Methodology

Where the data comes from

English councils are required to publish their spending over £500 to individual suppliers. We ingest each council's own published disclosure files directly — we don't estimate or infer transactions.

How we clean and normalise it

Supplier names are matched using fuzzy string matching at an 85% similarity threshold, so that near-duplicate spellings of the same supplier (for example "ACME LTD" and "Acme Limited") are merged into one canonical supplier rather than counted separately. Each transaction is also assigned to one of 15 standard service categories using keyword matching against its description, so spending can be compared across councils even though each council describes its own transactions differently.

Coverage and update cadence

We currently track 100 English councils. Councils publish disclosure files on their own schedule and in their own formats, so how recent the data is varies council by council — some are updated within the last few months, others less frequently, depending on what each council has published. Each council's dashboard shows the date range its data actually covers, so you can see exactly how current it is rather than assume a fixed cadence.

Limitations

• Source files differ in structure between councils, which occasionally leads to gaps or formatting quirks in fields like description or date.
• Transaction records carry limited context beyond supplier, amount, date, and category — they show what was paid, not the full contract or decision behind it.
• Fuzzy supplier matching reduces duplicate suppliers but is not perfect, particularly for very short or generic supplier names.
• Figures reflect what each council has chosen to disclose, not an independently audited account.