RSMeans’ construction project pricing turns on materials cost data analytics

Greenville, S.C.-based Gordian Co. has added Predictive Cost Data to its RSMeans Online service, citing the technology’s potential to deliver accurate, location-specific figures for more than 100 different types of construction projects up to three years out. With a few clicks, it delivers the cost of materials in a specific region during a particular quarter, helping users prioritize project timing and location.

Predictive cost technology is detailed in a white paper posted at

Predictive Cost factors 10 billion-plus points from 15 years of RSMeans data, coupled with advanced analytics Gordian scientists apply to more than one thousand indexes on public and private construction. Through a rigorous statistical program, a unique algorithm was produced for concrete, steel, wood and other material and labor segments. Thorough back testing from the last 10 years shows Predictive Cost attaining accuracy within 3 percent of actual cost indexes.

“Most of the tools available today make it difficult to plan and budget for future construction, especially more than one year out,” says Gordian Chief Data Officer Noam Reininger. “Going forward, you no longer have to plan tomorrow’s project with yesterday’s data because Predictive Cost has accuracy these previous methods lack.”

Predictive technology equips design and construction professionals, along with their clients, to effectively plan and estimate work. Until this point, Gordian notes, project stakeholders had few options outside of relying on current and historical costs, their own experience and studying trends to forecast building costs.

“Over time, material prices change substantially. Continually attempting to stay abreast of trends or only factoring in general inflation to try to account for these differences simply falls short,” Reininger contends. “With Predictive Cost Data, our algorithm allows for a level of accuracy never before possible.”