sd108- quantitative impacts of project change

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Quant i t at i ve I mpact s of Proj ect Change

byC. W. I bbs

&Wal t er E. Al l en

A Repor t t o The Const r uct i on I ndust r y I nst i t ut e

The Uni ver si t y of Texas at Aust i n

Under t he Gui dance of t hePr oj ect Change Management Resear ch Team

f r o mUni vers i t y of Cal i f orni a

Ber kel ey, Cal i f or ni a

May 1995

Revi ewed by CI I 23J un04

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TABLE OF CONTENTS

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . iii

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . v

Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . 1

1.1 Introduction . . . . . . . . . . . . . . . . . . . . . 11.2 Nature of Study. . . . . . . . . . . . . . . . . . . . 21.3 Purpose and Objective of the Study . . . . . . . . . . 31.4 Research Methodology . . . . . . . . . . . . . . . . . 41.5 Chapter Summaries. . . . . . . . . . . . . . . . . . . 61.6 Composition of Task Force. . . . . . . . . . . . . . . 7

Chapter 2 Literature Review . . . . . . . . . . . . . . . . . . . 8

2.1 Introduction . . . . . . . . . . . . . . . . . . . . . 82.2 Project Change Analysis. . . . . . . . . . . . . . . . 92.3 Project Change Management and Control. . . . . . . . . 112.4 Claims and Legal Issues. . . . . . . . . . . . . . . . 122.5 Construction Labor Productivity. . . . . . . . . . . . 14

Chapter 3 Data Collection And General Analysis . . . . . . . . . 16

3.1 Introduction . . . . . . . . . . . . . . . . . . . . . 163.2 Data Gathering - Questionnaire . . . . . . . . . . . . 163.3 Data Gathering - Interviews. . . . . . . . . . . . . . 183.4 Project Data . . . . . . . . . . . . . . . . . . . . . 19

Chapter 4 Research Hypotheses And Analyses . . . . . . . . . . . 27

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . 274.2 Hypothesis 1 . . . . . . . . . . . . . . . . . . . . . 284.3 Hypothesis 2 . . . . . . . . . . . . . . . . . . . . . 304.4 Hypothesis 3 . . . . . . . . . . . . . . . . . . . . . 324.5 Questionnaire Analysis . . . . . . . . . . . . . . . . 354.6 Statistical Analysis . . . . . . . . . . . . . . . . . 364.7 Research Findings. . . . . . . . . . . . . . . . . . . 37

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4.7.1 Hypothesis 1 Findings. . . . . . . . . . . . . . . . . 374.7.2 Hypothesis 2 Findings. . . . . . . . . . . . . . . . . 504.7.3 Hypothesis 3 Findings. . . . . . . . . . . . . . . . . 524.7.4 Qualitative Findings . . . . . . . . . . . . . . . . . 55

Chapter 5 Project Change Management Analysis . . . . . . . . . . 57

5.1 Introduction . . . . . . . . . . . . . . . . . . . . . 575.2 Total Project Contingency Draw-Down. . . . . . . . . . 585.3 Project Change Ratios. . . . . . . . . . . . . . . . . 605.4 Relationships Between Project Change and Schedule Overlap 645.5 Family of Curves for Schedule Recovery . . . . . . . . 685.6 Project Budget Recovery. . . . . . . . . . . . . . . . 73

Chapter 6 Summary of Quantitative Findings and Recommendations . 76

6.1 Introduction . . . . . . . . . . . . . . . . . . . . . 766.2 Hypotheses Findings and Recommendations. . . . . . . . 766.3 Change Measurement Findings and Recommendations. . . . 786.4 Summary. . . . . . . . . . . . . . . . . . . . . . . . 81

APPENDIX A Research Questionnaire . . . . . . . . . . . . . . . . 82APPENDIX B Cited and Un-Cited Bibliography . . . . . . . . . . . . 98APPENDIX C Summary Tables & Graphs . . . . . . . . . . . . . . . . 103APPENDIX D Glossary . . . . . . . . . . . . . . . . . . . . . . . 132

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LIST OF FIGURES

Figure Title Page

1. Questionnaire Respondents . . . . . . . . . . . . . . . . . . 192. Total Installed Cost (TIC) Distribution For All Projects Submitted 203. Types Of Project Owners Participating In Research . . . . . . 214. Type Of Construction For Projects Submitted . . . . . . . . . 225. Types of Projects Analyzed. . . . . . . . . . . . . . . . . . 236. Breakdown For Design/Build Projects . . . . . . . . . . . . . 247. Breakdown For Design/Bid/Build Projects . . . . . . . . . . . 258. Project Schedule Length . . . . . . . . . . . . . . . . . . . 269. Analysis I Constr. Change vs. Constr. Productivity. . . . . . 5310. Project "S" Curves & Total Project Contingency Draw-Down. . . 5911. Engineering Change (Final Cost/Initial Cost). . . . . . . . . 6112. Construction Change (Final Cost/Initial Cost) . . . . . . . . 6213. Total Project Change (Final Cost/Initial Cost). . . . . . . . 6414. Engr. Change vs. Schedule Overlap . . . . . . . . . . . . . . 6615. Const. Change vs. Schedule Overlap. . . . . . . . . . . . . . 6716. Probability of Engineering Schedule Recovery. . . . . . . . . 7017. Probability of Construction Schedule Recovery . . . . . . . . 7118. Probability of Total Project Schedule Recovery. . . . . . . . 7219. Probability of Finishing Over-Budget (Total $). . . . . . . . 74

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LIST OF TABLES

Figure Title Page

1. Summary Of Statistical Tests For I st Hypothesis. . . . . . . . 382. Summary Of Statistical Tests For I st Hypothesis (Continued). . 393. Summary Of Statistical Tests For I st Hypothesis (Continued). . 404. Summary Of Statistical Tests For I st Hypothesis (Continued). . 415. Summary Of Statistical Tests For I st Hypothesis (Continued). . 426. Summary Of Statistical Tests For 2nd Hypothesis . . . . . . . . 437. Summary Of Statistical Tests For 2nd Hypothesis (Continued) . . 448. Summary Of Statistical Tests For 3rd Hypothesis . . . . . . . . 459. Summary Of Statistical Tests For 3rd Hypothesis (Continued) . . 4610. Summary Of Statistical Tests For 3rd Hypothesis (Continued) . . 4711. Summary Of Statistical Tests For 3rd Hypothesis (Continued) . . 48

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QUANTITATIVE IMPACTS OF PROJECT CHANGE

EXECUTIVE SUMMARY

The goal of this research study was to quantify the impact that changes haveon engineering and construction project performance. Using previous CIIstudies and reports as a starting point, we developed and tested a series ofhypotheses about those impacts. We were particularly concerned withidentifying reliable, quantitative relationships between the amount andtiming of change and the consequences of such change. This report presentsour findings.

Our first research hypothesis was that:

o Changes which occur late in a project are implemented less efficiently than changes that occur early.

> were not able to prove this hypothesis to a meaningful level of statistical significance, though we did find and do report in this summary linear relationships between the amount of change and its timing.

The second hypothesis of our study was that:

o The more change there is on a project, the more of a negative impact it has on labor productivity.

> We were able to prove this relationship in a variety of ways to the 5% and 10% levels of statistical significance.

