U.S. Energy Sector in Crisis
The American Society of Civil Engineers1 has been assessing U.S. infrastructure since 1998 through their quadrennial Report Card for America’s Infrastructure2. While overall, American infrastructure has improved slightly (from C- in 2021 to C in 2025), energy infrastructure has worsened (from C- in 2021 to D+ in 2025). The energy sector is not only facing aging transmission systems but also an aging workforce that is nearing retirement. Yet electricity demand continues to surge.
While companies in the oil & gas industries can’t replace every aging asset overnight, they can achieve better, faster decision-making today with decision management platforms like Sparkling Logic SMARTS™. Through decision management, the energy industry can preserve institutional knowledge before it goes out the door, harvest decision intelligence from disparate data sources, and make smarter automated decisions that are auditable and in-compliance with regulatory and safety standards while they slowly repair, upgrade, and replace physical assets. In this post, well cover a few use cases.
Preserving Industry Expertise in Oil & Gas
Majority of the experienced engineers, inspectors, and maintenance specialists who build their careers around knowing the quirks of specific equipment and sites are planning on retiring over the next decade. Oil, gas, and energy companies can utilize SMARTS™ to capture and operationalize their expertise in one place. Companies can then make these validated decision frameworks available to new hires and other stakeholders. This not only will speed up the onboarding process, but also can be used to automated operational decisions related to maintenance and compliance.
Predictive Maintenance in Oil & Gas
Unplanned downtime is one of the costliest outcomes in energy operations. Energy companies can leverage SMARTS™ to continuously monitor equipment health through IoT and sensor data — pumps, compressors, rotating machinery. Using fully traceable business rules, machine learning, and other decision logic that encapsulates industry expertise, companies can trigger alerts and scheduling for maintenance. Instead of reacting to failures, maintenance teams get ahead of them. For operators managing distributed assets across large footprints, this shift from reactive to predictive maintenance directly reduces emergency costs and lost production time.
Automated Engineering Standards
The energy sector is one of the most heavily regulated industries in the world. Every equipment replacement or facility upgrade triggers a host of compliance reviews: EPA, OSHA PSM, API, etc. Today, much of that review is still manual, slow, and error-prone. Organizations in the oil & gas industry can encode these standards in one place through SMARTS™ and automatically flag spec gaps before orders are placed. Similar to predictive maintenance, organizations can deploy machine learning in SMARTS™ to identify recurring performance deviation patterns so that they can identify and address risks before falling into non-compliance.
For U.S. oil, gas, and energy companies navigating aging infrastructure, tightening regulations, and workforce transition, decision automation isn’t a future investment — it’s a present-day operational need.
Contact us today for a customized demo of SMARTS™ to learn how we can be a part of your modernization strategy!
Notes
1: American Society of Civil Engineers: https://www.asce.org/
2: Report Card for America’s Infrastructure: https://2021.infrastructurereportcard.org/