Forecasting Schedule Delays in IT Project Management Using Predictive Analytics Model

IT spending worldwide is projected to continue its growth, whereby using new technologies has become a significant factor in success rates of many companies. Moreover, IT projects are becoming more complex and more difficult to manage, as they involve uncertainty in terms of objectives, project timelines and associated cost. There is a significant disconnect between the tools available to project managers and the information generated across the entire project management lifecycle. Currently, there is a lack of real-time data for project managers and project stakeholders to make decisions, which leads to project cost overruns, schedule delays or complete project failures. The research established a need for a data-centric approach to IT project management, where historical data can be analyzed and used to make decisions during the project lifecycle. This research proposed a predictive analytics model to address schedule delays so that better decisions can be made to ensure project success. Specifically, this model presents an ability to forecast initiation time for IT projects based on presence of various identified project issues. This research assisted in better understanding of the causes behind schedule delays by providing cluster analysis tool, which reveals delays in schedule within various process areas of project initiation phase. By utilizing the proposed model in this research in the preliminary stages of project initialization, project stakeholders would be able to forecast how long a project will take to start. This model along with the cluster analysis tool can be used in the beginning stages of project lifecycle, so that the early identification of potential problems allows for the making of the necessary adjustments.

Author

• Mendenhall, Anya

Language

• en

Keyword

• cluster analysis
• random forests
• predictive analytics

Date created

• 2018

Type of Work

• Dissertation

License

• All rights reserved

Rights statement

• In Copyright

GW Unit

• Engineering Management

Degree

• D.Engr.

Advisor

• Guillaume-Joseph, Gina

Committee Member(s)

• Malalla, Ebrahim
• Rose, Nadejda
• Etemadi, Anirhossein
• Guillaume-Joseph, Gina

Persistent URL

•  https://scholarspace.library.gwu.edu/etd/44558d50p