The third hypothesis was that:

o The hidden or unforeseeable costs of change increases with more project change.

> We were to prove this relationship in a variety of ways to the 5% and 10% levels of statistical significance.

In each case, linear regression models are presented in this report toallow the reader to make general comparisons between specific projectexperience and that of the 104 projects analyzed in this study.

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In addition, we were able to extend our analysis in other directions.For instance, the amounts of change for these projects are reported for theengineering phase, construction phase and total project duration. The rateat which change accumulates over the duration of a typical project isillustrated, as are quantitative results for contingency usage. The amountof project change is compared to the degree of design-construction phasing oroverlap. Finally, families of curves are reported which represent theprobabilities of late completion or budget overrun, given late or earlyconditions at the 25% and 75% complete project status.

Based on these findings we offer recommendations to project managers forimproving their management of change.

Naturally, each design and construction project has its own specialcharacteristics. The results reported in this document therefore cannot beused blindly or arbitrarily. However, these results do represent a stepforward in understanding how change occurs and affects projects. Many morequestions remain to be studied and learned. This particular report providesa benchmark for future studies, both in terms of quantitative relationshipsthat have already been scientifically confirmed and in terms of research

methodologies.

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CHAPTER 1

INTRODUCTION

1.1 Introduction

The research has defined change as any event which results in a modification of the original scope, execution time or cost of work. Project

change is restricted to the detailed engineering and construction phases ofbuilding projects. This definition provides a framework for the research.

Project change has a tremendous effect on the financial performance of aconstruction project. Proper management of project change can determineoverall project success or failure. Improper project change management isexhibited in the increased incidence of negative impacts exhibited by projectcost overruns, claims and legal disputes.

A whole industry has developed to fight change order claims and legaldisputes. It is estimated that between $13 and $26 billion dollars [Allen93] is spent on new construction change orders annually across the nation.Additional financial resources are expended to resolve changes that lead toclaims and legal disputes. The total project change costs in the UnitedStates could reach $50 billion dollars annually.

Change occurs throughout all phases of a construction project. Detaileddesign and construction are very critical phases for project change. Thecosts of rework for engineering drawings or installed materials can besubstantial in the late phases of a construction project.

Once a project has reached the detailed design phase, a substantialportion of the project's scope is complete. Completion of detailed designalso signals the ultimate commitment of owners and financial institutions toproject construction. The construction phase leads to the commitment offacility usage or the production of revenue producing products.

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Project change during the detailed design and construction phases leadsto major disruptions of planned schedules, work methods, productivity andoverall project performance.

Research that focuses on the quantitative impact that change has on thedetailed design and construction phase of projects is limited. This studyexpands the body of knowledge concerned with project change during detaileddesign and construction. In the aspects of labor productivity and schedulerecovery, the study has developed graphs to measure or compare projectchange.

1.2 Nature of Study

The Construction Industry Institute (CII) sponsored this research toimprove the industry's understanding of project change. The goal of thisstudy is to quantify the nature and impact of change so that owners andcontractors can manage change better.

This research will serve as a catalyst for project change discussionbetween owners and contractors. By improving the industry's understanding ofchange there should be a reduction in legal disputes and other negativeaspects of project change implementation. This will improve efficiency,effectiveness and owner satisfaction in the construction industry.

The University of California, Berkeley team conducted this study betweenJune 1992 and February 1995. Meetings were held approximately every six

weeks to plan and review the research with the full Task Force andincorporate their suggestions.

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1.3 Purpose and Objective of the Study

The goal of this research is to quantify the impact of project changeduring the detailed design and construction phase. The research examines theeffects of project change on the macro and quantitative level, and sets afoundation or benchmark for the industry.

The study's objectives are built around testing three researchhypothesis. The first hypothesis is:

Changes that occur late in a project are implemented less efficiently than changes implemented early.

This hypothesis is based on the belief that the later change occurs in aproject, the less efficient and more costly is the total change cost. Thisresults in inefficient, ineffective and unsatisfactory project performance.

The second hypothesis is:

The more change there is on a project, the more of a negative impactthere is on labor productivity.

This hypothesis is based on the belief that when a larger amount ofchange occurs on a project there is a compounding and negative effect ontotal project efficiency.

This compounding effect may occur in all phases of a project, but thisstudy focused on the detailed design and construction phases of a project tolimit its breadth. This compounding effect of multiple project changes ispoorly understood, difficult to measure, and seldom reflected in theestimated cost of individual project changes. It becomes apparent when workcannot be completed on time and labor productivity does not measure up to theanticipated level of efficiency. Project managers sometimes refer to thecompounding effect of multiple project changes as the "ripple" effect.

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The third and final hypothesis was developed late in the study:

The Cumulative Change Effect (&) increases proportionately to the amount of change on a project.

The research team defines the Cumulative Change Effect, as the amount ofchange exhibited on a project arising from multiple changes being implementedover the course of an entire project. Cumulative change effect (&) is

widely understood to exist in the industry but difficult to quantify.

1.4 Research Methodology

A questionnaire was developed to collect the quantitative data neededfor analysis. CII Task Force Members and University Researchers collaboratedon its development. A pilot version was tested with some task forcecompanies prior to a revision and mailing to the full CII membership.

The pilot test revealed that period productivity information was notgenerally available in owner or contractor project files, especially forcompleted projects. The questionnaire was revised to collect project changedata at quartile and end of project milestones. The pilot test wasinvaluable in identifying this problem in our initial assumptions, prior tosending a questionnaire to the CII membership.

Each CII member company was asked to select five or more projects thatthey were involved as either owner, contractor or construction manager. Theproject selection criteria were established as:

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o Projects should have a Total Installed Cost (TIC) over $10 milliono Project should have been completed within the last five yearso Projects could be either domestic or foreign so long as costs and performance were not greatly influenced by currency exchange

The 14-page questionnaire (Appendix A) was sent to 90 CII membercompanies. The research team requested that a variety of completed projectsbe submitted. The data collection objective was to compile projectperformance data that were accurate and well organized. Questionnaires werereturned from 35 different organizations, representing 104 projects thatinvolved over $8 billion in Total Installed Cost (TIC).

The quantitative data requested were retrieved from completed projectrecords by company representatives familiar with the information. Projectcost, productivity and schedule data were the primary focus of thequestionnaire and research. The questionnaire also provided a means forcollecting data on contracting strategy, business relationships and contractadministration.

The data analysis phase evaluated quantitative data to test the researchhypotheses. Additionally, several project control tools were adopted fromexisting research to analyze project change control. These includedengineering and construction productivity trend lines, project costs andschedule family of curves, contingency draw-down graphs and project "S"curves for the projects analyzed.

A total of 79 statistical analyses were completed for the data analysis.Each analysis has a corresponding graph that represents the researchfindings. Of the 79 statistical analyses, 32 statistical analyses passedacceptable standards of veracity. Summary tables of the statistical analysesare included throughout this report and provide:

o Analysis number o Variables to be tested and data source o Number of observations o Simple statistics (Mean, Standard Deviations) o Correlation analysis (Coefficient and Significance Level) o Regression analysis (Best-fit line)

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The Journal of Construction Engineering and Management has published anumber of articles on the research being conducted in the area ofconstruction labor productivity. One of the most recent articles is ActionResponse Model and Loss of Productivity in Construction, which discusses agraphical model that depicts how a variety of factors may interact to cause aloss of productivity and how management action may mitigate, eliminate,initiate or exacerbate labor productivity performance [Halligan 94].

