Digital work platforms are often said to view crowdworkers as replaceable cogs in the machine, favouring exit rather than voice as a means of resolving concerns. Based on a qualitative study of six German medium-sized platforms offering a range of standardized and creative tasks, we show that platforms provide voice mechanisms, albeit in varying degrees and levels. We find that all platforms in our sample enabled crowdworkers to communicate task-related issues to ensure crowdworker availability and quality output. Five platforms proactively consulted crowdworkers on task-related issues, and two on platform-wide organisation. Differences in the ways in which voice was implemented were driven by considerations about costs, control and a crowd’s social structure, as well as by platforms’ varying interest in fair work standards. We conclude that the platforms in our sample equip crowdworkers with ‘microphones’ by letting them have a say on workflow improvements in a highly controlled and easily mutable setting, but do not provide ‘megaphones’ for co-determining or even controlling platform decisions. By connecting the literature on employee voice with platform research, our study provides a nuanced picture of how voice is technologically and organisationally enabled and constrained in non-standard, digital work contexts.

We apply an affordance lens on qualitative data from three case organisations using a digital voice channel providing employees with the opportunity to speak up via answering periodic mini‐surveys and making comments in an anonymous mini‐forum. We find that imbrications of material and social agencies (i.e., the voice channel's features and managerial reactions to voice) in the respective organisational contexts culminate in employees perceiving the channel as either affording or constraining voice, leading to perceived voice outcomes that eventually encourage or discourage them to speak up. Whether voice is encouraged or discouraged partly results from the mere interaction between employees and the digital voice channel independent of managerial reactions. Our findings thus challenge the emphasis on managerial behaviour and reactions to voice in explaining voice behaviour and outcomes in extant literature.

HR Analytics (HRA) are said to create value when providing analytical outputs that are relevant to decision-makers' immediate business issues. While extant research on HRA attributes success (or lack thereof) in providing business relevant outputs to the presence or absence of particular skills and resources, we know little about how practitioners actually mobilize these skills and resources in daily practice. Drawing on observational and interview data from a case study of an HRA team, we identify boundary spanning, customizing dashboards, and speaking a language of numbers as three epistemic practices in which team members combine and mobilize a particular set of skills and resources that allows them to accomplish epistemic alignment, i.e. aligning to decision-makers' perception of business reality when creating analytical outputs. Epistemic alignment enables the team members to produce complex analytical outputs while at the same time staying close to the decision-makers' immediate business problems. At the same time, team members are capable of accounting for conditions in the broader organizational context, such as compliance issues, dependencies, political tensions, and a prevailing data-driven decision culture. Our findings contribute to knowledge on how organizations can build effective HRA and how advanced forms of digitalization transform the work of HRM in contemporary organizations.

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