UK Power Networks is working to deliver support at scale to vulnerable consumers at risk of being left behind by the energy system transition. This project will develop a new digital tool that aims to utilise cutting edge technologies such as machine learning and artificial intelligence to enable tailored support to be effectively delivered to vulnerable consumers at scale. By working closely with current service delivery partners, the aim is to build a tool that supports existing services while also providing new options for consumers that would prefer to self-serve using digital channels.
Benefits
During RIIO-ED2, UK Power Networks is working to deliver support at scale to vulnerable consumers at risk of being left behind in the energy transition (aka Leaving No one Behind, LNB). This requires a step change in volumes of vulnerable and disadvantaged customers that are identified and supported. This is especially important in a context where other factors, such as the increasing cost of living, digital exclusion, increased inflation and increasing energy costs will contribute to increasing numbers of people at risk of being left behind.
A key challenge currently faced is an inability to scale services to meet the required significant increase in volumes compared to RIIO-ED1. Many of the partners funded by Distribution Network Operators (DNOs) to provide support to vulnerable consumers do so manually and are operating at capacity so unable to address the volumes of customers that require support. Many partners have growth plans to expand their reach, but this requires additional time and resources.
It is relevant to note that across the existing portfolio of services and initiatives that UK Power Networks provides, there has currently been a low uptake of digital products despite novel solutions being available. This comes despite an increased expression of interest from consumers in digital self-serve channels. This project looks to address this challenge in two ways:
Utilising innovative technologies to provide a tailored experience for customers. This will allow customers to interact with the tool to provide bespoke support, with the aim of providing a high level of customer service.
Working with frontline service delivery partners from the outset in design of the tool. Delivery partners could utilise the tool to enhance their existing service, support the growth of their service, or promote the tool to customers who can self-serve. This reduces the risk of under-utilisation of the tool relative to investment and will help increase the reach.
Learnings
Outcomes
The work to date has confirmed that there is a need for technology solutions that could utilise artificial intelligence, machine learning and data analysis to help deliver support to vulnerable consumers. We are coordinating a customer validation exercise to recognise the proposals that customers would like to see developed to inform further development.
A tender is currently in progress to identify the service delivery partner that will design, develop and build the digital tool.
Lessons Learnt
Through a series of interviews and workshops, the service delivery partners shared their insights on the behaviours, needs and perspectives of vulnerable consumers. Challenges that the delivery partners face and how they provide effective support was also discussed and collated.
These activities aimed to identify where technology such as artificial intelligence could perform tasks for front line staff, while identifying the parts of the process where a human touch provides the best outcome. Identifying which step of the process is best performed by which staff member or technology is important to optimising the outcomes of customer satisfaction with effective use of available resource.
The service delivery partners agreed that enabling some consumers to self-serve will free up resources for other consumers that need more support. For example, empowering consumers to find and apply trusted information themselves rather than being reliant on an interaction with a human can alleviate call wait times.
The proposals for the digital tool were shared with the service delivery partners and received positive feedback, validating that it would be valuable for consumers They confirmed that the proposed designs enable to tool to be used by customers to self-serve, or by service delivery partners to support clients during home visits, therefore maximising its value.
