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If time is money, accuracy pays! An Overview of Past and Future - - PowerPoint PPT Presentation

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If time is money, accuracy pays! An Overview of Past and Future Project Management Research Mario Vanhoucke Ghent University Vlerick Leuven Gent Management School University College London OR-AS Operations Research - Applications and

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SLIDE 1

If time is money, accuracy pays!

An Overview of Past and Future Project Management Research

Mario Vanhoucke

Ghent University Vlerick Leuven Gent Management School University College London OR-AS Operations Research - Applications and Solutions www.or-as.be

Stephan Vandevoorde

Airport Systems Division, Fabricom N.V./S.A.

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SLIDE 2

Mario Vanhoucke - Ghent University

Ghent University University College

The academic world The real world

Vlerick Business School EVM Europe Company Training

RESEARCH PRACTICE

Mario Vanhoucke (PhD) Academic career: Professional career:

Ghent University (Belgium) and University College London (UK) Vlerick Business School (Belgium, Russia, China) Director EVM Europe Partner OR-AS (Belgium)

My own consultancy company

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SLIDE 3

Mario Vanhoucke - Ghent University

Ghent University University College

The academic world The real world

Vlerick Business School EVM Europe Company Training My own consultancy company

RESEARCH PRACTICE

RESEARCH PRACTICE

meets

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SLIDE 4

Mario Vanhoucke - Ghent University

... "To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science." ...

Albert Einstein Scientist Maybe also a Project Manager

QUOTE

Why do we need research?

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SLIDE 5

Mario Vanhoucke - Ghent University

... Professor Vanhoucke's summary chapter in his new book "Measuring Time: . . ." provides an interesting twist to this discussion. ... Professor Vanhoucke's work is shedding a new light on using EVM for me. In retrospect, this has helped me understand better why EVM worked so well in some cases and failed so miserably in others. ...

Tony Barrett Professional Engineer (PE), Earned Value Professional (EVP), Project Management Professional (PMP). LinkedIn Earned Value Management discussion

QUOTE

Why do we need research?

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SLIDE 6

Mario Vanhoucke - Ghent University

Outline

Presentation: “Research meets Practice” Overview of research

  • Published in “Measuring Time”
  • Four EVM hypotheses

Quick preview of future research

  • The 1 mio € project
  • Further integration

Overview of projects

  • Used in the research
  • Different sectors

Quick preview of future work

  • EVM Europe
  • Further collaboration

Fasten your seatbelts

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SLIDE 7

Mario Vanhoucke - Ghent University

  • Main focus on controlling time
  • Four studies
  • Known
  • Earned

Value Management is quirky

  • Earned Schedule is not quirky
  • Schedule Risk Analysis
  • Refresh
  • Project life cycle

Assumptions

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SLIDE 8

Mario Vanhoucke - Ghent University

Project Life Cycle

Concept Static phase Dynamic phase Project delivery Feedback

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SLIDE 9

Mario Vanhoucke - Ghent University

Project Life Cycle

Concept Static phase Dynamic phase Project delivery Feedback

Dynamic Scheduling

Baseline Scheduling Schedule Risk Analysis Project Control From simple PERT/CPM to advanced resource leveling

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SLIDE 10

Mario Vanhoucke - Ghent University

Project Life Cycle

Concept Static phase Dynamic phase Project delivery Feedback From basic simulations to advanced risk profiles

Dynamic Scheduling

Baseline Scheduling Schedule Risk Analysis Project Control

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SLIDE 11

Mario Vanhoucke - Ghent University

Project Life Cycle

Concept Static phase Dynamic phase Project delivery Feedback

Dynamic Scheduling

Baseline Scheduling Schedule Risk Analysis Project Control

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SLIDE 12

Mario Vanhoucke - Ghent University

Dynamic Scheduling

Baseline Scheduling Schedule Risk Analysis Project Control

Project Life Cycle

Concept Static phase Dynamic phase Project delivery Feedback Integration!

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SLIDE 13

Mario Vanhoucke - Ghent University

Understand why EVM works so well in some cases and fails so miserably in others.

Study 1 Concept Static phase Dynamic phase Project delivery Feedback Study 1

static EVM measurement study

Static phase

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SLIDE 14

Mario Vanhoucke - Ghent University

Recognize the dynamic use of EVM information to measure project performance and predict future project behavior.

