Whereas previously the focus was mainly on enhancing the customer experience, the span of influence for digital transformation is uncovering new insights to drive operations more effectively and offer a much broader value chain. The possibilities extend to asset optimisation and management, energy consumption, field force optimisation, and revenue and debt management.
It is insights gained from improving network operations and analysing usage that should be combined with customer data to deepen customer engagement. For example, British Gas is using an insight rich customer portal providing its users with the ability to view a personalised breakdown (daily, weekly, monthly and annual) of their energy use. Likely spend is broken down into categories including hot water, heating, lighting and appliances, and comparisons with similar homes in the area are also provided. All those insights can be used by customers to make savings and British Gas is able to deliver personalised offers to their customers.
However, at present, such initiatives are the exception rather than the rule. According to Capgemini’s Big Data Black Out report, only 20 per cent of global utility companies have used advanced data analytics tools and techniques to drive business change despite over 75 per cent of companies stating that the use of such approaches was increasingly crucial for their future success. Insight-driven transformation can bring immediate benefits in many areas, but in order for businesses to help themselves and customers, utilities must seek to exploit the vast amount of data they hold.
A problem-solving approach to utilities operations
Insight-driven approaches have the potential to transform a huge range of utility companies’ operational processes.
The water industry, for example, faces significant challenges posed by an ageing infrastructure and increasing regulatory pressure. The integration of data aggregated from sensors, SCADA and asset management systems, blended with external data sources can enable the development of rich insights and advanced visibility of network leaks. These insights can be used to both accurately predict when and where leaks will occur and help find them quickly. Use of this data will limit wasted staff time by preventing unnecessary trips to remote locations, and allow correct selection of materials and excavation equipment. This will enable providers to deliver a much more advanced level of situation awareness and decision making, resulting in greater efficiency, fewer fines, and a reduced overall cost for the consumer.
Another challenge across all UK utilities is the growing levels of customer debt. According to Ofwat, customer debts in the UK water industry have increased from £1.9 billion in 2012 to £2.2 billion in 2014. Energy and water companies could make much better use of predictive analytics technologies to reduce these levels of debt. With their help, it is possible to segment debtors based on their demographics, value of debt or past payment history and arrive at a propensity to pay score. Based on their propensity to pay, companies can roll out various interventions.
Meeting the expectations of a digital age
This advanced use of data analysis will be necessary over the next four years as we see the continued installation of 53 million smart meters in 30 million homes and businesses – a move mandated by the Department of Energy and Climate Change. While C3 Energy has suggested the use of advanced analytics could deliver huge operational benefits, the sheer volume of data from smart meters is forcing utilities to rethink how they manage and exploit this torrent of data.
Utilities have historically struggled with the accuracy of their customer and billing data, and the prospect of mass smart metering could present a considerable challenge. Smart meters may take readings every 30 minutes, meaning a highly scalable analytics platform is therefore essential to capture and derive insights from this consumption data. Doing so will enable providers to forecast usage, help customers optimise their usage and improve performance in energy trading markets.
Similarly, Eon has rebuilt its customer engagement using digital technologies to compete more effectively in the retail market. Thanks to big data and analytics, Eon has been able to provide personalised advice and products to help customers control energy use and reduce their bills. Likewise, EDF Energy has used analytics to reduce customer churn, accruing potential savings of more than £30 million per year.
Overcoming the obstacles to business efficiency
The delivery of insight transformation is not without its challenges though – whether it is organisational barriers, cultural barriers, regulatory barriers or IT challenges. Utilities have a significant opportunity to re-invent and improve the efficiency of their businesses using insight-driven transformation across the entire value chain. Challenges associated with this approach may make it appear daunting, but the benefits are substantial and have already been demonstrated by other insight savvy sectors.
We are moving away from the world of process-driven transformation to the world where the next level of business transformation will be insight-driven and data-enabled. The potential gains for utilities are substantial. We have barely scratched the surface of what is possible.