Earned Schedule Training
Earned Schedule Training Earned Schedule Training
Foreseen Uses of Earned 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 EVA-11 Jun 12-17, 17, 2006 Copyright 2006 Lipke & Henderson 60
0,10 0,05 0,00 -0,05 -0,10 -0,15 -0,20 3 Research Efforts (2/3) Extracted results from [8]: Forecast Accuracy and the Completion of Work Simulation runs performed: 1 run project finish ahead of schedule, e, 1 run projects finish behind Mean Percentage Error (MPE) for early finish projects 0%-30% 30%-70% 70%-100% PD/SPI PD/SPI(t) Plans are made to present the research report “A simulation and evaluation of earned value metrics to forecast the project duration” at the 22 nd PMI-CPM Spring Conference 2006. [8] Vanhoucke Mario, Vandevoorde Stephan, A simulation and evaluation of earned value metrics to forecast the project duration , Working Paper 2005/317, July 2005, Ghent University 0,10 0,05 0,00 -0,05 -0,10 Mean Percentage Error (MPE) for late finish projects 0%-30% 30%-70% 70%-100% PD/SPI PD/SPI(t) IPMC 2005 Fall Conference - ES Practice Symposia Final 9 π Stephan Vandevoorde
- Page 9 and 10: Earned Value Management Schedule In
- Page 11 and 12: EVM Schedule Indicators • SV & SP
- Page 13 and 14: Introduction to Earned Schedule EVA
- Page 15 and 16: Earned Schedule Metrics • Require
- Page 17 and 18: Earned Schedule Indicators • Sche
- Page 19 and 20: SV Comparison 100 80 Early Finish P
- Page 21 and 22: Earned Schedule Predictors • Can
- Page 23 and 24: Earned Schedule Terminology Status
- Page 25 and 26: Earned Schedule Key Points • ES I
- Page 27 and 28: ES Applied to Real Project Data: La
- Page 29 and 30: Early Finish Project: SV($) and SV(
- Page 31 and 32: Prediction Comparisons EVA-11 Jun 1
- Page 33 and 34: IEAC(t) Prediction Comparison Early
- Page 35 and 36: EVA-11 Jun 12-17, 17, 2006 IEAC(t)
- Page 37 and 38: IECD Predictions using ES Technique
- Page 39 and 40: 2 My Experience Summarised • Sche
- Page 41 and 42: Earned Schedule Calculator Earned S
- Page 43 and 44: Interpolation Error EVA-11 Jun 12-1
- Page 45 and 46: Interpolation Error $$ ES(calc) BCW
- Page 47 and 48: Interpolation Error • After a few
- Page 49 and 50: BREAK - 15 Minutes EVA-11 Jun 12-17
- Page 51 and 52: Exercise # 1 • Complete Early & L
- Page 53 and 54: ES Exercise - Worksheet Year 01 Yea
- Page 55 and 56: ES Exercise - Answers Year 01 Year
- Page 57 and 58: Early Adopters • EVM Instructors
- Page 59: Available Resources • PMI-Sydney
- Page 63 and 64: Summary - Basic • Derived from EV
- Page 65 and 66: BREAK - 15 Minutes EVA-11 Jun 12-17
- Page 67 and 68: Analysis Tool Demonstration EVA-11
- Page 69 and 70: ES and Re-Baselining EVA-11 Jun 12-
- Page 71 and 72: Earned Schedule - Re-Baseline Examp
- Page 73 and 74: Critical Path Study EVA-11 Jun 12-1
- Page 75 and 76: EVA-11 Jun 12-17, 17, 2006 The Sche
- Page 77 and 78: To further compound schedule comple
- Page 79 and 80: Case Study Project • Commercial s
- Page 81 and 82: Schedule Management • Weekly sche
- Page 83 and 84: • Initial expectation EVA-11 Jun
- Page 85 and 86: The IECD vs Critical Path Predictor
- Page 87 and 88: Questions of Scale • We know that
- Page 89 and 90: Final Thoughts • ES is expected b
- Page 91 and 92: Schedule Analysis with EVM? • The
- Page 93 and 94: Earned Schedule Bridges EVM to “R
- Page 95 and 96: BREAK - 15 Minutes EVA-11 Jun 12-17
- Page 97 and 98: Earned Value Research • Most rese
- Page 99 and 100: EVA-11 Jun 12-17, 17, 2006 Discussi
- Page 101 and 102: Schedule Adherence EVA-11 Jun 12-17
- Page 103 and 104: Schedule Adherence • Result from
- Page 105 and 106: Schedule Adherence • Characterist
- Page 107 and 108: Effective Earned Value Effective EV
- Page 109 and 110: Effective EV Relationships • Rewo
0,10<br />
0,05<br />
0,00<br />
-0,05<br />
-0,10<br />
-0,15<br />
-0,20<br />
3 Research Efforts (2/3)<br />
Extracted results from [8]: Forecast Accuracy and the Completion of<br />
Work<br />
Simulation runs performed: 1 run project finish ahead of schedule, e, 1 run projects finish behind<br />
Mean Percentage Error (MPE)<br />
for early finish projects<br />
0%-30% 30%-70% 70%-100%<br />
PD/SPI<br />
PD/SPI(t)<br />
Plans are made to present the research report “A simulation and<br />
evaluation of earned value metrics to forecast the project duration” at the<br />
22 nd PMI-CPM Spring Conference 2006.<br />
[8] Vanhoucke Mario, Vandevoorde Stephan, A simulation and evaluation of earned value metrics to<br />
forecast the project duration , Working Paper 2005/317, July 2005, Ghent University<br />
0,10<br />
0,05<br />
0,00<br />
-0,05<br />
-0,10<br />
Mean Percentage Error (MPE)<br />
for late finish projects<br />
0%-30% 30%-70% 70%-100%<br />
PD/SPI<br />
PD/SPI(t)<br />
IPMC 2005 Fall Conference - ES Practice Symposia Final<br />
9 π Stephan Vandevoorde
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