CONSTRAINTS TO IMPLEMENTING EARNED VALUE MANAGEMENT (EVM) AS A TOOL FOR PROJECT PLANNING AND CONTROL – A SOLUTIONS PERSPECTIVE - A CASE STUDY AMONG NIGERIAN CONSTRUCTION PROJECT MANAGERS MASTER THESIS International Master of Science in Construction and Real Estate Management Joint Study Programme of Metropolia UAS and HTW Berlin Submitted on 20.08.2019 by Gbolahan Opeyemi Ola Metropolia UAS student number:1707883 HTW-Berlin student number: S0562663 First supervisor: Prof. Dr.-Ing. Nicole Riediger Second Supervisor: Arch. Eric Pollock
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CONSTRAINTS TO IMPLEMENTING EARNED VALUE
MANAGEMENT (EVM) AS A TOOL FOR PROJECT PLANNING
AND CONTROL – A SOLUTIONS PERSPECTIVE - A CASE STUDY
AMONG NIGERIAN CONSTRUCTION PROJECT MANAGERS
MASTER THESIS
International Master of Science in Construction and Real Estate
Management
Joint Study Programme of Metropolia UAS and HTW Berlin
Submitted on 20.08.2019 by
Gbolahan Opeyemi Ola
Metropolia UAS student number:1707883
HTW-Berlin student number: S0562663
First supervisor: Prof. Dr.-Ing. Nicole Riediger
Second Supervisor: Arch. Eric Pollock
i
ACKNOWLEDGEMENT
This thesis and the past two years of study, though challenging, were only
completed through the constant support and encouragement from my family and
friends.
I appreciate my mother and father for their prayers, care and concern. I want to
say thank you to my elder sister, Damilola, for being such a role model, and with
her husband, Adekunle, their endless support. I am also thankful to my younger
siblings and cousins (Boluwatife, Mojisola and Monisola) who have cheered me
on during this journey.
I am sincerely grateful for the immeasurable support from a cousin turned big
brother, Gbenga Komolafe and his beautiful family. Morenike, Seyi, Tosimi,
Segun, Tolulope and Shashank who have helped with logistics and advised me,
I say a big thank you.
I want to thank the faculty and administrative staff of HTW-Berlin and
Metropolia UAS that have taught and guided me throughout this program.
Once more into the fray, Into the last good fight I’ll ever know, live and die on this
day, live and die on this day. (Carnahan, 2012).
ii
International Master of Science in Construction and Real Estate Management
Joint Study Programme of Metropolia Helsinki and HTW Berlin
Date: 06.06.2018
CONCEPTUAL FORMULATION
Master Thesis for Mr Gbolahan Ola
Student number S0562663, 1707883
Topic: CONSTRAINTS TO IMPLEMENTING EARNED VALUE MANAGEMENT (EVM) AS
A TOOL FOR PROJECT PLANNING AND CONTROL – A SOLUTIONS
PERSPECTIVE - A CASE STUDY AMONG NIGERIAN CONSTRUCTION PROJECT
MANAGERS
Signature of the Supervisor
iii
CONSTRAINTS TO IMPLEMENTING EARNED VALUE
MANAGEMENT (EVM) AS A TOOL FOR PROJECT PLANNING
AND CONTROL – A SOLUTIONS PERSPECTIVE - A CASE STUDY
AMONG NIGERIAN CONSTRUCTION PROJECT MANAGERS
Master thesis proposal
International Master of Science in Construction and Real Estate
Management
Joint Study Programme of Metropolia UAS and HTW Berlin
By
GBOLAHAN OLA
HTW-Berlin registration number: S0562663
Metropolia UAS registration number: 1707883
First supervisor: Prof. Dr.-Ing. Nicole Riediger
Second Supervisor: Eric Pollock
Submitted on 16.04.2018
iv
INTRODUCTION
There are several developed techniques used in project control. Earned value
analysis (EVA) seems to be a widely known and accepted method to use on
projects to understand, manage and forecast performance. It is a technique that
measures three important baselines in project management (scope, cost and
time) to give the overall health and progress of a project. These measurements
provide the project manager with the ability to review the project beyond the
independent reviews of these three baselines. As most projects almost certainly
never go entirely according to the project plan and corrective measures are
required, information from the EVM process is crucial for evidence-based
decisions and actions needed to keep the project on its planned baselines or as
close as possible to them.
