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Chapter 7 138 This dissertation explored people analytics and its application to expatriate management through its seven Chapters. Chapter 1 introduced the concept of people analytics, elaborating on the contemporary rise in workforce data and analytical capabilities and their potential for evidence-based HRM. Chapter 2 explored the state of analytics usage in functional management disciplines, thus comparing people analytics to other applications of analytics. Chapter 3 discussed and illustrated how unconventional analysis can help to distill value from novel HRM data formats produced by digital technology. Chapters 4 explored the indicators of successful expatriation and how these are affected by organizational agents. Chapter 5 continued this line of research, quantifying the basis of evidence for various types of global mobility support during the expatriation process. Finally, Chapter 6 provided an applied example of people analytics to, among others, the topic of expatriate management. This study sought to quantify the impact of short-term expatriation and other HRM practices on employee retention, approaching HRIS data with scientific rigor. In this seventh Chapter, I first summarize the main findings regarding this dissertation’s two research questions: “What is the current state of people analytics?” and “How can people analytics make HRM more evidence-based?” Subsequently, I provide a general discussion on the future of people analytics where I elaborate on the current research streams, the bridges people analytics may form, the ethical and privacy concerns related to people analytics, the machine learning principles from which the HRM domain may benefit, and the viability of an HR-specific analytics function. This dissertation concludes with a discussion of its implications for science and practice and several specific avenues for future research on people analytics.