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DataIQ Awards 2019 winner – Breakthrough with data: EDF Energy, smart metering supply and demand optimisation

DataIQ Awards 2019 winner - Breakthrough with data: EDF Energy

UK energy suppliers have been mandated to install some 53 million smart meters by the end of 2020. For EDF Energy, this programme is second only to building a new nuclear power station at Hinkley Point C in terms of its importance and complexity. By using data-driven insight and moving to an operationally-led approach, it has been able to create a robust platform for tactical recruitment and strategic decisions.

At the heart of the success of the roll-out is the need to balance the demand for appointments with the supply of installation resources, represented by 1,000 skilled engineers nationwide. Starting in January 2018, the analytics team in the supply and demand function focused on two objectives: optimising field resourcing across three workforces nationwide (“right size”); and optimising the rational placement of resources to react with agility to demand (“right place”).

Optimising the size of the installation resource has financial implications in the scale of millions of pounds, yet needs to retain flexibility and avoid shortfalls which would be viewed negatively by the regulator. By using data-driven insight and modelling, senior leadership has been able to set an appropriate strategy. This has involved analysing the customer portfolio, modelling conversion rate and forecasting resource. The same data set is also used to define the right place for resources, but with a tactical perspective to optimise net smart meter installations.

Creating trust in this data-driven insight among operational functions has been critical to the success of the programme, repaying the time spent building their understanding. As a result, EDF Energy met the very challenging regulatory installation target in 2018, all the while achieving substantial cost reductions and avoiding financial penalties.

DataIQ Awards 2019
Year: 2019
Category: Breakthrough with Data

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