Thames Water is the UK’s largest water and sewerage company operating in a number of different local authorities in the South East of England. It employs 5,000 people in total and has 13.6 million customers across the region dealing with four million customer enquiries annually and attending 2,000 customer appointments per month.

The existing shift patterns and T&Cs had not been reviewed formally since 1993 and the organisation had over 100 different ones in place making shift planning, rostering and workforce management difficult and onerous. Thames Water was also relying heavily on costly overtime as the outdated shift patterns weren’t meeting the current demands of the business nor its customers. It was clear that the organisation needed to overhaul its shift patterns, rotas and rosters for a great number of reasons. Thames Water was facing cost pressures to ensure they provide value for money to customers. It couldn’t demonstrate it was operating efficiently in all areas and the business needed to make a millions in savings in this area. 

We delivered a demand-led shift planning, rostering and workforce management system for Thames Water as the utility company needed to make significant savings within the business to remain efficient and meet strict regulatory demands. Implementing Annualised Hours meant that the company saved over £10 million in additional overtime payments, reduced excessive working hours for shift workers and helped to increase the work-life balance of front-line teams.


  • Reduced 100 working patterns to 23
  • Extended appointment slots for customers
  • Improved customer service out of office hours 
  • Standardisation of T&Cs across all teams
  • Creation of a larger reserve of bank hours
  • Reduction in overtime
  • Variable hours for employees extending the day to 19.00 if required
  • £10 million saving (over 5 year AMP period) in overtime and working patterns payments 
  • Standardised longer working week, start and finishing times and annual holiday 
  • Introduction of winter shift pattern to increase resources at peak times
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