In an unstoppable scenario of diminishing margins, it has become an imperative for electric and gas utilities to take advantage of any capability that allows them to fight all potential “revenue leakage” in their networks. Non-technical Losses (NTLs, those arising for fraud, device malfunctions, and administrative errors) are a growing problem, estimated, by some sources, as 3,700 million euros, just in Europe. It is not strange that NTLs are always mentioned by utilities as the first element to “attack” in any Revenue Protection program.
In that context, it is quite of a paradox that many utilities approach their fight against NTLs in what we could call an “instinctive” approach. Many Revenue Protection programs are based in a combination of “gut-feeling” predictions and massive inspection campaigns that, at the end, become pretty ineffective and costly. Many utilities don’t take advantage of the capabilities that modern analytic methods, operating over the massive datasets coming from Smartgrids and other operational systems, can bring to improve the detection rate and effective management of this type of losses.
Join us in this webinar to discover:
- How an analytical platform in the cloud can be used to improve all the operations in your Revenue Protection workflow
- The various ways that the use of advanced analytics can enhance prediction efficiency for potential losses
- What types of external data sources can be combined with the information from the utility systems to increase detection rates
- The multiple ways that an optimized Revenue Protection program can amplify the bottom line of any electricity and gas utilities
Utilities that take advantage of more powerful analytics in their Revenue Protection activities can improve detection rates in a very significant way, more than a five-fold increase in case of some of our customers, providing quick returns on investment. And what may be even more important, better automation in the Revenue Protection workflow helps to achieve long-lasting operational efficiencies in the management of the network.
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