Whitehall could save £33bn with big data analytics, says Policy Exchange

Government could save £33bn a year applying big data analytics to departmental information, claims a report from the Policy Exchange

The government could save up to £33bn a year by applying big data analytics to departmental information, claims a new report from think tank the Policy Exchange.

The Policy Exchange estimated up to £22bn could be found by optimising the running of departments; up to £3bn by reducing fraud and error; and £8bn by collecting a greater share of unpaid taxes. 

In its report, The Big Data Opportunity the Policy Exchange called for a specialist Data Force unit to be set up in Whitehall to identify savings in tax avoidance and benefit fraud, with an objective to find £1bn in its first year.

Chris Yiu, author of the report, said: “The Cabinet Office estimates that fraud in the public sector costs taxpayers around £21 billion a year, £10bn lost to errors and £7bn in uncollected debts.

"When you add up all that, looking for a £1bn in savings should not be too hard.”

Yiu said the unit could be formed along the same agile model as the Government Digital Service, which has a £22m budget or the Open Data Institute which has a £10m budget.

Yiu acknowledged the £33bn figure was a top-end estimate, unlikely to be reached, as it would require using advanced technologies across government.

The Policy Exchange report suggested the Home Office could analyse airport queues in real time to anticipate bottlenecks and ensure enough desks are open to cope with fluctuations in passenger numbers. 

It added HMRC could collect more unpaid tax by accelerating the use of algorithms to mine data (including tax returns and third party data) and flag cases that need to be investigated to ensure the correct tax is paid.

The Policy Exchange applied the methodology used in a report published by research firm McKinsey, which found European public administrations could save up to €300bn.

Yiu said the report did not go into the details of how much or what big data analytic applications the government would need to buy, with that money potentially coming out of the budgets of individual departments.

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