The black swan effect is a metaphor that describes events that are rare, hard-to-predict and have a major impact. While a single black swan event is extremely rare, to have two happen at the same time is exceptional. That is the situation the oil and gas sector finds itself in this year.
Covid-19 caused an economic contraction that demolished oil demand at a time when supplies were already greater than world consumption. And, while the energy sector has experienced volatile market contractions before, the speed and magnitude of this current one is unprecedented.
As a result, energy companies are aggressively re-positioning their current operations with both a short- and a long-term approach. The energy companies that survive this market correction are the ones that are not only hyper-focused on maintaining cash liquidity through the storm but are also taking advantage of this time to reposition their operations.
It has never been more crucial to function in a more agile, reliable and efficient manner now and for the expansion period ahead.
Cash is king
The most critical area where energy companies are being affected is on their cash balances. As a result, the principal goal during these times is to preserve cash by eliminating non-essential or duplicative costs. One core area of focus is on non-essential costs in their supply chain processes.
Historically, energy companies tended to manage these processes with a focus on cycle-time improvements and or vendor price concessions. In the current environment, that is no longer enough. Principally, these teams are trying to leverage process insights that allow them to pursue improvements to take some cost out of operations. Thus, process mining is becoming one of the most relevant technologies they are pursuing within their finance, supply chain and field maintenance teams.
Additionally, one of the principal areas of duplicative costs is in the IT/OT application portfolio. Accordingly, the IT/OT application portfolio technology platform is one that enterprise architects are evaluating for rapid deployment within their planning environments. The technology allows them to quickly understand their application portfolio with a full view of their application inventory relative to cost, cross-application dependencies and capabilities. This information is critical if they are going to get costs out of the business without sacrificing the capabilities that support the business.
One of the most important strategies that is being pursued by leading companies in this sector is the transformation of its asset management practices. Ultimately, these leading companies will continue to invest in Industrial IoT (IIoT) technologies that not only allow them to manage their assets more efficiently, but also embed a foundational IIoT capability. This is a pathway to workflow automation that leverages a full understanding of workflow processes, real-time data and analytics. The goal is to be able to monitor and optimize processes in real time through the application of streaming, predictive and AI/ML analytics.
Additionally, prior to the recent market contraction, one of the principal IT strategies in the industry was the migration to cloud operations. This trend will accelerate. Energy companies will continue to adopt iPaaS technologies that allow them to accelerate their cloud-to-cloud integration capabilities.
Today, energy companies are selling less oil and gas. During times such as these, one of the first exercises they pursue is to decide which wells and refining assets to turn off. In a world of negative to low oil prices, the need to remove less efficient assets from production is critical.
While this approach ensures the best possible operating margins, it also concentrates operating risk in the wells that remain active – and the refining assets that are processing the oil and gas streams. Consequently, any unplanned service disruption in production and refining assets will have a massive negative financial impact.
Technology that allows them to ensure uptime performance for the remaining onstream production assets would be a welcome addition. By that token, self-service industrial analytics technologies are actively being deployed across the entire sector. These technologies provide production and reliability engineers with multi-asset visual data analytics that allow them to quickly identify reliability and production risk for multi-asset complex production processes.
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*This article originally appeared in Oil Review Middle East.