Other related and significant articles published in the Journal ofConstruction Engineering and Management are [Maloney 83], [Thomas 92]. TheMaloney article, Productivity Improvement: The Influence of Labor, presentsa frame work for analyzing the influence on labor productivity. He suggestthat project managers should reduce the negative forces and strengthen thepositive forces to increase labor productivity.

"Effects of Scheduled Overtime on Labor Productivity," written byThomas, rigorously examines the effects of scheduled overtime on laborproductivity. This article is interesting and relevant because projectchanges are often estimated and implement based on scheduled overtime.Thomas states that although there may be positive short-term benefits to

working an overtime schedule, the long-term consequences are typically viewedas detrimental.

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CHAPTER 3

DATA COLLECTION AND GENERAL ANALYSIS

3.1 Introduction

All CII member companies were asked to participate in this study toincrease the sample size and collect project data from a wide range of bothowner and contractor organizations. The CII membership consists ofapproximately 90 organizations that are involved in all phases of theconstruction industry.

3.2 Data Gathering - Questionnaire

Many CII companies submitted responses to our questionnaire. In somecases individual companies submitted as many as seven. The average number ofresponses submitted was three for all participants. Additional informationconcerning change control, cost growth, schedule slippage and general project

management issues was collected and proved beneficial to the overall study.

The questionnaire developed for this study was completed after extensive

input and review by the research subcommittee, and the full task force. Apilot test was performed with selected CII member companies inside the taskforce. The research sub-committee worked to develop a questionnaire thatspecifically identifies the quantitative data needed to manage project changeand conduct rigorous data analysis.

The first pilot test attempted to collect monthly period productivityand change data for detailed quantitative data analysis. The period data

would have allowed the research subcommittee more precise data to examine in what period change occurred, its impact on period productivity, and the

amount of change to anticipate. The pilot test indicated that firms wereeither not collecting or not preserving in easily-retrievable manner theneeded level of detail to analyze period productivity.

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The Berkeley research team and subcommittee redesigned the questionnaireformat to request data that is commonly collected on projects: period costsand schedule information, and end-of-project productivity data.

The format of each question was reviewed to determine the easiest and most straightforward method to request the research data. The majority of

quantitative data needed is organized on three pages of the questionnaire. Adata table, Page 11 of Appendix A, is the central data collection tool forthe questionnaire. Page 5 of Appendix A is designed to collect Original andFinal Control Budget information. The remaining quantitative data collectioneffort, Page 12 of Appendix A, is arranged to collect engineering andconstruction productivity data. The questionnaire was designed to becompleted by senior cost engineers and project managers who are familiar

with a specific project. The data needed to complete the questionnairerequire someone with a good understanding of an organization's internalcontrol systems and who knows how to retrieve the data requested.

The questionnaire was completed and mailed to the entire CII membershipin July 1993. One month after the questionnaire was mailed, follow-up phonecalls were placed to determine their status within the CII companies. Mostquestions were resolved quickly over the phone during the follow-up telephonecall. A copy of the questionnaire s final version is provided in Appendix A.

Task Force follow-up was helpful in tracking questionnaires anddirecting them to project managers and cost engineers with the specificproject experience needed to complete the questionnaire. Task Force membersinitiated follow-up within their own companies and worked with other industrycontacts to promote timely completion of the questionnaire. The follow-upsalso provide qualitative information on the ease or difficulty withcompleting the questionnaire and identifying those companies that would notparticipate in the study. Completed questionnaires were sent directly backto the University and confidently controlled. Two letter codes were used toidentify the 104 different projects submitted.

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The first closing date for data collection was September 17, 1993.After discussions with Task Force members and CII member's comments, thedecision was made to extend the closing date to December 31, 1993. Thisgave companies more time to participate in the study and increased thestudy's sample size.

3.3 Data Gathering -- Interviews

After reviewing submitted questionnaires and beginning data analysis,interviews were conducted with project mangers and cost engineers of threeCII member companies. The purposes of these interviews were to:

1) resolve unanswered questions on the questionnaire

2) clarify interpretations

3) obtain an understanding of the assumptions respondents used when completing the questionnaire

University researchers scheduled a full or half day with companyrepresentatives at a particular company headquarters or project site.Interviews were scheduled with several different project personnel that

worked on the particular project submitted and other personnel in the projectcontrols organization. The average time for interviews was approximately onehour. The primary focus was the questionnaires and projects submitted forthe study. Company interviews provided the research team a trueunderstanding of submitted projects and specific project control systems usedby CII participants. This information was helpful in understanding completedquestionnaires and CII company project change control systems.

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3.4 Project Data

The largest percentage of questionnaires were returned by Owner organizations(42) and firms that specialize in Engineering/Procurement/Contractoroperations (31). Other questionnaires were submitted by Engineering/Designfirms (13), Construction Managers (10) and Contractors (3). It should beclarified that these percentages represent the functional roles filled on thespecific project(s) submitted by participating organizations. See Figure 1.


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The Total Installed Cost (TIC) for project submitted range from a low of$3.2 million to a high of $1.2 billion. Most of the projects were in the 0to $100 million range (80.8%) with the biggest percentage in the $50-100

million range (25%). The largest percentages of projects over the $100 million threshold had a project range between $150-400 million (13.4%). Only

a few projects broke the $400 million barrier (2%).

TIC was one of the research project criteria for selecting submittedprojects. We requested that submitted projects have a TIC over $10 million.Ninety-two percent of the project submitted did meet or exceed the TICcriteria. Eight projects had TIC less than $10 million and of these three

were less than $5 million. A complete distribution of projects submitted canseen in Figure 2.


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The projects and data submitted came from a broad cross-section of theindustrial private sector. The four leading types of projects submitted forthis research came from the following industries:

o Refinery o Manufacturing o Petroleum/Natural Gas o Pharmaceutical/Chemical

A complete analysis of types of projects submitted and analyzed for theresearch is provided in Figure 5.

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Engineering design and construction schedules averaged approximately 16and 15 months respectfully for submitted projects. It is interesting to notethat engineering design schedules were one month longer than constructionschedules. Overall or total project schedules were approximately 23 months.Most of these projects had overlap between engineering design andconstruction. The construction phase of these projects generally startedaround the 40% point of engineering design to be completed in 23 months.Project schedule lengths for the different phases can be seen in Figure 8.

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CHAPTER 4

RESEARCH HYPOTHESES AND ANALYSES

4.1 Introduction

This research has three hypothesis. Hypotheses 1 and 2 were developed priorto starting the research, and Hypothesis 3 was developed as a result ofconducting this research. They are:

1. Changes that occur late in a project are implemented less efficiently than changes that occur early in the project.

2. The more change there is on a project, the more of a negative impact there is on labor productivity.

3. Hidden change increases with more project change.

Each hypothesis was statistically analyzed and evaluated with similarresearch criteria. The statistical test performed to verify the hypothesesincluded the student's t-test to measure significant differences between the

means of two samples; linear regression analysis to find the best fit linearline; and confidence interval fitting to create a range of reliability.

