Business
Severn Trent Water Case Study
Severn Trent Water Case Study.
About this update from Gb Group Plc
[{"type":"text","content":"\n RNS Number : 6744F GB Group PLC 18 January 2010 \n \nCASE STUDY: Severn Trent Water turns on identity management to achieve billing accuracy for 3.7m households\n~ GB Group (GB) hits meter reading metrics in just six months ~\n\nLONDON - 18 January 2010 - In the interim announcement on 25th November 2009, GB announced that it had recently won a seven year contract with the world's fourth largest water company to supply identity-based address management services. This long term strategic deal had been built up over the course of the previous year during which GB had undertaken a number of assignments with Severn Trent Water (STW), the success of which led to the strategic relationship. A case study which describes one of these assignments, and which has now been approved by STW, is set out below. This case study demonstrates GB's strategy of establishing a footholding and growing major accounts.\nSTW has achieved its meter reading accuracy target a mere six months after implementing identity management services from GB. STW is now well on the way to achieving DG8 (the meter reading regulation set by OFWAT) and ensuring billing accuracy of 99.85% for its metered customers, avoiding under or overpaid bills and tying in to STW's strategic targets to improve service in this area.\nWith around 1.2 million consumer water meters across a region covering approximately 21,000 square kilometres, STW faced a challenge: reading its customers' meters in a more efficient manner. The company's target is to read all of its meters every year. Regular meter reading ensures that water bills are as accurate as possible and is a fundamental part of customer service at STW.\nDuring the six-month test phase, GB had to optimise a range of challenging meter reading routes, selected by STW, matching individuals' identities to addresses and ordering the route for visiting those addresses to maximise efficiency. Experts at GB matched the data against the Royal Mail's Postcode Address File (PAF®), added geo-codes for geographical locations and then grouped the records together in the most efficient way to find the optimal route between the different points. Halving the number of unsequenced reads was a key goal. Through cont...