Abstract: A computing system such as a back-end platform for construction management software may employ a predictive model to provide individuals responsible for overseeing a construction project with a prediction of a “risk level” for a punch item, which indicates a risk of the punch item not being completed by the punch item's target completion date. Such a predictive model may be defined based on historical-punch-items data. After defining the predictive model, the computing system may receive data defining a given punch item and input such data into the predictive model, which may in turn output a given predicted risk level for the given punch item. Thereafter, the computing system may cause a client station to display an indication of the given predicted risk level for the given punch item.

Abstract: Disclosed herein is an interactive software tool for facilitating the creation, management, and tracking of an ITP for a construction project, which may be referred to as an “ITP software tool.” In one aspect, the disclosed ITP software tool may provide a first interface through which users can create a new ITP for a construction project. In another aspect, the disclosed ITP software tool may include a software engine that functions to automatically define inspection and test activities for inclusion in the ITP. In yet another aspect, the disclosed ITP software tool may provide a second interface through which users can manage and track the status of an existing ITP for a construction project. In still another aspect, the disclosed ITP software tool may include a software engine that employs predictive analytics in order to identify potential problems with an existing ITP for a construction project.

Abstract: A computing system such as a back-end platform for construction management software may employ a predictive model to provide individuals responsible for overseeing a construction project with a prediction of a “risk level” for a punch item, which indicates a risk of the punch item not being completed by the punch item's target completion date. Such a predictive model may be defined based on historical-punch-items data. After defining the predictive model, the computing system may receive data defining a given punch item and input such data into the predictive model, which may in turn output a given predicted risk level for the given punch item. Thereafter, the computing system may cause a client station to display an indication of the given predicted risk level for the given punch item.