Utility Week

UTILITY WEEK | 30TH AUGUST - 5TH SEPTEMBER 2019 | 23 Operations & Assets T here are no technical blockers today to achiev- ing the kinds of outcomes from data exploitation that utilities are now talking about as future scenarios. However, there are psychological blockers and entrenched, top down or "waterfall" approaches that make achieving the necessary transparency and accessibility of data very di• cult. For example, we are working with a large energy company that was struggling, with its current vendor, to get the value from data that it wants. It has a centre of excellence in the IT function for data science, and it will raise exciting use cases which it puts project teams behind. But six months a• er a project launches and with £100,000 spent, they may only just get access to the data they need to act on. They wanted us to create a better technology solution to get that data to them faster and free up IT to work on the use cases. Our proposal to them is simple. We can make data available through any existing interface they have – it doesn't matter who the vendor is. What is key is that we can make data available to everyone, everywhere, in near real time and in a way that has strong governance and approvals. By democratising access to the data and letting the business own the use cases, the value of data will be realised immediately. But that is a big leap of faith for many utilities today. Also, crucially, when companies take this step, they must think carefully about data taxonomy. Too many times I've seen companies invest time and money into bringing data together and working on use cases, and they fall down because there is an argument between two or more stakeholders about the meaning of some small phrase which fundamentally skews their interpre- tation of the data. When this happens, projects end up getting parked while teams work backwards to ‡ nd out where data originally came from and so which interpretation of its meaning is correct. It's a huge waste of time and resource – but it's not a technology problem, it's a lack of thought. All the tooling exists to track the linear sources of data. All the tooling exists to support the necessary workˆ ows and approvals of data. What is so o• en miss- ing is attention to detail in labelling data or a willing- ness to think di‰ erently and openly about how data from one part of the organisation could be used and interpreted by another – or a third party. Democratising access to data realises the value of that data immediately. Opinion Mark Truswell Enterprise sales director UK&I, Talend Brought to you in association with who latched on to the opportunities that could arise from achieving data democracy. Interestingly, while a number of collec- tive bene‡ ts were eyed in terms of e‰ ective and resilient system operation, the discus- sion that generated the most excitement was focused on the opportunity to use data col- laboration to help shi• the dial for public perception of utilities and transform the sec- tor's relationship with customers. Advocates of this view argued that using a clearly communicated open data programme to position utilities as leaders in the ‡ ght against climate change would align them with a "greater good" and help li• the insidi- ous cloud which so many consumers see looming over the sector. Doing this e‰ ectively, they said, would deliver far more value than any pounds and pence ‡ gure that might be forecast from an individual company's commercial exploi- tation of data – and could well create and wider watering hole of commercial opportu- nity and economic upli• . To help unleash this potential and moti- vate less enthusiastic companies, several attendees recommended that utility regu- lators consider incentives to advance the adoption of open data principles and prompt engagement in undertaking the necessary harmonisation of data referencing, as well as the build of a common data catalogue. As one attendee observed a• er the event: "There was such a contrast between those who accepted we must share data and those who clearly had some very entrenched views. If we want the bene‡ ts of data sharing, there will need to be some intervention to mandate the more progressive view." per cent of their time, so it was a real pain point and we knew they had not been able to get support from IT before to ease this, because the sources of data used changed too frequently, meaning the structure of the data also changed." The new architecture, combined with the new business service mentality of the data science function, meant the use case took three weeks to address and the trading team came away with a solution that freed up their time and empowered them to nimbly leverage a broader set of intelligence sources than ever. Once word got out among decision- makers that the data science was now a business resource – rather than IT – sub- missions for further use cases surged. "Within a year we had over 120 data sources connected [to the data lake]," says Griener. "Currently, we have 40 use cases in production, which equates to 1,500 users from within the business." There are also around 400 users from third party organisations, and Uniper has successfully monetised outputs from data use case experiments. The journey has highlighted the value of data science capabilities to the organisa- tion and glamourised the skill set involved. "Everyone wants to be a data scientist now," says Griener. But the shiŠ from data reconciliation and processing to true data science is a big one, and he says it's important to be able to manage expecta- tions around the potential for retraining. The value of data science has also raised questions about the strategic argument for freeing up more IT budget to expand a data science unit.

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