The UK’s water industry has a vision for a data-led future. Water utilities are already starting to use data in more intelligent ways to speed up and personalise their services. In the context of supply shortages and price pressures coming from the likes of PR19, there is now an additional focus on using data to address the sector’s environmental impact.
In particular, industry frontrunners are exploring the use of data analytics to detect and predict leaks within the network before they burst or become visible, allowing preventative measures to take place to minimise wastage. There are many areas where these capabilities are appealing: smart monitoring of reservoir fill and usage to avoid wastage from overflow; sewerage control to prevent flooding and bursting; as well as the monitoring of clean water pipes to avert wastage of freshly treated water.The UK’s water industry has a vision for a data-led future. Water utilities are already starting to use data in more intelligent ways to speed up and personalise their services. In the context of supply shortages and price pressures coming from the likes of PR19, there is now an additional focus on using data to address the sector’s environmental impact.
If data analytics can achieve so much, why is it yet to be deployed across the board? Up until now, the charge has largely been led by idealistic chief executives, and while their vision is great in theory, implementation is proving a little more complicated.
The reality is, many water companies don’t yet have the right data systems and processes in place to extract meaningful predictions, and data quality, security, integrity and access are particularly challenging to ensure. Coupled with a lack of experience in the complex area of data analytics, some water companies are scratching their heads about where to start.
A lot of this comes down to the uniqueness of the industry. Digitalising water is different from, say, media, finance, or the service sector, because we are dealing with a lot of legacy infrastructure. A complicated control network has grown across the water supply chain over the years, and many departments have been leading their own independent data projects. The data exists, but it is distributed across multiple, often disconnected, systems with limited visibility and data integrity.
A proactive and preventative approach requires a comprehensive data picture of what is happening across the entire network, from water extraction right through to sludge disposal. That means abolishing data silos and stitching sub-systems together.
The first step is conducting an exhaustive audit to determine where the data actually is. The second is ensuring these systems are connected and speaking to each other. This could involve upgrading old infrastructure – for example the ageing SCADA systems littered throughout the water industry – and replacing it with modern, integrated platforms.
From there, the next step is pinpointing what data is actually needed – and where the gaps are. This needs to be driven by the business reporting requirements – in other words, the information needed to efficiently manage the network and report within the regulatory regime. Even the most recently created report will not necessarily reflect the informational needs of today or tomorrow, so going back to the basic requirements is key.
At this point many companies realise the data available within their own four walls is not enough to understand the wider causes of environmental impact, for example weather patterns or demand fluctuations. This means investing in third party data to build a picture that also encompasses the outside factors impacting their networks.
The final step is assessing who needs the data, and what they should do with it. This is essential to developing a system capable of channelling information where it needs to go, and presenting it in a way that transforms data into tangible predictions or recommendations. Typically this takes the form of dashboards or mobile-friendly apps, but it really depends on the unique informational needs of the individual company.
Those who succeed in using data to shift towards a more proactive form of water management will find the benefits extend far beyond the mitigation of environmental impact.