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Chapter 1 18 2. How can people analytics make HRM more evidence-based? The first research question is approached from a wide perspective: to what extent have analytical initiatives been used to solve HRM issues and where do opportunities and hindrances for such people analytics lie? Hence, Chapter 2 sought to provide a first impression of the rise of data analytics in HRM and other functional domains, by looking at their respective streams of scientific research. Based on keywords provided by experts, I retrieved the networks of scientific publications that had examined analytics in light of organizational performance. Via network analysis and clustering techniques, I could subsequently estimate the extent to which data analytics has been applied to HR-related topics in order to improve the performance in and of organizations. In Chapter 3, I pose that the pace of technological development may be one of the reasons behind the slow adoption rate of advanced analytics within both the practical and scientific HRM domains. In particular, the traditional HRM research methodology may be less suitable for the analysis of the novel HRM data collected via digital technology. Therefore, Chapter 3 demonstrates how HRM professionals and researchers could apply alternative methods in order to deal with these novel data structures. A more diversified methodological toolbox could help to distill value from the new forms of HRM data, with “new” and “old” approaches acting as complements. The second research question is approached from a more narrow perspective – by focusing on a specific HRM issue. Aligning people analytics initiatives to strategic business issues facilitates the managerial buy-in for and progression of projects as their insights may inform concrete decisions and can thus have business impact. Therefore, Chapters 4 through 6 of this dissertation focus on the HRM topic of expatriate management. Expatriate management is an interesting topic from a people analytics perspective for three main reasons. First, expatriation is strategically important to organizations. Multinational organizations can have thousands of employees on overseas, international assignments at any point in time. On the one hand, these assignments are crucial to their international business operations – for instance, to explore and establish new market opportunities or to manage the business operations abroad or offshore. On the other hand, these assignments are crucial to the establishment and development of a global talent pipeline – for instance, to attract and deploy talented employees on a global scale, or to provide (future) managers with valuable operational, international, cross-cultural, and cross-functional experiences. Second, expatriation is quite costly to organize and manage. International assignment requires planning, preparation, administration, relocation, onboarding, premiums and allowances, and repatriation – often also for trailing family members. Expatriating talent is estimated to be up to four times more costly than hiring employees on local (non-expatriate) terms (McEvoy, 2011), with the total financial expenses of an international assignment ranging between $250k and $1M (Nowak & Linder, 2016). Third, success or impact of expatriation is notoriously hard to quantify. In practice, it is unclear how and when the costly investment in expatriation pays off. Data, metrics, and analytics surrounding expatriation and its objectives are frequently underdeveloped. Similarly, scientific research on expatriation has been plagued by misconceptions and