UPRN Matching for Local Authorities

The Day-to-Day Impact of Mismatched Address Data

The effects of poor address data in local government are rarely dramatic. They show up as small, repeated inefficiencies that accumulate into a significant drain on officer time and service quality. A housing officer searches for a property and finds two records that might refer to the same address. They spend time checking both before they can be confident they are looking at the right one. A revenues officer tries to match a council tax record to a planning application, but the addresses are formatted differently and the automated match fails. A social care referral cannot be automatically linked to the housing record for the same property because the address is recorded differently in each system, and a manager has to investigate the discrepancy before the referral can proceed. None of these problems is dramatic on its own. Add them together across a council of any size, and you have a significant volume of avoidable work. All of it traces back to the same root cause: records that refer to the same property do not share a common reference number. UPRN alignment across systems is what makes automated matching reliable.

Getting Started with UPRN Matching

Many councils approach UPRN matching as a large, complex, expensive project. In practice, the starting point can be straightforward. The most useful first step is to identify the two or three systems where address data inconsistency causes the most day-to-day problems. For most councils this is housing and revenues — the two services most dependent on accurate property records and most likely to need to exchange data. Export the address data from these systems into a CSV, upload it to Semilariti, and review the matched output and the confidence scores. This gives you a clear picture of how much of your address data is already clean, what proportion needs attention, and where the most significant inconsistencies lie. From there, the remediation plan follows naturally. High-confidence matches can be updated directly. Lower-confidence records can be reviewed and corrected by LLPG Custodians or data officers. Records that could not be matched reveal gaps in the data that need to be investigated at source.

Why UPRN Matching Is an Ongoing Need, Not a One-Off Project

Address data quality is not a problem you solve once and then set aside. New records are created every day. New developments add properties to the local area. System migrations bring in fresh data that may not be LLPG-aligned. Staff turnover means that data entry standards vary over time. Councils that treat UPRN matching as a periodic activity — running a cleansing exercise ahead of major projects, before data submissions, or at the start of a new financial year — consistently maintain better address data quality than those who treat it as a one-off remediation task. Semilariti is priced to make this practical. Monthly plans with no long-term contracts mean councils can use the service when they need it and scale up for larger projects without committing to annual contracts sized for enterprise data providers. The cost is a fraction of a traditional AddressBase licence, and there are no per-record fees for bulk processing.