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Major CAPEX oil and gas projects are inherently complex. With that complexity has historically come a very high degree of project risk and uncertainty impacting both owner organizations and EPC contractors alike.
In recent years, incremental improvements to the project forecasting process such as risk analysis and contingency management have helped, but the underlying planning philosophy of “begin with a fixed start date and figure out where we land in terms of project completion” hasn’t fundamentally changed. Worse yet, it hasn’t been very effective in helping achieve on-time, on-budget project completion.
Thankfully, there are two complementary technology and methodology advances that are changing this trend for the better.
Solution: Advanced Work Packaging
With the growing adoption of what is called Advanced Work Packaging (AWP), the approach to both CAPEX and field execution planning is getting a much-needed revamp. Firstly, AWP drives a project to plan backwards from an agreed-upon end goal such as First Oil or First Production.
By establishing a defined set of sequential execution milestones modeled through what is known as the Path of Construction, the project can focus on ensuring that execution is constraint-free by aligning materials, resources, design and engineering. To help proactively manage this process, the consolidation and visualization of these driving entities through multidimensional modeling enables an organization to optimize planning and ultimately execute with a much higher degree of certainty.
Secondly, AWP ties together long-range CAPEX planning with short-term daily field execution planning. For the first time, foremen in the field can manage their crew’s daily plans knowing they are in alignment with the bigger-picture project objectives, as well as execute knowing that the required materials and personnel are available at the right time and in the right place.
By focusing the entire project team from the get-go on de-constraining the Path of Construction, all project scope owners, including engineering and procurement, are marching in harmony. This eliminates a lot of pinch points with regards to interface management (a longtime risk driver of complex CAPEX projects).
AI and Machine Learning as Game Changers
One of the driving forces behind the rapid adoption of AWP is the emergence of AI, or knowledge-driven planning. For the first time, organizations are literally digitalizing decades of expertise and experience and then, through AI, intelligently mining this knowledge to assist in more accurate predictive planning.
Planning expertise comes in many forms and, as such, is not easily captured in, say, a database. This is where AI and machine learning can help. Historical project performance and the factors that drove such performance can now be stored and interrogated using unstructured data storage and AI inference engines. These knowledge-based systems are becoming a mission-critical digital asset for owner and contractor organizations alike. The reason? They are more effective than humans when it comes to identifying trends and patterns that can then be used to benchmark and calibrate future project outcomes.
Machine learning is a key component of AI. If AI is all about the computer assisting the human by making suggestions, then machine learning represents the ability for the computer to learn from the human expert. In the case where the human discards the computer’s suggestion or benchmark, then through machine learning, the computer is able to adjust its algorithm weightings so as to subsequently offer better and more context-aware suggestions. This is a powerful concept, as it means that even if an organization has limited historical data, the AI suggestions can grow smarter with increasing human interaction.
Throwing caution to the wind a bit though, don’t for a minute think that AI can completely replace the expertise of a human project controls expert. For AI to be effective, both human and computer interaction is needed. AI is assisting or augmenting a project controls team’s ability to create better, more achievable cost and schedule forecasts. It is acting as a digital assistant to both highly experienced planners as well as newcomers to the industry. Machine learning is, then, assisting the computer to grow smarter by absorbing more and more human expertise.
Summary
Technology alone doesn’t solve problems – neither does a philosophical concept alone. However, in the case of CAPEX project planning, we are fortunate to be at a point in time where a new technology such as AI has emerged concurrently with a newly emerging philosophy (AWP). The concept of planning backwards from a determined end goal makes a lot more sense than planning from left to right and hoping the end will just turn out okay.
Yet planning backwards only really works if the preceding work leading into the Path of Construction can be accurately forecasted and executed as planned. AI is driving that ability to better forecast and align engineering, procurement and construction. Combine AI with AWP and it’s hard to argue against the fact that we are at a pivotal point in time in the history of project management.
For more information on AWP solutions, visit InEight.com
Dr. Dan Patterson is chief design officer with InEight. In this role, he focuses on expanding upon his vision of creating next-generation planning and scheduling software solutions for the construction industry. Dan is a certified Project Management Professional (PMP) by the Project Management Institute (PMI).
