Integration of data for the purpose of predictive analytics into the processes and activities in the industry of construction is definitely not an easy task. However, the Predictive Analytics Strategic Council, which represents a coalition of major contractors and technology firms, released their first whitepaper containing outlines of how predictive analytics can be introduced to the industry of construction. The coalition made a proposal on how predictive analytics can be built based on data, which could then be integrated into construction workflow and processes.
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PASC Proposes Integration of Predictive Analytics in Construction
The industry of construction could draw many benefits from predictive analytics with the use of data. Specifically, this integration could be enabled by collecting massive volumes of project data that would serve as the key metrics for determining and compiling predictive analysis. Predictive algorithms are programmed to find connection between different pieces of data, that way tracing similarities and drawing conclusions based on the project history across different construction companies. Construction could use predictive analysis to prevent accidents on job sites and increase efficiency for example.
Construction Could Improve Safety with Predictive Analytics
By using large volumes of project data, predictive algorithms could use safety information and accident reports to compile analytics for other contractors and companies. This way, accidents could be prevented on construction sites. The industry of construction has the highest rate of accidents on jobsites when compared to other industries and sectors, while safety poses a major challenge.
Predictive Technology Not 100% Certain
Even though PASC proposes predictive analytics in their whitepaper, the authors of the paper claim that predictive technology can’t be taken as 100% certain. Predictive analytics relies on volumes of data and previous “experiences” on construction sites, analyzing factors that might have led to an accident on the job site.
