This project will deliver substantial societal advantages for vulnerable customers, including reduced stress during outages, relief from financial debt, and a contribution to reduced carbon emissions through participation in the energy transition. Furthermore, current customers will also gain from this initiative, as adding them to the PSR program grants access to extra support during power interruptions, including a 24/7 helpline and proactive outage updates.
What is the project about?
Spotlight tackles the challenge of identifying Priority Services Register (PSR), Fuel Poor (FP), and Leaving No One Behind (LNB) customers on an individual household level, going beyond the constraints of existing methods that rely on broad demographic trends. To achieve this, the project is pioneering an approach that involves tapping into data from diverse sectors like telecommunications and finance, thereby improving the precision of customer identification.
Beyond mere identification, Spotlight is committed to enhancing operational efficiency by optimising engagement strategies specifically tailored for PSR, FP, and LNB customers. Harnessing the power of data insights, the project intends to revolutionise how operational teams interact with these customers. This involves the strategic selection of engagement channels that cater to the diverse needs and vulnerability categories of the identified customer groups.
In essence, Spotlight is not just about identifying these specific customer segments; it’s about transforming the way assistance is provided. By leveraging innovative data-driven insights, the project aspires to ensure that interactions are not only more precise but also tailored to meet the unique needs of individuals within these identified vulnerable customer categories.
How we’re doing it
Spotlight will leverage data modelling and machine learning to identify vulnerable customers at a granular level. The project seeks to bring together existing data sources, and bring new ones, into a single platform. Once the data is integrated centrally, it will be processed to enable data driven approach to supporting vulnerable customers. The data models will be developed to be scalable to any future data that becomes available.
Spotlight’s innovative approach involves advanced clustering, machine learning techniques, and a diverse range of datasets to create a unique classification system for identifying vulnerable customers and those at risk of vulnerability. With the potential for nationwide replication, the project will focus on significantly increasing the granularity of vulnerability data, aiming for household-level insight rather than the current LSOA-level information. The project will target three categories: PSR, FP, and LNB. Spotlight aims to utilise new data modelling methods which have already been partially validated in other industries such as retail, telecoms, and technology. Spotlight seeks to adapt and apply these methods specifically to address customer vulnerability requirements in the electricity distribution sector.
What makes it innovative
Spotlight is a project focused on leveraging data modelling and machine learning to identify vulnerable customers at a granular level. The project seeks to bring together existing data sources, and bring new ones, into a single platform. Once the data is integrated centrally, it will be processed to enable data driven approach to supporting vulnerable customers. The data models will be developed to be scalable to any future data, which becomes available. Spotlight’s innovative approach involves advanced clustering, machine learning techniques, and a diverse range of datasets to create a unique classification system for identifying vulnerable customers and those at risk of vulnerability. With the potential for nationwide replication, the project will focus on significantly increasing the granularity of vulnerability data, aiming for household-level insight rather than the current LSOA-level information. Moreover, the project seeks to predict customer exclusion beyond existing definitions and formulate sophisticated engagement strategies employing methods like A/B testing.
What we’re learning
We are learning to create a unique classification system within the project to identify vulnerable customers and those at risk, possibly even at the household level. By analysing data gaps and conducting A/B testing, we’re gaining valuable insights. These insights will improve the way we support vulnerable customers by providing actionable information about their needs, effective engagement strategies, and helpful assistance during the energy transition. The knowledge we’re acquiring will not only enhance our support but also open avenues for innovative business arrangements, improved support solutions, and better allocation of resources. Ultimately, these developments contribute to a fair and inclusive path as we work towards achieving net-zero emissions.
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If you have an idea that could reshape or revolutionise the way we work, we want to hear from you.
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