Start by defining the business impact
A cleanup project should not begin with “this org looks messy.” Connect the debt to real outcomes: users are entering data twice, automation is failing, reports are unreliable, deployments are risky, or admins cannot tell which components are still used.
Inventory before deleting
Build an inventory of the configuration involved and identify dependencies. Fields, flows, validation rules, reports, integrations, permissions, and code can affect one another. Deleting something because it looks unused can create hidden downstream problems.
Prioritize by value and risk
A useful backlog separates high-impact debt from cosmetic cleanup. Prioritize items that create production risk, block important enhancements, cause user errors, degrade data quality, or consume significant administrative time.
Change in small, testable increments
A large “clean everything” release creates unnecessary risk. Break remediation into manageable changes, test expected and edge-case behavior, and keep rollback considerations visible.
Document the decisions
Good cleanup should make the org easier for the next person to understand. Capture what changed, why it changed, what depends on it, and who owns the process going forward.
Prevent the debt from returning
Technical debt is partly a governance problem. Better intake, requirements, naming, documentation, testing, and release discipline reduce the rate at which new debt accumulates.