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The Berkeley research team designed the questionnaire to collectHypothesis 2 data in the last section of the questionnaire on Page 12 ofAppendix A. Questions 24-29 requested project information on projectlabor-hours expended, labor hours expended for project change implementationand productivity ratios. Questions 24-26 requested detailed engineering dataand questions 27-29 request construction data. An average of 34 projects

were evaluated for validating Hypothesis 2.

Hypothesis 3 project data were developed by evaluating all the projectssubmitted. An average of 36 projects were utilized to validate Hypothesis 3.

4.6 Statistical Analysis

Statistical correlation and linear regression analyses were performed onthe data sets to test the three hypothesis. For Hypothesis 1, thecorrelation analysis evaluated relationships between installed material orlabor costs and total project change costs required to implement projectchange. When analyzing Hypothesis 2, the correlation between project changeand productivity was the major relationship evaluated. The primary tests forHypothesis 3 were to identify hidden costs associated with & and determinethe relationships to project change during engineering and construction,separately and collectively.

Linear regression analysis was performed to identify data trends anddevelop the linear relationship that best fits the sample data. Astatistical significance level test of 10% was used as the criterion fordetermining whether a hypothesis is proven.

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4.7 Research Findings

Summaries of the tests are presented in Tables 1 through 11. Thesetables contain the relationships tested and graphed, number of observationsand statistical analysis results. Tests that passed the 10% statisticalsignificance level are highlighted. The summaries for each Hypothesis arearranged in the following sequence:

o Hypothesis 1 Tables 1-5 o Hypothesis 2 Tables 6-7 o Hypothesis 3 Tables 8-11

4.7.1 Hypothesis 1 Findings

A total of 22 different relationship are graphed and tested forHypothesis 1. There are five major relationships with sub-grouprelationships that evaluate different combinations of the data from Page 11of the Questionnaire.

The specific relationships tested for both detailed engineering andconstruction with respect to absolute values (|x| where negative valuesbecome positive and total change is the positive sum of all observations) andnon-absolute values are:

o Permanent Materials vs. Total Change o Construction Labor vs. Total Change o Engineering Labor vs. Total Change o Permanent Materials vs. Percent Complete

The Research Committee was unable to statistically prove Hypothesis 1. Thecomplexity of projects and the numerous factors that influence theimplementation of project change complicates attempts to measure changeexclusively. Additionally, analyzing project change postmortem or after keypersonnel have moved to other responsibilities and memories have faded makesit difficult to collect accurate data.

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Even though our attempt to isolate the quantitative aspects of projectchange are not academically or statistically defensible for Hypothesis 1,trends have been identified. The research has advanced the tools or graphsfor analyzing project change. These tools in the form of graphs withconfidence intervals can assist other researchers and project managers intheir own evaluation of project change. Hypothesis 1 graphs are presented inAppendix C.

Strong relationships have been identified between permanent materialinstalled, construction labor and total project change. These relationshipsidentify critical areas for project managers to focus on during projectexecution or change implementation.

The research has identified critical variables and quantitative criteriafor analyzing project change. The critical variables and quantitativecriteria are:

o Permanent Material Installed o Construction Labor for Change Implementation o Engineering Labor for Change Implementation o Total Change Costs

These listed variables and criteria used to track and quantify changefor Hypothesis 1 will assist in change management. If additional researchfocuses on these variables at the start of projects, sets the analysisfoundation, and carries the analysis through project execution and start-up,then the benefits to the construction industry would be advantageous.

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The other two relationships, Engineering Change vs. Total Productivityand Construction Change vs. Total Productivity, exhibit the ripple effect onprojects. These two tests show the effects of early or upstream change inthe engineering or construction phase on total productivity.

When comparing engineering and construction research productivityrelationships, engineering change exhibits a stronger statisticalrelationship to the negative impacts of construction project change. Thisresearch finding may support the intuitive knowledge of engineering changeimpacting downstream construction. For example, engineering change that isnot identified until construction begins will require additional engineeringlabor hours, coordination of material and other project resources higher thanthe rework costs associated with identifying and resolving project changeearlier in the project cycle. The late identification of project change willtend to disrupt work flow, reduce productivity, increase project costs, andthus have a negative impact on overall project performance.

Hypothesis 2's verification was able to demonstrate by statisticalanalysis that project change adversely affects project productivity. Thestrongest statistical correlation is most evident when engineering andconstruction data are isolated and the two phases are evaluated independentlyof each other. That is, engineering change is tested against engineeringproductivity and construction change is tested against constructionproductivity.

When isolating construction change, the research indicates thatconstruction change greater than 5% results in negative constructionproductivity or productivity less than planned. The more constructionchange, the more negative impact on construction productivity. Whenconstruction change approaches 34%, construction productivity isapproximately 90% (Figure 9 Analysis 1 Construction Change vs. ConstructionProductivity) of norm.

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We believe that the Total Change ($) value is the more accurate datasource. An analysis of the correlation coefficient for calculations thatPASS , indicates that the Total Change ($) coefficient is almost twice asclose to one (1) when compared to Change % Growth Labor-Hours. Also, anotheranalysis conducted to test the hypothesis used Column 7 for the calculationof total change and resulted in identical mean values.

4.7.4 Qualitative Findings

The construction industry s methodology for collecting project changedata needs to be improved. Many of the 55 companies that did not submitcompleted questionnaires told us in follow-up telephone interviews that theydid not collect the information requested, did not track data in the format

we requested, or could not easily retrieve basic project change data fromhistorical records.

It can be strongly argued that many project managers have no costs basesto identify the indirect impact of a single change order. Consequently, whenthere are multiple project changes, the tasks to identify the total impact isvery difficult. This suggests that the construction industry needs tocollect and archive project change data more diligently and possibilitystandardize change management systems.

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5.3 Project Change Ratios

Data from 64 projects was used to develop the project change ratios.Three charts were prepared for the analysis. One for each phase:engineering, construction and total project performance.

Column 5 -- Facility Cost Forecast on Page 11 was used exclusively forthe analysis. This column represents the overall project facility costforecast. The forecast includes all costs related to the EPC process, i.e.,engineering, construction, contract administration and management expenses.

From column 5, the initial and final values were analyzed. The initialvalue indicates beginning facility costs and final column value thatrepresents end of project. The change ratio (Final Value/Initial Value)

was developed to compare the amount of change on a total project or within aproject phase.

If the final and initial values were identical, it was assumed there wasno recorded change on the project. If the final value was bigger than theinitial value, we postulated that project change was represented bythe percentage that the ratio was greater than one (1). For example, aproject that had an initial facility cost forecast of $61,900,000 and a finalfacility cost forecast of $66,000,000 would be represented in the changeratio as $66,000,000/$61,900,000 = 1.06. Consequently, this project had 6%change.

An analysis of engineering change revealed that most of the projects hadless than 4% project growth. Over the entire change ratio range, 70% of theprojects reduced engineering scope by 5% or had project growth of 11% (thesecond, third and fourth bars in Figure 11). The range or amount of changerecorded for the engineering phase is somewhat significant. However, it issignificant when acknowledging the downstream or compounding impact thatengineering change has on construction and total project performance. Theentire change ratio chart for engineering is presented in Figure 11.

