How can a reseller recognise customers who need this workflow coverage?
Customer discovery can focus on operational dependencies that make changing a rule harder than publishing its replacement document.
Use these discovery checks to identify whether a customer's intended application needs generated policy propagation tasks and whether your resale description captures the operational problem accurately.
- Ask whether work stays open across policy revisions, leaving agents to reconcile previously completed steps with obligations introduced before the next action. - Identify decisions that cross team boundaries, where one role can update its guidance while another continues working from an outdated instruction or checklist. - Check whether customer commitments constrain corrective action, so applying a new rule requires preserving an accepted promise while changing the remaining operational steps. - Look for local procedures derived from central policy, because updating the source document may leave dependent instructions inconsistent until their owners revise them. - Establish whether exceptions need explicit authority, making the difference between an approved departure and an accidental breach part of the customer's intended evaluation. - Ask whether errors surface downstream, after an apparently successful decision has already triggered billing, dispatch, scheduling or another consequential action by a separate team. - Confirm that the customer wants to assess operational behaviour, with observable actions and outcomes, rather than only summarisation of revised documents or retrieval.
Use concrete workflow signals to qualify demand before offering customers a broad policy reasoning collection.
- Audience:
- Licensed resellers
- Content type:
- Checklist
- Buyer question:
- What it is and why it matters
Content release: r-a220eb6e099b243b
Related questions
- How can a policy change break a handover between connected operational teams?
- Why does a changed policy require more than replacing a reference document?
- Why should a policy task expose events as well as the latest record state?
- Should an agent apply every policy update uniformly to all open cases?
- What should developers map before an agent propagates a policy change?
- Which business features make this workflow worth simulating?