Big Data – A new wave of innovation, competition and productivity
Every day we create 2.5 quintillion bytes of data – so much, that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: from sensors used to gather climate information, posts to social media sites, digital pictures and videos posted online, transaction records of online purchases, and from cell phone GPS signals, to name a few. This data is Big Data.
Like many new information technologies, Big Data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings. Like traditional analytics, it can also support internal business decisions. For instance, McKinsey & Company estimate that if US health care could use Big Data creatively and effectively to drive efficiency and quality, the potential value from data in the sector could be more than $300 billion in value every year. They also for example estimate that a retailer embracing Big Data has the potential to increase its operating margin by more than 60 percent.
Firms like Google, eBay, LinkedIn, and Facebook were built around Big Data from the beginning. However, one of the most dramatic conversions to data and analytics offerings is found at General Electric, a company that is more than 120 years old. GE’s manufacturing businesses are increasingly becoming providers of asset and operations optimisation services. With sensors streaming data from turbines, locomotives, jet engines and medical imaging devices, GE can determine the most efficient and effective service intervals for those machines using data and analytics. To assemble and develop the skills to do this sort of work, GE invested more than $2 billion in a new software and analytics centre in the San Francisco Bay Area. GE is even selling technologies to other industrial companies to use in managing Big Data and analytics, and has marketing campaigns involving such Big Data concepts as “Datalandia” and “Predictivity.”
United Parcel Service of America Inc. is a mere 107 years old, but it is one of the best examples of pushing analytics out to front-line processes—delivery routing in particular. The company is no stranger to Big Data, having begun to capture and track a variety of package movements and transactions as early as the 1980s. The most recent source of Big Data at UPS, however, comes from telematics sensors in over 46,000 vehicles. The data from UPS package trucks, for example, includes their speed, direction, braking and drive train performance. The data is not only used to monitor daily performance, but to drive a major redesign of UPS drivers’ route structures. This initiative, called ORION (On-Road Integrated Optimization and Navigation), is arguably the world’s largest operations research project. It also relies heavily on online map data and optimisation algorithms, and will eventually reconfigure a driver’s pickups and drop-offs in real time. The project has already led to savings in 2011 of more than 8.4 million gallons of fuel by cutting 85 million miles off of daily routes. UPS estimates that saving only one daily mile driver per driver saves the company $30 million per annum, so the overall dollar savings are substantial. The company is also attempting to use data and analytics to optimise the efficiency of its 2,000 aircraft flights per day.
In Australia, the use of Big Data is shaping as the new front in the battle for market share between the major retailers after Woolworths paid about $20 million in May for a 50 per cent stake in data analytics company, Quantium. Wesfarmers is ramping up its use of data analytics across its retail and industrial supply chains. In June, Coles launched a fee-free credit card that works in conjunction with the retailer’s Flybuys customer loyalty program to help Coles gain more insight into customer spending.
By 2020, McKinsey says the U.S. is expected to have a shortage of 190,000 data scientists — the computer engineers who mine Big Data to predict things like which Netflix movies customers want to watch next and what social media connections say about a bank customer’s ability to pay back a loan. It is therefore no surprise Big Data is going to college with university programs specialising in data mining starting up in the United States. The University of Rochester will spend $50 million to establish itself as a leader in the evolving field of Big Data research by constructing a 50,000-square-foot home for a new Institute for Data Science and hiring at least 20 new faculty members. The University of Virginia launched a new research centre called the Big Data Institute. Columbia University will also begin offering a new master’s degree in Big Data, in a program technically called “Quantitative Studies.” There are more: The University of San Francisco has its own master’s degree program underway. IBM is opening up a big data centre at Ohio State University. Other schools that offer programs are Stanford, which awards a graduate certificate in data mining, North Carolina State, Northwestern, and New York University, among others.
The effective use of Big Data has the potential to transform economies, delivering a new wave of innovation and productivity growth. Using Big Data will become a key basis of competition for existing companies, and will create new competitors who are able to attract employees that have the critical skills for a Big Data world. Organisations need to recognise the potential opportunity as well as the strategic threats that Big Data represent and should assess and then close any gap between their current IT capabilities and what is necessary to capture Big Data opportunities relevant to their business.
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