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A second analysis of construction change ratios showed commonsimilarities with engineering change ratios along the median points ofproject change. The largest number of projects exhibited less than 4%project growth; see Figure 12.

It is noteworthy that 37% of projects had reduction in scope during theproject construction phase. Project change caused by reduction in projectscope is common when a primary goal is to bring a project in under oron budget. In reducing project scope, the short-term objective is to save

money and bring the project in on budget. Most project managers can attestthat the objective is common and commendable. However, the ramifications andconsequential costs can be excessive on staff, contractors, and suppliers.Project change has similar hidden costs whether the change is an addition orreduction in scope. The full range of construction change ratios ispresented in Figure 12.

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5.4 Relationships Between Project Change and Schedule Overlap

Two analyses were conducted that examined the relationship betweenproject change and schedule overlap. One analysis evaluated engineeringchange and the other construction change. The analysis of engineering changeexamined 16 projects and the construction change analysis examined 11projects from the database. The projects were selected based on availabledata quality.

The project data were plotted and a linear, best fit line for the data was constructed. The linear regression line for engineering and construction

have upward sloping lines. This indicates that as a project has greaterschedule overlap, there is more change.

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This analysis helps us formulate a hypothesis for further research. Thehypothesis is that projects which have less schedule overlap have lessproject change. An analysis of design/bid/build projects with no overlap anddesign/build or fast-track projects with various degrees of overlap couldtest this hypothesis. The hypothesis is built on the assumption thatdesign/bid/build execution strategy is better than design/build in terms ofaccounting for project change.

The charts, plotted data and linear regression equations for bothanalyses are presented in Figures 14 and 15 on the following pages. Figure14, Engineering Change vs. Schedule Overlap, represents the best fit line forthe data points. The equation of the line y = b + mx is represented asEngineering Change = 0.074 + 0.109 (Schedule Overlap). This equation couldbe used at the start of a project to predict the amount of engineering changethat a project will exhibit based on the amount of schedule overlap betweenengineering and construction. To determine the amount of engineering changeon a project, a project manager can insert the actual percentage of scheduleoverlap and solve the equation.

Figure 15, Construction Change vs. Schedule Overlap, is very similar toFigure 14, which evaluates Engineering Change. The process to develop the twocharts is identical. The equation of the line for Figure 15 is ConstructionChange = -0.018 + 0.392 (Schedule Overlap). This equation can be used todetermine the amount of construction change a project will exhibit based ondesign and construction schedule overlap.

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5.5 Family of Curves for Schedule Recovery

A total of 43 projects in the database were used to develop the Familyof Curves for Schedule Recovery. The curves were first constructed to serveas a prediction tool that would provide the probability of a projectbeing early, on-time or late given some current status. The probabilities

were evaluated for engineering, construction and total project status.Several iterations were performed to determine by how much a project might or

might not be late. Initially, the critical points were established on arange of data points:

o Early (1% to 6%) o Exactly On-time o Somewhat Late (-1% to -4%) o Late (-5% to -20%)

The research team's academic and professional experience determined the most critical data point, trend and interest for the construction industry is

project on-time performance. It was further postulated that other criticalpoints or information for the construction industry are early and lateproject performance indicators. To provide these early and late performanceindicators, analyses of the 25% and 75% quartiles were performed.

In examining the status of projects at the 25% and 75% completion point, we wanted to determine the probability of projects completing on-time or

nearly on-time. The points or range examined for a project being on scheduleis based on the following increment:

o Ahead of Schedule o On Schedule o Behind 0 to -3% o Behind -3 to -6% o Behind Greater Than -6%

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Charts containing schedule recovery curves were developed forengineering, construction and total project performance. Some anomalies orstray data points are present in the curves. One example of this ispresented in Figure 16, Probability of Engineering Schedule Recovery. Forthe 25% complete curve, the data indicate that there is a higher probabilityof finishing on time when the project is -3 to -6% behind schedule (50%) thanif the project is 0 to -3% behind schedule (33%). Despite these anomalies,the curves do represent a common characteristic which is further discussed inthe evaluation and comparison of the three schedule recovery curves.

Using the on-time question as a reference point provides a goal toevaluate project performance. The other reference point established for thisanalysis is at what point in the project is the probability of on-timeperformance assessed. We specified the 25% and 75% project complete points asreferenced assessment points and designated these points as "recoveryassessment".

There is a high probability that the further behind one is at recoveryassessment , the greater the probability there is that the project will notrecover to have an on-time performance. In Figure 16, for example, on the 75%complete curve there is a greater probability of being on time if only 3%behind (60%) instead of greater than 6% behind (17%).

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The overall probability of construction schedule recovery does notexceed 50% at any time during the phase. Comparing the separateprobabilities developed for engineering and construction schedule recoveryindicates that construction recovery may be less probable than engineeringschedule recovery. It may be that a project s construction phase is furtheralong toward completion than in the engineering phase, thus making itharder to recover from being behind schedule. Further analysis in this areais needed to definitively state that this assumption is valid.

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The final analysis of schedule recovery curves examined total projectperformance. This analysis evaluated engineering and construction togetherto develop the Probability of Total Project Schedule Recovery Figure 18.


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The most apparent characteristic of total project schedule recovery isthe general downward trend, that is exhibited for both the 25% and 75%project complete linear lines. This characteristic is also exhibited inthe other two schedule recovery charts. It should be apparent from theanalyses for schedule recovery, that projects have a much higher probabilityof being late than early. Project managers and project team members shouldbe very conscious of the fact that on time schedule performance is notprobabilistically normal.

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5.6 Project Budget Recovery

An analysis of 19 CII project was conducted to identify the probabilityof a project finishing over budget. The projects were selected on the basisof cost and budget data from the questionnaire. Two pieces of data from thequestionnaire were used for the analysis. The Original Control Budget(Question 11) and the Final Value of Facility Forecast (Column 5) were thesignificant data for the analysis.

The analysis structure used for schedule recovery provided the frameworkfor our budget analysis. Project milestones of 25%, 50% and 75% of projectbudget status were evaluated against project status at the 100% completepoint.

If a project was + or - 5% of budget projections, it was considered onbudget. Project budgets that were below or above the 5% reference wereconsidered under budget or over budget, respectively. The chart prepared forthe Probability of Finishing Over-Budget is presented in Figure 5.9. Thesepoints indicate that from the data analyzed there is a zero probability thatthe project remained under or on budget until the end of project or 100%complete.

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Two points are readily apparent when reviewing the chart. The mostobvious point is the high probability of projects being over budget. This isfurther emphasized by the probabilities being higher than 90% for all threeof the project milestones, i.e., 25%, 50% and 75% complete.

The other significant point to discuss is the upward trend for theprobabilities moving from left to right on the chart. Starting with the 25%complete project status, there is a 33% chance that the project will be overbudget even if it is currently under budget. This probability increases to70% if the project is on budget at the 25% and is 100% if over budget at the25% complete milestone.

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Hypothesis 1: Changes that occur late in a project are implemented lessefficiently than changes that occur early in the project.

The research team concludes that this hypothesis is valid but can not bestatistically proven at this time. Additional research to further analyzethe impact of late project change on project efficiencies is needed.

