Water & Wastewater Treatment

WWT June 2017

Water & Wastewater Treatment Magazine

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www.wwtonline.co.uk | WWT | june 2017 | 17 "The right data, at the right time, helps make the right decision." Natalie Jakomis Head of daTa WelsH WaTer Welsh Water is driving and funding a long-term permanent change in mindset and behaviour when it comes to data. We treat data as a corporate asset: it's funded and managed just like all our other assets across the business. "Historically, we've had data challenges from our corporate legacy systems, and we could have been better at getting access to data, extracting that data and generating insight from it in a timely and efficient manner. "So what we've embarked on here is a data strat- egy journey, which we've called WISER - Welsh Water Information Strategy Enterprise Roadmap. "It's all about allowing Welsh Water to better exploit its data assets, so the insight that the data science team and the data teams across the business are able to generate can be turned into actionable behaviour more quickly and more effectively. "We've undertaken workshops to look at which business areas require immediate data governance attention to improve our service: assets, customers and water quality came out as the three prioritised 'data domains'. Within those data domains we are undertaking multiple workstreams: everything from business term definitions to classification standards and data quality key performance indicators. "Each domain has data owners - who are account- able at a very high level for the trustworthiness and safeguarding of the data – and data stewards, who are the 'doers' who are directly involved with it. In the past, members of the data team have spent a lot of time improving the quality of the data, and mapping and aligning data across systems – but that's not where their time is best spent. So as part of WISER, we're also looking at improving that data quality auto- matically, by ensuring the data flows correctly across different systems. "In a nutshell, WISER is about getting the right people involved, at the right time, in the right way, using the right data, to make the right decision, and ultimately leading to the right solution, to earn the trust of our customers every day." • Service reservoirs are large tanks, o en underground, that store treated drinking water ready for distribution to customers through the pipe network. Since drinking water is expected to meet the highest quality standards it is subject to a weekly regulatory testing regime. • The presence of bacteria such as E.coli (right), which may be harmful to human health, or coliforms, which can be an indicator of the conditions for E.coli to develop, leads to a water quality failure. These failures are extremely rare events, but when they occur they can require costly remedial action such as draining the service reservoir and rezoning the network; they can also disrupt service to customers and cause reputational damage. • For this reason, if a water company can predict where a failure might develop based on the analysis of data showing contributory factors, this will prove an advantage because relatively minor interventions may be able to prevent a failure • Welsh Water investigated the association between bateriological non-compliance and several contributory factors including residual disinfection level (free chlorine), heterotrophic plate counts (colony counts), asset condition, rainfall and the distance between the treatment works and the service reservoir. • The predictive model has been used to create a dashboard for Welsh Water's operational staff to easily view the service reservoirs which have the highest risk of failure using a single metric which is colour coded. While more data is available if required, this single point provides a spur to action for time-pressed operational workers to prioritise any remedial actions necessary • The predictive model is an example of how data can be marshalled into actionable intelligence. Welsh Water's Information Strategy Enterprise Roadmap (WISER) is a plan to better exploit the not-for-profit company's data assets and turn them into beneficial action more quickly and effectively. • THE SET UP • WIDE ANGLE The Works: Data

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