Improving energy productivity helps make industry more competitive. Working at South Humber Bank Power Station, Cofely UK used real-time monitoring and scheme improvements – to make existing energy assets operate far more efficiently. They introduced real time energy intelligence with half hourly billing for steam and power, and provided industrial customers with advice based on their data to optimise their steam power balance and reduce their energy costs by up to 40%. Real time data screens in the control room have helped improve decision making and operational efficiency, and the site has secured further investment for additional CHP capacity. Cofely UK’s efforts won them the Industrial and Commercial Award at last year’s Association for Decentralised Energy Awards.

Another 2015 ADE Award winner was City West Homes, who have taken an innovative approach to joining up data sets to deliver energy bill savings for low income households. The project involved residents of eight tower blocks in Central London, all of whom had electric storage heating in their flats. Technology and creativity combined in the solution. New half-hourly smart meters were installed, enabling customers to identify when electricity prices would be cheapest. Individual consumption is remotely monitored and storage heating top-ups are driven during off-peak periods, so that residents have affordable heat exactly when they need it.

Data can also drive behaviour change, as Camden Council discovered when looking to help residents on a district heating network to reduce their costs. Using data from individual metering, Camden Council were able to adapt their letters to customers to show their gas consumption compared to their neighbours (on average), with a smiley face or sad face to indicate if they were consuming less or more than average. The project saw a reduction in gas consumption of 6%, at a cost of just £6 per tonne of carbon.

Data needs context to become useful information. Saying that Household A spends £500 per year only becomes useful if you know how that compares to Household B, or if you know that £500 is a certain proportion of A’s income.

Data can tell us about the past, but it cannot predict with certainty. It shows us patterns which might be repeated but it doesn’t always predict the shocks. The past is not always an accurate guide to the future.

Big data can tell us a lot about a group of people or buildings, but it might not accurately describe one individual. Data de-personalises. Whether you’re working with an industrial energy customer or a vulnerable householder worried about their bills, it’s important to look beyond the numbers.

The roll-out of smart meters to homes and businesses across the country, and the introduction of individual heat metering to district heating schemes, mean that we will be awash with energy data. That data can help us to unlock real savings on energy bills, reductions in carbon emissions and the transformation of our energy system, so long as we use it wisely. To borrow from Peter Parker’s Uncle Ben: with great data comes great responsibility.