Case study
Sophisticated data models help Scottish Water understand domestic water consumption
Summary
Scottish Water looks after Scotland’s most precious natural resource. From source to tap, they keep customers supplied with world class water. The public water and waste water organisation is responsible for providing water and wastewater services to 2.56 million household customers and 152,806 business premises. Sustainability is a major focus. Scottish Water’s strategic plan supports Scotland’s ambitions for renewable energy generation and carbon reduction.
Company size
1,000 – 5,000
Industry
Utilities
Products used
Challenge
Scottish Water has been working with CACI for over 10 years to deliver accurate models that help predict and review household water consumption.
Understanding water use
Martin Walton, Asset Planner at Scottish Water explains the challenge: “There are hardly any domestic water meters in Scotland. So, we have had to find other ways to stratify our customer base. Using Acorn data, we have built and refined models over the years that give us a clear view of how water is being used. We need this information to help us reduce water consumption by monitoring and controlling leakage, testing and maintaining network assets and influencing consumer behaviour.”
Solution
Acorn data is often associated with marketing, product development, service planning and optimisation. But for Scottish Water, it’s the foundation of a sophisticated model that determines expected usage in locations across Scotland. The insight helps operations and engineering teams to prioritise their activities and pinpoint key areas for investigation.
Scott Young, Leakage Delivery Team Leader at Scottish Water, describes the approach: “In terms of water supply, Scotland is divided into over 3,000 areas, each with a district meter. We inform supply and demand analysis within these areas using our Acorn model. We compare district meter flows to those within the Acorn model to see whether actual water usage is similar to the projected household demand for that area. When there’s a difference, we can investigate whether this is because of unrecorded usage, network anomalies or leakage.”
Martin Walton adds: “The modelled per household consumption dataset has proved to be a very accurate predictor of consumption for the domestic properties we supply.”
Results
Scott Young says: “With the Acorn data, we’ve been able to break down demand by area to understand the opportunity for leakage reduction. Using big data in the digital space is quite a radical change from the traditional mainstream approach to leakage detection. Now, we can identify areas of concern with a high degree of accuracy, even in areas with plastic pipes, where traditional soundings to find leakage are less effective.
“We look at the typical usage profile based on zone control groups that we measure and sample from. We build out models for every area using detailed data from Acorn. This combined approach produces a very accurate flow pattern and a strong benchmark comparator. We refine the model further by taking into account factors that influence peaks and troughs or that could be causing leakage.
“The data modelling also helps us to spot issues with valves at the district boundary. When anomalies appear in area flow measurements compared to the model, we can see where a district is breached and water is leaving. We confirm this by checking data relating to adjacent districts, where that water may be going. These are priority issues to fix so it’s really valuable to identify them quickly.
“When I send a team out on the ground to locate and fix a problem identified via the Acorn data model, we have a very high degree of confidence that we’ll find it where we predicted. That means we can detect and stop leaks more quickly and efficiently.”
