Data Governance: Integration & Systems Alignment

When systems don’t talk, people work harder—and often, less effectively. Integration isn’t just about data pipelines; it’s about aligning logic so teams can make better decisions with less friction. High-functioning organizations evolve from isolated tools to ecosystems where information moves seamlessly. When we connect systems thoughtfully, we reduce errors, build trust, and free people to focus on solving real problems.

How are discrepancies managed when integrating data from external sources like employer feeds or partner HR systems?

This question reveals how well conflicting or incomplete external data is detected, escalated, and resolved. A response that points to ad hoc reviews, manual corrections, or periodic “data cleanups” signals Level 1 or 2. References to structured discrepancy reports, staff workflows for resolution, or scripted validations suggest movement into Level 3–4. Fully embedded resolution queues and automated discrepancy alerts point to Level 5.

What tools or practices are used to reconcile Salesforce records with external systems to ensure a single source of truth?

This probes alignment between internal and external systems. If Salesforce is treated as a source of truth but reconciliation is manual, the organization is likely in the Level 2–3 range. Mentions of field-level mapping documentation, reconciliation routines (e.g., daily job code crosswalks), or ETL automation tools indicate Level 4. Use of real-time sync engines, reconciliation dashboards, or versioned data lineage tools suggests Level 5.

Assessing the Baseline

These questions help evaluate whether the organization:

• Treats integration as a governance process, not just a technical handoff.
• Has tools and processes to flag and resolve mismatches, rather than react when issues bubble up.
• Maintains a coherent, authoritative view of participant and employer data across platforms.

If reconciliation is largely manual or happens after errors reach staff or members, maturity is below Level 3. If discrepancies are detected automatically, routed for resolution, and logged with history and accountability, the organization is operating at Level 4 or 5.

Leveling Up - Data Integration & Systems Alignment

In most organizations, data lives in many places—especially when pulling from systems like Salesforce, Excel, HR feeds, or employer-submitted lists. This domain focuses on helping the organization build a clear, reliable view of its data—even when that data comes from many sources. 

Level 1 reflects a common starting point: disconnected systems and manual fixes after problems arise. Leveling up begins with reconciliation—spotting mismatches, mapping sources, and creating basic workflows to reduce error. 

By Level 3, consistency and automation take the lead—scripted imports, field mapping, and validation layers help eliminate rework. At Level 4, those integrations become auditable and responsive, with logs, alerts, and lineage tracking. Level 5 brings it all together with systems that support cross-functional decision-making through coordinated, trusted data flows.

Each activity here reflects the real-world messiness of integration—batch files, field drift, and evolving logic. The aim isn’t perfection—it’s progress toward smooth, dependable data movement across the whole organization.

 From Level 1 to Level 2

• Identify all external data feeds (e.g., employer lists, HRIS, survey tools)
• Document integration pain points and manual reconciliation steps
• Create a cross-system field mapping spreadsheet
• Develop a protocol for reconciling mismatches between systems (e.g., Salesforce vs Excel)
• Flag duplicates or conflicts for manual review and resolution

 From Level 2 to Level 3

• Schedule routine (e.g., weekly) reconciliation tasks for key datasets
• Standardize import templates and expected field values
• Automate one or more low-risk imports (e.g., employer utilization data)
• Use unique identifiers to link records across systems
• Create a log of resolved discrepancies and track volume over time

 From Level 3 to Level 4

• Implement automated discrepancy alerts and exception reports
• Build dashboards to show integration health (e.g., unmatched records, stale values)
• Document integration logic (transformations, filters, frequency)
• Assign stewardship of reconciled fields to responsible teams
• Create a shared “truth table” view for key records (participants, employers)

 From Level 4 to Level 5

• Shift toward real-time or near-real-time sync where feasible
• Track source system provenance and last-updated timestamp per field
• Automate resolution workflows for high-frequency issues
• Publish an integration roadmap that includes system dependencies
• Align integration success metrics to program delivery outcomes