Auditable DevOps Automation via VSM and GQM
Mamdouh Alenezi
TL;DR
The paper tackles the misalignment between DevOps automation and strategic project-management outcomes by proposing an integrated VSM-GQM-DevOps framework that creates auditable traceability from observed waste to goals and automation. It combines Value Stream Mapping to diagnose end-to-end waste with the Goal–Question–Metric method to formalize measurement around stakeholder objectives, and pairs this with maturity-aligned automation prioritized by a defensible scoring approach. A mixed-method, multi-site validation protocol—employing interrupted time series analysis, quasi-experimental rollouts, and qualitative triangulation—demonstrates empirically how auditable automation can reduce waste and improve delivery performance and project-management outcomes. The framework yields practical artifacts (VSM workshops, GQM templates, a waste-to-automation catalog, and prioritization heuristics) that support governance and ROI, with maturity-aware guidance for incremental adoption and replication across diverse organizational contexts.
Abstract
DevOps automation can accelerate software delivery, yet many organizations still struggle to justify and prioritize automation work in terms of strategic project-management outcomes such as waste reduction, delivery predictability, cross-team coordination, and customer-facing quality. This paper presents \textit{VSM--GQM--DevOps}, a unified, traceable framework that integrates (i) Value Stream Mapping (VSM) to visualize the end-to-end delivery system and quantify delays, rework, and handoffs, (ii) the Goal--Question--Metric (GQM) paradigm to translate stakeholder objectives into a minimal, decision-relevant measurement model (combining DORA with project and team outcomes), and (iii) maturity-aligned DevOps automation to remediate empirically observed bottlenecks through small, reversible interventions. The framework operationalizes traceability from observed waste to goal-aligned questions, metrics, and automation candidates, and provides a defensible prioritization approach that balances expected impact, confidence, and cost. We also define a multi-site, longitudinal mixed-method validation protocol that combines telemetry-based quasi-experimental analysis (interrupted time series and, where feasible, controlled rollouts) with qualitative triangulation from interviews and retrospectives. The expected contribution is a validated pathway and a set of practical instruments that enables organizations to select automation investments that demonstrably improve both delivery performance and project-management outcomes.