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.

翻译：DevOps自动化能够加速软件交付，然而许多组织仍难以从战略项目管理成果（如减少浪费、提升交付可预测性、加强跨团队协作及面向客户的质量）的角度论证自动化工作的合理性并确定其优先级。本文提出\textit{VSM--GQM--DevOps}——一个统一且可追溯的框架，该框架整合了：（i）价值流映射（VSM），用于可视化端到端交付系统并量化延迟、返工与交接；（ii）目标-问题-指标（GQM）范式，将利益相关者目标转化为精简且与决策相关的度量模型（结合DORA指标与项目及团队成果）；（iii）与成熟度匹配的DevOps自动化，通过小型、可逆的干预措施来改善实证观察到的瓶颈。该框架实现了从观察到的浪费到目标对齐的问题、度量指标及自动化候选方案的追溯性操作，并提供了一种可论证的优先级排序方法，以平衡预期影响、置信度与成本。我们还定义了一项多站点、纵向混合方法的验证方案，该方案结合了基于遥测的准实验分析（中断时间序列分析，并在可行时采用受控推出）与来自访谈及回顾会议的定性三角验证。预期贡献在于提供一条经过验证的实施路径及一套实用工具，使组织能够选择那些可证明同时提升交付绩效与项目管理成果的自动化投资。