Effects of Scheduling Practices on Project Sucess

Effect of Scheduling Practices on Project Success

By Andrew Griffith, Ph.D., P.E., PMP Independent Project Analysis, Inc.

I. Presentation Objectives

A. Provide data that you can use to help justify the investment in project scheduling How?

B. Present the results of an Independent Project Analysis, Inc. research study

1. Demonstrates a measurable link between scheduling practices and project outcome success

2. Based on data from actual projects

METHODOLOGY

II. Independent Project Analysis, Inc. A. Project management research and consulting company based in Ashburn, Virginia

B. Capital project benchmarking

1. Project system benchmarking

2. Individual project evaluations

3. Project system monitoring

C. IPA approach is based on extensive, detailed, and robust databases

III. Characteristics of the IPA Process Plants Database

A. Over 7,000 capital projects from a wide range of industries

B. Over 200 companies worldwide

C. Quite detailed: up to 2,000 factors per project

D. Includes all phases of the project life-cycle, from R&D through operations

Effect of Scheduling Practices on Project Success By Andrew Griffith, Ph.D., P.E., PMP Independent Project Analysis, Inc.

PMI College of Scheduling

Topic of the Month – April 2005

E. All project types covered: greenfield to revamp

F. New projects added constantly

IV. Application of the IPA Methodology

Benchmarking

IPA

Databases

Project

Evaluations

Project System

Monitoring

Contingencies

Schedule

Histories

Cost

Histories

Project

Definition Technical

Characteri

i

Management

Strategies

Performances




V. IPA Approach: Linking Inputs and Outputs

VI. Research Hypothesis

There is a positive and significant relationship between

scheduling practices used early in the project life-cycle and the

FEL Technical

Difficulty

Project

Management

Project

Practices

Cost Schedule Safety Operational

Performance

Inputs That Affect

ParametricStatistical

Techniques

Performance Outputs




ultimate success of the project.

VII. Scheduling Practices Data A. Collected during every project interview

B. Measures characteristics of the project schedule

C. Anchored at the time of project authorization for all projects in the study

D. Validated with electronic schedule files and hard copy printouts

VIII. Project Outcome Performance Metrics A. Measure relative performance for a wide range of outcome metrics - not just one success measure

B. Based on data collected after mechanical completion and startup

C. Derived using parametric statistical techniques

D. Normalized based on project characteristics, location, currency, escalation, etc.

E. Includes both predictability and absolute metrics

IX. Predictability vs. Absolute Metrics

Predictability Metric Absolute Metric

Outcome performance relative to estimated performance

Outcome performance relative to industry average for comparable projects

Based on actual performance of project vs. the estimated performance

Based on performance vs. Industry average - derived using statistical models

Deviations are not normalized for project characteristics

Models normalize for project characteristics

Reported as a percent deviation from the estimated performance

Reported as an index with Industry average set to 1.0

Cost growth & schedule slip Cost index & schedule index




X. Approach A. Developed sample database

1. Project scheduling practices

2. Outcome performance metrics

3. Other project practices and characteristics

B. Applied statistical tests

C. Controlled for other project characteristics

D. Interpreted the results and formed conclusions

XI. Sample Characteristics

Characteristic Study Sample

Number of Projects 494 completed projects

Number of companies represented 59 different owner organizations

Industries All industries covered by IPA database

Project locations Worldwide locations

Project types All project types: Greenfield to revamp

Project sizes Average estimated cost: $24MM ($100K to almost $1B)




ANALYSIS

XII. Scheduling Practices That Drive Better Project Outcome Performance A. Integration of all project phases into a single schedule

B. Application of CPM techniques

C. Resource-loading

D. Review by core project team

XIII. Integrated Schedules A. Integrates all project phases into a single master schedule

1. Definition, detailed engineering, procurement, construction, shutdown/turnaround, and commissioning and startup

B. Only 33% include all applicable project phases

1. Many missing FEL, shutdown/turnaround, and/or commissioning and startup

XIV. Integrated Schedules - Correlated With Better Cost Performance

0.7

0.8

0.9

1.0

1.1

1.2

1.3Integrated Schedule Not Integrated

Cos

t Ind

ex(A

ctua

l / In

dust

ry B

ench

mar

k)

pr < 0.02 +1 Std.

-1 Std.Mean




XV. Integrated Schedules - Also Correlated With Less Schedule Slip

XVI. Based on CPM A. Is the project schedule based on the Critical Path Method (CPM)?

1. Activities networked together

2. Activity start and finish dates based on network calculations

3. Critical path and activity float defined

B. Less than 50% of schedules in the sample were based on CPM

XVII. Use of CPM Correlated with Less Cost Growth

XVIII. Use of CPM Also Correlated with Less Schedule Slip

-40%

-20%

0%

20%

40%

60%

80%

100%Integrated Schedule Not Integrated

Perc

ent S

ched

ule

Slip

(Act

ual /

Pla

nned

Dur

atio

n)

-30%

-20%

-10%

0%

10%

20%

30%

40%Applied CPM Did not Apply CPM

Perc

ent C

ost G

row

th(A

ctua

l / E

stia

mte

d C

ost)

+1 Std.

