Innovation by the numbers (Part 2): Implications and opportunities for the emerging role of advanced analytics in the workplace

Abstract

In Vol. 2, No. 4 (2013) of Corporate Real Estate Journal, the author summarised a decade-long research project focused on studying innovation teams across more than 110 projects with Fortune 1,000 companies. A key aspect of the research was the exploration, development and testing of what became known as the ‘innovation-connectivity (I-C) performance path’, a model for exploring the interrelated ways in which 16 elements of people, technology and place (P-T-P) can be employed to enhance team processes and enable innovation. Throughout 2014, the author built on this research by studying the team and individual work processes of advanced analytics and big data teams in 22 large companies in North America. Analytics is a method of gleaning intelligence from data and using it for evidence-based strategy, ongoing operations and real-time decision making that translates into business advantage. In the broadest terms, analytics teams sort through huge amounts of data to uncover ways to drive innovation by doing something new or different. Given their focus, analytics teams proved to be excellent case studies to use to apply the I-C performance path, which in previous research showed that innovation teams rated highly on all 16 elements of P-T-P, demonstrated significantly higher levels of collaboration, better project results and superior overall innovation performance. Analytics teams reinforced the relevance of the 16 P-T-P elements, consistently describing their application in a unique way specific to their daily work processes. Due to space constraints, the material has been divided into two parts, appearing in successive issues of the Corporate Real Estate Journal. Part one, which was featured in the previous issue (Vol. 4, No. 4), provided an overview of the field of analytics and the processes undertaken by the data scientists who perform the work. Part two focuses on a comprehensive discussion of ways in which P-T-P can be used to enable superior performance for analytics teams.