Big data and analytics: strategic and organizational impacts

Notwithstanding the interest and the hype that surround Big Data as a key trend as well the claimed business potentiality that it may offer the coupling with a new breed of analytics, the phenomenon has been yet not fully investigated from a strategic and organizational perspective. Indeed, at the moment of writing this book, apart from a series of articles that appeared on the Harvard Business review by McAfee and Brynjolfsson (2012) and on MIT Sloan Management Review by Lavalle et al. (2011) and Davenport et al. (2012), most of the published monographic contributions concern technical, computational, and engineering facets of Big Data and analytics, or oriented toward high-level societal as well as general audience business analyses. An early joint academics-practitioners effort to provide a unified and comprehensive perspective has been carried out by the White Paper resulting from joint multidisciplinary contributions of more than 130 participants from 26 countries at the World Summit on Big Data and Organization Design held in Paris at the Université Panthéon-Sorbonne during May 16–17, 2013 (Burton et al. 2014). However, it is worth to be mentioned that since 2013 new editorial initiatives have been launched such as, e.g., the Big Data journal (Dumbill 2013). Thus, following up the insights discussed in (Morabito 2014), the present book aims to fill the gap, providing a strategic and organizational perspective on Big Data and analytics, identifying the challenges, ideas, and trends that may represent “food for thought” to practitioners. Accordingly, each topic considered will be analyzed in its technical and managerial aspects, also through the use of case studies and examples. Thus, while relying on academic production as well, the book aims to describe problems from the viewpoints of managers, adopting a clear and easy-to-understand language, in order to capture the interests of top managers and graduate students. Consequently, this book is unique for its intention to synthesize, compare, and comment on major challenges and approaches to Big Data and analytics, being a simple yet ready to consult toolbox for both managers and scholars. In what follows we provide a brief overview, based on our previous work as well (Morabito 2014), on Big Data drivers and characteristics suitable to introduce their discussion also with regard to analytic