Measuring Integral Earned Schedule (IES) · IEScum = X + [( ΣAUEV%t– Σ AUPV%x) / ( Σ AUPV%x +1...
Transcript of Measuring Integral Earned Schedule (IES) · IEScum = X + [( ΣAUEV%t– Σ AUPV%x) / ( Σ AUPV%x +1...
Measuring Integral Earned Schedule (IES) Measuring Integral Earned Schedule (IES) and Predicting the Project's Final and Predicting the Project's Final
Completion Duration: Completion Duration: The Application of Kinematics Approach to The Application of Kinematics Approach to
Earned Value Management MetricsEarned Value Management Metrics
Mojtaba Zarei-KeshehMojtaba Zarei-Kesheh
[email protected]+44 (0)7828 126738
Presentation for the EVA Europe Geneva Presentation for the EVA Europe Geneva 2009 2009 CERN, Geneva CERN, Geneva -- 2525NovNov20092009
The first annual earned value conference for contin ental Europe
� Traditional and Current EVM methodologies� Introduce the Integral Earned Schedule (IES) Concept� Develop the Schedule Performance Indicators and Predictors
Objective
and Predictors� Comparison of Different Methods
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� On the whole complex construction projects are likely to be finished more than six months late, due to poor time control. (‘Managing the Risk of Delayed Completion in the 21st Century’, CIOB research 2008)
TIME IS NOT MONEY
� Money: if you leave it, it might actually accumulate.� Time: expires at a regular and consistent rate whether you use it or not. (Keith Pikavance, President of CIOB, conference 2008).
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� CPM: The most reliable method to predict theproject’s time dimension (Fleming & Koppelman)� CP analysis as a predictor: too time-consuming &incapable of providing early warning signal due toits retrospective nature.
CPM or EVA?
� C/SCSC & ANSI/EIA 748:� These standards do not define the analysis to beperformed on EVM other than to state cost andschedule variances need to be computed.
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Physical % CompleteIn current project
BAC Schedule % CompletePerformance % Complete
Data Date(DD)
Activity DurationIn project baseline (PMB)
BAC = Budget at Completion
Traditional EVM Data Relationship
BASIC INPUT DATA
DERIVEDDATA
CPI
EV PVAC
SPICV SV
BAC = Budget at CompletionPV = Planned ValueEV = Earned ValueAC = Actual Cost
CV = Cost VarianceCPI = Cost Performance IndexSV = Schedule VarianceSPI = Schedule Performance Index
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SV = EV - PV
SV & SPI in Primavera P6!
SV = EV - PV
SPI = EV / PVEVA Europe 2009Copyright Zarei-Kesheh 2009 7
THE BUDGET-BASED CAMP
(Traditional EV Schedule Metrics:
Budget-based)
SPI(£) = EV / PV
SV(£) = EV – PV = £ ?
At completion (For late finish project):
THE TIME-BASED CAMP(21st Century EV Schedule Metrics:
Time-based)
SPI(t) = ES / AT
SV(t) = ES – AT = Time delay
Two Different EV Camps
At completion (For late finish project):
� SPI(£) ends up at 1!
� SV(£) ends up at £0!
Schedule Variance in units of budget make
no sense!
They behave erratically for projects behind schedule.
At completion (For late finish project):
� SPI(t) does not creep toward 1
� SV(t) does not creep toward £0
Schedule Variance in time units
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�The idea is to identify the point in time where the areaunder planned value curve (AUPV) equals the current areaunder earned value curve (AUEV).
�Integral Earned Schedule (IES) looks at when the
Integral Earned Schedule (IES) Camp“Integration of Time & Cost”
�Integral Earned Schedule (IES) looks at when thecurrent AUEV was to be accomplished.
� The area under PV and EV curves can be computedusing integral approach (trapezoidal rule).
