Demand-planning analysts were spending 5–6 hours every single day manually pulling, matching, and reconciling data across five sources and three platforms. I built an internal app — in 3 days — that does it for them.
The demand-planning team at Accenture was the last mile between raw data and decisions — but they were spending the bulk of their day not planning, but plumbing. Every morning meant opening five different data sources, manually cross-referencing them across three separate platforms, reconciling mismatches by hand, and then assembling outputs for reports and system uploads.
Five to six hours. Daily. For a task that was entirely deterministic — the same steps, the same logic, the same pain — just with different data each time. There was no single source of truth. No automation. No tooling. Just analysts, spreadsheets, and a growing backlog of ad-hoc requests on top.
Rather than a single script, I built a small suite of connected tools inside one internal app — each owning a step of the workflow, so the analyst drives the whole process from one place instead of stitching steps together manually.
Built end-to-end with Claude Code, which let me move from problem to working tool in days, not sprints, and iterate directly against real analyst feedback.
The clearest signal that it worked wasn't a metric — it was behaviour. The team started using the app without being told to. No rollout deck, no change-management session. They just switched.
A multi-day manual cycle compressed to a few clicks. Fewer hand-off errors, and analysts back on analysis instead of data prep.
The point wasn't the automation. It was giving skilled people their judgment time back.