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UTILITY WEEK | 8TH - 14TH MAY 2015 | 27 Customers The relationship with data and com- plaints extends to switching. The quality of data flowing around the industry means that oen suppliers acquire customers with inaccurate or missing meter readings, cus- tomer information or other data attached to their accounts. This lack of accurate cus- tomer data was deemed to be a major issue by smaller suppliers in particular, which are entirely dependent on acquiring customers to grow their customer base. Smaller suppliers explained that incor- rect or incomplete records of new customers causes problems and long delays with the switch, or creates issues when the first bill is issued. All suppliers acknowledged the frus- tration that poor data can and will be inher- ited, despite improvements in an individual company's systems and processes. These problems could also be exacerbated by moves to significantly reduce switch- ing times to three days – and ultimately to 24 hours. The suppliers interviewed were almost unanimous in their opinion of the impact poor quality data and missing infor- mation would have on their ability to meet the new targets, despite efforts across the industry to amend codes to speed up the movement of data. The problems caused by data – inac- curate bills, delays to switching, complex exceptions and an inability to resolve issues at first point of contact – undoubtedly link it to the root causes of customer complaints. However, many believe the issues to be a temporary problem, and that the introduc- tion of smart meters by the end of 2020 will solve much of the issues. The truth is that smart meters may not be the panacea that some in the industry hope them to be. The problems caused by missing or inaccurate customer data could actually be exacerbated by the huge increase in data flowing around the industry, from hundreds of workflows to hundreds of thousands each day. A 2014 report by Elexon and MRA into data quality acknowledged this, and sug- gested that data issues may hinder the smart transition without a major data cleanse. The sheer volume of data could also cause problems: suppliers will receive 96 domestic meter readings a day, compared with one or two a year. One big six supplier admits that its systems already struggle with the bulk data, and the additional mass of smart data will only add to the issue, views echoed by smaller suppliers interviewed for the research. The research makes it clear that data quality is increasingly a business risk, impeding both business performance and customer satisfaction. By addressing data quality, suppliers can address the issues it causes: inaccurate bills, switching delays, meter read issues and sudden bill increases. While work is taking place at an industry level to ameliorate data issues by improving settlement processes and the wider smart programme, this will take time. The funda- mental issue highlighted in the report is the quality and accuracy of data, caused by the complex industry structures and processes. It is unlikely that any new measures to tar- get the data quality issues that prompt com- plaints and dissatisfaction will be introduced any time soon, so suppliers will not be forced to improve these aspects. In the absence of an industry solution, suppliers must cre- ate their own single source of energy data, which reconciles settlement and billing data before it enters their systems, to identify and tackle any inconsistencies and exceptions. As the public face of the industry, suppli- ers will continue to be held responsible for the ongoing service and performance prob- lems caused by data. Suppliers cannot afford to ignore the issue. Rob Stait, director, Ensek TACKLING THE DATA PROBLEM Before investing in new systems or new customer experience initia- tives, there are steps that utilities can take to address data quality issues to improve many of the main drivers of customer dissatisfac- tion and complaints Managing exceptions: Ensure a historical view of events affecting a meter or customer is easily accessible so that trends can be spot- ted, root causes identified and unnecessary work avoided. Improving data: Prioritise errors and exceptions by both customer impact and business performance risk – understanding the age profile of issues will identify those that can be resolved more easily. Metering agents: Ensure that agents working on behalf of sup- pliers are working to the same data quality objectives – processes such as billing and direct debit reviews sit at the end of a long chain, which is only as strong as its weakest link. Transfer of supply: Review the quality of data inherited from previous suppliers when a customer joins to identify exceptions. Meter level data: Most importantly, reconcile industry settlement data with customer billing data at a meter point level rather than at portfolio level. This will offer a true measure of unbilled/never billed/under-billed/re-billed accounts. This provides the strongest platform from which to ensure "shock bills" are not issued, identify discrepancies between the industry and billing view of supplier's portfolios and ensure that financial performance is transparent and clearly understood. The sheer volume of data could also cause problems: suppliers will receive 96 domestic meter readings a day, compared with one or two a year Data: a barrier to business performance Data was identified as the main barrier to operational business performance, above investment, systems and processes, and the skills and attitude of the workforce. Big six Challengers 1. Data (avg 1.8) 2. Systems & processes (avg 2.3) 3. Lack of investment (avg 2.7) 4. Culture & attitude (avg 3.8) 5. People & skills (avg 4.3) 1. Data (avg 1.9) 2. Systems & processes (avg 2.3) 3. Lack of investment (avg 2.7) 4. Culture & attitude (avg 3.7) 5. People & skills (avg 4)