A shift from traditional provider/consumer relationship to one of engaged citizen/collaborator would mean we could share not only the responsibility for addressing challenges but also the resulting benefits in the form of lower bills, supply security and environmental quality.
But how can we harness this mindset change and translate it into how companies and citizens act?
The behavioural science and data sweet spot
Effective solutions in this area lie at the intersection of behavioural design – the creation of experiences or tools that help to nudge or directly change peoples’ behaviours by providing targeted information, guidance and agency – and the data science that surfaces the relevant insights, personalisation and triggers that give these tools the intelligence and power to create value and promote use.
But we’re not underestimating the challenge of extracting value from disparate data sets of variable quality to create things that people care about.
Data sources are growing thanks to the roll out of smart meters, IoT network sensors and connected home appliance, however, the data sets still tend to sit in silos and can be hard to integrate so the real value is often unrealised. But here’s where the old adage of progress over perfection comes into play - the opportunity is there, we just need to start exploring the possibilities.
Our experience
And that’s exactly what we did at a recent hackathon during Northumbrian Water's Annual Innovation Festival. Like most hackathons, it’s a great way to set problem/opportunity areas – such as supporting customers to monitor and reduce usage – and bring together sector experts, data engineers and UX designers, setting them loose on real data sets to see what they come up with.
The hack was specifically focused on how can we collect and use data to make people aware of how much water, energy and associated carbon they are using in everyday life?
Value came from multi-disciplinary teams collaborating – with designers and UXers looking at customer needs and designing experiences that would engage and appeal while the back-end teams looked at data sources, combining smart meter data with 3rd party insights and approaches for visualisation.
Learning and opportunities
Northumbrian Water took away a number of consumer facing ideas and there was a recognition that in most instances, value comes from making solutions specific to the circumstances and needs of consumers whilst at the same time aiming to reduce any friction.
If you couple good design that makes things easy and engaging with quality data and insights you’ll see positive results. But we’ve already talked about data and how gaps in availability and frequency are a limitation to change.
This is where machine learning approaches could be applied helping to fill the data gaps with ever-more-accurate assumptions. Training models on patterns of activities and behaviours to learn about and best predict things like sources of usage, events leading up to demand for water and prompts that may reduce demand.
So what can water companies do to achieve this?
Well, aside from a load of skilled data scientists, if the utilities sector as a whole opened up data where it was feasible to do so, learning models could be pointed at the best possible range of data and then by applying clever design, this could be put in the hands of business or consumers in the right way. All part of a trial, test and learn approach.
It’s not a quick fix we know, but we could all see some quick wins along the way. As consumers and business leaders.
If you want to know more about how machine learning, AI and design can help solve your business challenges in utilities, or elsewhere, we’d love to hear from you.