-1 Std.Mean

pr < 0.00

pr < 0.00 +1 Std.

-1 Std.Mean




XIX. Use of CPM Also Correlated With Better Cost Performance

XX. Resource-Loaded

A. Critical project resources loaded into the schedule using appropriate units of measure

B. Only 24% were resource-loaded

C. Mix of resource categories for projects with resource-loading

D. Construction labor 73%

E. Engineering labor 58%

F. Construction Equip. 24%

0%

10%

20%

30%

Applied CPM Did Not Apply CPM

Perc

ent S

ched

ule

Slip

(Act

ual /

Pla

nned

Dur

atio

n)

0.7

0.8

0.9

1.0

1.1

1.2

1.3Applied CPM Did Not Apply CPM

Cos

t Ind

ex(A

ctua

l / In

dust

ry B

ench

mar

k)

pr < 0.03 +1 Std.

-1 Std.Mean

pr < 0.03




G. Estimated cost 21%

H. Other 10%

XXI. Resource-Loading Correlated with Better Cost Performance

XXII. Resource-Loading Also Correlated with Less Schedule Slip

XXIII. Project Team Review

A. Review by the core project team

1. Supports buy-in to plan

2. Provides a check for accuracy and feasibility

0.7

0.8

0.9

1.0

1.1

1.2

1.3Resource-Loaded Not Resource-Loaded

Cos

t Ind

ex(A

ctua

l / In

dust

ry B

ench

mar

k)

+1 Std.

-1 Std.Meanpr < 0.01

0%

10%

20%

30%

Resource-Loaded Not Resource-Loaded

Perc

ent S

ched

ule

Slip

(Act

ual /

Pla

nned

Dur

atio

n)




B. 76% of the project schedules were reviewed by the team

XXIV. Team Review Correlated with Less Cost Growth

Conclusions and Recommendations

XXV. Single Schedule Definition Rating

A. Definitive - Resource-loaded CPM schedule that covers all major project phases

B. Preliminary - CPM schedule that covers all major project phases, but not resource-loaded

C. Factored - Milestone schedule showing the timing required for major project milestones and phases

D. No Schedule - No project schedule developed other than possibly a target completion date

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%Reviewed by Core Team Not Reviewed by Core Team

Perc

ent C

ost G

row

th(A

ctua

l / E

stim

ated

Cos

t)

+1 Std.

-1 Std.Mean

pr < 0.00




XXVI. Sample Distribution

XXVII. Schedule Definition Drives Better Cost Performance

Definition Rating Percent of Sample

Definitive 13%

Preliminary 29%

Factored 55%

No Schedule 3%

0.90 0.95 1.00 1.05

Milestone

CPM Schedule

Resource-Loaded

Average Cost Index(Actual / Industry Benchmark)

pr < 0.00




XXVIII. Schedule Definition Also Correlated with Better Schedule Performance

XXIX. Schedule Definition Also Drives Lower Schedule Slip

0.4

0.6

0.8

1.0

1.2

1.4

1.6Definitive Preliminary Factored

Exec

utio

n Sc

hedu

le In

dex

(Act

ual /

Indu

stry

Ben

chm

ark)

+1 Std.

-1 Std.Meanpr < 0.02

0% 5% 10% 15% 20% 25% 30%

Milestone

CPM Schedule

Resource-Loaded

Average Percent Schedule Slip(Actual / Planned Duration)




XXX. Schedule Definition Also Correlated with Less Cost Growth

XXXI. Conclusions

A. Sound scheduling practices drive better project outcomes

B. Significant benefits of good scheduling practices

1. 7% better cost

2. 12% better schedule

3. 6% less cost growth

4. 23% less schedule slip

XXXII. Transferability of Findings

A. Sample is limited to capital projects in the heavy industrial sector

B. Measure of scheduling practices anchored at the time of project authorization - not at the start of construction

However

C. Relationship between practices and outcomes is consistent across project types and industries

D. General findings are applicable to all project types

pr < 0.00 -30%

-20%

-10%

0%

10%

20%

30%

40%Definitive Preliminary Factored

Per

cent

Cos

t Gro

wth

(Act

ual /

Est

imat

ed C

ost)

+1 Std.

-1 Std.Mean




XXXIII. Recommendations

A. Use the results of this study to help justify the investment in sound scheduling practices

B. Benchmark schedule development

1. Design an applicable metric for schedule definition

2. Systematically measure schedule definition at authorization for all projects

3. Measure trends and strive to improve

Contact Information

Andrew F. Griffith

Independent Project Analysis, Inc.

44426 Atwater Drive, Suite 100

Ashburn, Virginia 20147

Phone: 703-729-8300

E-Mail: [email protected]

Effects of Scheduling Practices on Project Sucess

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