Fintech — Territory Assignment via Flow

TL;DR

Replaced brittle manual assignment with a Screen Flow rules editor and testable decision subflows.
Bulk-safe record-triggered Flow applies rules consistently; changes are auditable.
Ops team edits rules without engineering, cutting maintenance time by over half.

Fintech sales org covering multiple regions, products, and partner tiers. Frequent go-to-market changes made assignment logic hard to maintain.

Assignment rules lived in a mix of validation rules, formula fields, and old WFR. Changes were slow, error-prone, and non-auditable.

• Rules editor — Admin Screen Flow with a table-like UI to add/edit rank-ordered rules (region, product, ARR band, tier).

• Decision subflows — Compact, testable subflows evaluate rules and return the correct owner/queue.

• Bulk application — Record-Triggered Flow runs on create/update with guardrails to avoid recursion; batch re-apply tool for backfills.

• Auditability — Every rule change captured with who/when/why; change set includes unit test scenarios.

• Safety net — Fallback owner for unmatched records + weekly report of unmatched to drive rule coverage.

Window	Quarter before vs quarter after go-live
Industry	Fintech
Clouds	Sales Cloud
Flow Types	Screen Flow, Record-Triggered, Subflow

−60%

Ops maintenance time

−70%

Rule change lead time

0 added

New Apex debt

Maintenance time from Ops Jira tickets; lead time measured from request creation to production rule update. Audit logs verify change coverage.

1 sprint build + 1 week UAT + 1 week backfill & monitoring.

Sales Cloud, Screen Flow (rules editor), Record-Triggered Flow, Subflows, Custom 'Rule Change' log object.

How do we prevent rule conflicts?

Rules are rank-ordered; the first match wins. A linter screen flags overlapping or unreachable rules before save.

What if a record doesn't match any rule?

It's routed to a fallback owner and logged in an 'unmatched' report reviewed weekly; admins add coverage via the editor.