The document describes a tool developed by NASA to measure schedule performance by comparing two project schedules. The tool extracts schedule data from MS Project files to calculate schedule variance, performance index, and cost performance index at the task and project levels. These metrics are designed to assess whether the project is earning planned duration and completing tasks within planned timeframes. The tool is still being refined but provides a way to measure schedule performance without requiring detailed resource cost data.

1. Measuring Schedule Performance
NASA Project Management Challenge 2011
8 - 10 February 2011
Tony Harvey
 Los Angeles  Washington, D.C.  Boston  Chantilly  Huntsville  Dayton  Santa Barbara
 Albuquerque  Colorado Springs  Ft. Meade  Ft. Monmouth  Goddard Space Flight Center  Ogden  Patuxent River  Silver Spring  Washington Navy Yard
 Cleveland  Dahlgren  Denver  Johnson Space Center  Montgomery  New Orleans  Oklahoma City  San Antonio  San Diego  Tampa  Tacoma  Vandenberg AFB
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2. Acknowledgements
 NASA JSC, Constellation Mission Operations Project funded the
concept development and tool development
 Terri Blatt for her support in applying the technique to the MOP
PP&C environment
 Greg Hay for keeping monthly revisions of the MOP schedule and
providing them for use in testing the schedule comparison tool
 Mike Stelly for his help with the presentation content
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3. Overview
 What is Schedule Performance?
 Purpose: develop methods/techniques to analyze schedule
performance over time
 Development to date consists of two pieces:
Performance Metrics and Toolset for analyzing data
 Toolset takes two schedules and extracts appropriate data
 MS Project-based schedules
 Prototype stage of development
 Batch program that created an Excel style tab-delimited text output
 Excel macros to format the spreadsheet for easy viewing
 Prototype Desktop program for immediate display and optional saving to an Excel
file
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4. What is Schedule Performance?
and Why do we need more metrics?
 The collection of project cost performance measures based on
actual resource cost is often made difficult by inaccurate or missing
resource cost data
 Yet even basic schedules includes quantitative data, which can be
used in measuring schedule performance. This includes:
 Task start and end dates
 Task durations
 Task completion assessment
 The VALUE expressed in all schedules is in the TIME COST
(duration) of the tasks
 Using two schedules in a comparison process provides
 A statement of planned activity, in the earlier schedule
 A statement of performed activity, in the later schedule
 Schedule Performance is simply “measuring a project’s ability to
complete its planned activities in a given timeframe”
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5. Schedule Performance,
Definition of Terms
 Paralleling the traditional earned value approach to performance
measurements we can define terms for measuring our schedule
performance against the plan as follows:
 Planned Duration Of Work Scheduled (PDWS)
 Original planned duration of activities
 Planned Duration of Work Performed (PDWP)
 Earned duration of completed activities
 Actual Duration of Work Performed (ADWP)
 Actual duration of completed activities
Schedule 1
Original plan is for 10
days, therefore
PDWS=10
Schedule 2
Completed 100% of the 10 Activity took 12 days to
day planned activity, therefore complete, therefore
PDWP=10 ADWP=12
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6. Schedule Earned Value
Metrics
 Based on the performance measures a number of metrics can be
calculated
 Schedule Variance for Duration (SVd): PDWP - PDWS
 The difference between earned duration and planned duration
 Negative values imply a schedule slip
 Schedule Performance Index for Duration (SPId): PDWP/PDWS
 Schedule efficiency factor representing the relationship between the earned
duration and the planned duration
 Values less than 1.0 indicate a performance shortfall
 Schedule Cost Performance Index (SCPI) : PDWP/ADWP
 A Schedule cost efficiency factor representing the relationship between the
earned duration and the actual duration
 Values less than 1.0 indicate a cost (duration) overrun
If PDWS=10, PDWP=10, and ADWP=12, then
Schedule Variance (SVd): PDWP – PDWS = 10 - 10 = 0
- Interpretation: The scheduled task is earning value on schedule
Schedule Performance Index (SPId): PDWP/PDWS = 10 / 10 = 1.0
- Interpretation: The scheduled task has earned value perfectly against its planned value
