile devices or digital tags attached to cargo goods as they move through supply chains.
By 2020, seven billion people on the planet will be joined on the Internet by an estimated 200 billion “things” (cameras, gauges, sensors, meters, appliances, transaction systems, etc.) generating data through machine-to-machine communication. IDC estimates this machine-generated “Internet of Things” will account for fully 40 percent of information in the digital universe by the end of this decade. Much of this data will be gathered in tracking and reporting models, where it can be analyzed and transmitted to self-learning applications and then fed back to decision-makers – all in real time.
Innovators in healthcare are already analyzing these external, informal data streams to identify and track epidemics of infectious diseases in real time, faster than traditional reporting methods followed by public health bureaucracies at the United Nations or global non-governmental organizations.
The web site healthmap.org, developed by scientists affiliated with Boston Children’s Hospital, monitors emerging public health threats around the world using crowd sourcing and analysis of informal online data sources. Co-founder John Brownstein says Healthmap’s smart-phone app, “Outbreaks Near Me” took $10,000 to build and was two weeks ahead of the U.S. Centers for Disease Control in tracking and reporting the spread of the virus H1N1.
A new book, The Human Face of Big Data, by photojournalist Rick Smolan, documents the many ways people are recording and analyzing their biometric data, their eating patterns, sleeping patterns and exercise habits, to generate new information that can help them predict how their bodies are aging, so they can improve their health before medical emergencies occur.
The promise of tomorrow’s better living standards turns on predictive analytics that informs and even anticipates our needs. This new data paradigm will change almost every form of human endeavor, helping us to make healthcare and transportation more efficient, enabling citizens and law enforcement to work together to reduce crime, even allowing people to choose their mates with better hopes of finding the right match.
As Smolan notes, “the real-time data streaming in from satellites, and from billions of sensors, RFID tags, and GPS-enabled cameras and smart phones, is enabling humanity to sense, measure, understand and affect aspects of our existence in ways” that would have amazed our grandparents.
In this new era, information technology will leap beyond the acquisition and sharing of data on past activities and embark on a revolutionary course defined by real-time insights, smarter decision-making and predictive analytics that foretell a new generation of technology-driven economic gains.
The technology to drive such gains exists. What’s needed most are people who know how to ask the right questions and know where to look for answers, who can recognize patterns that others do not see, and who can collaborate smoothly with colleagues in an organization to turn insights into smarter decisions—and tomorrow’s economic growth.
