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Earned ScheduleEarned Schedule…an extension to EVM theory…an extension to EVM theory
Walt LipkeSoftware Division
Tinker AFBwalter.lipke@tinker.af.mil
(405) 736-3341
E.V.A. - 10 Symposium
May 17-20, 2005 London, England
Kym HendersonEducation Director
PMI Sydney, Australia Chapterkym.henderson@froggy.com.au
61 414 428 537
2
PurposePurpose
To discuss and encourage the application of a new method of schedule analysis derived from Earned Value Management, termed “Earned ScheduleEarned Schedule.”
3
OverviewOverview
• The Problem with EVM• Earned Schedule Concept• Applications• Status & Future• Summary
The ProblemThe Problem
EVA-10 SymposiumMay 18-20, 2005London, England
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Earned Value BasicsEarned Value Basics
Time
$
BCWSBCWPSPI =
ACWPBCWPCPI=
BACBCWS
ACWP
BCWP
SVCV
6
• Traditional schedule EVM metrics are good at beginning of project– Show schedule performance trends
• But the metrics don’t reflect real schedule performance at end– Eventually, all “budget” will be earned as the work is completed,
no matter how late you finish• SPI improves and ends up at 1.00 at end of project• SV improves and ends up at $0 variance at end of project
– Traditional schedule metrics lose their predictive ability over the last third of project
• Impacts schedule predictions, EAC predictions
•• Project managers don’t understand schedule Project managers don’t understand schedule performance in terms of budgetperformance in terms of budget– Like most of us!
So, what’s the problem?So, what’s the problem?
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Earned ValueEarned ValueCost and Schedule VariancesCost and Schedule Variances
+$
-$
001 02
CV = BCWP - ACWP SV = BCWP - BCWS
Note: Project completion was scheduled for Jan 02, but completed Apr 02.
J F M A M J J A S O N D J F M A
CVSV
CV = BCWP - ACWP SV = BCWP - BCWS
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Earned ValueEarned ValueCost and Schedule Performance IndicesCost and Schedule Performance Indices
0.0
0.5
1.0
1.5
2.0
J F M A M J J A S O N D J F M A
CPISPI
01 02
Note: Project completion was scheduled for Jan 02, but completed Apr 02.
BCWSBCWPSPI =
ACWPBCWPCPI =
IND
EX V
ALU
E
Earned ScheduleEarned ScheduleConceptConcept
EVA-10 SymposiumMay 18-20, 2005London, England
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Earned Schedule ConceptEarned Schedule Concept
BCWSBCWPSPI($) =
ATESSPI(t) =
$
Time
BCWS
BCWP
Projection of BCWPonto BCWS
7ATBCWS(May) - BCWS(June)
BCWS(May) - BCWP($) 5 ES
June of Portion May of AllES
=
+=
+=
J J JF M MA A S O N
BCWSBCWPSV($) −=
ATESSV(t) −=
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Schedule Variance ComparisonSchedule Variance Comparison
-400
-300
-200
-100
0
J F M A M J J A S O N D J F M-3
-2
-1
0
0
20
40
60
80
100
J F M A M J J A S O N D J F M0
0.2
0.4
0.6
0.8
1
SV($) SV(t)
Early Finish Project
Late Finish Project
$ Mo
$ Mo
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Schedule Performance Index Schedule Performance Index ComparisonComparison
0.98
1.00
1.02
1.04
1.06
1.08
1.10
1.12
J F M A M J J A S O N D J F M
0.70
0.80
0.90
1.00
1.10
1.20
1.30
J F M A M J J A S O N D J F M
SPI($) SPI(t)
Early Finish Project
Late Finish Project
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Earned Schedule IndicatorsEarned Schedule Indicators
•• Key PointsKey Points::–– ES Indicators constructed to behave in an ES Indicators constructed to behave in an
analogous manner to the EVM Cost Indicators, analogous manner to the EVM Cost Indicators, CV and CPICV and CPI
–– SV(t) and SPI(t) are SV(t) and SPI(t) are notnot constrained by BCWS constrained by BCWS calculation referencecalculation reference
–– SV(t) and SPI(t) provide SV(t) and SPI(t) provide durationduration based based measures of schedule performancemeasures of schedule performance
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SV($) versus SV(t)SV($) versus SV(t)BCWS
Earned Schedule (ES)
BCWP
Actual TimeActual Time
SV(t)
$
SV
• Earned schedule metrics relate work performed to actual time, not work scheduled
• Retain utility over time• Only return to 0 or 1.00 where “on time” completion achieved
• Earned schedule metrics relate work performed to actual time, not work scheduled
• Retain utility over time• Only return to 0 or 1.00 where “on time” completion achieved
ApplicationsApplications
EVA-10 SymposiumMay 18-20, 2005London, England
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ES Applied to Real Project Data:Late Finish Project: SV($) and SV(t)
Commercial IT Infrastructure Expansion Project Phase 1 Cost and Schedule Variances
at Project Projection: Week Starting 15th July xx
-160
-140
-120
-100
-80
-60
-40
-20
0
20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
Elapsed Weeks
Dol
lars
(,00
0)
-16
-14
-12
-10
-8
-6
-4
-2
0
2
Wee
ks
CV cum SV cum Target SV & CV SV (t) cum
Stop wk 19
Re-start wk 26Sched wk 20
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Early Finish Project: Early Finish Project: SV($) and SV(t)SV($) and SV(t)
Commerical IT Infrastructure Expansion Project: Phases 2 & 3 CombinedCost and Schedule Variances
as at Project Completion: Week Starting 9th October xx
-25.0
-15.0
-5.0
5.0
15.0
25.0
35.0
45.0
