All notable changes to this project are documented here.
- Published experimentation_insights_kpi as a public, portfolio-grade system focused on business operations systems.
- Packaged the current implementation, documentation, validation flow, and proof surfaces into a repo that can be reviewed by technical and operating stakeholders.
- Clarified the core problem the project is addressing: signal sprawl, metric ambiguity, and decision work that depends on too many disconnected tools.
- Existing approaches in CRM reporting, BI dashboards, workflow tools, and spreadsheets were useful for parts of the workflow.
- They still left out a decision layer that could turn fragmented state into priorities, evidence, and next-best action.
- This release made the repo read like an operational capability rather than a narrow technical demo.
- Cut the first coherent internal version of experimentation_insights_kpi with stable domain objects, review surfaces, and decision outputs.
- Established the first reviewable version of the architecture described as: TypeScript platform for experiment lift analysis, rollout decisioning, KPI interpretation, and growth-oriented experimentation workflows.
- Focused the repo around actionability instead of passive reporting.
- Built the first runnable prototype for the repo's main workflow and decision model.
- Validated the concept against pressure points such as attribution lag, pricing ambiguity, usage-metering gaps, forecast drift, and disconnected journey signals.
- Used the prototype phase to test whether the project could drive action, not just present information.
- Defined the system around operator-first and decision-legible outputs.
- Chose interfaces and examples that made sense for RevOps, growth, product operations, and executive teams.
- Avoided reducing the project to a generic dashboard, CRUD app, or fashionable wrapper around the stack.
- The original idea surfaced while looking at how teams were handling signal sprawl, metric ambiguity, and decision work that depends on too many disconnected tools.
- The recurring pattern was that teams had data and tools, but still lacked a usable operating layer for the hardest decisions.
- Earlier platform, governance, and operator-tooling work made one pattern hard to ignore: the systems that create the most drag are often the ones with partial controls and weak operational coherence, not the ones with no controls at all.
- That pattern shaped the thinking behind this repo well before the public version existed.