When a Supplier Collapses, Bad Data Gets Expensive Fast

When a supplier unexpectedly closes, the immediate concerns are usually operational. How will services continue? Who has access to the records? Can another provider take over without disruption?

But there is another question businesses should be asking: how reliable is the data they depend on?

Recent UK reporting about supplier disruption is a reminder of how quickly organisations can find themselves relying on records that need to be transferred, checked or used at short notice.

The wider lesson applies to almost every business managing customer information. Whether you're running a marketing database, contact centre or CRM system, poor data quality can turn an already difficult situation into a much more expensive one.

And the problems often begin long before anyone notices them.

Why disruption exposes poor data quality

Most businesses collect customer data over months or years. Contact details are added, imported, updated and shared between different systems.

Over time, phone numbers change, email addresses become inactive, customers move and duplicate records accumulate.

While everything is running normally, these problems can be easy to overlook.

But when a business needs to migrate its CRM, change suppliers, respond to an audit or contact customers urgently, unreliable records can suddenly become a serious obstacle.

Imagine a company transferring 50,000 customer records to a new platform. If thousands contain invalid contact details, duplicates or outdated preferences, the migration becomes more complicated.

Teams may spend hours identifying errors, correcting information and checking which records can safely be used.

Poor data doesn't just affect marketing performance. It can slow down essential business operations.

What does GDPR Article 5 say about data accuracy?

Data accuracy isn't simply good practice. It's also an important part of UK data protection law.

Article 5(1)(d) of the UK GDPR establishes the accuracy principle, requiring personal data to be accurate and, where necessary, kept up to date.

The Information Commissioner's Office (ICO) explains that organisations should take reasonable steps to ensure personal information is correct, maintain appropriate processes for checking accuracy and correct inaccurate information when necessary.

What counts as reasonable depends on how the information is being used.

For example, an outdated address in a historical transaction record may be perfectly appropriate. But an incorrect address being used for a current customer delivery could cause problems.

For businesses managing large contact databases, this makes regular data hygiene an important part of responsible data management.

It doesn't mean every record must be constantly rechecked. It means having proportionate processes to identify and address inaccuracies when they matter.

How bad contact data creates unnecessary costs

Small inaccuracies can have a surprisingly large impact when repeated across thousands of records.

Invalid phone numbers

Outdated or incorrectly formatted telephone numbers can waste call centre time, reduce successful contact rates and make outreach campaigns less efficient.

Invalid email addresses

Emailing addresses that no longer work can increase bounce rates, waste campaign resources and make it harder to assess marketing performance.

Outdated suppression checks

Businesses carrying out telephone marketing need to consider whether numbers are registered with the Telephone Preference Service (TPS) or Corporate Telephone Preference Service (CTPS), alongside their own suppression and do-not-call records.

Failing to maintain appropriate checks can create compliance risks, particularly when databases are transferred between systems or reused for new campaigns.

Duplicate and inconsistent records

Duplicate contacts can lead to repeated communications, conflicting customer information and unnecessary administrative work.

Individually, these issues may seem manageable. Across a large database, the costs can quickly add up.

Why clean data makes migrations and audits easier

A CRM migration should be an opportunity to improve your data, not simply move existing problems into a new system.

Before transferring records, businesses should understand what information they hold, where it came from, whether it remains accurate and whether it is still needed.

This makes it easier to identify duplicates, remove unnecessary information and ensure suppression preferences are preserved.

The same principles apply to audits.

When customer records have clear sources, accurate contact details and documented validation processes, organisations are better placed to explain how their data is managed.

Clean data also helps marketing and operations teams work more efficiently, reducing the time spent investigating errors or attempting to contact people using outdated information.

"Bad data rarely becomes a problem overnight. The real cost appears when businesses suddenly need to rely on records they haven't checked in months or years."

Five data hygiene checks your business can make this week

You don't need to wait for a major system change to review your database.

Here are five practical checks to get started.

1. Check when your data was last validated

Identify records that haven't been reviewed recently, particularly those used for active campaigns or customer communications.

2. Validate phone numbers and email addresses

Check contact details for invalid formats, inactive addresses and other potential errors before launching your next campaign.

3. Review your suppression lists

Make sure your processes account for relevant TPS, CTPS and internal do-not-call records. Check that opt-outs and objections are carried across systems correctly.

4. Identify duplicates and incomplete records

Look for repeated contacts, missing fields and inconsistent formatting that could create problems during imports, migrations or reporting.

5. Make data validation part of your routine

Rather than treating database cleaning as a one-off exercise, consider validation at collection, before major campaigns and at appropriate intervals.

The right frequency will depend on the type of data, how quickly it changes and how your organisation uses it.

Where does automated data validation fit in?

For businesses working with large datasets, manually checking every record isn't always practical.

Automated validation tools can help identify potential problems before they affect campaigns or operations.

Depending on the checks required, this can include:

• Phone validation: Checking telephone number format and other available validity indicators.

• Email validation: Identifying invalid or potentially undeliverable email addresses.

• TPS and CTPS screening: Checking numbers against the relevant UK telephone marketing preference registers.

• Do-not-call checks: Supporting screening against applicable suppression records.

• Address validation: Checking and standardising address information.

These checks help improve data quality, but they don't replace the need for an appropriate lawful basis, consent where required, or effective internal compliance procedures.

For marketing teams, contact centres and technical buyers, validation is most useful when it becomes part of an ongoing data management process.

Don't wait for disruption to find out your data is outdated

Supplier failures, CRM migrations and unexpected operational changes can happen with little warning.

While businesses can't prevent every disruption, they can make sure their records are in better shape when they need them.

Regular validation, effective suppression management and clear data ownership can reduce avoidable errors and make day-to-day operations more efficient.

When reliable data matters most, the worst time to start checking it is after something has gone wrong.

Review your current data hygiene process and identify where validation could make a difference.

Explore Data Soap's validation options, try the £4.99 starter pack or speak to the team about your requirements.

Explore Data Soap pricing

Further reading: ICO guidance on the accuracy principle.