55.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Elapsed Weeks
Dol
lars
($,0
00)
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
Wee
ks
Target SV & CV CV cum SV ($) cum SV (t) cum
Stop wk 16
Re-start wk 19
Sched wk 25
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IEAC(t) Predictions using IEAC(t) Predictions using ESES Techniques: Techniques: Weekly Plots of IEAC(t) Weekly Plots of IEAC(t)
Late Finish Project ExampleLate Finish Project Example
Commercial IT Infrastructure Expansion Project Phase 1Earned Schedule, Independent Estimate At Completion (time) - IEAC(t)
as at Project Completion: Week Starting 15th July xx
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
Actual Time (Weeks)
Dur
atio
n (W
eeks
)
Planned Schedule Earned Schedule cum IEAC(t) PD/SPI(t)
Stop wk 19 Re-start wk 26
Plan Dur wk 20
19
IECD Predictions using IECD Predictions using ESES Techniques: Techniques: Weekly Plots ofWeekly Plots of
Independent Estimate of Completion DateIndependent Estimate of Completion Date
Commercial IT Infrastructure Expansion Project Phase 1Earned Schedule, Independent Estimates of Completion Date (IECD)
as at Project Completion: Week Starting 15th July xx
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
Actual Time (Weeks)
Dur
atio
n (W
eeks
)
27 Jan 90
10 Feb 90
24 Feb 90
10 Mar 90
24 Mar 90
07 Apr 90
21 Apr 90
05 May 90
19 May 90
02 Jun 90
16 Jun 90
30 Jun 90
14 Jul 90
28 Jul 90
Planned Schedule Earned Schedule cum Planned Completion Date Independent Estimate of Completion Date
Stop wk 19 Plan Dur wk 20Compl Apr 7
Re-start wk 26
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ES vs EVM ComparisonES vs EVM Comparison
Earned Schedule Earned Value
SV(t) and SPI(t) valid for entire project, including early and late finish
SV($) and SPI($) validity limited to early finish projects
Duration based predictive capability analogous to EVM’s cost based indicators
Limited prediction capabilityNo predictive capability after planned completion date exceeded
Facilitates Cost – Schedule Management (using EVM and ES)
EVM Management focused to Cost
Status & FutureStatus & Future
EVA-10 SymposiumMay 18-20, 2005London, England
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TimeTime--Based Schedule Measures Based Schedule Measures ––An Emerging EVM PracticeAn Emerging EVM Practice
• Inclusion of Emerging Practice Insert into PMI - EVM Practice Standard– Dr. John Singley, VP of CPM
• Included in Box 3-1 of EVM Practice Standard– Describes basic principles of
“Earned Schedule”– Provides foundation for further
development of and research intended to result in Earned Schedule acceptance as a valid extension to EVM
• EVM Practice Standard released at 2004 IPMC Conference
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Early AdoptersEarly Adopters• Incorporation of ES into EVM Instruction
– Several instruction sources now offer ES “as part of EVM”
• Requests for information and ES calculator– Calculator provided freely to > 50 requestors
• Tool vendor interest• Growing evidence of use on real projectsreal projects
– Evidence of use in a number of countries• USA, Australia, Sweden, Belgium …
– Applications across weapons programs, construction, software development, …
– Range of project size from very small and short to extremely large and long duration
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Foreseen Uses of Foreseen Uses of Earned ScheduleEarned Schedule
• Enables independent evaluation of schedule estimates: ETC(t), EAC(t)– Client, Contractor, Program and Project Manager ….
• Facilitates insight into network schedule performance– Duration based Schedule indicators– Identification of impediments/constraints and potential
future rework– Evaluation of adherence to plan
• Improvement to Schedule and Cost prediction– Client, Contractor, Program and Project Manager ….
• Application of direct statistical analysis of schedule performance
SummarySummary
EVA-10 SymposiumMay 18-20, 2005London, England
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SummarySummary• Derived from EVM data … only• Provides time-based schedule indicators• Indicators do not fail for late finish projects• Application is scalable up/down, just as is EVM• Schedule prediction is better than any other EVM
method presently used– SPI(t) behaves similarly to CPI– IEAC(t) = PD / SPI(t) behaves similarly to
IEAC = BAC / CPI
•• Facilitates bridging EVM to the scheduleFacilitates bridging EVM to the schedule
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ReferencesReferences1. “Schedule is Different,” The Measurable News,
March & Summer 2003 [Walt Lipke]2. “Earned Schedule: A Breakthrough Extension to Earned Value Theory?
A Retrospective Analysis of Real Project Data,”The Measurable News, Summer 2003 [Kym Henderson]
3. “Further Developments in Earned Schedule,”The Measurable News, Spring 2004 [Kym Henderson]
4. “Connecting Earned Value to the Schedule,” The Measurable News, Winter 2004 [Walt Lipke]
5. “‘Forecasting Project Schedule Completion’ by Using Earned Value Metrics”Presentation by Ing. Stephan Vandevoorde, Senior Project Manager, Fabricom Airport Systems, Belgium
6. “Earned Schedule in Action”, Publication pending, [Kym Henderson]
http://sydney.pmichapters-australia.org.au/Click “Education,” then “Presentations and Papers” for .pdf copies, except (6)