Significant advantages of using EVM is that it increases project accountability,
and it can anticipate future project setbacks along the three cardinal baselines
early enough. Through using index-based forecasting, project managers are able
to determine amongst other parameters, cost and schedule variance, Schedule
Performance Index (SPI), Cost Performance Index (CPI), Budget at Completion
(BAC), Estimate of costs To Completion (ETC) and most importantly the To
Completion Performance Index (TCPI).
RESEARCH PROBLEM
Cost and schedule overruns are the usual criticisms of project execution in
Nigeria. As early as Idoro (2009) mentioned that project delay is the major
problem facing the Nigerian construction Industry. It is common that when a
schedule overrun occurs, project durations are extended or more resources are
applied to the project to crash its schedule; in both cases, this leads to additional
project costs. While most projects start with varying levels of detailed planning,
during execution, there is minimal effort committed to monitoring and control
and use of EVM as a tool for monitoring and steering a project to better
v
performance. Its skills and adoption among Project managers in Nigeria appear
low, even in the face of tight project constraints and increasing global completion
in the local market. This thesis would seek to study the applicability of EVM in
controlling projects in Nigeria. It would consider the method of integrated project
control (if any), among construction managers, it would also seek to determine
the best approach to address the constraints how earned value could be
implemented in the construction project organisation.
RESEARCH QUESTIONS
1. What is the impact of EVM on overall construction project performance?
2. What are the constraints for implementing EVM in Construction projects?
3. What is the most effective way to enhance the application of EVM in
construction projects for better performance?
METHODOLOGY
To accomplish the objectives of the research, the author conducts exploratory
research through literature reviews, surveys and focus groups/interviews. The
literature review will focus on project management control and earned value
management and its usefulness in construction projects. Survey questionnaires
would be randomly distributed to project managers and focus group/interviews
would be conducted for senior project managers, architects and Engineers.
Results from the analysis of distributed questionnaires would be used to answer
research question 1& 2, while focus group or interviews would be used to answer
research questions 1 & validate solutions to question 3 that the researcher would
provide.
vi
EXPECTED RESULTS
This thesis presents earned value method to solve the problem of poor project
control; with emphasis on Nigerian construction projects. Through researching
project contracts; project accountability culture; and performance recording and
analysis methods, Conclusions from this thesis should provide a framework for
project managers on how to use EVM at an organisational level.
THESIS OUTLINE
This thesis would be divided into five chapters. First chapter; the Introduction
and study background of earned value management. The second chapter will
cover literature reviews the author would connect the research topic to previous
academic works where more in-depth studies into the concept of earned value
management from multiple perspectives.
The fourth chapter, called ‘Results/Findings’, represents the author’s analyses
of research data. Lastly, the Discussions Conclusions and Recommendations
chapter closes out the research and the author shows his
interpretation/observation from the data analyses within the context of the
research topic.
REFERENCE
Idoro (2009), “Evaluating the level of use of bar chart and its influence on project
performance in the Nigerian construction industry”, Department of Building,
University of Lagos, Akoka, Lagos, Nigeria, COBRA 2009, Pp 37-44
vii
ABSTRACT
This thesis examines the constraints to implementing Earned value management
in construction projects and provide solutions to these constraints. This thesis
begins by presenting the historical background of EVM, how it is derived and
effectively used, the benefits possible through its use, and finally, its limitations.
To answer the research questions, literature reviews and questionnaires are
used. Seventy-three construction project managers participated in the survey.
Notably, a key observation from literature review, reveals that current
information do not examine comprehensively, the relationship between EVM and
strategic project organization.
From fragmented works of literature and the analysis of survey responses, the
author identifies several factors that impede the effective implementation and
use of EVM. These factors are; flexibility to scope changes, error reporting and
data manipulation, standardization of processes, punishment of contractors and
lastly, IT and software support.
