Utility Week asked sector leaders how a more collaborative and cohesive approach to data will be key to managing the risks associated with climate change and the impact on critical infrastructure.
With utilities facing rigorous decarbonisation 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 spotlight firmly on the need for energy and water companies to garner a greater understanding 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 companies are investing actively in advanced data analytics to help mitigate key threats to the resilience of their infrastructure – including extreme weather, water scarcity, rising failure 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 blockers to progress? And how can more cohesive data sharing be achieved?
These were just some of the questions posed during the virtual round table discussion, which convened senior asset strategy and technology leaders from energy and water companies. 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 that it will be impossible to deliver network decarbonisation “without cracking this whole space of data and asset intelligence, and the use of software 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 software 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 decisions 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 decisions across networks.
“It is useful to have evidence based and time sensitive information to support our price control submissions,” commented one executive from a gas company. “We have developed 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 infrastructure, 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 consensus across the debate on the importance of educating the workforce about the value of data and the benefits of the digital transformation, 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 emergence 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 workforce when it comes to the assurance of quality data. “I’ve always been a great believer that if you bring in a new solution or a system, 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 leader from a water company added: “If we’re going to the effort of creating data, we need to make sure the quality is right.”
The right skills are needed to leverage the right data
The debate continued on the importance of ensuring high quality data is efficiently captured, 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 challenges clients typically face when incorporating data into projects. He raised concerns that the vision with which a programme starts is often “disconnected from the quality of data and the data that is available”, which prevents project teams from harnessing the benefits of connected, intelligent assets.
The group also identified constrained skills resources around data engineering and data science as a major blocker for the sector.
According to one participant, acquiring the necessary skillset to undertake asset intelligence will be “one of the biggest challenges that we will all face moving forward”. They added that it is often necessary to recruit externally to bring the requisite data science skills into the business, and that upskilling existing staff can be a time-consuming process.
There was collective acknowledgement in the group that a longer-term strategy to alleviate gaps in knowledge and skills will be required to facilitate an effective data-driven approach to asset management.
Alleviating the risk of cyber attack
While the digital transformation of asset management brings many benefits, it also creates new risks, particularly around cyber threats to the network.
One data expert from an energy network operator explained that their organisation has already made a significant investment in replacing control systems, cultural programmes and improving network security. “A lot of the work we have been doing is looking at actually reducing the amount of cyber interaction with assets. For example, removing controls where they are no longer required and putting in diodes so that you are just transferring data and there is not a two-way network communication,” the participant added.
Another insisted that a fundamental culture shift is needed so that more people within an organisation take personal responsibility for cyber security. “Everybody should feel that cyber security is part of their role, whatever their role is,” they said.
However, one energy director said that while cyber security is an important category of risk, it is important that organisations are not fixated on this issue and blind to all of the other risks that can impact infrastructure assets.
Creating a more cohesive approach to data sharing
Various participants discussed the value of pulling data together into a centralised hub to facilitate better understanding of asset condition across projects.
One water company executive explained that key to the implementation of a clear data strategy is ensuring that there is a collaborative approach to asset management, which ensures that both engineering and data expertise is brought together cohesively.
Summing up, Greg Hanson, VP EMEA and LATAM sales specialists at Informatica, said: “The impact of events like the Covid-19 pandemic has demonstrated the joint opportunity and benefits of data sharing, particularly around obfuscated data.
“There is a huge opportunity for utilities to anonymise data, share it and reap the rewards that increased intelligence could bring.”
Comment
The future of utilities will be data determined
Greg Hanson, VP EMEA and LATAM sales specialists, Informatica
To address the utility sector’s most pressing priorities – decarbonisation, asset health and optimisation, customer experience, regulatory compliance – digital innovation is the common denominator.
And data is the energy source that will power their progress and modernisation: from enabling digital services that make customers’ lives easier and safer, to measuring the company’s socio-environmental performance through meaningful, accurate ESG reporting. Utilities have traditionally defined their asset estate in terms of pipelines, cables, drains and plant but it’s time that data was also considered a strategic component of their infrastructure.
It’s no longer just a matter of democratising business users’ access to data. It’s about getting high quality, trusted, real-time data flowing continuously through the organisation, and applying it in combination with AI and machine learning to optimise and automate operational business processes. Data can help utilities run in a way that’s more predictive, proactive and preventative, and deliver valuable business outcomes.
For each organisation, and the industry as a whole, becoming truly data-driven will demand a cultural shift. What emerged from the group discussion was that it’s not immediately obvious to individuals how their roles fit into the bigger picture of an organisation-wide data strategy.
Several participants told us anecdotally that they had come across instances of bad data, but these ad hoc experiences mask the extent of the problem. By the time the impact of bad data becomes visible, it’s merely the tip of the iceberg and the issue is inevitably much more pervasive and pernicious. As data informs and automates an exponential number of business processes, reliance on flawed data will only accelerate the pace of flawed decisions and actions, with any transformation initiatives potentially doing more harm than good.
There is a clear need for company-wide education and support to improve data literacy and embed the fundamental importance of data quality into the fabric of the business. Utilities should promote the visibility of their data strategy by making it a central tenet of internal and external communications such as their annual reporting, business vision and strategy.
By measuring and publishing their progress towards becoming a data-determined business, utilities can demonstrate they are moving in the right direction and bring all stakeholders along on the journey. The cultural and operational pivot will demand investment in people as well as technology – from data stewards to drive change management on the ground, to chief data, digital and governance officers to lead by example and maintain alignment between the data strategy and key business priorities.