MBSS Light Pricing Explained: Plans, Add‑Ons, and Value Comparison

How to Migrate to MBSS Light: Step-by-Step Checklist

1. Prep and assess (Day 0–2)

• Inventory: List current systems, data types, integrations, and users.
• Goals: Define success metrics (downtime ≤ X, data integrity 100%, user adoption ≥ Y).
• Compatibility: Confirm MBSS Light supports needed features/APIs.

2. Plan migration (Day 3–5)

• Scope: Choose full vs. phased migration.
• Timeline: Schedule low-traffic window(s).
• Stakeholders: Assign owner, technical lead, and communication lead.
• Backups: Create full backups and verify restore process.

3. Map data & workflows (Day 6–8)

• Schema mapping: Map source fields to MBSS Light fields.
• Transform rules: Define data cleaning, normalization, and deduplication steps.
• Integration points: Document APIs, webhooks, and third-party connectors.

4. Build migration tools (Day 9–12)

• Scripts/connectors: Develop ETL scripts or use available connectors.
• Test harness: Create test datasets and an isolated MBSS Light sandbox.
• Logging & rollback: Implement detailed logs and reversible steps.

5. Test migration (Day 13–16)

• Dry run: Run full migration on sandbox; validate data integrity and workflows.
• Performance test: Measure import throughput and system load.
• User acceptance: Have key users verify core functionality.

6. Prepare go-live (Day 17–18)

• Finalize cutover plan: Step-by-step sequence, timing, and responsible persons.
• Communication: Notify users about downtime, changes, and support channels.
• Support ready: Staff support team and prepare quick-reference guides.

7. Execute migration (Day 19)

• Lock source if needed: Pause writes to ensure consistency.
• Run migration: Monitor logs, errors, and performance.
• Verify: Check record counts, key samples, and integrations.

8. Post-migration validation (Day 20–21)

• Smoke tests: Confirm critical workflows function.
• Data audit: Run checksums/sample comparisons for integrity.
• Issue triage: Fix high-priority defects immediately.

9. Optimize & train (Week 4)

• Performance tuning: Adjust settings, indexing, and workflows.
• User training: Run live sessions, distribute FAQs and how-tos.
• Monitor adoption: Track usage metrics vs. goals.

10. Closeout & documentation (Week 5)

• Document: Final architecture, runbooks, and lessons learned.
• Rollback decommission: Decide when to decommission old systems.
• Post-mortem: Hold retrospective and capture improvement items.

Notes:

• Adjust timelines for data volume and complexity.
• If integrations or compliance requirements exist, add legal/IT approvals to the plan.