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EV
% o
r P
V%
EV(ATn-1)%
)Integral Approach (Trapezoidal Rule
Time (Periods)
EV
% o
r P
V%
EV(ATn) %
ATn% - ATn-1%
ATn-1 ATn
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� Calculate cumulative values of AUPV% and AUEV% using Integral Approach (Trapezoidal Rule)
� Now other calculations is similar to ES calculation! In Lipke’s ES Calculator:
IES Metrics and Indicators calculation
Lipke’s ES Calculator:�Substitute PVcum with AUPV%cum �Substitute EVcum with AUEV%cum�Substitute ES with IES �Substitute SV(t) with SV(IES) �Substitute SPI(t) with SPI(IES)
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� IES cumulative =
Whole time (months or periods) completed for ΣAUEV% ≥ Σ AUPV% +
Fractional Time Completed (I)
IEScum = X + [(ΣAUEV%t– Σ AUPV%x) / (Σ AUPV%x+1 – Σ AUPV%x)]
(x = whole time (month, period,..) earned ; x+1 = month or period following; t = Time
Integral Earned Schedule (IES) Formula
(x = whole time (month, period,..) earned ; x+1 = month or period following; t = Time
Now)
� Indicators:
� Schedule Variance (IES): SV(IES) = IES – AT
� Schedule Performance Index (IES): SPI(IES) = IES / AT
where: AT: Actual TimeEVA Europe 2009Copyright Zarei-Kesheh 2009 12
Prediction Terminology
Anbari Jacob Lipke Zarei
Planned Value Rate Earned DurationEarned Schedule
Integral Earned Schedule
P.F. = 1IEAC(t)PV1 =
IEAC(t)ED1 = PD + AT (1 -SPI)
IEAC(t)ES1 = IEAC(t)IES1 =
PredictionMethod
P.F. = 1PD - (SV/(BAC/PD)) After PCD:
IEAC(t)ED1 = AT (2 - SPI)
AT + (PD - ES) AT + (PD - IES)
P.F. = SPIIEAC(t)PV2 =
PD / SPI
IEAC(t)ED2 = PD / SPI
After PCD:IEAC(t)ED2 = AT / SPI
IEAC(t)ES2 = PD / SPI(t)
IEAC(t)IES2 = PD / SPI(IES)
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� For labor-intensive projects IES (our integration of time and money) is analogous to estimating work in terms of staff-hours;� Thus: the work duration is estimated by the number of staff available� More people-less time, less people-more time;
Analogous ways to think of integration of time and money (IES)
� More people-less time, less people-more time;� So the value of the work is the product.� IES: the same approach in EVA analysis;� The product of time and money (PV, staff) defines work scope;� The product of EV and time is the work completed.
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� The Real-life Project:� Reporting 100% complete as of Jul 2009� £ 2,208 million pounds contract� Planned Completion Date = Feb09� Actual Completion Date = Jul09
Real-life Project Data
� Actual Completion Date = Jul09� 5 Periods Slip
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-1500
-1000
-500
0
500
-6.0
-4.0
-2.0
0.0
2.0
SV(t)cum SV(EAS)cum Target SV SV(£)cum
Per
iods
SV(IES)cumZarei
Schedule Variance Comparison
-2500
-2000
-10.0
-8.0
0 5 10 15 20 25 30 35 40 45 50 55
Time (Periods)
At period 30, or the 50% completion point, the SV(IES) shows the more reliable and consistent SV trend, it correlates very well. SV(IES) predict also the final delay at this point reliably!
The SV(t) starts to show the real final delay from 97% completion point! Incapability in providing thereal final delay in early /middle stage of project.
SV(IES): always normal & consistent trend
SV(t): upward and downward trends! inconsistent trend
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0.80
0.90
1.00
1.10
1.20
SPI(t)cum SPI(EAS)cum SPI(£)cum Target SPI
Inde
xV
alue
SPI(IES)cumZarei
Schedule Performance Index Comparison
0.50
0.60
0.70
0 5 10 15 20 25 30 35 40 45 50 55
Inde
x
Time (Periods)
SPI(IES): always overall normal & consistent trend
SPI(t): always overall abnormal & inconsistent tren d: Look at the upward and downward trends! Ooops! So confusing for PM!
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� SV(£):
�Expressed in pounds units;
� in the vertical direction
� SV(t):
�Expressed in time units
Schedule Variance
�in the horizontal direction
� SV(IES):
�Expressed in time units
�Consider both vertical and horizontal direction(integration of time and cost together), then looks athorizontal direction ☺
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58
60
62
IEAC(t)PV1Anbari
IEAC(t)ED1Jacob
IEAC(t)ES1Lipke
IEAC(t)EAS1Zarei
Planned Duration Final Duration
Dur
atio
n (P
erio
ds)
P.F. = 1
IEAC(t) IES1
Look at the upward and downward trends! So confusing for PM!
