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Labour Optimisation Manager

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Job Description - Labour Optimisation Manager

Labour Optimisation Manager – Multi-Site Retail & Hospitality

Hybrid (Travel to sites) | Up to £65,000 + Car Allowance + 20% Bonus

Are you passionate about optimising workforce efficiency through data, insight, and smart planning? Do you thrive at the intersection of people, performance, and predictive analytics?

A national, multi-brand operator is hiring a Labour Optimisation Manager to lead smarter workforce planning across a diverse estate of retail and hospitality units.

This is a hybrid role combining home working, occasional office visits, and site visits across the UK to engage with key stakeholders. Travel isn't daily, but the ability to visit locations when needed is essential — a car allowance is included, and a full UK driving licence is required.

The Job
  • Own and refine labour models that reflect operational needs and trading patterns

  • Use data to guide forecasting, budgeting, and workforce deployment

  • Collaborate with operational managers to improve efficiency and cost control

  • Build reporting tools to monitor labour impact and performance

  • Support wider transformation projects across labour planning and workforce systems

  • Partner with HR, Finance, Tech, and brand stakeholders across the organisation

About you
  • Experience in labour modelling, workforce planning, or WFM

  • Background in multi-site retail, catering, or hospitality environments

  • Strong analytical and commercial thinking

  • Confidence working with operational stakeholders and presenting insight

  • WFM systems experience (e.g. Kronos, Quinyx, etc.)

  • Full UK driving licence required due to occasional site visits

Reasons to apply
  • Shape national labour strategy across a complex, well-known brand portfolio

  • Join a supportive central team with strong collaboration and autonomy

  • Competitive package: £65k + up to 20% bonus + car allowance

  • Generous discounts, enhanced family benefits, and smart pension options

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