Improved methods of change measurement should be developed andimplemented to quantify the scope and full impact of project change.

Hypothesis 2: The more change there is on a project, the more of a negative impact there is on labor productivity.

The research validated this hypothesis statistically by showing thatgreater amounts of change have greater negative impacts on laborproductivity. Validating the hypothesis statistically supports earlierresearch completed concerning the ripple effects of project change.It is recommended that construction professionals develop, test, implementand enforce change management procedures to better manage the amount andtiming of project change.

Hypothesis 3: Hidden change increases with more project change.

The research identified hidden change and statistically proved thedirect relationship between hidden change and project change. This findingfurther supports the findings and recommendations presented for Hypothesis2.

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Construction professionals must improve the identification and measurements techniques for project change to better measure hidden change

impacts.

6.3 Change Measurement Findings and Recommendations

Five methods for measuring project change are presented as a secondindustry contribution. The methods are a starting point for constructionprofessionals as well as additional research to measure project change.

Total Project Contingency Draw Down

The rate of contingency draw-down was measured and graphed againstschedule completion rates. This analysis developed a chart that can be usedby construction professionals to compare one project or a group of projectagainst the research findings.

The most significant findings are that:

o contingency draw-down occurred at a fairly constant downward trend up to the 70%-75% project completion point

o rapid draw-down occurred in the last quartile of project completion typically occurs

Rapid contingency draw-down can be curtailed by:

o implementing project change earlier in the project cycle

o providing better project information and detail to the design or construction team

o developing, implementing and enforcing change management procedures

o involving users and owners that are experienced in construction issues early in the project

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Additional research should be conducted to determine whether design/bid/build and design/build execution strategies affect these findings.

Family Of Curves For Schedule Recovery

Charts are included for engineering, construction and total projectstatus at the 25% and 75% completion points provide the probabilities ofprojects finishing on-time. The charts reveal that there is a highprobability that projects that fall behind schedule at an early stage areunlikely to recover. Specifically, this research found that projects at 25%and 75% complete milestones have the following characteristics:

o projects have a higher probability of being late than early

o the last quartile of projects are difficult to control

o if a project is behind greater than 3% there is a low probability that the project will recover to finish on schedule

o the later a project is at the 25% or 75% complete, the less chance it can be recovered

o in the construction phase of a project there is less than a 50% chance that the project will finish on time whether the project is ahead or behind schedule

If on time performance is a critical factor to project success, it isrecommend that project managers attempt to keep projects ahead of schedule.Also, if projects are behind schedule, project managers should acknowledgeearly in the project cycle that the probability of completing on time is lessthan 50%.

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Project Budget Recovery

One chart was developed that shows the probability of a project goingover budget. The significant finding is that:

o For all projects studied there is over a 90% probability that a project will run over budget

It seems that current cost control systems are not being employedeffectively or are not achieving the objective of keeping projects withinbudget. If budget control is critical to the construction industry,additional resources will have to be directed towards project control.

6.4 Summary

This CII research project has focused on the quantitative impact ofproject change. Three variables that are impacted by project change arecosts, schedule and labor productivity. It is hoped that this research hasidentified methods for measuring and ultimately limiting the amount andnegative impact of project change.

The research has made two significant contributions to the constructionindustry. The first contribution is the statistical validation of twohypotheses. The second contribution is the quantitative methods developedand tested to measure project change. Additional research is needed toadvance the industry s understanding of project change impact. Furtherresearch should focus on reducing the negative impact of change and improvingthe project change process. The industry needs a standardized change

management model to uniformly measure, track and process project change.

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APPENDIX A RESEARCH QUESTIONNAIRE


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COLLEGE OF ENGINEERINGTHE UNIVERSITY OF TEXAS AT AUSTIN

Construction Industry Institute3208 Red River Street, Suite 300, Austin, Texas 78705-2650(512) 471-4319Fax: (512) 499-8101

MEMORANDUM

TO: CII Board of Advisors

FROM: Richard L. Tucker

DATE: August 12, 1993

RE: Task Force 43, Project Change Management Questionnaire

Attached is a questionnaire which we are asking you to complete per theenclosed instructions. Task Force 43, Project Change Management, has workedhard to develop this document and has tested it on two occasions with thosecompanies represented on the task force. While we all recognize the timedemanded by questionnaires and surveys, the ability to access companiesrepresented by our membership to obtain real project data adds much validityto our research projects.

This task force was established in January 1992, and funding for theirresearch project was approved in April 1993. Publication of their results iscurrently scheduled for the second quarter of 1995. Your participation helpsensure that these publications are of value to our members.

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CONSTRUCTION INDUSTRY INSTITUTE TASK FORCE 43

QUESTIONNAIRE ON THE IMPACT OF PROJECT CHANGE

CII Task Force 43 was established to study more effective ways to manageproject change. As part of our research, we are sending this questionnaireto all CII members for the purpose of collecting information about thequantitative characteristics and effects of project changes. Extensiveresearch has previously been completed that identifies the qualitative impactof change. But that prior research has not focused on the quantitativeimpact of project change because of the difficulty in obtaining accurate andconsistent quantitative data. Our research is examining the impact ofproject change on the macro level and in a quantitative manner. The datacollected will be analyzed to develop change impact graphs and multipliersfor use by project managers in the engineering and construction industry.

We also hope to glean additional information that will improve change management procedures and improve the working relationships between owners

and contractors. This will help our task force prepare a general publicationon Best Practices of Change Management. The confidentiality of your answers

will be preserved in accordance with CII Level 2 confidentiality guidelines.Your answers to this completed questionnaire will be returned directly to theresearchers who will remove any company and project identification from thesurvey forms. We suggest that a project manger or senior cost engineer fromyour company complete this questionnaire. It covers a wide range of issuesrelated to cost, schedule, change orders, and project management. A glossaryof key terms is provided at the end of this questionnaire as Attachment 1.

INSTRUCTIONS

Please select 5 or more projects with which you were involved as eitherowner, contractor or construction manager. We are requesting severalprojects from each CII member to increase our project sample size andstrengthen our findings. If you are not able to supply 5 projects, pleaseprovide as many as you can.

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The projects that your organization provides for this research projectshould represent a variety of completed projects. We are specificallylooking for project performance data that is accurate and well organized.

This questionnaire is designed to expedite your responses and minimizethe amount of time required to complete the questionnaire. Quantitativeproject information is needed to perform the research project change analysisand develop industry change multipliers.

Projects selected should meet the following criteria:

o Projects can be either domestic or foreign so long as costs and performance were not greatly influenced by currency exchange

o Projects should have a Total Installed Cost (TIC) over $15 million

o Projects should have been completed within the last 5 years

Make copies of this survey form for each project. If you wish, feel freeto send a copy of this questionnaire to the contractor or client that you

worked with on this project.

Send the completed questionnaires to the researcher listed below. Ifyou need additional copies or information contact the researcher directly:

Professor Bill Ibbs Dept. of Civil Engineering c/o Walter E. Allen 3636 Rhoda Avenue Oakland, California, 94602

Phone: (510) 530-8661 Fax: (510) 643-8919

Please return all completed pilot questionnaires no later thanSeptember 1, 1993.

