Why are schedule overruns so common among megaprojects? A recent study conducted by Oxford’s business school found that approximately 90% of megaprojects with a budget of $1 billion or more have cost and schedule overruns.
From subways and bridges to dams and data centers, time overruns are a recurring problem in the world of megaproject delivery. So how can governments and private sector companies do better to deliver on time? To answer this question, we must first understand the reasons why delays occur in the first place.
In this article, we will discuss three main reasons why megaprojects frequently run late and how you can improve delivery time by enhancing your schedule data with AI and Machine Learning:
One of the biggest reasons why megaprojects so frequently run over time and over budget is because project teams have not been able to predict what path a project will take. The critical path method focuses on measuring only the tasks that are critical to a project and estimating a timeline for the completion of those tasks alone.
However, the critical path can change throughout the lifespan of a project. As tasks are completed and other tasks are delayed, unforeseen circumstances may render non-critical tasks as critical and vice versa. If project teams are not able to respond to those changes, the project is delayed and does not finish on time.
Project teams need to closely monitor activities and the resources by measuring planned progress against actual progress.
People tend to see the future in rosy terms. Nobody wants to look ahead and picture the worst, so we unconsciously envision positive outcomes. This is what psychologists call “optimism bias.”
In life, optimism bias can be helpful; it drives us forward and feeds our ambition. But in project planning, it can translate to overconfidence and poor forecasting.
When project teams fail to account for risks and complexities that can occur, it creates forecasts that are more optimistic than realistic. And because the timescale and costs of the project are understated from the very beginning, schedule overruns are almost impossible to avoid.
Good decisions are based on having sufficient, accurate, and timely data. Optimism bias tends to occur most often when there are weaknesses in information that can easily be ignored. But by strengthening the schedule data, project teams can provide more accurate estimates and make better decisions.
Another thing that many megaprojects have in common is a lack of risk management protocols. It’s hard to produce timely reports on progress, budget, and timelines when so much of the data that project teams have to work with is outdated and does not align with the current state of the project.
Teams often rely on payments made to contractors as a measure of progress because it is too difficult to accurately measure how much work has been performed. This means there is no common understanding of performance or how to accelerate project delivery.
A better approach would be to use real-time data that correlates to construction progress such as how much concrete has been poured or how much earth has been moved. This would give project teams a more accurate foundation for analyzing and managing project risks.
Until now, Primavera P6 and MS-project were the default systems available to help teams execute megaprojects. These systems of record still hold tremendous value, but it’s clear megaproject teams need something more. They need a system of intelligence that can work with these softwares to analyze project data, draw out important insights, and coordinate action.
Foresight is a first-of-its-kind platform designed to be a system of intelligence for megaprojects. Using artificial intelligence and machine learning, Foresight analyzes project data from Primavera P6 and MS-Project to identify:
Book a demo today to discover how Foresight can help you build your projects faster.