Analytics and predictions for planning construction processes

The construction industry is digitally underdeveloped compared to other sectors. A large amount of documents is used during processes such as quality inspection, maintenance planning, incident reporting, or issuing permits to work. All these documents are traditionally on sheets of paper that are filled in by hand and transferred between the different stakeholders. A few companies are starting to digitize their processes, making them both more efficient and more reliable. With their new platform, they now have access to past construction data, and a key issue is to be able to learn from them. In particular, during the quality inspection, many construction defects are reported, and then rectified. These steps are logged, and data gathered during the process can be leveraged to improve the planning of defect rectification. Two solutions are examined to pursue this goal: a visualization application is developed to easily explore defects data, dive into the relevant details, and identify possible improvements to prevent these defects or speed up their correction. In addition, a forecasting model is designed to predict the time to correct a defect and help to estimate the duration of the inspection stage. The visualisation tool is successfully used by several customers, the main remaining issue is to use it at a larger scale for around a hundred different companies. The forecasting attempt shows encouraging results but may require further improvements to be usable.