Study 2 Study 1 Concept Static phase Dynamic phase Project delivery Feedback

static EVM measurement study

Study 2

dynamic EVM measurement study

Dynamic phase

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SLIDE 15

Mario Vanhoucke - Ghent University

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3 Study 1 Study 2 Concept Static phase Dynamic phase Project delivery Feedback

static EVM measurement study dynamic EVM measurement study

Study 3

dynamic project control study

Feedback

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SLIDE 16

Mario Vanhoucke - Ghent University

Recommend a set of best practices to use EVM during project control.

Study 4 Study 1 Study 2 Concept Static phase Dynamic phase Project delivery

static EVM study dynamic EVM study

Study 4

best practices

Study 3

dynamic project control study

Feedback

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SLIDE 17

Mario Vanhoucke - Ghent University

The results

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SLIDE 18

Mario Vanhoucke - Ghent University

Understand why EVM works so well in some cases and fails so miserably in others.

Study 1

Which technique for which project?

Future assumptions

Planned Value Method Earned Duration Method Earned Schedule Method Future = Plan Future = SPI Future = SPI x CPI

Forecasting methods

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

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SLIDE 19

Mario Vanhoucke - Ghent University

Future assumptions

Planned Value Method Earned Duration Method Earned Schedule Method Future = Plan Future = SPI Future = SPI x CPI

Forecasting methods

Understand why EVM works so well in some cases and fails so miserably in others.

Study 1 Future assumptions Forecasting methods

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

Which technique for which project?

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SLIDE 20

Mario Vanhoucke - Ghent University

Understand why EVM works so well in some cases and fails so miserably in others.

Study 1 Future assumptions Forecasting methods

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

Which technique for which project?

Planned Value Method Earned Duration Method Earned Schedule Method Future = Plan Future = SPI Future = SPI x CPI

Accuracy along the completion stage (early, middle or late) Early stages

Low accuracy for all methods

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SLIDE 21

Mario Vanhoucke - Ghent University

Understand why EVM works so well in some cases and fails so miserably in others.

Study 1 Future assumptions Forecasting methods

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

Which technique for which project?

Planned Value Method Earned Duration Method Earned Schedule Method Future = Plan Future = SPI Future = SPI x CPI

Accuracy along the completion stage (early, middle or late) Early stages

Low accuracy for all methods

Middle/late stages

ES method is the best

Mistake starts from

From 50% to 60% completion

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SLIDE 22

Mario Vanhoucke - Ghent University

Understand why EVM works so well in some cases and fails so miserably in others.

Study 1 Future assumptions

Planned Value Method Earned Duration Method Earned Schedule Method Future = Plan Future = SPI Future = SPI x CPI

Forecasting methods

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

Which technique for which project?

The network structure has an impact on the accuracy Close to parallel

EVM won’t work

Close to serial

EVM performs very well

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SLIDE 23

Mario Vanhoucke - Ghent University

Recognize the dynamic use of EVM information to measure project performance and predict future project behavior.

Study 2

0.5 1.0 1.5 2.0 W0 W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11

SPI(t) - unstable

0.5 1.0 1.5 2.0 W0 W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11

SPI(t) - stable

☝On time! ☟Late! Accuracy ≠ Stability

p-factor - schedule adherence

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SLIDE 24

Mario Vanhoucke - Ghent University

Recognize the dynamic use of EVM information to measure project performance and predict future project behavior.

Study 2

!"#$% !"&% !"&$% !"'% !"'$% !"(% !"($% )%

# * ! ! % ' * ! ! % ) ! * ! ! % ) + * ! ! % ) , * ! ! % ) # * ! ! % ) ' * ! ! % + ! * ! ! % + + * ! ! % ! * ! ! % + * ! ! % , * ! ! % # * ! ! % ' * ! ! % ) ! * ! ! % ) + * ! ! % ) , * ! ! % ) # * ! ! % ) ' * ! ! % + ! * ! ! % + + * ! ! % ! * ! ! % + * ! ! % , * ! ! % # * ! ! % ' * ! ! % ) ! * ! ! % ) + * ! ! % ) , * ! ! % ) # * ! ! % ) ' * ! ! % + ! * ! ! % + + * ! ! % ! * ! ! % + * ! ! % , * ! ! % # * ! ! % ' * ! ! % ) ! * ! ! % ) + * ! ! % ) , * ! ! % ) # * ! ! % ) ' * ! ! % + ! * ! ! % + + * ! ! % ! * ! ! % + * ! ! % , * ! ! % # * ! ! % ' * ! ! % ) ! * ! ! % ) + * ! ! % ) , * ! ! % ) # * ! ! % ) ' * ! ! % + ! * ! ! %

