Colin Gault head of product at POWWR

Gault has spent over 15 years working in the energy sector. In his most recent role, Gault ran Digital Innovation for Scottish Power, where he was responsible for evangelising innovative technology and developing agile ways of working. Although he started out in more technical roles as a consultant and analyst, his passion for innovation, collaboration and problem solving has led to him spending the last decade in product roles. At POWWR, Gault leads the Product Management team and is tasked with establishing more strategic, consistent, and value-driven processes. By providing a clear overview of the energy market, Gault works with his team to ensure POWWR’s solutions are user-centric and benefits driven.

Posts by Colin Gault head of product at POWWR:

How Predictive AI is Helping the Energy Sector

In the past year or so, we have seen the emergence of many new and exciting applications for predictive AI in the energy industry to better maintain and optimise energy assets. In fact, the advances in the technology have been nothing short of rapid. The challenge, though, has been in supplying the ‘right’ data to make them effective.

It will be interesting to see what the future holds for predictive AI. Whilst there is much to admire, predictive AI is still in the emerging technologies phase and needs to overcome the challenges of scaling up. This article focuses on the benefits of the technology and what the energy sector will need to focus on over the next 12 months to ensure it doesn’t try to run before it can walk.

A three-step strategy to better energy management

As energy costs have continued to rise, the need for better energy management has increasingly been discussed in boardrooms up and down the land. However, it is often difficult for internal advocates to justify the ROI of such projects due to the insufficiency or inaccuracy of the data available. So much so that Garner suggests that ROI and conflicting priorities are seen as the top two challenges faced by over 40% of cases.

There is no doubt that data can be the proof point required. But how much onus should be placed on the business to establish the effective modelling strategies required to generate the requisite data to prove ROI and environmental benefits, and how much should be the energy supplier?