A council which allows staff to work just four days a week has been accused of introducing a ‘lodgers’ charter’ amid fears taxpayers will be harmed.
South Cambridgeshire District Council will tomorrow agree to let all office workers reduce their working hours by 20 per cent for next year without loss of pay, after saying a pilot project had been successful.
He even expands the lawsuit to include the binmen, despite fears that they won’t have time to complete all of their tours.
But it can be revealed today that official reports released by the Lib Dem-led council – which has an £18million head office known to be empty amid so many staff working from home – raise major questions on politics.
The documents reveal that civil servants are taking advantage of the more relaxed regime to enjoy longer lunch breaks and dog walks.
South Cambridgeshire District Council (pictured) will tomorrow agree to let all office workers reduce their working hours by 20%
Local politicians complain that it is “impossible” to reach anyone on a Monday or Friday.
And despite the council’s bragging, many key performance targets were missed, including the time call center operators took to answer the phone.
Last night Tory MP Jacob Rees-Mogg called the four-day week experiment – which the unions want to introduce in the public sector – a “charter for idlers”.
He added: “Councils need to remember that they are providing a public service and the public expects it to be provided five days a week.”
South Cambridgeshire MP Anthony Browne said: ‘People are furious about this because council taxes have gone up.
“Council should focus on South Cambridgeshire residents instead of its staff. In many areas, it struggles to provide services.
Elliot Keck of the Taxpayers Alliance – which is today launching a campaign against the four-day week – said: ‘Taxpayers will rightly be concerned that the council tally will spread across the country.
Asked about the missed targets, South Cambridgeshire insisted: “There are no serious issues which require concern when comparing data with longer timescales, outliers and seasonality.”