Catalog every spreadsheet, purpose, owner, and downstream consumer. Eliminate dead sheets, consolidate duplicates, and fix missing fields. Decide which history to migrate and what stays archived. Post one cleansing challenge and we will suggest pragmatic heuristics, including sampling, profiling, and lightweight enrichment to raise quality without delaying your first release.
Select a scope where success is visible and dependencies are manageable. Instrument everything, gather feedback daily, and adjust workflows, fields, and labels quickly. Celebrate wins publicly to build momentum. Tell us your pilot criteria, and we will share patterns for picking a slice that proves value while avoiding hard-to-change architectural decisions.
Define a precise switchover plan: freeze spreadsheets, export, validate, import, verify, and open access. Prepare a rollback checklist and a support room staffed by experts during peak hours. Communicate expectations clearly. Share your cutover runbook draft, and the community can pressure-test timing, ownership, and escalation paths before the big day.
Interview doers to capture what truly happens, not the tidy process diagram. Represent states, transitions, and responsibilities explicitly. Add timers for SLAs and notifications for stalls. Comment with a tricky edge case, and we will discuss modeling it with conditional paths that remain understandable for operators and maintainable for your platform team.
Start with low-risk automations that save time immediately, then expand to higher-impact steps. Require idempotency, retries, and alerts for failures. Provide dashboards showing throughput, latency, and error rates. Share the automation you plan first, and we will suggest guardrails to ensure it helps during outages rather than creating confusing side effects.
Not every decision should be automatic. Route ambiguous cases to skilled reviewers with context, recommended actions, and deadlines. Capture outcomes to improve rules later. Describe an exception you encounter frequently, and we will outline a review queue design that reduces delays while keeping accountability and data quality front and center.