One-page checklist (10–20 minutes)
- Frequency of updates: Do records need to move between systems in real time, hourly, nightly or less often? Mark one.
- Acceptable delay: How long can the receiving user tolerate waiting (seconds/minutes/hours/days)?
- Cost of errors: What happens if a record is wrong or lost? (High = customer impact or money; Medium = rework; Low = convenience)
- Number of users & systems: How many people rely on the synced data, and how many systems need it?
- Data ownership and quality: Is there a clear owner and a single authoritative source, or is the data duplicated and messy?
- Maintenance capacity: Do you have someone to monitor and update integrations when things change (yes/no)?
Score it quickly: flag any item as “real-time required”, “high cost of error”, or “no maintenance capacity” — these drive the choice.
Map results to an approach — quick rules and examples
If you flagged real-time and high cost of error, aim for immediate sync (webhooks/real-time API) or a lightweight API connector that delivers near-instant updates. Example: lead routing from a website to a salesperson — low delay, one-owner field (owner), and high cost of losing leads means immediate sync or a reliable webhook connector.
If updates can wait hours and errors are moderate, a nightly batch or scheduled export/import is often the simplest reliable fix. Example: posting invoices from sales into accounting where same-day cash reporting isn’t required — a nightly batch reduces complexity and maintenance.
If one system must be the single source of truth to avoid duplicates and rework, centralise that dataset rather than syncing bi-directionally. Example: staff rota where payroll and rotas must agree — choose the roster app as the source and push a daily summary to payroll or use a single system for both.
Next steps: one paragraph for each recommended path
Immediate sync — implement webhooks or a small real-time API integration. Start by documenting the exact events that must trigger a sync, identify a single owner for the event schema, build or buy a connector that retries on failure, and add simple monitoring alerts so you know when it breaks.
Nightly batch — design a clean, atomic export/import. Decide the cut-off time, use CSV/JSON with strict field names, include checksums or counts to verify success, and run a short reconciliation report each morning to catch mismatches before users act on them.
Single source of truth — stop trying to keep two masters. Pick the system with the best data hygiene and assign a business owner. Migrate records carefully (dedupe, standardise), lock write access in non‑owner systems, and publish a short runbook explaining where to update which field.
Lightweight API / Zapier-style connector — use this when events need to flow quickly but you don’t have engineering time for full integrations. Map fields clearly, limit the number of triggers to what matters, add error-handling steps and a simple dashboard showing recent runs so anyone can spot failures.
Documented manual process — accept manual handoffs when frequency is low, errors are cheap and maintenance capacity is zero. Write a one-page runbook with step-by-step actions, responsible person, check points and where to paste data; review monthly and automate the most repetitive parts later. If you’d prefer practical help turning one of these options into a plan, Optira can assist with a short session to pick the least risky route.