Utility companies' record on serving vulnerable customers remains mixed. Though most Water companies have met or exceeded Ofwats’ targets for Priority Services Register (PSR) coverage, challenges remain in data accuracy and consistent service. Meanwhile, Energy customers face record debt levels, and the poor handling of pre-payment meters hangs over the sector.
Having a good PSR database doesn’t directly translate into knowing which customers fall into vulnerability, nor does it close the gap on serving customers with priority needs, and we need to be mindful of how changing that spectrum of risk factors can be. For example, someone experiencing a power outage today might not be affected, but a change of life circumstance might make an outage in a month’s time a far bigger deal. Having to react accordingly, or keep on top of customer vulnerability in general, is where services stumble.
We know people on the edges need more attention. But those at risk of falling into the ‘vulnerable customer’ category, perhaps for multiple reasons, also need to register on companies’ radar quicker – before it’s too late to effectively intervene.
How do Utilities currently support these ‘edge cases’?
Grants, lower tariffs and payments plans are available, but binary categories like income level can risk people falling through the cracks when they’re just outside of a certain boundary but no less vulnerable.
Customers can register as ‘vulnerable’ for several reasons, but when utility companies aren’t explicit about PSR, grants or low-income tariffs and data isn’t being used in a preventative way, customers may only become aware of their options when there’s already a level of financial turmoil.
The result? Customer needs aren’t met, the cost to serve and resolve goes up and negative sentiments drags down customer reported satisfaction.
So, what if warning signs in data can identify customers at risk of vulnerability?
Applying advanced analytics to existing data can be an effective way to quickly identify trends or flags that shifts reactive to proactive.
For example, Transform UK built an attrition model for Health Education England (HEE) to ensure early intervention for trainee doctors thinking about dropping out.
We created a machine learning classifier to assign a score to every student along chosen points in the training journey where we’ve previously noticed vulnerabilities. This allowed the HEE to better identify where people were struggling and offer support. This included everyone from trainees who were from less affluent areas struggling to get to training centres to older candidates who had parental responsibilities and less time to dedicate to coursework.
In theory, similar models could analyse data held by water and energy suppliers to prompt financial intervention. For example, direct debit reductions over a period might signal customers struggling to pay, triggering preventative measures before they get to a point of non-payment.
In saying that, the cadence of that data is a crucial component. If we could build a large language model to flag when vulnerable customers were at risk, we couldn’t afford a week or two lag in the insights pulling through. We need accurate, real-time data and integrated systems that can prompt intervention before issues arrive; proactivity as opposed to reactivity.
The work we do with a public sector department exemplifies how data sets can be a changemaker for those on the edges.
With consolidated data, we’re able to ensure the right funding gets back to the local authority, and to better support anyone are at risk of vulnerability.
We’re not there yet with unified data in the utilities sector
The department has access to their own data and that shared by agencies, but if utilities don’t have those same relationships in place, how can we have a single customer view of data?
Regulators can in theory act as data brokers or enablers – building on data sharing happening between government departments like the Department for Work and Pensions, HM Revenue and Customs and the Department for Energy Security Net Zero - to better identify financially vulnerable customers.
But then you still need to clarify exactly what sort of data is useful when highlighting at-risk customers and solving the problem of data unification, management and safeguarding what is essentially sensitive data. Lessons gained from similar scenarios in other sectors, such as the HEE example, can be extremely valuable here.
Developing the human lens
Once the data and analytical models are in place, and vulnerable customers and their needs can be better identified, attention needs to turn to how they are served. The value of better visibility will only be realised if it results in services and experiences designed and delivered in a way that meets their needs. At Transform, we’ve found a holistic view the most beneficial in bringing technology, infrastructure, processes and users together.
In our research, working on a high-stakes project for HM Courts and Tribunal Service (HMCTS), we found a large percentage of appellants weren’t engaging. Through deep discovery we looked at the wider context to understand what was making it hard for people to interact with the service.
Compensating for digital inaccessibility by speaking ‘offline’ to charities and local community groups and really listening to what the data was telling us, we were able to contextualise the cracks people were falling into.
We’ve done this on many other projects, including Office of Veteran’s Affairs, Anglian Water, and Rail Delivery Group, allowing us to design services with people that actually served them. Because one-size-fits-all transformation rarely fits everyone.
One thing is certain; change is needed
The future of Utilities customer services and how it intersects with predictive analytics, or even AI-driven tech, might not be crystal clear yet. What is, however, is the opportunity to better serve and focus efforts on prevention rather than the cure.
Transform sees a solution where, like most of our most impactful projects, we bring together the three pillars - good data foundations, intelligent analytics, and human-centered service design - to identify vulnerable customers and intervene before it becomes worst-case scenario.
Our whitepaper on ‘Designing for the edges to benefit the whole’ further explores how we can unite data, AI and design to build comprehensive services where no one falls through the cracks.
To talk about our thinking, end-to-end solutions thinking or utilities challenges further, reach out to talk to Ben Lever, Director of Water and Energy, today.