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Operational runbooks as living documents: A longitudinal study of document evolution under assisted post-incident revision

By Rocker D'Antonio, Harry Xie, Xuan Guo
2026
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Operational runbooks increasingly function as living documents within operational workflows: they are maintained by people, used in incident support, and continuously revised as organizational knowledge changes. Yet little is known about how such document collections evolve over time in production settings, or which interpretable signals are useful for monitoring document change. We analyze 17 weeks of version-controlled runbook snapshots produced during post-incident revision with machine-assisted review and human oversight. We quantify document evolution using lightweight linguistic and structural signals grounded in prior work on procedural language, technical communication, and document organization. Correlation analysis shows mixed patterns of association, including both positive and negative relationships, with effect sizes ranging from negligible to moderate and varying across corpora. Temporal summaries further distinguish comparatively stable signals from revision-sensitive ones, supporting monitoring of document maintenance workflows rather than one-shot quality judgments. An illustrative analysis on public GitHub product documentation shows that signal behavior differs across corpora, reinforcing the need for context-aware interpretation. These results identify which metric classes provide stable anchors and which provide edit-sensitive indicators for managing operational documentation as an engineered document resource.
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