Between now and 2027, investment in infrastructure and sustainability capital projects is expected to hit $130 trillion. Effective spending at this level will require a solid delivery strategy to mitigate the schedule and cost overruns that so often plague capital projects.
Part of this mitigation can be found by using advanced analytics, with the opportunity to reduce project costs and overruns by as much as 30 to 50 percent. These advanced solutions can solve complex, nonlinear problems in resourcing, sequencing, design, and construction and engineering processes. For example, a generative-scheduling tool, powered by AI, can test millions of schedule configurations and find the optimal work sequence and resources for a construction project in a matter of minutes. This tool offers a counterintuitive approach to human-led planning that simply adds labor to accelerate delivery. Similar to navigation tools that plot the fastest route to a destination, generative scheduling can generate optimized sequencing and resourcing plans that can save both time and money.
A generative-scheduling approach works by building a model that considers the physical and spatial constraints that govern how work needs to be done on-site. Once the model is created, it is asked “what if” questions about subjects including labor, equipment, installation rates, access, and productivity, producing hundreds of thousands of scenarios for how the work could be completed. An advanced-analytics algorithm then rapidly tests these scenarios to explore different options and generates a resource-loaded schedule that forecasts the costs and timing of the project, allowing project owners to select the option that best delivers their objectives.
Learn more about generative scheduling in this short video, which explains some of the challenges that project owners today are facing, as well as the opportunities that exist for generative-scheduling tools to help reduce costs and minimize schedule overruns.