How Artificial Intelligence Moves Critical Path Method (CPM) Schedules Closer to Reality
By Dr. Dan Patterson
January 09, 2020
Since its introduction in 1956, the basic premise of Critical Path Method (CPM) hasn’t changed that much. Today, despite its rather dismal track record, nearly every major project uses the method for planning. In the end, projects fail not because of poor execution, but because the plan was overly optimistic and aggressive.
Fortunately, there’s a better way. Thanks to emerging technologies, today’s planners can quickly deliver realistic project plans in a fraction of the time by leaning on artificial intelligence (AI). AI helps provide smart suggestions based upon an organization’s historical project knowledge rThese tools work in tandem with some fairly common programs and improve upon the age-old process of CPM scheduling.
THE EVOLUTION OF AI
In just the past five years, the speed and increasing affordability of computing power has utterly changed the AI landscape, enabling the technology to reside on a planner’s desktop or in the Cloud. From a planning perspective, that means a computer is not merely a mechanism for receiving inputs, but is now proactively guiding the planner.
AI is not some magic tool whereby a contractor pushes a button and generates a schedule, but it can be leveraged and manipulated to provide realistic, dependable suggestions. In effect, it improves the planning process by enabling a computer to mimic the way a human makes decisions.
The proliferation of AI has helped fuel a knowledge-based approach to planning. For example, if a plan was previously created in Primavera or Microsoft Project, those schedules and plans all reside in a knowledge library that stores historical schedule information as well as unstructured data such as risks and opportunities.
The “brain” of the knowledge-based system is the inference engine. When a planner asks for a suggestion, the inference engine requests inputs in order to understand the context, such as the type of project, location, quantities and other variables. It then uses those variables to understand context, interrogate the knowledge library and provide suggestions.
From there, it can guide the planner in the decision-making process and provide a corresponding confidence level.
Artificial intelligence planning puts AN END TO “FROM-SCRATCH” PLANNING
With an artificial Intelligence planning approach, a contractor doesn’t begin with a blank sheet of paper, but instead relies upon historical data as a foundation. After all, there are commonalities on all projects.
By using a template, a planner can begin with some reliable building blocks for putting the plan together – and adjust along the way. For example, instead of having a work breakdown structure go 12 levels deep, a contractor can reduce that number while retaining much of the data.
Today’s tools can also define high-level timelines, thereby providing a benchmark plan as the project progresses. Along the way, a contractor can better understand the alignment or misalignment of the plans, and whether or not they’re executing as per the original plan.
Task durations can also be established using historical rates of productivity. In the process, the AI-enhanced program asks a series of questions (e.g., scope of work, number of units, and so forth) and then uses historical productivity rates to determine the duration. This provides a more defendable, realistic estimate that is based upon past performance.
Through it all, the human component remains vital and necessary, as plan validation must be performed by the scheduler, team members and other stakeholders. The computer then takes those opinions and develops a consensus view.
In effect, with the incorporation of artificial intelligence planning capabilities, the entire planning process becomes more of a collaborative partnership between computer and planner – a huge leap forward in the world of project planning.