Five data sources, one reporting system
Consolidated WFM, CRM and QA data into an automated reporting layer: ETL pipelines at 200,000+ rows a week feeding 30+ live Looker Studio dashboards.
Reporting latency −50%, admin workload −40%
The knot
The operation ran on five or six systems that didn’t share data: the WFM platform, the CRM, the QA platform and a few others. Every report meant someone exporting from each of them, pasting the exports together and hoping the totals matched last week’s version. Reports arrived late, took hours of admin time, and described a week that was already over.
What I did
- Wrote ETL pipelines in Google Apps Script that pull from every source and land the data in one shared layer. They currently handle 200,000+ rows a week.
- Rebuilt the reporting as 30+ Looker Studio dashboards reading from that layer. CSAT, FCR, AHT, TTFR, SLA, occupancy, adherence and volume are visible in near-real time.
- Added 60+ low-code automations in Apps Script and Slack Workflow Builder for the repetitive work around it.
- More recently, added LLM tooling for reporting narratives and forecast anomaly checks. I review the output before it goes to anyone.
What changed
Reporting latency fell by half and admin workload by 40%. The WFM reporting infrastructure is now used across the company.
What I’d tell someone doing the same
Build the data layer before the dashboards. When two reports read from different exports they will eventually disagree, and the time spent arguing about which one is right costs more than building the layer did.