Luton’s data-driven transformation: unleashing local potential with Local Partnership LLP

Host: Matt MastersGuests:Mark Fowler, Deputy Chief Executive, Luton Borough CouncilJordan Mendel, Senior Director in Data Analytics, Local Partnerships LLPEpisode Summary:In this episode, Matt Masters sits down with Mark Fowler and Jordan Mendel to discuss the ambitious corporate transformation underway at Luton Borough Council. The conversation delves into the appetite for change and the early stages of cultivating a transformative culture within the council.Mark and Jordan share their experiences working with the Local Government Association (LGA) and the importance of testing the rationale behind their initiatives. They emphasize the need to engage with the people driving these changes and gather feedback to ensure the project’s framework resonates with the community.A significant part of the discussion revolves around the three-year program designed to bridge a £28 million financial gap. The team, praised for their collaboration with partners, provided valuable feedback on governance, resourcing, and the ability to track and evidence benefits. Sheridan’s contributions to data insights were particularly highlighted.The episode also explores the challenges and strategies for moving forward, with the LGA providing a solid platform now in the delivery phase. The goal is to release £8 million in savings with an initial investment of £1.5 million over the first 12 months.Data transformation and focus are central themes, with Mark’s enthusiasm for data-driven decision-making standing out. The link between data and transformation is underscored as a crucial point, with the 2040 vision offering a unified approach to eradicating poverty. Mark discusses the importance of being data and evidence-led, overcoming historical challenges, and shaping the organization to achieve meaningful impacts.Listeners will gain insights into the confidence needed to drive improvements, track progress, and adapt to changes, ultimately aiming for cost reductions that exceed current expectations.