Data quality: a routine that keeps business records usable

Key takeaways

A data quality process keeps customer, supplier and product records complete, correct and free of duplicates through written rules and regular checks. One-off clean-ups decay within months; a weekly routine does not. UK GDPR also requires personal data to be accurate and kept up to date. The checks outsource well; the rules are yours.

• Write rules for required fields and formats.
• Check new records weekly against the rules.
• Merge duplicates on a set routine.
• Fix data at the source, not just in reports.

What makes data poor quality?

Missing fields, inconsistent formats, duplicates, out-of-date details and records entered in the wrong place. Each has a cost: returned post, failed deliveries, wrong reports, and marketing sent to people who should not receive it. Most problems start at entry, when there is no rule about what a complete record looks like.

• Which business processes should you outsource?
• Admin errors costing money? When accuracy says outsource

What rules should a data quality process have?

For each key record type, define required fields, allowed formats such as postcode and phone, how to spot duplicates, who can create records, and when records should be reviewed or deleted. Keep the rules on one page so they can be followed by anyone.

• Required fields per record type.
• Formats for addresses, phones and dates.
• Duplicate matching rules.
• Review and deletion periods.

• Decision tables: turn judgement calls into clear rules
• Single source of truth: one place for each business fact

Which data quality work can be outsourced?

Weekly checks of new and changed records, merging duplicates, filling gaps from reliable sources, standardising formats and producing a short quality report. The business owns the rules, decides on deletions and fixes the processes that create bad data.

• Outsourcing CRM admin and data hygiene
• Data enrichment: fill the gaps in your customer records

When is a data quality process not needed?

When a system has very few records and one person maintains them carefully. It becomes essential once several people enter data, records feed reports or marketing, or systems are connected, because errors then spread.

• Integrations between systems: who watches when they break?
• How much volume makes a process worth outsourcing?

What does this look like in practice?

A pattern we see: a business pays for a big data clean-up, then the same problems return within six months because nothing changed at entry. A short weekly check against written rules keeps the gains.

• See client work
• BPO Solutions for UK businesses

Data quality checklist

Set these up once and review quarterly.

• One-page rules per record type.
• Weekly check of new records.
• Duplicate merge routine.
• Quality score tracked over time.
• Root causes fixed at entry.
• Retention and deletion rules applied.

• The process selection score: outsource, split or keep?
• IT processes to outsource in a small business

Next step

Tell us which system holds your most important records and what goes wrong with them. We will suggest rules and a weekly check.