When big data meets dataveillance: the hidden side of analytics

Abstract

Among the numerous implications of digitalization, the debate about 'big data' has gained momentum. The central idea capturing attention is that digital data represents the newest key asset organizations should use to gain a competitive edge. Data can be sold, matched with other data, mined, and used to make inferences about anything, from people's behavior to weather conditions. Particularly, what is known as 'big data analytics'-i.e. the modeling and analysis of big data-has become the capability which differentiates, from the rest of the market, the most successful companies. An entire business ecosystem has emerged around the digital data asset, and new types of companies, such as analytical competitors and analytical deputies, are proliferating as a result of the analysis of digital data. However, virtually absent from the big data debate is any mention of one of its constitutive mechanisms-that is, dataveillance. Dataveillance-which refers to the systematic monitoring of people or groups, by means of personal data systems in order to regulate or govern their behavior-sets the stage and reinforces the development of the data economy celebrated in the big data debate. This article aims to make visible the interdependence between dataveillance, big data and analytics by providing real examples of how companies collect, process, analyze and use data to achieve their business objectives.

Big Data Surveillance and the Body-subject

“…A key component of any big data strategy is to generate what is termed 'actionable insight' for firms using it (Degli Esposti, 2014). Particularly in marketing settings, the object is to leverage insight about consumers gleaned from data in order to 'persuade' (or manipulate) them into buying a product or using a service and to target marketing efforts more effectively.…”

“…The concept emerged as a label to describe a number of factors around the changing landscape of commercial and government data collection, use and application. Following the expansion of eCommerce in the early 2000s, businesses realized they had huge information resources about their operations that could reveal new insights about how best to compete (Degli Esposti, 2014). Information about customer purchase patterns, sales, their business and supply chain partners, and sentiment analyses from social media data became cheaper to store and exploit using new analytical techniques (Jacobs, 2009).…”

Beyond the security paradox: Ten criteria for a socially informed security policy

“…Finally, more recent studies of privacy concerns demonstrate that most people feel resigned and powerless when confronted with the current reality of mass dataveillance (Degli Esposti, 2014, Turow et al, 2015.…”

Big Data in Organizations and the Role of Human Resource Management

“…Sorgdrager 2004), whether these results are appropriate for categorizing potential employees. Social media profiling (Esposti 2014) is part of employment screening, and "there truly has been an explosion in how technology has changed and continues to change selection practice" (Ryan & Ployhart 2013: 20.11). Not only do organizations use social media, but they do extensive background checks.…”