To conclude, the author presents recommendations to overcome each impeding
factor and offers two strategic EVM organisational models centered around these
recommendations. These models having varying emphasis on individual factors
are designed to cater to different implementation environments.
viii
TABLE OF CONTENTS
ACKNOWLEDGEMENT .......................................................................................................................... i
CONCEPTUAL FORMULATION ............................................................................................................ ii
ABSTRACT ............................................................................................................................................... vii
TABLE OF FIGURES .............................................................................................................................. x
LIST OF TABLES ..................................................................................................................................... x
LIST OF ABBREVIATIONS .................................................................................................................. xi
1 INTRODUCTION ............................................................................................................................. 1
1.1 INTRODUCTION ...................................................................................................................... 1
1.2 RESEARCH PROBLEM .......................................................................................................... 2
1.3 SPECIFIC THESIS OBJECTIVE .......................................................................................... 3
1.4 BROADER RELEVANCE OF THE THESIS ...................................................................... 3
1.5 RESEARCH QUESTIONS ...................................................................................................... 4
1.6 METHODOLOGY ..................................................................................................................... 4
1.7 THESIS SCOPE ........................................................................................................................ 4
1.8 EXPECTED RESULTS ............................................................................................................ 5
2 LITERATURE REVIEW ................................................................................................................. 6
2.1 INTRODUCTION ...................................................................................................................... 6
2.2 HISTORICAL BACKGROUND .............................................................................................. 7
2.3 EVM AND PROJECT MANAGEMENT: CONCEPTUAL CONNECTIONS ............... 10
2.4 EVM INDEXES, PERFORMANCE ANALYSIS AND FORECAST .............................. 13
2.4.1 Primary EVM Indexes ................................................................................................... 13
2.4.2 Performance Metrics ...................................................................................................... 14
2.4.3 Forecast metrics ............................................................................................................. 18
2.5 EVM, PROJECT DELIVERY AND CONSTRUCTION PERFORMANCE ................. 22
2.6 PROCUREMENT AND EVM ............................................................................................... 25
2.7 EVM AND PROJECT MANAGEMENT INFORMATION SYSTEMS .......................... 28
2.8 CRITICISMS/LIMITATIONS OF EVM .............................................................................. 30
3 METHODOLOGY ........................................................................................................................... 34
3.1 INTRODUCTION .................................................................................................................... 34
3.2 RESEARCH PHILOSOPHY AND DESIGN ...................................................................... 34
3.3 SAMPLE POPULATION ........................................................................................................ 36
ix
3.4 SAMPLING PROCEDURE ................................................................................................... 36
3.5 VALIDITY AND RELIABILITY OF THE RESEARCH INSTRUMENT ....................... 37
3.5.1 Validity .............................................................................................................................. 37
3.5.2 Reliability ......................................................................................................................... 37
3.6 DATA ANALYSIS TECHNIQUE .......................................................................................... 37
3.6.1 Analysis of quantitative data ..................................................................................... 37
3.6.2 Analysis of qualitative data ........................................................................................ 38
3.7 MEASUREMENT OF VARIABLES .................................................................................... 38
4 DATA ANALYSIS ........................................................................................................................... 39
4.1 INTRODUCTION .................................................................................................................... 39
4.2 QUESTIONNAIRE RETURN RATE ................................................................................... 39
4.3 QUESTIONNAIRE ANALYSIS ............................................................................................. 39
5 RECOMMENDATIONS AND CONCLUSION ........................................................................ 51
5.1 FLEXIBILITY TO SCOPE CHANGES ............................................................................... 51
5.2 ERROR REPORTING AND DATA MANIPULATION ..................................................... 53
5.3 STANDARDIZATION OF PROJECT MANAGEMENT PROCESSES ........................ 56
5.4 PUNISHMENT OF CONTRACTORS ................................................................................. 58
