Real-Time KPI Tracking Systems: A Review of Automated Performance Monitoring and Data-Driven Decision Making

Abstract

Abstract

Organizations now generate operational and financial signals at a velocity that the quarterly reporting cadence of the twentieth century cannot absorb, yet a large share of monitoring infrastructure still surfaces lagging indicators days or weeks after the events they describe. This paper systematically reviews the literature on real-time key performance indicator tracking systems, examining how automated performance monitoring reshapes the production, interpretation, and consumption of management information and how those changes translate, or fail to translate, into superior decision making. Following PRISMA 2020 reporting guidelines, a structured search across multiple databases identified an initial corpus that was screened against explicit inclusion and exclusion criteria, yielding a final synthesis set spanning finance, accounting, auditing, business intelligence, and management control research published between 1991 and 2024. The evidence is organized around three themes: the architecture and data infrastructure that make continuous indicator tracking technically feasible; the behavioral and decision pathway through which dashboards, alerts, and analytics influence managerial judgment; and the governance, assurance, and continuous control implications of monitoring systems that operate without scheduled human intervention. Three findings recur across the corpus. First, the value of real-time tracking is conditional rather than automatic, mediated by organizational absorptive capacity, control philosophy, and indicator design quality. Second, faster information frequently amplifies measurement weaknesses, producing alert fatigue, shorttermism, and gaming when indicator selection is poor. Third, continuous monitoring blurs the boundary between performance measurement and assurance, raising unresolved questions about auditability and accountability. The paper argues that real-time tracking delivers competitive advantage only when technical immediacy is matched by deliberate measurement governance, and it specifies a research agenda for testing this contingency empirically.