Reporting & anomaly-detection pipeline
An operations team replaced a six-hour weekly reporting grind with an automated narrative report — and started catching problems in a day instead of a fortnight.
Representative engagement — the figures below model a typical project of this kind, not a named-client audited result.
Six hours of copy-paste, and problems found too late
The weekly report was assembled by hand — about six hours of an analyst's time copying numbers from seven systems into a deck.
Because nobody was watching continuously, real problems — a margin dip, a shipping-cost spike — often surfaced a week or two after they started.
A report that writes itself and flags what changed
We built a pipeline that consolidates all seven source systems nightly, computes the KPI set, and generates a written narrative summary of what changed and why.
It flags statistical anomalies against trend and seasonality with a severity score, so the team sees a developing problem within a day — not at month-end.
- Nightly consolidation of 7 source systems
- Automated KPI computation
- A written narrative summary of what changed and why
- Anomaly detection against trend and seasonality, with severity scoring
What changed, by the numbers.
Reporting that is continuous, not weekly
The Monday report now arrives written and ready to read, and the analyst reviews it in minutes instead of building it for an afternoon. More importantly, anomaly detection turned reporting from a weekly rear-view mirror into something close to a live signal — problems get caught while they are still small.