Uptime, engineered: how SLB cut downtime 55% and avoided $7.8M with predictive maintenance

SLB, a global oilfield services company, developed a Dataiku-based operational intelligence ecosystem to improve the reliability of high-value equipment operating in harsh field conditions. Beginning as a 2022 pilot involving fewer than 10 assets, the initiative expanded over four years to more than 110 assets, 24 equipment models, and operations in five countries. The system automatically ingests equipment and maintenance data, interprets it according to operational stages such as pumping or mixing, and uses context-specific models to identify developing failures more accurately than conventional threshold alarms. Developed by a cross-functional team of data, engineering, and reliability specialists, the platform retains human oversight by requiring reliability engineers to validate findings before field action is taken. SLB reports that the program reduced equipment downtime by about 55%, increased fleet availability from 84% to 93%, avoided roughly $7.8 million in capital investment, and generated an estimated $2.5 million to $15 million in economic impact over three years.

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