The digitalisation of electrical infrastructure calls for new skills. Big data expertise is at the heart of this transformation.
According to the International Energy Agency’s Digitalization and Energy 2017 report, digital tools will enable electricity suppliers to improve their productivity and reduce their costs. Digital technologies can make electricity grids smarter and reduce operating and maintenance costs as well as capital investment.
In predictive maintenance, connected sensors can be used to repair equipment before a fault occurs. The data generated by the sensors can also be used to adapt the use of the equipment to its capacity and to grid requirements. In infrastructure management, new technologies such as drones can facilitate maintenance of pylons – though of course, expertise in piloting the small flying machines as well as processing and exploiting the images they capture is required!
In all these cases, big data is at the heart of the transformation, and electricity sector jobs must adjust to the new circumstances. “The first phase of the digital transition, which may seem basic, is to digitise all paper documents used on worksites. This does not revolutionise the job of the field technicians, but it does directly affect the way they work. We therefore need people who are able to understand the specifics and limitations of our activities and to engage in dialogue with the developers of these digital solutions to ensure that they are adapted to our needs and therefore adopted,” says Omexom digital innovation project manager Benoît Kieffer.
What is needed is people who understand the business activity as well as IT architectures and database management. Example: digital innovation manager.
Attracting the big data wizards
Alongside the traditional jobs that digital technologies are improving, new skills are emerging in such fields as big data, blockchain, and machine learning. Omexom looks to startups to acquire these capabilities. “For example, we are working with Sterblue to carry out electricity pylon inspections using drones. The photos are then decoded using an algorithm trained by our experts,” says Benoît Kieffer.
“At VINCI Energies, the data scientist is not going to be sitting there coding 24 hours a day. His or her work will achieve concrete results.”
The next step is to develop an automated drone flight and photography programming solution. When combined with the machine learning algorithm, this gains time by preparing the work of the expert. The Omexom brand business units have to analyse and process an increasing volume of data generated by equipment that is increasingly digital and increasingly connected. The teams have the expertise to recover and use some of this data but they do not yet have the skills to interpret it more broadly and to make wider use of it. This means that we must attract data scientists and data analysts – two profiles that are in high demand.
However, the VINCI Energies brand has advantages enabling it to attract these data wizards. “At VINCI Energies, the data scientist is not going to be sitting there coding 24 hours a day, disconnected from reality,” says Benoît Kieffer. “His or her data work will be combined with expertise in our sector to achieve concrete results and work up a package solution for a customer. Their job with us is not like the job of a pure data or IT player, who is not always able to understand our industrial customers.”