The normal path is only part of the process
An automation diagram often shows a request moving neatly from one system to another. The harder questions appear when a required field is missing, an API is unavailable or a business rule changes between two steps.
List those conditions alongside the happy path. Decide which failures can be retried, which need corrected data and which require a person to make a decision. These categories need different behavior.
Give every exception a useful record
A review item should identify the original request, the failed step, the reason and the current owner. Preserve the evidence needed to understand what happened without exposing more sensitive data than the reviewer needs.
Avoid an error queue that simply accumulates technical messages. Translate a failed operation into an action: correct the product identifier, confirm the destination, approve an adjustment or retry after the dependency recovers.
Design recovery as carefully as processing
A retry should not create a second order or apply an adjustment twice. Use a stable business identifier and define what an already-completed action looks like. If several systems are involved, record which steps succeeded before trying the rest again.
Some failures are ambiguous: the receiving system may have accepted a request even though the response was lost. Recovery should check the existing result where possible. Blind repetition can turn a temporary connection problem into a data problem.
Agree the review rhythm
Specify who sees new exceptions, who can approve changes and how unresolved work is escalated. A useful dashboard answers what needs attention and what is blocking it.
Measure whether the queue is actionable. If reviewers repeatedly need to ask for the same missing context, improve the record. If most items need the same correction, improve the source process. The queue is a source of design evidence, not merely a place to hide failures.