Digital Leadership and Employee Well-being: Reconciling Productivity Analytics with Humanistic Management Values

Abstract

Digital workplaces generate continuous behavioural data — keystrokes, meeting metadata, response latencies, task telemetry — and a growing industry converts this exhaust into productivity analytics for managers. The same period has seen organisations publicly commit to employee well-being as a strategic priority. These two movements are on a collision course: analytics regimes optimised for measurable output can erode autonomy, trust, and psychological safety, the very foundations on which sustainable performance and well-being rest. This paper examines the tension conceptually and asks what digital leadership means when leaders hold unprecedented visibility into employee behaviour. Drawing on job demands–resources theory, self-determination theory, and the emerging literature on algorithmic management, we identify four mechanisms through which productivity analytics can damage well-being — surveillance strain, metric displacement, autonomy erosion, and datafied distrust — and four corresponding reconciliation practices: purpose-bound measurement, transparency and co-governance of metrics, aggregation over individualisation, and leader interpretation duty. We integrate these into a Humanistic Analytics Framework that positions analytics as a resource for collective work redesign rather than an instrument of individual monitoring, and derive implications for leadership development, HR policy, and works-council negotiation. The paper contributes to digital leadership scholarship by specifying the value commitments that distinguish leading with data from managing by surveillance.