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Faith & Ministry

Untangling HR for a Multi-Campus Ministry

Replacing manual handoffs between Rock RMS, Netchex, and Sage Intacct with a phased automation backbone.

Industry
Faith / Multi-Site Ministry
Engagement
Discovery + Phased Implementation Partnership
Timeline
Phased rollout, Q4 2025 onward
Built with
  • Rock RMS
  • Netchex
  • Sage Intacct
  • n8n
  • Make.com
  • Node.js
  • Postgres

Challenge

The church operates multiple campuses with a volunteer-heavy workforce layered on top of paid staff. Three core systems held overlapping but inconsistent records: Rock RMS for people data, Netchex for payroll, and Sage Intacct for the general ledger. Onboarding a new staff member meant manual entry in all three. Terminations risked stranded access. Reconciliation between payroll and the GL was a monthly fire drill.

Approach

We delivered this as a partnership agreement, not a transactional scope of work, because ministry moves at relational speed, not procurement speed. The plan ran in phases so the organization was never asked to trust automation before it had earned that trust.

  1. Discovery and data audit. We mapped every field across all three systems and identified the canonical source of truth for each attribute.
  2. Read-only sync layer. n8n flows pulled from Rock RMS and reconciled against Netchex without writing anything yet, surfacing drift in a weekly report.
  3. Bidirectional automation for onboarding and offboarding triggers, with a human approving each commit point.
  4. GL automation. Netchex payroll runs auto-post to Sage Intacct with cost-center mapping per campus.
From the original proposal

We're not selling you software hours. We're committing to a season of work together, measured in trust, not tickets.

Partnership Agreement, October 2025

Outcomes

  • Eliminated dual-entry for staff lifecycle events.
  • Surfaced three years of accumulated data drift in the first week of read-only sync.
  • Compressed reconciliation from days to minutes per pay period.
  • Established a partnership model that survives staff turnover on either side.

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