Utility Week

UTILITY Week 14th October 2016

Utility Week - authoritative, impartial and essential reading for senior people within utilities, regulators and government

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26 | 14TH - 20TH OCTOBER 2016 | UTILITY WEEK Customers Market view D igital technologies provide immense opportunities for utility companies to offer new services and to change the way customers buy their products. Whereas previously the focus was mainly on enhanc- ing the customer experience, the span of influence for digital transformation is uncov- ering new insights to drive operations more effectively and offer a much broader value chain. The possibilities extend to asset opti- misation and management, energy con- sumption, field force optimisation, and revenue and debt management. It is insights gained from improving net- work operations and analysing usage that should be combined with customer data to deepen customer engagement. For exam- ple, British Gas is using an insight-rich cus- tomer 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, heat- ing, lighting and appliances, and compari- sons 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. Accord- ing 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 cru- cial 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. 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 accu- rately predict when and where leaks will occur and help find them quickly. Use of this data will limit wasted staff time by prevent- ing unnecessary trips to remote locations, and allow correct selection of materials and excavation equipment. This will enable pro- viders 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 utili- ties is the growing levels of customer debt. According to Ofwat, customer debt in the UK water industry 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 to reduce these levels of debt. With their help, it is possible to seg- ment 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. 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. The sheer volume of data from smart meters is forcing utilities to rethink how they man- age 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 meter- ing could present a considerable challenge. Smart meters may take readings every 30 minutes, meaning a highly scalable analyt- ics platform is 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. Similarly, Eon has rebuilt its customer engagement using digital technologies to compete more effectively in the retail mar- ket. 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 cus- tomer churn, accruing potential savings of more than £30 million per year. The delivery of insight transformation is not without its challenges, though, whether it is organisational barriers, cultural bar- riers, regulatory barriers or IT challenges. Utilities have a significant opportunity to reinvent and improve the efficiency of their businesses using insight-driven transfor- mation across the entire value chain. Chal- lenges associated with this approach may make it appear daunting, but the benefits are substantial. We are moving away from the world of process-driven transformation to the world where the next level of business transforma- tion will be insight-driven and data-enabled. The potential gains for utilities are large. Mark Powell, UK head of insights and data, Capgemini Digital insights Good quality data and advanced analytics can be exploited by utilities to provide insights into all aspects of their businesses. The potential gains are huge, says Mark Powell. Challenges are identified based on responses of surveyed utility executives. The figure represents the percentage of respondents who voted for the challenge as being the most important impediment to analytics implementation. Source: Capgemini Big & Fast Data: The Rise of Insight-Driven Business, 2015 TOP CHALLENGES FOR UTILITIES IN IMPLEMENTING BIG DATA ANALYTICS High data storage and manipulation costs Data complexity Data access issues Data privacy issues Skills shortage Lack of management support 23% 18% 13% 13% 8% 26% Data management }

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