Register Quality Checks

Quality checks are the tests an entity runs on its register to find out whether it can be trusted. They check whether entries are complete, whether links between providers, services, functions, contracts, and data hold together, whether descriptions are consistent, and whether the register agrees with contracts and with services actually in use. A register that has never been checked may look impressive and still mislead, because its errors are invisible until somebody tests it. Checks make those errors visible while they can still be fixed cheaply, before an incident, an exit, or a supervisory question exposes them.

This guide sets out the checks that matter most, how to run them without turning quality into a bureaucratic exercise, and how to handle findings so the same errors do not recur. The emphasis is on checks that test meaning, not just presence. A field that is filled with a plausible but wrong value passes a presence check and fails a meaning check, and it is the meaning checks that protect the entity.

Completeness checks ask whether every arrangement that should be in the register is there, and whether every entry has the facts it needs. The first question is answered by comparing the register with independent sources, such as contracts, supplier records, and technology inventories, and by asking service owners to confirm their dependencies. The second question is answered by scanning entries for missing providers, services, functions, contracts, or data and location facts. Both questions matter, and neither is answered by counting rows. A register with many rows can still miss an entire category of arrangement, such as branch-level services or group-provided services.

Link checks test the connections that give the register its value. Does every service link to at least one function. Does every function that depends on ICT have its services recorded. Does every arrangement link to a real contract. Does every provider entry use a consistent name and identity. A register that fails these checks may contain correct facts in isolation, but it cannot answer the questions that matter, such as which functions a provider failure would interrupt, or which contracts govern a failing service. Link checks can often be run systematically once the register is structured, which is another reason format discipline matters.

Consistency checks look for contradictions. The same provider described differently across entries, the same service given different locations, or the same function linked to different providers without explanation all deserve questions. Some contradictions will prove genuine, because services differ, but they should be explained in the entries rather than left for a reader to puzzle over. Unexplained inconsistency erodes trust faster than an admitted gap, because a reader who finds one contradiction will wonder how many more exist.

Accuracy checks compare register entries with the documents and realities they claim to describe. For a sample of entries, the checker opens the contract and confirms the parties, scope, and key terms. They confirm with the service owner that the service described is the service in use, and with the function owner that the function link is correct. They check data and location facts against provider documentation. Sampling keeps this work proportionate: a well-chosen sample, weighted towards new, changed, and high-impact arrangements, will find most accuracy problems without requiring every entry to be re-verified at once.

Findings should be logged, assigned, corrected, and re-checked. A finding without an owner tends to linger, and a correction without a re-check may introduce a new error. The register owner should track findings to closure and report patterns, not just individual fixes, to the governance that oversees third-party risk. Patterns point to process fixes: if amendments repeatedly cause errors, the amendment workflow needs a register step. If one team's entries repeatedly fail, that team needs support or training, not blame.

Quality checking should also be proportionate to change. A stable register with few changes needs lighter checking than a register undergoing migration or restructuring. Scaling checks to change keeps the work sustainable and prevents quality from becoming a ritual that teams resent. The aim is a register that the entity can rely on with confidence, because it has been tested in ways that match its risks, and because its findings have been acted on visibly. That confidence is what makes the register useful in a disruption, when there is no time to doubt the map.