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Although self-management is not a new phenomenon, there is a lack of understanding about how to transform organizations towards self-managing teams (SMTs). The purpose of this paper is to propose a guiding framework for how the empowerment process can be managed.

The paper sets out 12 guidelines on how to address the transition towards SMTs based on a case study at a large Dutch healthcare organization. The lessons are drawn from observations, documents and more than 55 interviews with key informants.

This paper provides a holistic overview of lessons learned from the transformation process towards SMTs. The 12 recommendations are targeted at four stakeholder groups, namely, the management/board, HRM department, coach-managers and members of the SMTs.

The originality lies in the systematic approach including lessons learned for all levels of the organization.

Driven by the rapidly accelerating pace of technology-enabled developments within human resource management (HRM), human resource (HR) analytics is infiltrating the research and business agenda. As one of the first in its field, the purpose of this paper is to explore what the future of HR analytics might look like.

Using a sample of 20 practitioners of HR analytics, based in 11 large Dutch organizations, the authors investigated what the application, value, structure, and system support of HR analytics might look like in 2025.

The findings suggest that, by 2025, HR analytics will have become an established discipline, will have a proven impact on business outcomes, and will have a strong influence in operational and strategic decision making. Furthermore, the development of HR analytics will be characterized by integration, with data and IT infrastructure integrated across disciplines and even across organizational boundaries. Moreover, the HR analytics function may very well be subsumed in a central analytics function – transcending individual disciplines such as marketing, finance, and HRM.

The results of the research imply that HR analytics, as a separate function, department, or team, may very well cease to exist, even before it reaches maturity.

Empirical research on HR analytics is scarce, and studies on scenarios, values, and structures of expected developments in HR analytics are non-existent. This research intends to contribute to a better understanding of the development of HR analytics, to facilitate business and HR leaders in taking informed decisions on investing in the further development of the HR analytics discipline. Such investments may lead to an enhanced HR analytics capability within organizations, and cultivate the fact-based and data-driven culture that many organizations and leaders try to pursue.

The field of e-HRM and human resource information systems (HRISs) has developed very rapidly in recent years. More than two decades have passed since the publication of DeSanctis's (1986) seminal work on HRISs, and the topic continues to command the attention of scholars and practitioners around the world. If anything, interest in this topic has been increasing, as evidenced by citation counts, international academic workshops dedicated to this topic, and a number of special issues of international journals. In line with this trend, and responding to a perceived need to advance our understanding and theoretical grounds in this field, this volume forms a timely contribution.

While there is a growing body of research demonstrating that HR Shared Services can offer a value-creating structure for HRM within organizations, there remains considerable room for improving our understanding of it. The premise of this chapter is that the mixture of HR Shared Services outcomes leans on the diversity of the governance structures, which rest in turn on several contingency factors. This means that every HRM Shared Services Model (SSM) is unique in its structure, and thus the value proposition of every HRM SSM is unique. Therefore, instead of promoting a standard package of values expected from HR shared services, organizations should develop unique value propositions that are contingent on their unique governance structures.

Absorptive capacity (for e-HR adoption): The potential of the HR function to seek out and assimilate knowledge about e-HR technologies and incorporate this into their vision of a changed HR function (Reddington, Martin, and Bondarouk).