This document discusses project monitoring and control using earned value analysis (EVA) and burn graphs. It provides an overview of EVA, including its origins, explanations of key EVA concepts and metrics, examples of how to apply EVA, and potential shortcomings. It also covers burn graphs as a visual project monitoring tool, how they can be used in agile projects, and examples of burn graph types. Tools for implementing EVA and burn graphs are listed. The document concludes with potential discussion points about applying EVA and adopting burn graphs.

1. Project Monitoring and
Control with
EVA and Burn Graphs
Guy Davis
Kendra Hamilton
Ed Dantsiguer

2. Agenda
 Origins of EVA
 EVA Explained
 EVA Examples
 Shortcomings of EVA
 Agile side of EVA
 Burn Graphs
 Tools
 Discussion

3. Overview of EVA
 “The essence of [Earned Value Management
Systems] is that some level of detail
appropriate for the degree of technical,
schedule, and cost risk or uncertainty
associated with the program, a target value
….is established.” Paul Solomon 2002.

4. History of EVA
 PERT/Cost (1963)
 DoD Cost/Schedule Control Systems Criteria (C/
SCSC) (1967).
 Government Performance and Results Act (1993),
Federal Acquisition Streamlining Act, Title V (1994),
Clinger-Cohen Act (1996)
 EIA-748-1998 “Earned Value Management System”
 Office of Management and Budget (Circular A-11, Part
7) (2003)

5. Motivation for EVA
 Integrates work, cost, and schedule metrics.
 Early warning signal.
 Driving by looking in the front windshield
instead of the rear view mirror. Statistical
projection.
 U.S. Government requirement.

6. EVA Explained 1/3
 EVA concentrates on project
management and control
Requires a number of tasks to be

performed before utilizing EVA:
 Work Breakdown Structure
Cost (WBS)
 Creation of detailed plan (critical
path plan)
 Includes all activities that have to
Earned be performed, their durations,
Value costs and relative contributions to
Schedule Technical the overall deliverable
Performance

7. EVA Explained 2/3

8. EVA Explained 3/3
 EVA is used to determine current project
performance and estimate/forecast future
project performance
 Based on 3 data points:
Budgeted Cost of Work Performed (BCWP)

Actual Cost of Work Performed (ACWP)

Budgeted Cost of Work Scheduled (BCWS)


9. Budgeted Cost of Work Performed
 Planned (budgeted/estimated) cost of work
that has been completed until this point
 Answers: “How much was performed work
supposed to cost?”
Based on features/activities completed and

the budgeted amount for these features/
activities in the original project plan

10. Actual Cost of Work Performed
 Actual cost of work that has been completed
until this point
 Answers: “What was the actual cost of work
actually performed?”
Based on features/activities completed and

cost of these features/activities in real life

11. Budgeted Cost of Work Scheduled
 Planned (budgeted/estimated) cost of work that was
supposed to be completed
 Answers: “How much work should have been done
and how much was it meant to cost?”
Based on features/activities planned/scheduled and

the budgeted amount for these features/activities in the
original project plan
Budget at Completion (BAC) is the total funds allocated

(budgeted) for this project to complete

12. Derived Metrics
 Schedule Variance (SV)
 SV = BCWP – BCWS
 Compares what is done with what was supposed to be
done
 SV < 0  project is behind schedule
 Cost Variance (CV)
 CV = BCWP – ACWP
 Compares actual project cost with budgeted project
costs
 CV < 0  project is over budget

13. Schedule/Cost Performance Index
 Schedule Performance Index (SPI)
 SPI = BCWP/BCWS
 SPI < 1  project is behind schedule
 Cost Performance Index (CPI)
 CPI = BCWP/ACWP
 CPI < 1  project is over budget
 Cost Schedule Index (CSI)
 CSI = CPI * SPI
 CSI < 1  project is not tracking to plan
 The further away CSI is from 1, the less likely is
successful project recovery

14. Using EVA Metrics in Project
Control 1/2
 Each individual EVA metric is not greatly
useful on its own
Metrics need to be considered as a group

Ex: Just because a project has a CSI of 1

does not imply that the project is doing well – it
may be well ahead of schedule while also
being well ahead of its budget

15. Using EVA Metrics in Project
Control 2/2
 ACWP metric can be used to project future activity
costs/durations
This is called Estimate To Completion (ETC)

The end of the projected ETC curve is

the Estimate At Completion (EAC)
 estimated schedule and cost required to complete the
project based on current productivity and spending
Comparison between EAC and BAC shows is the

project is likely to be on schedule and/or on budget
 Variance at Completion (VAC)  schedule difference
between BAC and EAC

16. Recommended Performance
Metric Values
Per the “U.S. Marine Corps Acquisition Procedures Handbook,” June 1997

17. EVA Task Types
 Discrete Effort
Activities with start and end time that result in

deliverables
 Apportioned Effort
 Effort required to support discrete effort tasks (Ex:
inspections, quality control)
 Proportional to the type/size of discrete effort tasks that
they support
 Level of Effort
Overhead activities with no concrete deliverables (Ex:

management and administrative activities)

