Sprint Communications Comapny L.p.

Paul R Sapenaro

Deandra T Cassone

Jason Norwood Ward

George R Kather

Joseph E Dudley

Noel R Marchbanks

A computer implemented method is provided for flexible project governance based on predictive analysis. Project complexity factors are analyzed to determine a project complexity index. Initial development gates are selected for a project based on the project complexity index. Project governance factors are periodically analyzed to determine a project governance index. Actions for project reporting and for the initial development gates are selected based on the project governance index.

Flexible project governance based on predictive analysis

Computer implemented methods and systems are provided for identifying high to high complexity projects. Some method embodiments include defining proposed project data for identified factors, calculating a planning team index for a project associated with the proposed project data, and identifying the project as complex when the planning team indicator falls on one side of a breaking point. The factors are those identified as determinative of project complexity.

Systems and methods for identifying high complexity projects

A computer implemented system for project prediction is provided. The system includes a data manager to obtain historical project data. The system also includes an analyzer to analyze the historical project data and an analysis cycle time to generate models for a proposed project cycle time. Additionally, the system includes a user interface to select one model for the proposed project cycle time, wherein the selected model includes linear sub-models corresponding to a historical data range, and apply proposed project data and analysis cycle time to one linear sub-model corresponding to a proposed data range to predict the proposed project cycle time. Furthermore, the system captures proposed project data and obtains additional project data to update the selected model. The models provide for the accurate prediction of cycle times, or project costs, in an enterprise development environment.

Enhanced project predictor

A computer implemented system for project prediction is provided. The system includes a data manager to obtain historical project data. The system also includes an analyzer to analyze the historical project data to generate models for a proposed project cycle time. Additionally, the system includes a user interface to select one model for the proposed project cycle time, wherein the selected model includes linear sub-models corresponding to a historical data range, and apply proposed project data to one linear sub-model corresponding to a proposed data range to predict the proposed project cycle time. Furthermore, the system captures proposed project data and obtains additional project data to update the selected model. The models provide for the accurate prediction of cycle times, or project costs, in an enterprise development environment.

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Overland Park, KS, United States of America

Paul R Sapenaro