GitHub engagement dropped 20% in two weeks among security teams. Diagnose the issue

Problem Statement Description

Product context: Microsoft is a productivity, software, AI, gaming, and cloud company; its products include Windows, Microsoft 365, Teams, LinkedIn, Xbox, Azure, Dynamics, and Copilot.

You are the PM responsible for GitHub experiences used by enterprise security teams, such as security alerts, code scanning, secret scanning, Dependabot, audit logs, policy workflows, and security overview dashboards. Over the last two weeks, measured engagement from security-team users has dropped by 20%. This decline appears segment-specific and is large enough to raise concern about user trust, workflow disruption, or measurement integrity.

Your task is to diagnose the issue as a root-cause analysis. Security teams often use GitHub differently from developers: they may review vulnerabilities, triage alerts, enforce policies, monitor repositories, coordinate with engineering teams, and report on compliance. A drop in engagement could reflect a product problem, workflow change, instrumentation issue, customer behavior shift, enterprise configuration change, or external factor.

Assume you do not yet know whether the drop is real user behavior or a data artifact. You should structure how you would investigate the anomaly, identify likely causes, validate or reject hypotheses with evidence, and determine what actions are needed to mitigate impact and prevent recurrence.

The experience should consider:

- How “engagement” is defined for security teams, including numerator, denominator, active user criteria, and relevant security workflows.

- Whether the drop is isolated by enterprise account type, company size, region, platform, repository type, role, plan, or GitHub feature area.

- Instrumentation checks such as event schema changes, logging gaps, identity mapping, bot filtering, permission changes, or dashboard pipeline issues.

- Product and workflow hypotheses, including recent releases, UI changes, alert-volume changes, notification behavior, policy enforcement, or degraded performance.

- External and organizational factors such as customer security cycles, compliance deadlines, holidays, incident response periods, or migration to adjacent tools.

- Evidence needed to prioritize hypotheses, including time-series trends, cohort comparisons, funnel steps, customer feedback, support tickets, and system health metrics.

- Mitigation options if the issue is real, including communication, rollback considerations, customer outreach, or targeted fixes.

- Prevention mechanisms such as better monitoring, segmented alerts, launch guardrails, and post-release validation for enterprise security workflows.

Your goal is to present a clear RCA approach that separates measurement issues from actual user impact, narrows the investigation through meaningful segmentation, identifies the most plausible root cause, and defines how Microsoft/GitHub should respond while protecting enterprise trust and security-team productivity.