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PROJECT INFORMATION

Project Name __________________________________________________Project Location - City & State _____________________________________Project Country _________________________________________________

What was the Total Installed Cost (TIC) for the Project ___________________

1. Is your organization an/a:

Owner _____________ Construction Contractor only_____________ Turnkey (EPC) firm _____________ Construction Manager_____________ Engineering/Design Firm _____________ 2. What was the contracting strategy for this project?

Design/Build ______________ Separate design/construction (Design/Bid/Build) ______________ Some other form ______________ 3. What was your organization's role for this project?

Owner______________ Engineering______________ Construction Contractor______________ Turnkey Contractor______________ Other (Describe)______________ 4. Was the owner of this project Private Sector Company_________ Government Agency _________ Other (Describe)_________

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11. What was the Original Control Budget (OCB) for:

engineering labor_____________ construction labor_____________ permanent materials_____________ other expenses_____________ Total OCB_____________

12. When was this OCB established?

pre-engineering__________ 10% engineering__________ other (specify)__________ 13. What was the Final Control Budget (FCB) for:

engineering labor_____________ construction labor_____________ permanent materials_____________ other expenses_____________ Total FCB_____________

14. When was this FCB established?

pre-engineering _________ 10% engineering_________ 50% engineering_________ 100% engineering_________ other (specify)_________

15. Were there any project changes that were escalated or settled outsidethe routine change order procedures; e.g., mediation, arbitration or formallitigation?

Yes ___________No __________

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16. If the answer to question #15 is yes, what percent of TIC did thosechange costs represent according to dispute resolution method category?

Total Percentage ______________ Litigation ______________ Mediation ______________ Arbitration ______________ Executive Conference ______________ Some other mechanism (please describe) ______________

17. Did the original project budget estimate contain a cost account orcontingency for project changes?

Yes _________ No __________.

18. If yes, what was the amount _____________ and how was the change orderbudget calculated:

1. Fixed Percentage _______ What was the percentage __________ 2. Risk Analysis by specific item ____________ 3. Other method, please explain _________________________________ _________________________________________________________________

19A. Were the majority of project changes priced and approved within yourorganization's established time period? Yes __________ No __________

19B. Were the majority of project changes processed in accordance with yourorganization's standard operating procedures? Yes ________ No _______

20. If the answer to question 19A or 19B is no, what caused the delay. Negotiations _________Completion of Estimate _____________ Slow Approval Process _________Completion of Paper Work __________ Other_________________________________________________________

21. In general what type of pricing method was used to estimate theseproject changes?

Unit Pricing ______________Forward Pricing ____________ Retrospective Pricing _________Time & Materials ___________

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22. Do you think that the number of changes on this project were: more than normal _____, comparable with industry norm _____ or lower than normal _____.

23. In which area of your project was construction productivity mostaffected by change orders and by cumulative change impact:

Site & Earthwork______ Metals & Specialties____ Wood/Plaster/Insulation______ Subcontractors____ Concrete______ Electrical____ Steel______ Mechanical____ Piping/Instrumentation______ Admin./Overhead____

INSTRUCTIONS FOR COMPLETING QUESTIONNAIRE CHART

The remaining portion of this questionnaire requires quantitativeinformation from the project. Most of this information should be collectablefrom monthly project reports and project close-out files. The shaded areasof the chart represents the most important information needed for ouranalysis. Please make them your top priority.

In general, if you have any questions about our terminology refer toCII publications 6-1, Project Control for Engineering, and 6-5, ProjectControl for Construction. Otherwise call the Berkeley research team.

Headings for Table 1: TOTAL PROJECT CHANGE IMPACT

The main purpose of this table is to test our 1st hypothesis:

Changes that occur late in a project are implemented less efficiently than changes implemented early.

Col. 1. Percent Complete: The table seeks data at several milestone points based on progress of the work. The first set of percentages refers to percent complete milestones in detailed engineering; the second set to milestones in construction.

100% complete in engineering is defined as the time when the last specification or drawing required for construction is issued.

Field engineering or field representation for the purpose ofinterpreting drawings, the production of "as-built" drawings,project data books and reports, operating manuals and the like, are

considered outside "detailed engineering".

0% complete in construction is the time of physical mobilization at the site.

100% complete in construction is at the time that the physical scope of the facility agreed in the contract is physically

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complete, and the owner has obtained beneficial use of the facility.

Col. 2. Project Week Plan: This column seeks information on when the accomplishment of project milestones were to be achieved in the

project plan. The project calendar starts with the kickoff of "detailed engineering" and runs continuously to the end of construction. Insert in this column the point in time during the project calendar, expressed in weeks from the project start, when the physical complete milestone (e.g., 25% engineering) was scheduled to be reached (e.g., project week 15). For construction

dates, follow the same procedure, again counting project weeks from the start of detailed engineering. For example, if construction mobilized 18 weeks after the start of engineering, one would insert "18" for 0% construction, and all other milestone dates would follow this calendar.

The project schedule to be used here is the "Original Control Schedule", sometimes referred to as the "Baseline Schedule". It may be that the construction control schedule was established

later than the engineering control schedule. If the baseline schedule for physical percent complete is expressed as an "early" schedule and a "late" schedule, use the average between the

two values.

Col 3. Project Week Actual: This column seeks information on when physical milestones on the project were actually achieved. The

project calendar, again, starts with the kickoff of detailed engineering and ends with actual construction completion.

To establish the project week for each physical milestone, physical progress for the engineering or construction may need to be re-calculated from the point of view of the completed project, including scope changes. For example, if the engineering scope of a project was increased 30% after the original 50% milestone was achieved, the dates 25% and 50% milestones that were originally reported would have to be revised to reflect the new final scope.

Col. 4. Change % Growth in Forecast Labor-Hours: At each of the points indicated in the project, give the growth in the labor-hour forecast as a percentage of the original control budget reported at the time the actual percentage milestone was achieved. For detailed engineering, give the percentage of growth in the forecasted engineering labor-hours only. In construction, give the percentage of growth of the forecasted construction labor-hours only. In both, include both direct and indirect (project-specific overhead) labor-hours. It is possible for the forecast for construction labor-hours to increase above the control budget during engineering and before construction mobilization.

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Col. 5. Facility Cost Forecast ($): This column represents the overall project facility cost forecast, reported at the time the actual milestone was achieved. This forecast should not include the cost of land or owner costs related to facility operation. Only owner costs related to the EPC process are included; e.g. owner's engineering, contract administration and engineering management expenses.

Please give a short explanation of what is and is not included in the forecast, and the originator of the forecast (owner, engineer, contractor):

_______________________________________________________________

________________________________________________________________

In projects with overlap of engineering and construction, show the forecast under engineering until construction mobilization, then show the forecast under construction.

Col. 6. Total Project Contingency ($): In this column, give the remaining total project contingency at the actual milestones indicated. As in the "Total Facility Cost Forecast", show the contingency figure under engineering until construction mobilization, then show the

figure under construction.

The remaining columns of this table gives the cumulative estimated costs of change orders.

Col. 7. Total Change ($): Give the cumulative total estimated cost of the change orders numbered in column 7.

In Columns 8-11, give the breakdown of the change order cost given in Column 7. The sum of columns 8-11 should equal the figure in column 7.

