Data Challenges facing the
Energy and Renewables industry

There’s a lot of talk about the energy and renewables sector’s “data driven future” – but is the industry really ready for it? 

It’s been a turbulent couple of years for the industry, and as the sector stabilizes and looks to new ways of working, it needs data to fuel its goals and ensure that it can comply with both changing compliance requirements and consumer expectations, as we cover in our guide: Power up with MDM: Fuel your data strategy with high-quality master data.

The good news is that the sector is generating data faster and with greater frequency than it ever has before. The not-so-good news is that this accumulation of data is a challenge in and of itself: yes, energy and renewables firms need data, but quantity does not equal quality. They need to know that the data they have is ready for the tasks they need it for – and there are several obstacles that are standing in their way. 

Here, we look at six of the highest-priority data challenges facing the sector, and look at the one solution that could help to tackle all of them. 

Increased M&A activity

Over the last two years, 31 energy suppliers have collapsed or gone into administration in the UK, with 17 ailing energy firms purchased by competitors in 2021 alone. Yet crisis-driven M&A is not the only way that the energy and renewables market is changing. The acceleration in demand for renewable energy is also pushing major players in the industry to explore their investments and future M&A activity, to help meet environmental targets and diversify their energy sources. 

Whatever the reason for an M&A deal, it always brings with it issues around integration, particularly when it comes to data. It’s bringing together two businesses, with two wildly different data systems, not to mention cultures and ways of working. While a lot of effort is often put into bringing data quality standards up to scratch for the purposes of pre-deal reporting, there’s often little to no planning of how that data quality will be maintained or integrated. The mistake that many companies make is to leave the problem post-merger and hope that it will be gradually fixed alongside other initiatives, but the truth is that the data silos in creates will only worsen over time, becoming more entrenched both culturally and technologically.

For energy and renewables firms either considering, in the process of or having recently closed an M&A agreement, data integration has to be a priority if they want to navigate the challenging times ahead. Data is a must-have tool for all of the energy sector’s goals: all relevant data has to be available and ready to use. 

Sharp increase in users

Thanks to the turbulence of the last two years, surviving energy companies have found themselves with a sudden influx of users. While some have been acquired through more traditional M&A activity, as mentioned above, others have been allocated as a result of Ofgem’s “Supplier of Last Resort” process, which finds replacement energy suppliers for displaced customers. 

This creates its own unique challenges, with the new supplier receiving a vast amount of consumer data in a short space of time – data that is often in a different format, with different categorization and definitions. Due to the sudden nature of this change, it’s even more difficult to carry out data quality diligence. This can become a significant data silo, kept separate from the rest of the organization's data and, consequentially, diluting insights and impacting data-driven efficiency.

Multiple data sources

It’s important to recognize that data silos aren’t only created by M&A or customer acquisition through Ofgem. Data silos can occur in any business, for any number of reasons – from different departments managing independent systems or databases, to individuals keeping data on spreadsheets or offline systems on laptops and PCs. Remote working during Covid lockdowns has exacerbated these silos, with a lack of organizational appreciation and understanding of data driving reckless behaviour that, at best, prevents data from being used but, at worst, can result in non-compliance. With the energy and renewables sector likely to face more stringent data compliance in the near future, these silos – and the behaviour that enables them – has to be eradicated. 

Data overload and ‘real-time’ recording

Last year, over 2.5 million smart meters were installed in UK, across domestic and commercial properties – bringing the total number of smart meters installed in Britain since 2012 to almost 28.6 million. Each smart meter receives electricity data every 10 seconds, and gas data every 30 minutes. Additionally, by 2025 half hourly readings will be the default for all meters, smart or otherwise – a significant step up from the current daily reading minimum. 

That’s a lot of data to process – and it’s not just how it’s processed, but when. What’s the point in collating data at regular intervals if you continue to measure and react to that data with the same low frequency as before? These vast volumes of near real-time data have to be available and accessible before energy and renewables firms can implement next-generation systems like advanced analytics, data streaming processes and automations. 

Policy uncertainty and reporting requests

That difficult period between 2012 and 2022 has caused increased scrutiny of the sector by governments and regulators, as they seek to find ways to prevent further destabilization in future – particularly, how they can spot when energy companies are facing financial difficulties. Ofgem has stated that it will be looking at how it can most effectively use data and digitalization to support energy companies, which could mean that further data reporting will be needed from those firms in the near future. Then there’s the rising prevalence of ESG, from both a financial and investment angle and a regulatory perspective. 

For the energy sector to be ready for whatever policies or reporting requirements arise, they need to take a data-first approach, looking at the quality and availability of all of their data. This will help prevent a scramble for specific information if new policies are introduced. 

Decentralization of energy sources  

The way that we produce energy in the UK is changing. The increase in renewable sources is gradually decentralizing energy production, with a combination of both commercial sources – such as wind farms – and consumer-led energy production – like personal solar panels – shifting the market away from a centralized grid. Again, this is generating higher volumes of data and multiple data sources, both across the industry and within individual companies. If companies want to be able to use this data to improve efficiency, make better financial decisions and generally act smarter and faster in the years ahead, they need to be ready to embrace ever-increasing volumes of data sustainably, with a focus on availability and quality. 

Tackling data management as a first step

While a lot of the industry is looking ahead to digitalization and the opportunities it brings, some are missing the basics that form the foundation of any data-driven initiative: access to good quality, reliable data, whenever and wherever its needed. 

If businesses across the energy and renewables sector want to tackle any single one of the issues listed above, they are going to need to introduce robust data management measures to ensure that their data remains available and accurate. The answer is Master Data Management (MDM). 

An effective MDM solution, like those delivered with Agile in partnership with MDM technology providers, includes the implementation of MDM toolsets with wraparound MDM initiatives like Data Quality, Data Governance and Integration. The result is a platform that makes good quality data accessible and available, and the foundations of a data culture that can use and manage that data effectively. 

You can read more about how energy and renewables business can utilize MDM to meet both commercial and compliance goals in our guide, Power up with MDM: Fuel your data strategy with high-quality master data.