10008785Utilizing novel data sets and prediction methods to better identify and engage with customers in vulnerable circumstances and encourage sustainable water consumption in the residential sectorClosedFeasibility StudiesInnovate UKWhether it's the day-to-day use of water in the home, the use of water for increased hygiene measures in the fight against Covid-19, or for recreational activities, the pandemic has shown how central this valuable resource is to our everyday lives. It is however a resource that can no longer be taken for granted with an increasing number of households facing water affordability challenges (a challenge compounded by the Covid pandemic) and with continued pressures on water supplies globally. Combining emerging concepts in Big Data, behavioural science and machine learning, this project seeks to develop accurate residential water end-use demand forecasting models (providing similar functionality in assessing customer consumption and demand forecasting as smart meters which has seen limited adoption in the UK water industry) with the specific the aim of addressing priority challenges which include: -Better identifying and supporting vulnerable customers, -Achieving an improved understanding of customer demand to help monitor and avert potential household water-efficiency problems eg leaks, -Optimise the use of data around consumption patterns to truly understand and influence customer behaviour. -Helping households to reduce water consumption and practice more sustainable behaviours with guidance to achieve this, specific to that household. The approach has been specifically designed with input from the UK's Water utility companies and driven by stated objectives from Regulatory bodies including Ofwat and Ofgem for the improved use of data to address these critical challenges. If successful, the project will deliver significant benefit for Utilities, Regulators and customers with the potential address a recognised sustainability and social challenge that could positively impact every UK household. The solution could also be exploited across wider utility markets including energy where similar challenges exist along with wider geographical territories.