Human approval checkpoints
Measure approvals that actually change the outcome
A high approval rate does not show that review is useful. Look at corrections, missed errors and the time people need to understand a proposal.
In this article
Define the purpose of the checkpoint
An approval may confirm authority, check factual correctness or accept a business consequence. These purposes need different evidence. A reviewer can be authorised to approve an address change while still overlooking an incorrect postcode.
Write down what the checkpoint is meant to catch. For a generated proposal, that might include the wrong target, incomplete address or a change no longer allowed by the order's state. Use reviewed examples to establish whether people can detect those issues from the information shown.
Do not treat the presence of a person as proof that the system is safe. The review interface and workload determine whether that person has a realistic chance of making the intended judgement.
Track decisions and corrections
Measure approved, rejected, revised and expired proposals separately. Record what changed after review in a privacy-conscious way, such as the field category and reason rather than copying sensitive values into analytics.
A correction rate can reveal useful intervention, but its interpretation depends on the incoming proposal quality. A low rate might mean excellent proposals or inattentive review. Use sampled audits or controlled fixtures to distinguish them.
Include cases with known errors in a non-production evaluation. Observe whether reviewers identify the problem and whether the workflow prevents execution until it is resolved. Never introduce deliberate errors into real business actions merely to test attention.
Measure effort and delay
Track time waiting for a reviewer separately from time spent actively reviewing. A slow queue and a confusing interface require different remedies. Record how often reviewers open the underlying source or ask the requester for more information.
Repeated requests for the same missing detail suggest that the proposal is incomplete. Improve the evidence shown rather than simply reminding reviewers to work faster.
Also monitor stale approvals and re-review frequency. If harmless target changes invalidate most proposals, the dependency rule may be too broad. If meaningful changes slip through, it may be too weak. Review examples before adjusting it.
Connect review to business outcomes
Sample executed operations to confirm they match the approved proposal and still satisfy the intended rule. This checks the full path, including failures after a correct human decision.
Use the results to decide where review belongs and what information it needs. An approval checkpoint earns its place when it preserves required authority or catches consequential mistakes at a manageable cost. Click counts and approval percentages alone do not establish that value.
Primary sources
OWASP: transaction authorisationReferences checked 11 September 2026.