Stats boss quits for health reasons after data controversy

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Jonathan Josephs

Business reporter

PA Media Office workers and commuters walking through Canary Wharf in LondonPA Media

The head of the UK Office for National Statistics (ONS), Sir Ian Diamond, has resigned with immediate effect due to health reasons, at a time when the ONS faces a crisis of confidence in its work.

"Due to ongoing health issues, Sir Ian has decided he is unable to give the full commitment he would like to drive the organisation forward," the ONS said.

Last month, a report from the Office for Statistics Regulation (OSR) laid out its concerns about the quality of the ONS's data.

These concerns focused on, but were not limited to, the widely recognised problems with the Labour Force Survey which is used to measure the unemployment rate in the UK.

Dr Sarah Cumbers, chief executive of the Royal Statistical Society, said: "Sir Ian Diamond showed outstanding leadership of the ONS and the wider statistical system during the pandemic, helping to make the UK a world leader in delivering timely data in a rapidly changing environment."

Dr Cumbers also acknowledged the OSR report.

"Given the recent scrutiny of the system, we look forward to engaging with the Cabinet Office and the UK Statistics Authority to consider how the National Statistician role should evolve, and to working with Sir Ian's successor to address the ongoing challenges," she said.

The report looked at concerns around business surveys and found that ONS staff were not always being listened to when flagging emerging problems to senior managers.

A lack of confidence in the quality of data makes it more difficult for the government and companies to make fully informed decisions.

Since the pandemic, statistics agencies around the world have struggled to get the response rates that they would like to ensure their data is of the quality they would like.

The regulator said it would like more assurance that the ONS has sufficient steps in place to regularly review and improve sample design and representativeness, bias, survey methodology, and imputation.

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