Final Duration Predicting Comparison
48
50
52
54
56
0% 20% 40% 60% 80% 100%
Dur
atio
n (P
erio
ds)
Physical Percent Complete
From 30% Completion point, IEAC(IES1): higher accur acy than others, consistent Early Warning Signal behavior / trend, correct fina l durationOther methods: abnormal, aberrant and inconsistent behavior / trend
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6570
75
80
85
90
IEAC(t)PV2Anbari
IEAC(t)ED2Jacob
IEAC(t)ES2Lipke
IEAC(t)EAS2Zarei
Planned Duration Final Duration
Dur
atio
n (P
erio
ds)
P.F. = SPI,
SPI(t),
SPI(IES) IEAC(t) IES2
Look at the upward and downward trends! No consistency!
Final Duration Predicting Comparison
Seeing is believing!
45
50
55
60
65
0% 20% 40% 60% 80% 100%
Dur
atio
n (P
erio
ds)
Physical Percent Complete
From 13% Completion point (early stage), IEAC(IES2) : begins to show accurate and reliable prediction; consistent behavior and trend, the most accurate result, correct final duration. This is consistent and reliable EARLY WARNING SIGNAL!Other methods: abnormal, aberrant and inconsistent behavior / trend specially in early stage.
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�Time & Cost Integration for assessing and measuring scheduleperformance and predicting final duration;
�IES: Integration of both time and cost together;
� Unique characteristics of the area Under Planned Value curve(AUPV) and area under EV curve (AUEV) in Real Projects (notapplicable for artificial and unrealistic projects);
� SV(IES):
IES Summary
� SV(IES):
�normal & consistent trend from early stage of project;
�capability to predict real final delay of project (EarlyWarning Signal); CONSISTENCY AND ACCURACY
� IES method:
�consistent, stabilized and correct predictive behaviour fromthe early stage of project (Early Warning Signal).
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� Project Managers do not need the predictive results at the latestage of project ☺
� At the late stage, PM cannot take corrective action; everybody isaware of delay ☺
� IES method claims to predict correct final duration from earlystage. Useful info for PMs! That is called: Early Warning Signal!
� IES method:
IES Summary
� IES method:
� provide consistent results (real final delay, final duration) fromearly stage; CONSISTENCY AND ACCURACY
�advance programme control;
�give opportune time to project planners and PMs to takecorrective action.
�The other methods do not have this capability!
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� Mr. Ray Stratton PMP, EVP
for his book that motivated me to walk in EVM world; alsofor his technical advice during my research on EVM/IES;
� Prof. Mario Vanhoucke
for his constant encouragement during my IES research;
� Mr. Walt Lipke
Thank you to ...
� Mr. Walt Lipke
for his technical advice during my work on ESimplementation in Thameslink Programme (London) and foruse of ES Calculator.
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Thank you to ...
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EVA Europe Geneva 2009, CERNL to R: Kym Henderson, Walt Lipke, Mojtaba Zarei-Ke sheh,
Stephan Vandevoorde , Prof. Mario Vanhoucke, Prof. Pierre Bonnal
� Anbari F. (2003) Earned value method and extension. Project ManagementJournal
� Fleming, Q. et al. (2005) Earned value project management, 3rd ed, PMI
� Jacob, D. (2003) Forecasting project schedule completion with earned valuemetrics. The Measurable News (March)
� Jacob, D. et al. (2004) Forecasting project schedule completion with earnedvalue metrics revisited. The Measurable News (Summer)
References
� Lipke, W. (2003) Schedule is different. The Measurable News (March)
� Lipke, W. (2009) Project duration forecasting … a comparison of earned valuemanagement methods to earned schedule. The Measurable News (Issue 2)
� PMI-EVM Practice Standard, (2005), PMI
� Vanhoucke, M. et al. (2006) A simulation and evaluation of earned valuemetrics to forecast project duration. J Oper Res Soc
� Vanhoucke, M. et al. (2006) comparison of different project durationforecasting methods using earned value metrics. International Journal of ProjectManagement 24
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