In today’s competitive energy and industrial sectors, finding ways to improve revenue while reducing operational costs is essential. This one-day, hands-on course is specifically designed for Production, Facilities, and Operations personnel, as well as Maintenance staff, who want to gain practical skills to identify and implement efficiency improvements. Participants are encouraged to bring their own operating cost data to use throughout the day to make their learning experience immediately relevant.

The course begins with an in-depth look at facilities, exploring their purpose, capabilities, and limitations, while also considering internal and external constraints that can impact performance. From there, participants learn how to build a compelling economic case to justify optimization projects, ensuring that proposed improvements are clearly linked to measurable benefits.

Effective data management is a central focus, with guidance on how to identify what information is available, what additional data may be needed, and how to analyze it to make informed operational decisions. The course also covers the essential principles of project management for optimization initiatives, including planning, budgeting, scheduling, and tracking progress to ensure projects are delivered on time and deliver the expected results.

Through interactive exercises and real-world examples, attendees will gain the knowledge, tools, and confidence to evaluate operational performance, identify opportunities for improvement, and implement strategies that drive efficiency and profitability. By the end of the course, participants will be equipped not only to optimize current operations but also to sustain improvements over the long term, making this a highly practical and valuable learning experience for professionals seeking measurable results.

Who Should Attend

This course is designed for Production / Facilities / Operations Support Engineers, Operations and Maintenance personnel with a basic understanding of field and plant operations.