Data Analysis and Project Health

Kenneth has 14 years of healthcare experience in government and private industry. Over eight years of experience managing healthcare IT projects, operations, contracts, and personnel. His work experience includes project management, contracts and procurements, data analysis, claims adjudication, business writing, and business process modeling. Kenneth was certified in 2006 as a Project Management Professional.

  Decision Making   Leadership   Risk Management   ProjectsAtWork  

Project data analysis should go beyond simply churning out schedules, status reports and gantt charts. With careful attention to the quality and reliability of the data collected, you can zero in on issues and risks that may jeopardize the outcome of your project.

Data analysis in project management is often limited to churning out project schedules, status reports, and earned value measures. While those things are certainly important, there are many other areas that can benefit from data analysis, particularly the overall health of the project.

When reviewing the overall health of a project, two primary areas that need data analysis are the project plan and risks and issues. While looking at these areas, the project manager should keep in mind one of the key principles of data analysis — garbage in yields garbage out. If the data collected is not thoroughly tested for reliability, then the end result of the analysis will not be valid. To protect the project from a dubious result, the data should be taken through multiple quality checks and the analysis should be reviewed by peers familiar with the data and the project.

The Project Plan

There are many ways to analyze the project plan, such as earned value, the critical path, lead and lag times, so on and so forth. When looking for a way to analyze the data in the project plan for a project, the way in …

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