Three Topics That will Dominate IT Landscapes Discussions in Energy Trading Companies in 2023 and Their Implications
Jan 3, 2023
The past two years have been pretty volatile and emotional for energy traders (in good and bad ways). ROITI’s CEO Ventsislav Topuzov shares some insights in the article below. As things settle down into a kind of “new normal” there are several effects of the volatility that drive business demand for IT solutions and will bring new strains on companies’ teams. The topics are not new but the increased pressure for time to market brings a much tighter focus.
The main market developments with significant second-order impacts on IT landscapes in my view are:
- Investment in RES and the rise in PPAs has been growing steadily, but the level of pressure in this area now that big oil companies have very actively entered the market is on a whole new level A total of $226 billion was invested in renewable energy globally in the first half of 2022, according to BloombergNEF. A few examples from the past year include CWP Global signing a landmark agreement to launch a major green hydrogen project in Djibouti, as well as bp taking a big stake and operatorship of Australia’s largest RES project.
- The rise of LNG will mean not only new portfolios for players entering the market to manage but also new complexity to handle them in IT landscapes. The LNG trade volume has grown continuously over the past decades, reaching over 500 billion cubic meters as of 2021, according to Statista.
- Highly volatile markets mean far smaller willingness to take on risk for traders which in turn means far fewer fixed price contracts and risk being passed on to end customers or producers S. natural gas price volatility hit a record in 2022, according to the Energy Information Administration (EIA). “The 30-day historical volatility of U.S. natural gas prices, based on the Henry Hub front-month futures prices, averaged 179% in February 2022”.
The Three Key IT Landscape Topics
The above three aspects of energy market developments lead to the following impacts on the internal teams:
- Far more complexity for Back Office functions. LNG and RES PPAs are highly custom and complex contracts and the stage of market development means standardization is not on the immediate agenda. This means a lot of manual work in settlements and contract management with a high chance that Excel is the most suitable software for a large part of the activities at this stage. Additionally, RES PPAs come with a certificate position to manage – and their behaviour (as well as their value) can range wildly across registry jurisdictions.
- More RES in the portfolios means more need for algorithmization of decision-making and trading. This trend has been around for a while but the push for faster time to market without compromising quality is greater than ever.
- Finally, as risk is being pushed increasingly up- and downstream, the risk management capabilities of producers and consumers will need to increase out of necessity rather than desire. The role of trading companies as risk aggregators and managers will not diminish (on the contrary), but as there is considerably more risk in the market as a whole, they will be reluctant to take on an ever-increasing amount.
How does this reflect on the IT landscape?
What can be observed across the board is increasing investment for digitalization – of more specific variations.
The new complexity of the traded products can be addressed in three ways:
- Automating further existing processes to free time for existing teams to settle new products. Pros: last bits of established processes can be automated. Time of experienced people can be refocused on new priorities without losing oversight of the existing business.
- Buy or build new solutions aimed specifically at PPAs, certificates, and/or LNG where this is a topic. Pros are clear – new solutions to new problems should alleviate the strain on the teams and bring efficiency into processes which may turn out to be sources of revenue and competitive advantage. Over time, further investment will be needed as the markets evolve, but the evolution is likely to be in the direction of standardization in the mid to long term, and this will make things easier.
- Increasing Back Office headcount. Companies are traditionally unwilling to spend more in this area, as over time as processes get well defined, there is room for automation. However, experienced back office people can be crucial in a reality with the growing importance of origination and non-standardized contracts with new counterparties. KYCs, long-form confirmations, and complex settlements all require good knowledge of internal processes and market realities. Having the flexibility to address them promptly can easily go through onboarding new hires on more established processes which gives a faster time to market for them.
Two of the options above require pretty much immediate investment in IT capabilities. The third one depends on the bet how fast and how much of a role the more non-standardized business lines will play and how long will it take for them to mature into well-defined processes which are automatable.
More algorithms in trading are fairly straightforward, although there are key design components which need to be carefully considered like infrastructure, data correctness and security, and algo limits (or basically how much space you allow for human intervention should things go wrong). There are three types of competencies which are key in this area:
- Data engineering – basically ensure that data is where it needs to be in a format which is analyzable and comparable across data sources at the time when it is needed – and it is needed a lot and reliably;
- Data science – typically, there has been an Analysis department at every large energy company. Now that much more data is relevant for decision-making and more random variables enter the picture (wind, sun, among others), the analysts’ role becomes much more complex involving an increasing focus on data engineering but adding “come up with a model to predict this variable” tasks on top. Because of the added complexity and increased push for more variables to be taken into account faster, data science is in short supply – and demand is set likely to increase in the foreseeable future;
- DevOps – data, model, and system reliability is a very key component in the algorithmization of trading and (to use my favourite Nassim Taleb’s term) an antifragile infrastructure is very important to assure the analytics are correct and that they are based on the correct data. DevOps engineers (and variations like ML Ops) are the key people having the technical competency to ensure these effects.
Last but not least, more risk passed from traders to producers and consumers means they need to build up risk management and trading capabilities and do it fast, as the markets will become tougher for them. IT landscape-wise, the key considerations will be along the lines of:
- Selecting ETRM systems. While options on the market are abundant, potential buyers like e.g. large power producers are considered critical infrastructure and regulations to the origin of the company providing software may apply. This adds a twist to the selection process and limits the choice. On the other hand, portfolios will be heavily tilted towards a specific type of complexity and potentially the problems to solve will be fewer than traders’ problems. This could generally help the market to develop competition across systems covering different asset classes;
- Control over data. More active trading companies have spent the last years (perhaps decades) progressively ensuring control over data, developing governance policies, and ensuring different views on data use the same source (which is ideally also the correct one 😊). This will be a challenge in the context of creating trading and risk management capabilities for companies that are not used to complex data governance. Specifically, it will lead to a higher total cost of ownership (TCO) of data solutions until the right policies and practices come into place;
- Putting an operational model in place. While asset operators will have experience with monitoring and supporting critical processes and likely have something to build on, consumers may not necessarily be prepared. Putting the right operational processes around supporting a more trading-oriented landscape will require identifying critical roles, processes, and systems, identifying SLAs that need to be covered around them, and finding the right competencies to fill in the gaps.
Overall, there is a mixture of sources of complexity for trading IT landscapes. High volatility, more RES, and the increased importance of LNG will pose different challenges to the markets as a whole, and individual players. 2023 will be marked by increased pressure on the market participants to try and catch up with the trends in energy trading IT and try to jump over steps to get to a modern and business-supporting landscape.
We live in interesting times. 😊