!"#$%&'$()%#$*$+"$(,-./0"12*3(

  • ./012%)%
  • ./012%+%
  • ./012%3%
  • ./012%,%
  • ./012%$%
  • ./012%#%
  • ./012%&%

Night shift Night shift Night shift Night shift

Accuracy (EVM) versus stability (p-factor) EVM

Average accuracy

p-factor

Schedule adherence

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SLIDE 25

Mario Vanhoucke - Ghent University

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

When management has a certain feeling of the relative sensitivity of the various activities on the project objective, a better management’s focus and a more accurate response during project tracking should positively contribute to the overall performance of the project.

Mario Vanhoucke Omega - International Journal of Management Science

Effort

The lower the better

Results

The higher the better

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SLIDE 26

Mario Vanhoucke - Ghent University

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

management focus versus accurate response

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SLIDE 27

Mario Vanhoucke - Ghent University

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

management focus versus accurate response

1 2 3 4 5 6

Project network

Uncertainty Monte-Carlo simulation Simulation output

Project schedule Distributions

1 2 3 4 5 6 1 2 3 4 5 6

Uniform distribution Triangular distribution Triangular distribution (with skewness)

1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution

Baseline schedule

1 2 3 4 5 6 1 2 3 4 5 6

Etc...

Criticality index, sensitivity index, cruciality index, schedule sensitivity index, ... Schedule risk analysis

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Mario Vanhoucke - Ghent University

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

management focus versus accurate response management focus

low impact = safe High impact = dangerous

1 2 3 4 5 6 7 8 9 10 25 50 75 100

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Mario Vanhoucke - Ghent University

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

management focus versus accurate response management focus

low impact = safe High impact = dangerous

1 2 3 4 5 6 7 8 9 10 25 50 75 100 1 2 3 4 5 6 7 8 9 10 25 50 75 100

Control No control

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Mario Vanhoucke - Ghent University

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

management focus versus accurate response management focus

1 2 3 4 5 6 7 8 9 10 25 50 75 100

low impact = safe High impact = dangerous

1 2 3 4 5 6 7 8 9 10 25 50 75 100

Control No control

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SLIDE 31

Mario Vanhoucke - Ghent University

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

management focus versus accurate response management focus

1 2 3 4 5 6 7 8 9 10 25 50 75 100

low impact = safe High impact = dangerous

1 2 3 4 5 6 7 8 9 10 25 50 75 100

Control No control

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SLIDE 32

Mario Vanhoucke - Ghent University

1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivity Chart 1 2 3 4 5 6 7 8 9 10 0,25 0,50 0,75 1,00 Sensitivy Action threshold Full control (0th percentile) No control (100th percentile) ! Action threshold 1 2 3 4 5 6 Project network Project schedule Distributions 1 2 3 4 5 6 1 2 3 4 5 6 Uniform distribution Triangular distribution Triangular distribution (with skewness) 1 2 3 4 5 6 Activity 1 Activity 2 Activity 3 Activity 4 Activity 5 Activity 6 25 50 75 100 Criticality Index 25 50 75 100 12/04/08 23/04/08 3/05/08 15/05/08 Completion Time Distribution 1 2 3 4 5 6 1 2 3 4 5 6 Etc... Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Schedule risk analysis Management focus Accurate response

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

management focus versus accurate response

Activity 10

Project Objective Work Item Work Item Work package Work package Work package Work package

Activity 1 Activity 5 Activity 2 Activity 4 Activity 8

Project Objective Work Item

Activity 9 Activity 7 Activity 3 Activity 6

Accurate response

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SLIDE 33

Mario Vanhoucke - Ghent University

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

The network structure has an impact on the EVM accuracy Close to parallel

EVM won’t work

Close to serial

EVM performs very well

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SLIDE 34

Mario Vanhoucke - Ghent University

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

low effort / high results high effort / low results

The network structure has an impact on the SRA accuracy Close to parallel

Low effort → high results

Close to serial

High effort → low results

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SLIDE 35

Mario Vanhoucke - Ghent University

Master the schedule risk analysis technique to support corrective actions during project progress.

Study 3

100% Parallel 100% Serial

IT Research Tunnel Satellite Bridge Construction Water Production Centre Maintenance Airport Infrastructure

low effort / high results high effort / low results

SSI!

