By Roslyn Tate
Big data has become quite the buzzword recently, but for those yet unaware, let’s start with a definition: Big data refers to large collections of information that can be processed to reveal valuable insights. A common example of big data in action can be found in baseball, where teams have turned away from drafting players based on their popularly-perceived merit to judging them according to ever-growing reams of in-game statistics.
But big data isn’t just valuable for baseball teams; industry can leverage it as well to improve bottom lines. Data Science, a burgeoning new field of academia dedicated to collecting, organizing and analyzing information, has revealed how businesses can reduce costs and increase profits by relying on big data. Greater sustainability too is possible through the right applications of big data.
Greater sustainability through clearer inventory
Big data makes it possible to process large amounts of information on real-time conditions, which can help businesses make better-informed decisions about the production and distribution of goods. Not only does this cut down on costs, it minimizes the amount of materials consumed and waste products produced through manufacturing and shipping.
A real-life example of this is can be seen at Pirelli, the world’s fifth-largest tire manufacturer. Working with SAP, a German software company that offers businesses big-data solutions, Pirelli was able to outfit its inventory operations with sensors that deliver second-by-second data. The result is a clearer picture of where inventory stands and what needs to be produced, thereby helping Pirelli reduce redundant goods and deliveries, keeping tires from reaching landfills and greenhouses gasses from the atmosphere.
Greater sustainability through energy efficiency
Big data not only makes real-time conditions knowable, but it can also help businesses optimize their responses to it. In this way, not only are businesses aware of problems as they arise, they’ve already worked out the best possible solutions. This again increases efficiency while eliminating waste.
Another real-life example: The equipment in IBM’s data centers produces huge amounts of heat and requires cooling to properly function. Whereas IBM would, in the past, cool the entire facility, it has since developed mobile measurement technology that can identify isolated hot spots within the data center and target them with air conditioners or chimneys. Not only does this reduce the data centers’ energy consumption, but it also saves IBM quite a bit on its electricity bills.
Greater sustainability through integrated systems
It’s one thing for big data to allow goods to ‘talk’ to businesses, as in the case of Pirelli’s tires, or a system to talk to itself, as in the case of IBM’s air conditioning, but big data can also allow different systems to talk to one another. Many businesses rely on processes that, while interrelated, are often isolated, operating on their own in ignorance of what’s going on with the very relevant but utterly disconnected process next door. Big data can eliminate this barrier.
Take the case of Microsoft’s headquarters in Redmond, Washington. In an effort to reduce the redundancy of a comfortable workplace being the byproduct of an enormously wasteful competition between a building’s air conditioning and heating systems, the facilities team organized existing sensors into a single energy-efficiency system. Not only did this avoid the $60 million capital investment that the feat would have otherwise required, it discovered a garage exhaust fan that had been running for over a year, costing the company $66,000.
Greater sustainability through smarter predictions
We’ve covered how big data can be responsive, efficient and integrated, but it can also be predictive. It can leverage historical data as a statistical basis for future performance, allowing businesses to “see” what the future holds based on similar situations in the past, as well as model new outcomes, revealing what a course of action will yield according to the interactions of various influences.
This application of big data is perhaps most pronounced in the agricultural industry. Humans can encourage desirable traits in plants by cross-pollinating them, selecting the most promising new hybrids and repeating the process to reinforce those characteristics. This used to be a very time-consuming process as it required scientists to bring a seed to maturation, cross-breed it, bring that seed to maturation, cross-breed it, bring that seed to maturation, cross-breed it, and on and on. Big data is now allowing organizations like the Donald Danforth Plant Science Center to model the evolution of hybrid plants, reducing the development time dramatically. This, clearly, holds great promise for a more sustainable food supply.
While the possibilities of big data ushering in true sustainability are enormous, much of the work remains to be done and many of the rewards are far from being reaped. It’s the work of humans today that will create a more socially responsible, environmentally friendly and economically equitable world tomorrow. Businesses have a role in this by utilizing technology to make the smart decisions now. To that end, big data may be fittest tool available to you.
Image credit: Pixabay
Roslyn Tate is an editor of data science information on the 2U Inc. website. The data science team at 2U strives to provide aspiring analysts and entrepreneurs with the knowledge they need to choose the best degree for their goals.