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Achieving good data is crucial for meeting your pension scheme’s goals. But there’s little point if you don’t keep your data in good condition.

 As we’ve said before, 2025 is crunch time for Britain’s pension schemes to get their data in order. After decades of drift, our industry faces a hard data deadline in the shape of pensions dashboards. 

The first, largest schemes must be ready to connect to dashboards next month and almost all schemes must connect by the end of October 2026. And there are many other reasons why pension funds need good data – from a range of new rules to preparing for buyout and providing digital services.

Don’t be surprised if your data has deteriorated

Many schemes will be carrying out data exercises for the first time to meet these requirements. But plenty of pension funds will be surprised to find they have to repeat an exercise they carried out only a few years ago. 

This is because, having spent time and money getting their data in good order, they didn’t maintain it. And if you don’t maintain your data, it goes bad quickly. 

You wouldn’t buy a new luxury car and drive it for years without checking the tyres or having it serviced. Well, the same applies to your pension scheme’s newly acquired clean data. 

In our white paper about the importance of good data, we discuss why good data is essential, how to get it – and how to keep it. This article will give you an insight into this overlooked third element in a data strategy.

Derisking plans can be thwarted by bad data

Picture the scene. After more than a decade of ultralow interest rates, a defined benefit pension scheme is in a position to target buyout. Higher rates have put the scheme in surplus and trustees decide to join the £50 billion or so of bulk purchase annuity transactions expected this year. 

The trustees assume their scheme’s data will be in good shape. After all, they only paid for a data correction exercise a couple of years ago. But when their administrator sends data samples to the insurer problems appear. Some benefits are incorrect and the insurer asks for a full data audit. The transaction is delayed, stress levels rise and costs increase. 

This is an all-too common scenario. You can read first-hand experiences from bulk annuity purchasers in our recent insight on the pitfalls of derisking here.

Data begins to decay almost immediately

The problem in many of these cases is that the scheme administrator didn’t maintain the data once the exercise was finished. It shouldn’t be a surprise that this happens – data starts to go wrong quickly without care and attention. Members die and change address, and processes slip unless they are checked. Just one year after a successful data cleanse exercise, a pension scheme typically suffers a 15% decay rate, according to Target Professional Services. 

A once and done approach to data upkeep was always bad practice and it won’t survive today’s demands. Take pensions dashboards. Your data may be in good shape when you connect, but dashboards are for ever. Your members’ information needs to be correct every time they check their pension. If not, they will be unhappy and so will the regulator.

Data maintenance is part of a lifetime journey

To keep your pristine data in order, you need a data maintenance plan that sets out, among other things: 

• How often data is checked 
• How issues are fixed 
• Who will fix the problem 

These tasks are getting easier as technology develops. In the near future, much of the work to maintain your data will be carried out automatically – reducing costs and increasing efficiency. 

As an industry we are in a new era when it comes to data. It’s time for us to catch up with the rest of the business world and stay there by making sure our data remains in great shape as part of a lifetime data journey. 

You can read more about these subjects in our white paper – Good Data: Why It Matters, How to Get It, How to Keep It. Please click here to download a copy.