Patent ID: 9563864
Date: 2017-02-07
CPC Classifications: G06Q

Claim:
1. A method of detecting patterns that increase a risk of late delivery of a project, comprising: gathering historic and current development data associated with the project; obtaining a catalog of patterns, each pattern associated with a data measure and an analysis routine capable of detecting a pattern according to the data measure in a given data set; executing the analysis routine associated with the pattern to the historic and current development data to identify the pattern in the historic and current development data; and issuing a notification responsive to identifying the pattern in the historic and current development data, wherein the executing and the issuing are performed for said each pattern in the catalog of patterns, the catalog of patterns comprising at least a pattern that arises in the project indicating what has gone wrong in the project to threaten on-time delivery of the project, the pattern in the historic and current development data detected based on a series of predicted likelihood of on-time delivery of the project predicted over time by a combination of machine learning and stochastic simulation, wherein the machine learning comprises training a machine learning algorithm to predict an estimated effort needed to complete each of unfinished tasks belonging to the project based on a set of completed tasks belonging to the project if available and a set of completed tasks not belonging to the project if available, the stochastic simulation comprising a Monte Carlo simulation based on repeated random sampling of scheduling and assigning of the unfinished tasks to team members subject to resources and scheduling constraints.