Enterprise Personal Analytics: The Next Frontier in Individual Information Systems Research

Organizations have long used analytics to improve performance. Modern enterprise technological landscapes are being impacted by the increasing individuation of information systems (IS). One promising technological advancement in this regard will be the use of personal analytics within an enterprise setting. While traditional organizational intelligence metrics deliver a big picture of structures, processes, and roles, more detailed and personalized analytics enables employees to scrutinize their personal productivity in terms of their desired versus their actual way of working. Personal analytics empowers individuals to analyze and exploit their own data to achieve a range of objectives and benefits across their work (e.g. productivity, quality, performance) and personal lives (e.g. sleep, exercise, health). This topic has only been minimally analyzed in IS research. Furthermore, there have been increased calls by academics to investigate the individuation of IS which has largely gone unnoticed in the IS research discipline. While the mainstream application relatively niche, we believe its impact will fundamentally change enterprises across all sectors. Thus, in the scope of this monograph, we shall focus on this emergent category of analytics which we refer to as “enterprise personal analytics†which encompasses the concept of organizations enabling their employees to use their individual analytics to manage their digital working lives from descriptive, diagnostic, predictive, and prescriptive points of view. Our comprehensive review of the existing empirical research on the use of personal analytics within an organizational setting identified that the only consistency pertaining to the concept was inconsistency. Therefore, this monograph offers the following theoretical and practical contributions: 1. We present an overview of specific analytics trends which have shaped the personal analytics landscape which include: learning analytics, the quantified self, human-centric analytics, gamification, sports analytics, personal cloud, and Neuro IS. 2. We present a framework, derived from a comprehensive review of the personal analytics literature, which consists of various combinations of research stakeholder perspectives and concerns. This framework can be used to guide and coalesce future IS research on enterprise personal analytics. 3. We provide an overview of possible research questions aimed at highlighting how the framework can be used. 4. We propose a visual mapping artefact aimed at assisting companies with their enterprise personal analytics digital transformation journeys.