PMBOK

SI CI CRU(r) ... SSI!

PMBOK

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Mario Vanhoucke - Ghent University

Recommend a set of best practices to use EVM during project control.

Study 4

Project Objective Work Item Work package Activity Work Item Work Item Work Item Work package Work package Work package Work package Work package Work package Work package Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Project Objective Work Item Work Item

Project performance problem! Which activities are critical and responsible for the problem?

EVM: top-down WBS levels

Project Work item Work package Activities

Project Objective Work Item Work package Activity Work Item Work Item Work Item Work package Work package Work package Work package Work package Work package Work package Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Activity Project Objective Work Item Work Item

Negative effect on project performance? Highly sensitive activities in trouble!

SRA: bottom-up

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SLIDE 37

Mario Vanhoucke - Ghent University

Recommend a set of best practices to use EVM during project control.

Study 4

0% 10% 20% 30% 40% 50%

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Tracking Efficiency Parallel networks Serial networks

Traditional EVM Earned Schedule EVM Schedule Risk Analysis

If time is money, accuracy pays!

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Mario Vanhoucke - Ghent University

Recommend a set of best practices to use EVM during project control.

Study 4

0% 10% 20% 30% 40% 50%

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Tracking Efficiency Parallel networks Serial networks

Traditional EVM Earned Schedule EVM Schedule Risk Analysis Combination

If time is money, accuracy pays!

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Mario Vanhoucke - Ghent University

Research study 1 = accuracy study

Integration of dynamic scheduling

Research study 2 = project success study

Integration of project life cycle

Awarded by IPMA (Rome, Italy) PMI (Brussels, Belgium) American Accounting Association (Denver, US)

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SLIDE 40

Mario Vanhoucke - Ghent University

  • The more than a million euro research project

Concept Static phase Dynamic phase Project delivery Feedback Project success?

Future research

“In projects, there is no substitute for delivery”

Kym Henderson

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Mario Vanhoucke - Ghent University

  • Searching for static and dynamic project drivers to predict and control

the impact of management/contingency reserve on a project’s success

  • Over a million euro project funded by the Flemish Government
  • Synergy between Ghent University (Belgium), University College London (UK) and

George Washington University (USA)

  • Scope
  • Further integration
  • Further validation (Stephan

Vandevoorde)

  • Further commercialization (www.ProTrack.be en www.p2engine.com)

Future research

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SLIDE 42

Mario Vanhoucke - Ghent University

Results (Phase 1) New book

“Project Management with Dynamic Scheduling” available at Springer See: www.or-as.be/bookstore

Preliminary results (Phase 2)

“An integrated project control process for research and practice” Jeroen Colin and Mario Vanhoucke

Share your ideas for all other phases!

In collaboration with our partners:

Future research

@ORASTalks

Wednesday presentation

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SLIDE 43

Mario Vanhoucke - Ghent University

Outline

Presentation: “Research meets Practice” Overview of research

  • Published in “Measuring Time”
  • Four EVM hypotheses

Quick preview of future research

  • The 1 mio € project
  • Further integration

Overview of projects

  • Used in the research
  • Different sectors

Quick preview of future work

  • EVM Europe
  • Further collaboration
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SLIDE 44

Mario Vanhoucke - Ghent University

How relates the research with the real world?

  • 2007-2010: students collected real life data
  • 8 different Belgian companies
  • Total 48 projects types

Research Meets Practice!

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SLIDE 45

Mario Vanhoucke - Ghent University

  • Schedules sorted by SP Indicator
  • Each sector has a proper network structure
  • This explains “why EVM works / fails on projects”

Research Meets Practice! Finding 1

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SLIDE 46
  • Which control method is the best?

Mario Vanhoucke - Ghent University

Research Meets Practice! Finding 2

0% 10% 20% 30% 40% 50% 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Control Efficiency Parallel networks Serial networks Legend

