At a time of soaring gas and electricity prices you might assume that energy companies’ treasury teams are sitting back and watching the moolah roll in. But the deep structural shift caused by the energy transition in the form of reduced focus on fossil fuels and increased emphasis on renewables has forced a major strategic re-evaluation.
Because energy is a physical business, companies must consider where the resources are.
They need to make capital intensive investments in renewables and their cash is generated in multiple jurisdictions, all of which requires increasingly sophisticated forecasting. This makes accurate cash flow planning using data – and liquidity management tools such as notional pooling – more important than ever, explains Christine McWilliams, Global Head of Commodity and Energy Trade at Citi.
“If you are a finance or treasury professional responsible for forecasting or trying to manage liquidity, there is the movement of energy prices as well as everything that is happening in the world to keep you on your toes every morning,” she says.
“Geopolitical developments that could impact supply and the clean energy transition which throws up alternatives which may or may not have a certain degree of government support or carbon offsets add so much complexity to what you have to think about when you are forecasting your liquidity position.”
According to McWilliams, treasurers are being asked to support a business transition into clean energy sources which may have a different cost profile to traditional energy sources such as crude oil as well as presenting different logistical challenges.
The supply chain for oil is well established, albeit subject to disruption from unforeseen events. However, investments in renewable sources have to take account of where it is produced and how to get it to where the demand lies.
“This process is underpinned by good data, because if you don’t have reliable data around your costs it is going to be hard to forecast some of these scenarios and advise the business on what to do when it switches,” says Williams.
Over recent years, energy companies have increasingly moved towards more centralised transactional processing centres to give them greater insight into metrics, such as the volume of letters of credit outstanding or their global account balances. By increasing the reliability of the data at their disposal this has enabled treasury teams to provide greater input into business decisions.
Williams says the goal is to increase efficiency and control, providing improved analytics so treasurers can make more informed decisions around liquidity. As energy companies explore new business models such as energy-as-a-service, the potential risks and rewards of different sources should become more transparent, helping to guide future investment.
Despite the investment in digitisation that has been made across many different organisations, there is still an element of underutilising data that is already there – data that is residing within these organisations that isn’t being interrogated or factored into treasury forecasts.
Williams acknowledges that even within the world’s largest corporates there are business units or jurisdictions that still rely to some extent on manual processes, which makes this data that much more difficult to get to. But she also warns that the algorithms that underpin artificial intelligence need to be structured properly to produce useful outcomes.
“This is something we will learn more about in the coming years,” she says. “In the meantime, companies should focus on establishing clear data policies and procedures, making it accessible from a single location in a standard file format or ERP system that enables treasurers to create value from it.”