18. Crediting Earned Value
 Discrete Effort
Credited upon completion with actual cost and duration

tracked
 Apportioned Effort
 Credited upon completion of related discrete effort
tasks
 Level of Effort
Credited according to plan (regardless of actual cost

and duration)

19. Crediting Earned Value Methods
 Milestone Events
 Weighted Milestone Gates
 Percentage Complete
 Fixed Formula
 Level of Effort
 Percentage Complete and Milestone Gates

20. EVA Example 1/2
 Planned/Scheduled Data:
Duration of 10 months

Includes 10 features with multiple tasks

Budget of $100 million

 Actual After 6 Weeks:
55% of the work has been completed

$85 million has been spent


21. EVA Example 2/2
Earned Value Analysis
200
150
Cumulative Spending
100 BCWS
BCWP
ACWP
ETC
50
0
0 3.75 7.5 11.25 15
Time, Working Weeks

22. Success Factors for EVA
 Quality of the baseline; need to include all
details.
 Take action early based on performance
indicators.
“I hate everything that merely instructs me without
augmenting or directly invigorating my activity”
Goethe

23. Shortcomings of EVA
 Based on past performance; assumes constant rate of
spend and value creation
Assumes a direct relationship between time and cost.

Value measured in technical components, not

expected business value.
Project must be fully defined at outset; the devil is in

the details.
Time required for measuring project’s progress


24. EVA Tools
 Excel
 Welcom “Cobra” http://www.welcom.com/
 Schedulemaker http://www.schedulemaker.com
 Planisware “OPX2” http://www.planisware.com/
 RiskTrak http://www.risktrak.com/index.htm
 Winsight http://www.cs-solutions.com/
 Primavera Systems http://www.primavera.com/

25. EVA compared to Agile
 Full project view vs. Iterative view
 Tasks fully defined vs. Changing requirements
 Attempts to forecast future vs. Determination
of next iteration
 EVA is not suitable for truly “Agile” projects

26. EVA in an Agile/Iterative Project
 Approach 1:
Stories = BCWS

Tasks = BCWS in more detail

Assignments = ACWP

Velocity = BCWP

Testable requirements = 0% or 100% BCWP


27. EVA in an Agile/Iterative Project
 Approach 2:
Do EVA on individual iterations

 Approach 3:
 Generate micro estimations for current iteration
and macro estimations for future iterations

28. Burn Graphs
 Origins of Burn Graphs
Cumulative flow diagrams from lean production

 Goal: to provide a succinct view of progress.
 Allows project sponsors to steer the project.
 Allows scrum master report visually to
stakeholders.
Allows the team to gain experience estimating

by getting direct feedback. (Empowering)

29. Burn-Down Graphs
 Shows remaining estimated effort on item
Usually in ideal engineering time (IET hours)

 Calculated for any level of task abstraction

30. Scrum Backlog Graphs
 Product Backlog Graph
High-level view of overall project progress.

Completion date: work left versus resources

available.
Quantitative tool for making trade-offs.

 Sprint Backlog Graph
Detailed view of a single sprint's progress.

Sprint signatures: compare current with past

results.
First notice of schedule slips seen here.


31. Not always pretty...

32. Burn-up Graphs
 Shows progress on completion of item
Usually displays percentage complete

Just the inverse of a burn-down graph


33. Cumulative Flow Diagrams
 Tracks number of features (and status) over time
 Better for reporting than:
% complete graph of feature milestone percentages

Features completed over time


34. Overview of Burn Graphs
Drawbacks
Benefits
 Metric choice is key
 Easy to compile/track
 Over-simplification?
 Feedback to the team
and status to the Hides dependencies

customer Should be able to

 Highlights: zoom to see levels
Schedule slips  Traditionalists will resist

implementation?
Scope creep


35. Burn Graph Tools
 Open-source
Outreach Project Tool (OPT)

XPlanner

 Commercial
 Version One
MS Excel


36. References
Anderson, David J. “Using Cumulative Flow Diagrams with FDD”. Feature Driven Development. 2003. http://

www.featuredrivendevelopment.com/node/view/515
Anderson, David J. Agile Management for Software Engineering. Prentice Hall. 2003

Alleman, Glen B., Henderson, Michael, “Making Agile Development Work in a Government Contracting

Environment” Proceedings of the Agile Development Conference, IEEE, 2003.
Fleming, Quentin W., Koppelman, Joel M., “Earned Value Project Management: A Powerful Tool for Software

Projects”, Crosstalk, July 1998.
Hayes, Heather, “Using Earned-Value Analysis to Better Manage Projects”, Pharmaceutical Technology,

February 2002.
Howes, Rodney “Improving the Performance of Earned Value Analysis as a Construction Project Management

Tool”, Engineering, Construction and Architectural Management, 2000.
Schwaber, Ken and Mike Beedle. Agile Software Development with Scrum. Prentice Hall. Upper Saddle River,

NJ. 2002
Solomon, Paul J., “Practical Software Measurement, Performance-Based Earned Value,” Crosstalk,

September, 2002.

37. Discussion Points
 Can EVA be applied to agile projects?
 What metrics would you use for burn graphs?
 Would you adopt burn graphs at your
organization?