Big Data: What It Means for Business Strategy

Introduction to the Big Data Revolution

Once, data about consumers was relatively difficult to amass. Now, in the digital age, businesses are confronted with a plethora of sources of consumer data. "Data now stream from daily life: from phones and credit cards and televisions and computers; from the infrastructure of cities; from sensor-equipped buildings, trains, buses, planes, bridges, and factories. The data flow so fast that the total accumulation of the past two years — a zettabyte — dwarfs the prior record of human civilization" (Shaw 2014). The big data revolution has the power to be as transformative as the Internet in the ways that businesses conduct commerce and consumers understand themselves.

"Big data is distinct from the Internet, although the Web makes it much easier to collect and share data. Big data is about more than just communication: the idea is that we can learn from a large body of information things that we could not comprehend when we used only smaller amounts" (Cukier & Schoenberger 2013). This distinction is important: big data is not merely a technological upgrade but a fundamentally new way of generating knowledge about human behavior and commercial patterns.

Datafication and the Limits of Small Data

In the past, small samplings of large populations were used to make sweeping generalizations. However, big data allows for the creation of unexpected connections. "Big data is also characterized by the ability to render into data many aspects of the world that have never been quantified before; call it 'datafication.' For example, location has been datafied, first with the invention of longitude and latitude, and more recently with GPS satellite systems. Words are treated as data when computers mine centuries' worth of books. Even friendships and 'likes' are datafied, via Facebook" (Cukier & Schoenberger 2013). The greater the ease of data analysis, the more likely datafication will penetrate unexpected spheres of daily life.

Big data may be contrasted with traditional consumer databases that rely on sampling. "Modern sampling is based on the idea that, within a certain margin of error, one can infer something about the total population from a small subset, as long as the sample is chosen at random… it falls apart when we want to drill down into subgroups within the sample" — say, gay males under 30 with incomes of more than $30,000 (Cukier & Schoenberger 2013). In such cases, "the random sample is largely useless, since there may be only a couple of people with those characteristics in the sample, too few to make a meaningful assessment of how the entire subpopulation will vote" (Cukier & Schoenberger 2013). However, if the sampling encompasses the entire population of consumers — if it is sufficiently "big" — then the problem disappears (Cukier & Schoenberger 2013).

Big Data as a Business Tool

Big data is thus not just a trend or a catchword, but a new source of information that enables businesses to more accurately segment and target customers. The greater accuracy and complexity of big data also give a competitive advantage to companies with the money and resources to obtain large data sets. Even large customer databases do not allow for the types of correlations that big data provides. "Datafication is a far broader activity: taking all aspects of life and turning them into data. Google's augmented-reality glasses datafy the gaze. Twitter datafies stray thoughts. LinkedIn datafies professional networks" (Cukier & Schoenberger 2013). Unlike asking consumers directly about their buying habits or drawing correlations between purchases and consumer behavior, big data can mine unintentional clues that people reveal about themselves. A small company could once manage with simple customer satisfaction surveys of loyal shoppers — such an approach is now largely a relic of the past.

Big data is also not confined to the business sphere. Some consider it a mindset and a philosophy as much as an analytical technique. "There is a movement of quantification rumbling across fields in academia and science, industry and government and nonprofits… Half the members of the government department are doing some type of data analysis, along with much of the sociology department and a good fraction of economics" (Smith 2014). Big data has thus penetrated a wide variety of domains and will likely continue to reshape how academics and policymakers understand human behavior. The relationship between the marketplace of ideas and the academic world is only likely to grow as higher-level quantitative analysis becomes ubiquitous.

References

Corbin, K. 2014. CIOs must balance cloud security and customer service. CIO Magazine. Available at: http://www.cio.com/article/2379776/government/cios-must-balance-cloud-security-and-customer-service.html [Accessed 2 November 2014].

Cukier, K.N. & Schoenberger, V. 2013. The rise of big data. Foreign Affairs. Available at: http://www.foreignaffairs.com/articles/139104/kenneth-neil-cukier-and-viktor-mayer-schoenberger/the-rise-of-big-data [Accessed 2 November 2014].

Smith, J. 2014. Why big data is a big deal. Harvard Magazine. Available at: http://harvardmagazine.com/2014/03/why-big-data-is-a-big-deal [Accessed 2 November 2014].