Col. 8. Permanent Material ($): Includes the cost of permanent materials and permanent equipment.

Col. 9. Construction Labor ($): Includes the cost of all construction craft labor and their immediate supervisors.

Col. 10. Engineering Labor ($): Includes the cost of all engineering labor and their immediate supervisors.

Col. 11. Other Costs ($): Includes all costs associated with owner costs (if known); engineering personnel; construction indirect personnel; subcontractors; and construction equipment and materials.

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Our 2nd hypothesis is:

The more change there is on a project, the more of a negative impact there is on productivity.

To test this hypothesis, please answer the following questions:

20. What was the total number of labor-hours expended for engineering on this project? ____________

21. What was the total number of labor-hours expended for authorized changes originating during the project's engineering phase? __________

22. CII's definition of a project's productivity ratio is earned labor-hours divided by expended labor-hours. What was the final productivity ratio for the engineering work on this project? __________

23. What was the total number of labor-hours expended for construction during the construction phase on this project? ___________

24. What was the total number of labor-hours expended for authorized changes that originated during this project's construction phase? __________

25. What was the final productivity ratio for the construction work on this project? (Productivity ratio is earned labor-hours divided by expended labor-hours.) ________

26. When was the original control budget for engineering developed for this project?

Pre-engineering _____ 10% engineering complete _____ 30% engineering complete _____ 50% engineering complete _____ 100% engineering complete _____ Other (Please specify) _____

27. When was the original control budget for construction developed for this project?

Pre-construction _____ 10% construction complete _____ 30% construction complete _____ Other (Please specify) _____

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POINT OF CONTACT INFORMATIONYour Name ______________________________________________________Title __________________________________________________________Role During The Project_________________________________________Street Address _________________________________________________City/State/Zip _________________________________________________Telephone ______________________________________________________Fax ____________________________________________________________

Would you be available for a follow-up telephone interview.Yes _____________ No ___________

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Attachment I General Glossary of Terms

Change: Any event which results in a modification of the original scope, execution, time or cost of the work.

Change Order Formal documentation which recognizes the existence of a changeand modifies the agreement between contracting parties accordingly.

Detailed engineering: Engineering and design work perfumed to produce drawings and specifications for construction. Differs from "conceptual

engineering' which includes studies, estimates and other consultingactivities performed to assist the owner in establishing the scope of

the project

Direct Labor: Labor which is consumed directly in the production of engineering deliverables or in the fabrication or erection of physical

construction quantities. For the purposes of this research, "directlabor" includes only labor included in the calculation of progress(percent complete).

Indirect Labor: Other labor attributed to the project, but which is not included in the calculation of physical progress.

Owner: The organization that will ultimately occupy the facility, and is ultimately paying for design and construction of the facility.

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APPENDIX B CITED AND UN-CITED BIBLIOGRAPHY

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Appendix B Bibliography

Cited

Allen, Walter E. A Methodology for Evaluating the Effective Processing ofProject Change, Dissertation Proposal, December 1993.

Anbari, Frank T., A Systems Approach to Project Evaluation, ProjectManagement Journal, Vol. 16, No. 3, August, 1985.

Borcherding, John D., Improving Productivity in Industrial Construction,Journal of the Construction Division, Proceedings of the American Society ofCivil Engineers, Vol.102, No.CO4, December, 1976.

Bitner, L. M., Project Management: Theory Verses Application, ProjectManagement Journal, Vol. 16, No. 2, June 1985.

Construction Industry Institute, Productivity Measurements: An Introduction,Austin Texas: Publication 2-3.

Construction Industry Institute, Project Change Management, Austin Texas:CII Special Publication 43-1, September 1994.

Clark, William G., Claims Avoidance and Resolution, Transactions of theAmerican Association of Cost Engineers, Boston Massachusetts, R-1, pp. 1-6,1990.

Dellon, Alfred L., and Dellon, Irene J., Documentation and Verification inthe Change Process, Transactions of the American Association of CostEngineers, New York, NY., C-7, pp. 1-5, 1988

Diekmann, J.E., and M.C. Nelson. "Construction Claims: Frequency andSeverity." Journal of Construction Engineering and Management, Vol .111, No.1American Society of Civil Engineers, March, 1985

General Accounting Office, Internal Controls: EPA Needs to Improve ControlsOver Change Orders and Claims, Document GAO/RCED-88-16, Washington D.C.,1987.

Halligan, David W., et all. Action-Response Model and Loss of Productivity inConstruction , Journal ofConstruction Engineering and Management, Vol. 120, No.1 American Society ofCivil Engineers, March 1994

Hester, Weston T., Kuprenas, John A., Chang, T.C., Construction Changes andChange Orders: Their Magnitude and Impact , Construction Industry Institute,Source Document 66, October 1991.

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Un-cited

Construction Industry Institute, Evaluation of Design Effectiveness, AustinTexas: Publication, 1986

Construction Industry Institute, Organizing for Project Success, AustinTexas: Publication 12-2, February 1991

Construction Industry Institute, Preview of Construction Implementation,Austin Texas: Publication 34-2, February 1993.

Construction Industry Institute, Project Control For Construction, AustinTexas: Publication 6-5, September 1987.

Construction Industry Institute, Project Control For Engineering, AustinTexas: Publication 6-1, July 1986.

Civitello, Andrew M. Jr., Contractor's Guide to Change Orders, Prentice-Hall,Inc., Englewood Cliffs, 1987.

Department of the Army Office of the Chief of Engineers, Modification ImpactEvaluation Guide, Washington, D.C., July 1979

Ibbs, C. William., Ashley, David B., Neil, James M., and Feiler, Frank W.,"An Implementation Strategy For Improving Project Control Systems", ProjectControls: Needs and Solutions, American Society of Civil Engineers, New York,New York, June 1987

Johnson, Charles F., "Early Warning Signs - Trending Techniques",Transactions of the American Association of Cost Engineers, San Francisco,California, pp. 125-128, July 1978, Morgantown, West Virginia: AmericanAssociation of Cost Engineers.

Mitchell, Paul James, "Holding Down the Cost of Change", The Role of theResident Engineer, ASCE Publications, New York, New York, 1985

Rogge, David F., "Delay Reporting Within Cost Accounting System", Journal ofConstruction Engineering and Management, Vol. 110, No.2, June 1984

Scott, Donald F., "Effective Contract Administration in ConstructionManagement", Journal of the Construction Division, Proceedings of theAmerican Society of Civil Engineers, Vol. 100, No. CO2, June 1974

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Un-cited

Suchanic, George, "Change Order Impacts on Construction Cost and Schedule",1980 Transactions of the American Association of Cost Engineers, Washington,D.C., F-3, pp. 1-7, 1980

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APPENDIX C SUMMARY TABLES & GRAPHS

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Appendix D Glossary

Approved Changes: Changes which are approved by both parties. Approvedchanges are divided into two classifications discretionary andunavoidable changes.

Change: Any event which results in a modification of the original scope,execution, time or cost of work.

Change Order: Formal documentation which recognizes the existence of achange and modifies the agreement between contracting parties accordingly.

Consequential Cost: Consequential costs are additional costs incurred as aindirect result of some earlier project

sd108- quantitative impacts of project change

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