Forecasting is an essential part of the construction process. Not only does it set time and budget expectations for customers, but also potential profits for contractors. 

Accuracy is critical; however, historically, construction has missed the mark. According to a global construction survey by KPMG, only 31% of construction projects came within 10% of their budget over 3 years, and only 25% came within 10% of their original deadline. 

As construction projects grow increasingly larger and more complicated, the problem will only worsen. The construction technology space has the potential to address many of the industry’s legacy issues, but the technology itself isn’t enough. It needs data.


While multiple factors go into construction’s accuracy problem, one of the biggest culprits is a lack of quality data. In fact, poor data is estimated to have cost the construction industry $1.8 trillion in 2020. It’s not that construction isn’t collecting data, but most data collection methods are done via spreadsheets and pen-and-paper processes, making them rife with inaccuracy and errors. And a forecast is only as good as its data. 

Fortunately, with advances in construction technology, it is now possible to automatically collect and feed data straight from the jobsite to forecasting software and other construction management programs. Not only does this data improve the accuracy of forecasts, but it also improves the forecasting process as a whole. 

Here are three ways real-time data can improve the forecasting process throughout the construction lifecycle:


Not only can data improve forecast accuracy, but it can also provide contractors with actionable insights to improve production rates and reduce forecast rates. For example, if a contractor is continuously experiencing budget overruns and they incorporate site data into their forecasting software, they may notice the projected production rate of their crew is significantly lower than what they’d been using in bids. They discovered through the timesheet data that crews had been consistently working for a ninth hour to finish things. They can now apply this knowledge to the next job schedule, giving crews a longer time frame and reducing the need to hustle into overtime.


The only constant on a jobsite is that it’s constantly changing. Between weather delays, change orders, sick workers, equipment breakdowns, and a mile-long list of other possible slowdowns, forecasts need to be updated frequently to provide the most accurate view of progress. When fed real-time data from a jobsite, forecasting adjustments can be made automatically instead of at the end of the day; this gives contractors more time to react and adjust operations.


A long-term benefit of establishing feedback loops through data is that it improves forecasting accuracy over time. The more data to work from, the better the predictions will be. This can also help track fluctuations in production rates over time as crew members come and go, new equipment is added and so on. Additionally, this data can lead to more optimized operations and better decision-making when scheduling and bidding. 


With improved forecasting backed by real-time data, contractors can improve their profits, use their resources better, and keep a pulse on the productivity of their business as a whole. 

About the Author:

Marcel Broekmaat is chief product officer at Assignar, a cloud-based construction operations platform. For more, visit

Modern Contractor Solutions, January 2023
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