- What Is Analytics?
- Why Is Analytics Important in Project Management?
- How Can Project Managers Use Analytics in Project Management?
- Project Management Analytics Approach
- Summary
- Key Terms
- Case Study: City of Medville Uses Statistical Approach to Estimate Costs for Its Pilot Project
- Case Study Questions
- Chapter Review and Discussion Questions
- Bibliography
Why Is Analytics Important in Project Management?
Although switching to the data-driven approach and utilizing the available analytical tools makes perfect sense, most project managers either are not aware of the analytical approach or they do not feel comfortable moving away from their largely subjective legacy approach to project management decision-making. Their hesitation is related to lack of training in the analytical tools, technologies, and processes. Most project management books only mention these tools, technologies, and processes in passing and do not discuss them adequately and in an easily adaptable format. Even the Project Management Body of Knowledge Guide (PMBOK), which is considered the global standard for project management processes, does not provide adequate details on an analytics-focused approach.
The high availability of analytical technology today can enable project managers to use the analytics paradigm to break down the processes and systems in complex projects to predict their behavior and outcomes. Project managers can use this predictive information to make better decisions and keep projects on schedule and on budget. Analytics does more than simply enable project managers to capture data and mark the tasks done when completed. It enables them to analyze the captured data to understand certain patterns or trends. They can then use that understanding to determine how projects or project portfolios are performing, and what strategic decisions they need to make to improve the success rate if the measured/observed project/portfolio performance is not in line with the overall objectives.