Operations teams were working with stale data — reports were generated overnight and reviewed the following morning, meaning anomalies and issues went undetected for hours. There was no unified view across operational systems.
Operations managers, team leads, and executives who needed live visibility into operational KPIs to make fast, data-driven decisions and detect issues before they escalated.
Built a live operational analytics system that unified multiple data sources into a single real-time dashboard. Teams could monitor KPIs as they changed, set anomaly alerts, and drill into root causes without waiting for scheduled reports.
Product Manager responsible for defining the real-time data architecture requirements, stakeholder alignment across operations and engineering teams, and driving delivery of the MVP and subsequent iterations.
Planned AI layer includes predictive anomaly detection using ML models trained on historical operational patterns, enabling proactive alerting before issues impact customers.