Data-Driven Project Management: Project Metrics That Matter

Course details

Many companies are shifting toward data-driven decisions for their operations, as well as their projects. In this course, project management expert Cyndi Snyder Dionisio brings together all the formulas, metrics, and related strategic thinking that you need to bring data-driven decision-making to project management. Cyndi explains that the focus of project management is evolving from outputs to outcomes, and that to measure outcomes, you need to select the appropriate metrics and KPIs. She walks you through business metrics, work metrics, schedule metrics, and more, showing you how to make effective use of each. Cyndi goes over forecasting metrics, as well as risk metrics, then covers qualitative measures, best practices, and tips on avoiding three measurement pitfalls. She concludes by breaking down the requirements so you know what you must have, should have, could have, and won’t have to make the transition to data-driven project management.

Concepts

0. Introduction

01 - What is data-driven project management
02 - Selecting project metrics that matter

1. Collecting and Analyzing Business and Work Data

03 - Business metrics - Net present value
04 - More business metrics
05 - Work metrics

2. Collecting and Analyzing Schedule Metrics

06 - Schedule metrics for agile management - Velocity and burn charts
07 - Schedule metrics for agile management - Cumulative flow diagrams
08 - Schedule metrics for critical path management

3. Collecting and Analyzing Cost and Resource Data

09 - Cost metrics - Introduction to earned value management
10 - Earned value metrics - Schedule variances and indexes
11 - Earned value metrics - Cost variances and indexes
12 - Resource metrics for cost performance

4. Forecasting Metrics

13 - Cost forecasting with earned value metrics
14 - Schedule forecasting

5. Collecting and Analyzing Risk Data

15 - Risk metrics - Risks and impediments
16 - Risk metrics - Expected monetary value and decision trees
17 - Risk metrics - Establishing and managing risk reserve

6. Other Data Considerations

18 - Qualitative measures for stakeholder satisfaction
19 - Best practices for sharing data
20 - Avoiding three measurement pitfalls

Conclusion

21 - MoSCoW for data-driven project management