Utility Week

28 | MARCH 2022 | UTILITY WEEK Data analytics Roundtable Asset intelligence is key Utility Week heard from sector leaders that a collaborative and cohesive approach to data is essential to manage the risks of climate change and its impact on critical infrastructure. W ith utilities facing rigorous decar- bonisation requirements, there are fresh demands on the way asset strategy, management and investment is undertaken across the sector. The journey to net zero has cast the spot- light firmly on the need for energy and water companies to garner a greater understand- ing of their asset base and ensure critical infrastructure is resilient to the impacts of a changing climate. According to recent industry research conducted by Utility Week, around 90% of energy network operators and water compa- nies are investing actively in advanced data analytics to help mitigate key threats to the resilience of their infrastructure – including extreme weather, water scarcity, rising fail- ure rates for ageing assets, and demand-side engagement in energy flexibility. So in a changing world that is shaping a new need for better asset intelligence, what approach are utilities taking to leverage new technologies to meet these requirements? What are the primary concerns and block- ers to progress? And how can more cohesive data sharing be achieved? These were just some of the questions posed at a virtual roundtable discussion that convened senior asset strategy and technol- ogy leaders from energy and water compa- nies. The event was hosted in association with Informatica and Cognizant. Here we highlight some of the key talking points. Calculating current and future carbon costs There was collective agreement among participants that the sector has reached a "watershed moment" in terms of net zero and the role that asset intelligence must play to help decarbonise utility networks. One senior technology leader at a power company said it will be impossible to deliver network decarbonisation "without cracking this whole space of data and asset intelli- gence, and the use of so‰ware and artificial intelligence [AI] in an engineering sphere". The participant described the adoption of new technologies as "a real game-changer for utilities" and added: "Our focus needs to change from engineering and assets … to a very strong data focus and a real awareness, understanding and want for so‰ware and AI to play a very significant role here." Another participant agreed that there is a "sea change in terms of attitudes" to asset intelligence because the need to cut carbon is driving a fresh mindset across the sector. The group agreed that there is increased focus on the impact that asset management decisions can have in terms of economic and carbon cost, both now and in the future. "Having a really good understanding of your asset allows you to make those deci- sions about whether to replace it, or perhaps it can be refurbished or the life of the asset can be prolonged by how it is managed, so that making the costly decision to replace it is a last resort," the participant added. The importance of informed investment decisions Growing pressure from energy and water regulators is driving utilities to deliver more for less. As budgets are stretched, utilities must make increasingly complex decisions on where investment should be made. The discussion continued with a focus on the ways in which digital tools are providing increased understanding of asset health and helping to support capital investment deci- sions across networks. "It is useful to have evidence-based and time-sensitive information to support our price control submissions," said one execu- tive from a gas company. "We have devel- oped a lot of tools to enable our colleagues in asset investment to present evidence to the regulator on when is the best time to replace an asset or what are the other options." Another agreed that asset intelligence does not just play a crucial role in providing greater insight into the condition of infra- structure, but it also helps utilities to justify costs to the regulator while supporting clear strategies for future asset investment. Defining ownership and tackling cultural barriers Establishing a clear strategy and ownership of data processes was discussed as a critical factor for success. There was general con- sensus across the debate on the importance of educating the workforce about the value of data and the benefits of the digital trans- formation, particularly for field operatives. Most agreed that while their business has started this journey, there is a long way to go. "We've seen in other industries the emer- gence of roles like chief data officers, which helps to support that data culture, but there is still work to do here. We really need to define that ownership of data," said one participant. A senior figure from a water company admitted that the biggest issue facing their business is the cultural challenge associated with getting buy-in from the frontline work- force when it comes to the assurance of qual- ity data. "I've always been a great believer that if you bring in a new solution or a sys- tem, it should make it easier for the people who are the end users. It should be to their benefit, because otherwise they will simply try to find workarounds to stop doing it." Another senior water participant added: "If we're going to the effort of creating data, we need to make sure the quality is right." The right skills to leverage the right data The debate continued on the importance of ensuring high quality data is efficiently cap- tured, stored and managed. While there was agreement that this is vital to improving risk management and decision making across networks, there was an acknowledgement that this is not always delivered in practice. Viewed through the prism of capital asset programmes, Arvind Pal Singh, head of industry consulting, Europe – products and resources at Cognizant, outlined the chal- lenges clients typically face when incorpo- rating data into projects. He raised concerns that the vision with which a programme starts is o‰en "disconnected from the quality of data and the data that is available", which

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