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SLIDE 47

Mario Vanhoucke - Ghent University

Detailed Schedule

ProTrack’s Assistant Bring research results to professionals

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SLIDE 48

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 19%

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SLIDE 49

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 29%

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SLIDE 50

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 49%

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SLIDE 51

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 59%

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SLIDE 52

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 68%

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SLIDE 53

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 79%

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SLIDE 54

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 89%

slide-55
SLIDE 55

Mario Vanhoucke - Ghent University

Cashflow Modelling – AD = 100%

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SLIDE 56

Mario Vanhoucke - Ghent University

How It Started

  • Up to 2003
  • Lots of EV Research done mainly in U.S.
  • But only cost related
  • 2003 – 2004 The Measurable News
  • March 2003, Forecasting Project Schedule Schedule is Different, Walt Lipke
  • March 2003, Completion with EV Metrics, D.S. Jacob
  • Spring 2004, Further Developments in Earned Schedule, Kym Henderson
  • 2005 – 2006
  • Discussions in London about time related EV Research with CPM members Walt Lipke & Kym Henderson
  • First Academic Publications on “EV Time Related Research”
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SLIDE 57

Mario Vanhoucke - Ghent University

  • 2007 PMI Belgium Chapter Event: EV / ES
  • Speakers: CPM Members Walt & Kym
  • Mario received Research Collaboration Fund of 5.000 €

How It Started

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SLIDE 58

Mario Vanhoucke - Ghent University

EVM Landscape in Europe

  • No real statistics / research available
  • Some sensitivity to sharing information
  • Companies using see EVM as part of their competitive advantage
  • No imposed EVMS guidelines (apart from MOD / UK)
  • Evidence of increased intrest / usage of EVM across many countries:
  • CERN, (no EVM regulatory mandate)
  • General Dynamics Land Systems Europe (Required to follow US ANSII and Australian EVM standards,

sometimes Concurrently)

  • Google: EV papers from many european countries
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SLIDE 59

Mario Vanhoucke - Ghent University

EVM Europe

  • A growing need to bring “European EV users” together
  • Summer 2008: London
  • CPM Member Kym Henderson called in a meeting
  • Decision to create “EVM Europe Association”
  • Spring 2009: EVM Europe officially created
  • Mission:
  • to promote EVM usage in continental Europe
  • to combine academical / practitioners experiences
  • to collaborate with other organisations such as CPM
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SLIDE 60

Mario Vanhoucke - Ghent University

1. Yearly Conference

  • Conference to be hosted with Universities / Colleges
  • A dedicated academical track unique for EVM conferences
  • So far:

2009: Geneva, Switserland – University of Geneva / Lausanne 2010: Ghent, Belgium – Ghent University 2011: Valencia, Spain – Polytechnical University of Valencia 2012: Twente, The Netherlands – Twente University

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SLIDE 61

Mario Vanhoucke - Ghent University

2010 Ghent Conference

  • Working session on the PMI PS EVM 2nd Ed.
  • Chaired by P

.M. Greg Schmidt

  • “Europeans” advocated strongly on inclusion of ES Method as an extension to EV
  • Accepted by the committee
  • Global standard which will benefit European users and promote adoption of

EVM in Europe

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SLIDE 62

Mario Vanhoucke - Ghent University

  • 2. Student Involvement
  • Student presentations at all EVM Europe Conferences
  • European student presentation at this EVM World Conference
  • PS-10 An Integrated Project Control Process For Research and Practice Ir. Jeroen Colin
  • 2011 PMI Belgium Best PM Dissertation Price (University Contest)
  • Using EVM and Earned Schedule to assess project maturity in Belgian companies.
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SLIDE 63

Mario Vanhoucke - Ghent University

  • 3. PM Knowledge Center
  • Spread the message: www.pmknowledgecenter.com
  • Free online information tool
  • Can readily be used in courses
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SLIDE 64

Mario Vanhoucke - Ghent University

  • 4. Practitioner Review Committee
  • GOA Research Project
  • September 2012: kick off
  • September 2014: 1st review, topflag academic publications.
  • September 2016: 2nd review, topflag academic publications, a project control book.
  • September 2018: 3th review, academic paper, implementation in ProTrack.
  • September 2019: final review, delivery of PhDs and ProTrack and P2 Engine.
  • January 2012: decision to form a P

.R.C.

  • Chaired by Prof. Pierre Bonnal, founder & director of EVM Europe
  • To translate, publish and present the research findings to the practitioners
  • Stay tuned with Twitter: @ORASTalks
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SLIDE 65

Mario Vanhoucke - Ghent University

Thank You CPM

  • For publishing “The Measurable News”
  • For bringing the Europeans together
  • For continuously supporting the EVM Europe Initiative
  • For having us here
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SLIDE 66

Mario Vanhoucke - Ghent University

Follow us

@ORASTalks

The Netherlands, November 2012 www.evm-europe.eu