Chapter 7 144 7.2.4 RQ2: Intermediate Conclusion & Future Directions In conclusion, this dissertation explored how people analytics can stimulate evidence-based HRM in practice, illustrated by an application to expatriate management. First, Chapters 4 and 5 demonstrated how scientific literature can be leveraged to explore a quantification of HRM impact. Next, Chapter 5 specifically demonstrated how to identify and quantify the impact of general best practices. Finally, Chapter 6 illustrated how people analytics may help to quantify the local impact of HRM practices through the analysis of longitudinal HRIS data in the own, organizational context. This dissertation only touched the surface of the potential applications and implications of people analytics for expatriate management. For instance, the chapters of this dissertation mostly follow the conventional research process associated with basic science (e.g., theory-driven explanatory modelling) rather than following an applied science or design science approach (see Simon, 2001; Van Aken, 2004). I did conduct several predictive and exploratory projects during the past four years, also on the topic of expatriate management (e.g., predicting likelihood of expatriate success; exploratory network analysis on successful international moves). However, we did not turn these projects into scientific papers because of our impression that contemporary management and psychology journals would not be interested in publishing such research. Such impressions result in a self-fullfilling and reinforcing cycle indeed keeping applied and design science projects out of HRM journals. We hope that in the future, scientific culture will change in such a way that scholarly communities become more open to and accepting of these forms of research. A second deduction, in hindsight, is that my dissertation is fixated on the success of international assignments in the eyes of the organization and, in part, the expatriate. Prior to Chapters 4 and 5, it would have been interesting to explore what different stakeholders (e.g., expatriates, families, organizations, supervisors, colleagues, local communities) consider to be expatriate success . Here, interviews regarding success and failure cases – combined with text analysis – could have helped to create a more holistic measure of success. Similarly, Chapter 6 was limited to short-term assignments and their impact on retention. It would have been more interesting to explore other types of assignment (e.g., commuting, long-term) and their effects on alternative outcomes, such as performance, career progression, knowledge-sharing, or (family) well-being. 7.3 People Analytics and the Future of HRM The following section discusses several topics related to the future of people analytics. First, I elaborate on the presence of people analytics in the current scientific literature. Second, I discuss people analytics’ potential to form bridges between and within communities in science and practice. Third, I elaborate on the difficult ethical questions regarding how HRM data can and should be collected and processed. Fourth, I discuss machine learning principles and what they could bring to the HRM domain in general. Fifth and finally, I compare the added value of the current approach to people analytics in light of the (dis)advantages of integration within a centralized business analytics function.