Published by Jessica Weisman-Pitts
Posted on October 11, 2022
6 min readLast updated: February 3, 2026
Digitalisation is bolstering productivity and efficiencies throughout the industrial world, not least in the Utilities sector. Following the introduction of high-speed, reliable connectivity, traditional manual data collection methods are now almost obsolete.
Digitalisation is bolstering productivity and efficiencies throughout the industrial world, not least in the Utilities sector. Following the introduction of high-speed, reliable connectivity, traditional manual data collection methods are now almost obsolete.
Alastair MacLeod, CEO and founder of remote connectivity provider, Ground Control, examines how new methods of data monitoring and collection have culminated in vast increases in data volume, presenting suppliers with an unrivalled opportunity to streamline and improve business performance.
Data is empowering providers to deliver better, more consistent utility supply to consumers, despite ever increasing demand. However, there’s still a dilemma here.
Connectivity has been identified as a common barrier to the full exploitation of the Internet of Things (IoT). Inmarsat’s 2021 report states that 58% of electrical Utility providers are unable to implement IoT projects due to availability of reliable connectivity in the areas required.
Ultimately the long journey of data has resulted in less reliance on manual collection and more on automation. Dependable connectivity has enabled machine-to-machine (M2M) technology to deliver big data, providing the means to understand consumer trends and effectively predict future utility usage.
Indeed, companies failing to incorporate a robust data strategy into their business plan are likely to find themselves at a major competitive disadvantage in the very near future, if not already. Our recent paper, “Data’s journey in shaping digital transformation in Utilities, and what it all means”, examined this very dilemma, and how far Utilities companies have come in terms of collecting and analysing data to streamline their operations.
The beginning of data collection in Utilities
The Utilities sector has always made a significant effort to collect utility data, most frequently capturing pole data and meter readings. But pole data collection has its limitations. Many poles are in remote areas and some companies have such a high number (some exceed one million), retrieval ties up valuable resource making it neither feasible nor financially viable, to gain enough insight into grid activity, nor gain this insight fast enough, in order to make smarter business decisions.
Likewise, the reading of consumers’ meters has seen a similar journey moving from manual to smart, connecting wirelessly to report on usage in real-time – empowering users with more informed utility control.
However, the exploitation of big data is only possible due to innovations in connectivity. The development of computers, smart phones, the internet, and IoT have all provided a means to access more data than ever before.
Today, M2M technology and IoT are such integral parts of our everyday lives that they often go unnoticed. For Utilities, they present an excellent opportunity to capitalise on a vast array of information that, when turned into actionable insights, revolutionises customer services, streamlines operations, and increases productivity and safety.
How data is driving digital transformation in the Utility sector
Electrical grids and gas distribution systems make up critical infrastructure. Outages and supply interruptions result in huge financial burden and penalties for the supplier, and severe (often prolonged) disruption for consumers. With increasing pressure for renewable energy and from customers seeking to generate their own power, digital transformation could be the catalyst Utilities need to bolster consumer interest.
The UK Department of Energy and Climate Change has invested heavily into its smart grid vision and route map – building a smart grid across the UK. Smart meters and sensors along grid lines transmit usage data to providers, enabling them to match supply with demand. Likewise, smart appliances can alter the times of electricity usage, avoiding peak times when pressure on the grid is high, resulting in lower costs and reduced risk of outages.
It is these detailed insights into customer habits that does and will allow Utilities to achieve maximum efficiency and customer satisfaction. And at a time of expensive grid updates, usage trends could prove invaluable to planning and prioritising engineering work, and the most efficient means of distributing utility supply.
At the end of 2021, there were 27.8 million smart and advanced meters in homes and small businesses across the UK. But reports show 8% of the UK’s landmass remains uncovered by mobile networks – so connectivity considerations are essential.
Furthermore, real-time flow of electricity through the grid is monitored, recorded and time-stamped using GPS by phasor measurement units (PMUs). Combined with smart meter data, such timely information provides an opportunity for power suppliers to identify necessary maintenance before it culminates in a full-scale power outage. When outages do occur, knowing the exact location and nature of the issue without having to wait for technicians to manually investigate, increases worker safety and significantly reduces the time to restoration.
Extreme weather also heavily contributes to grid vulnerability. For instance, when a lightning strike caused blackouts in 2019, leaving more than one million UK customers without electricity with two power plants disconnected from the grid, the two energy firms in question were fined in excess of £10.5 million. As extreme climate events become more frequent, the smart grid can identify areas of highest risk, enabling opportunity to effectively plan to minimise disruption.
Humans are fallible
The full potential of data can only be realised once it has been processed and applied to decision-making. But humans are fallible, and our brains are not equipped to deal with the volumes of data transmitted through the smart grid.
Devices are already communicating with one another; the next step is learning to make decisions based on the data they collect. Automation entails minimal human input and is therefore less fallible, more accurate and much faster than human-led processes. Possible applications include automatic dispatch of repair teams to outages, automatic scaling of supply during demand variations, and generation of utility bills based on data from individual customer smart meters.
Coming back to Inmarsat’s 2021 report, in that 58% of providers don’t have the connectivity to implement IoT projects, the challenge is clear – that without a connectivity ecosystem, to underpin all this advancing technology, we are still in the dark when it comes to data insight. Afterall, data gaps and delays can create a wildly inaccurate picture.
And that’s where satellite comes in. It can be used as a primary connectivity option, or as a failover in the event of terrestrial network interruption, creating a more resilient, future-proof grid.
Connectivity is becoming more reliable than ever, and myriad options are available to create a bespoke network to support big data collection and M2M interactions across entire Utilities networks. But despite availability, optimal connectivity solutions are not always implemented.
There still exists some scepticism around the complete value of data; and analysing it has to some extent, become a box-ticking exercise. So, arguably, further education is needed in the sector to optimise connectivity and ensure the full value of IoT and digitalisation projects are realised. With the vast and disparate nature of Utilities and its infrastructure, connectivity will be the key to unlocking the power of big data in this sector.
Digital transformation refers to the integration of digital technology into all areas of a business, fundamentally changing how it operates and delivers value to customers.
Data analytics is the process of examining data sets to draw conclusions about the information they contain, often used to enhance decision-making and improve business outcomes.
Automation is the use of technology to perform tasks without human intervention, often to increase efficiency, reduce errors, and lower operational costs.
The Internet of Things (IoT) refers to the network of interconnected devices that communicate and exchange data with each other, enhancing automation and data collection.
Renewable energy is energy derived from natural sources that are replenished at a faster rate than they are consumed, such as solar, wind, and hydroelectric power.
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