Schedule Cost Performance Index (SCPI): PDWP/ADWP = 10/12 = .833
- Interpretation: The scheduled task took longer (cost more) to complete than originally planned
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7. Project Level Measures,
A Simple Example
Schedule 1
Task 1 Task 2 Task 3 Task 4 Overall Project
PDWS: 10 PDWS: 10 PDWS: 8 PDWS: 2 PDWS: 30
PDWP: 10 PDWP: 8 PDWP: 7 PDWP: 0 PDWP: 25
ADWP: 12 ADWP: 10 ADWP: 8 ADWP: 2 ADWP: 32
Schedule 2
Schedule Variance (SVd): PDWP – PDWS = 25-30 = -5
- Interpretation: The cumulative effect of all schedule tasks analyzed are 5 days behind schedule
(not to be interpreted as the overall project is 5 days behind schedule)
Schedule Performance Index (SPId): PDWP/PDWS = 25/30 = .83
- Interpretation: The project has currently earned 83% of the duration that it had planned to-date
Schedule Cost Performance Index (SCPI): PDWP/ADWP = 25/32 = .78
- Interpretation: Tasks are taking longer to complete than originally planned
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8. Why Create a Schedule Comparison
Tool from Scratch?
 There are no existing tools that create these performance measures
 We were motivated to build a tool that could be used for comparing
ANY two schedule instances from the same project
 Performance measures can be output in a user friendly format (Excel)
or directly to a database
 Comparing the current schedule against the original schedule provides
performance measures for the project up to the current schedule’s
status date (Data Date)
 Using schedules with monthly Data Date intervals will provide
performance measures for that month interval
 Monthly performance measures can be used for performance trending
 Performance Indices can be used for duration projections and schedule
confidence level analyses
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9. Creating a
Schedule Comparison
Tool
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10. Key Requirements for our
Schedule Comparison Tool
 Use any two revisions of a project’s schedule
 Create output that “aligns” the two schedules at the task level
 Tasks are aligned by Task Name
 Create Performance Measures for each task
 Create Performance Measures for the project
 Retain the schedule hierarchical structure
 Schedules are by their nature organized in a hierarchical structure of
summary tasks and regular tasks
 Create Performance Measures at each Summary task level
 Allows performance measures to be used to reflect the task
organization, as modeled in the schedule hierarchy (project teams?,
project phases?)
 Create data capable of being stored in a database
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11. Real World Data
Summary
Performance
Metrics
Task
Schedule 1 Performance
Schedule 2
Structure Metrics
Schedule 1 Task Data
Projected
Task Data Durations
using SCPI
Project
Performance
Indexes
Interpretation of Project Metrics
•All currently analyzed tasks are cumulatively behind schedule
by 61.32 days.
•Analyzed tasks have earned 92.1% of the duration they should
have earned
•Tasks are being accomplished at a 65.5% efficiency rate
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12. Current Issues &
Future Development
 Current Issues
 Metrics and process
 SPId tends toward 1 as task nears completion
 May exceed 1 if task finishes early
 SPId subject to how scheduler determines “% complete” field
 SCPId is used for new duration estimate
 SCPI (PDWP/ADWP) can be zero when task is in progress
 Tool
 Uses task names as the identifier to compare tasks
 Renamed tasks are not comparable unless new name “contains” old name
 Changes in schedule hierarchy makes analysis difficult
 Tool option allows looking one level deeper
 Added tasks are ignored
 Deleted tasks are excluded from performance metrics
 Future Development
 Data capture for trending analysis
 Extraction of task “confidence measures” (low, mode, high duration)
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13. Conclusions
 Strengths
 Does not require resource cost data for performance measures
 Allows ANY two revisions of a schedule to be compared
 Creates Task, Summary Task and Project-level performance measures
 Summary Task performance indices identify items needing attention
 Weaknesses
 Relies on project percent complete measures from the schedules
 New (projected) duration estimation function needs refining
 Conclusion
 Useful performance measures can be obtained from basic schedule data
 Performance indices are useful focusing functions
 Schedule comparison provides an earned value (duration) perspective
without an EVMS
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