Next UMD PM Symposium: May 10-11, 2018 NewsPolicies & SupportContact

Why ENCE 667

In order to control a project and keep it on budget and schedule, we need to have a quantified sense of where the project is … how is it doing, is it on time, is it on budget, are the deliverable's being delivered? This requires an understanding of measurement theory, statistics, and other tools for assessing and quantifying project performance.

ProfessorGregory Baecher, PhDGregory Baecher, PhDTAQianli Deng, MSQianli Deng, MSStats Credits 3 Offered Next* Spring, Fall Online Prequisite Permission


Business Intelligence

Big data and the statistical evaluation of business performance has revolutionized the engineering industry. We examine these trends explore how business intelligence can be used in project management.

Bayesian statistical methods

Naturally, business intelligence and big data requires a familiarity with basic statistical thinking. One of the most important concepts in modern business intelligence is Bayesian thinking.

Key performance indicators

Most project performance metrics address the details other project, but we also need indicators of company performance. These are usually called, key performance indicators and coming a variety of styles.

Earned value management

Earned value management is a modern and widely used approach to tracking project schedule and costs. This method originated in US federal procurement's but is now widespread and industry.

How to measure anything and measuring intangibles

A great many things in project management appeared to have no obvious metrics or scales, and yet we need to measure them. There are many clever ways to do so, and we review some of them.

Scoring algorithms

The way project managers define scales is often ad hoc and misleading. There are theoretically correct ways to construct scoring algorithms, which we review.

Quality control and assurance

Earned value management and other engineering project management tools tend to focus on cost and schedule, yet quality is equally important. Most quality control insurance metrics arise in manufacturing and not in the project industries. We explore how quality metrics can be developed for projects.

Financial metrics

When judging investment decisions in new projects we rely on a variety of financial metrics, some of which are covered in traditional engineering economics courses, but there are variety of financial metrics that go beyond simple engineering economics.


Offered Next: Spring, Fall Online*
Week 1Introduction
  • Metrics and measurement
Week 2Work breakdown structues
  • Project networks
  • Framework for project control
Week 3Project scheduling
  • Cost weighted schedules
  • AOS, AON, bar charts, precedence diagrams
  • CPM & PDM calculations
Week 4Earned value management
  • Project control
  • Integrating scope, time, & cost
  • What's wrong with EVM
  • Reporting variances
Week 5Earned schedule & resource management
  • Smoothing resource profiles
  • scheduling with limited resources
  • Time - cost tradeoffs
  • Optimization
Week 6Quality management
  • The ISO 9000 standard
Week 7Quality assurance & commissioning
  • Quality metrics
  • Insurance metrics
Week 8Measurement & key performance indicatorsWeek 9Measuring intangiblesWeek 10Subject matter experts & expert judgementWeek 11Reasoning with sparse informationWeek 12Risk management metricsWeek 13Miscellaneous & summary

*All course content, including schedule, topics, and books are subject to change semester-to-semester. Not all books on this page may be required readings and additional readings may be assigned. Please check the UMD Schedule of Classes for most up to date semester offerings. Instructors give students specific semester details once they are enrolled.