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Discussion 147 scholars seem to regard the novel statistical modelling procedures as a natural evolution of their fields and do not refer to people analytics, even though their studies fit the definition closely. 7.3.1.4 Ambiguity Overall, there are divergent streams of research related to people analytics. This may be the reason behind some of the ambiguity surrounding the topic. For instance, the traditional strategic HRM scholar imagines large quantitative survey studies linking HRM interventions and behavioral data to performance outcomes when thinking of people analytics. In contrast, micro-level HRM researchers may not be familiar with the term people analytics even though they work on novel, complex data analytics projects on a regular basis. At the same time, scholars outside of the social sciences are predicting employee behaviors with highly complex, unstructured data using black-box algorithms in machine learning pipelines, but not labelling it people analytics. Finally, the average HRM professional in practice will think of HR controlling, reporting, and dashboards when hearing the words people analytics, but is unaware of the potential value and pitfalls of more advanced data uses. An improved understanding of what people analytics and related concepts precisely entail, what they require of the data (e.g., volume, quality, causality), and what they can, and cannot do, seem prerequisites for people analytics to really take off in the future. 7.3.2 Bridges through People Analytics Despite the ambiguity and slow development, the stream of people analytics brings new perspectives to science and practice. With its different purpose, people analytics has the potential to bridge the worlds of science and practice. Moreover, the complexity of the HRM issues people analytics seeks to solve could bridge different disciplines within these worlds. 7.3.2.1 Bridges between Science and Practice Many authors in the field of people analytics have suggested that a large, problematic gap exists between research and practice (Minbaeva, 2017a, 2017b; Rasmussen & Ulrich, 2015; Simón & Ferreiro, 2017; Van den Heuvel & Bondarouk, 2017). Paradoxically, the worlds of HRM science and practice are increasingly collaborating under the banner of people analytics. For instance, practitioners and scholars have teamed up to disseminate information and knowledge across the science-practice border (e.g., Rasmussen & Ulrich, 2015; Chapter 3), to conduct applied empirical research with scientific value (e.g., Chapter 6; Kryscynski et al., 2017; Simón & Ferreiro, 2017; Van de Voorde, Paauwe, & Van Veldhoven, 2010), and to host PhD projects, academic conferences, and educational programs. As an applied or design science , taking the middle ground between descriptive theory and actual application (Van Aken, 2004, p. 225), the beauty is that people analytics research often comes with direct tangible benefits for both worlds. On the one hand, people analytics may provide strategic information for the organizations under study whereas, on the other hand, people analytics is a means to explore new HRM theories or to confirm their practical value. The organizations often