5.5 IT PROJECT SUPPORT ........................................................................................................ 60
5.6 CONCLUSION ......................................................................................................................... 63
DECLARATION OF AUTHORSHIP ................................................................................................... 67
APPENDIX A ............................................................................................................................................ 68
BIBLIOGRAPHY ..................................................................................................................................... 72
x
TABLE OF FIGURES
FIGURE 1: PROJECT MANAGEMENT PROCESS ...................................................................... 6
FIGURE 2: EVM HISTORICAL TIMELINE .............................................................................. 8
FIGURE 3: GRAPHICAL REPRESENTATION OF THE BODY OF KNOWLEDGE SEARCH RESULTS ....... 9
FIGURE 4: GRAPHICAL REPRESENTATION OF THE BODY OF KNOWLEDGE SEARCH RESULTS ..... 10
FIGURE 5: PROJECT AHEAD OF SCHEDULE USING SCHEDULE VARIANCE ............................. 15
FIGURE 6: PROJECT OVER BUDGET USING COST VARIANCE ............................................... 16
FIGURE 7: EVMS SYSTEM. ............................................................................................ 30
FIGURE 8: ENGINE CHOICE CHECKLIST TO BUILD AN EVMS ............................................... 61
FIGURE 9: MODEL 1 TO OVERCOME IMPLEMENTATION CONSTRAINTS OF EVM ...................... 64
FIGURE 10: MODEL 2 TO OVERCOME IMPLEMENTATION CONSTRAINTS OF EVM .................... 65
LIST OF TABLES
TABLE 1: SUMMARY OF METRICS, MEASUREMENTS AND INTERPRETATION ............................. 20
TABLE 2: EVM MEASUREMENT SCENARIOS AND CORRECTIVE ACTIONS................................. 21
xi
LIST OF ABBREVIATIONS
ABBREVIATION DESCRIPTION
AC Actual Costs
ACWP Actual Cost of Work Performed
AEC Architecture, Engineering and Construction
BAC Budget At Completion
BCWP Budgeted Cost of Work Performed
BCWS Budgeted Cost of Work Scheduled
CPI Cost Performance Index
CR Critical Ratio
CV Cost Variance
C/SCSC Cost/Schedule Control System Criteria
EAC Estimate At Completion
ES Earned Schedule
ETC Estimate to Completion
EV Earned Value
EVM Earned Value Management
EVMS Earned Value Management Systems
PMB Project Management Baseline
PMIS Project Management Information System
PV Planned Value
SPI Schedule performance index
SV Schedule Variance
TCPI To Completion Performance Index
WBS Work Breakdown Structure
WPM Work Package Method
1
1 INTRODUCTION
The difficulty of measuring progress does not justify the conclusion that it should
not be done. You cannot have control unless you measure progress- (Heagney,
2012).
1.1 INTRODUCTION
Sound project management practices and techniques have increasingly become
integral to managing construction projects since project management began in
its modern form in the 1950s. As new projects continue to drive for cost
efficiencies, multi-stakeholder satisfaction, tight schedules and competition
along shrinking profit margins, the competencies of project managers have
become critical to the success of public and private construction offices.
Complex projects in the execution phase, are composed of large volumes of
activities that generate real-time data which are used by project managers to
measure and anticipate future behaviour of the project; and taking necessary
actions where needed. Performance measurement of program outputs and
outcomes provide vital information on current program status and how much
progress has been achieved towards important program goals (NAPA, 1994). The
project manager is proactive and finds problems early, looks for change and
prevents problems (Mulcahy, 2013).
Selectively paramount from data generated from completed and ongoing project
activities are indicatives of the rate of progress/milestone completion and actual
costs. Through analysis of these, useful information is derived in respect of the
triple constraints of project management. These constraints are scope, time and
cost. As mentioned in (Project Management Body of Knowledge book, 2013),
these constraints must be controlled by the project manager (pp 12) and are part
of the bases of measuring success on a project (pp 32). It is the duty of project
2
managers, therefore, to keep up to date with current project data related to these
constraints and trend analysis methods (to derive actual performance), to be
informed enough to maintain control and manage the project to successful
completion. This is known as monitoring and control. The project manager
measures progressive performance against planned performance to determine
project performance in terms of substantial completion, schedule and budget.
“Based on project performance measurement, the project team can activate a
project control process to ameliorate any issues and return the project more in
line with its scheduled course,” thus combating project failure (Ritz, 1994).
Projects lacking monitoring and control could easily experience delayed
completion and poor budget performance. Likewise, as cited in (De Marco, Rafele,
& Briccarello, 2009), (Sterman, 2018), control decisions delayed until late in the
project are mostly expensive and ineffective.
While several decades of modern project management practices have seen the
development of multiple techniques for project monitoring and control, this
thesis will mainly focus on overcoming the current constraints of the use of
Earned Value Management, and improving its application among project
managers.
1.2 RESEARCH PROBLEM
Cost and schedule overruns are the usual criticisms of project execution in
Nigeria. As early as (Idoro, 2009) mentioned that project delay is the major
problem facing the Nigerian construction Industry. It is common that when
schedule overrun occurs, project duration is extended, or more resources are
applied to the project to crash its schedule; in both cases, this leads to additional
project costs. While most projects start with varying levels of detailed planning,
during execution, there is minimal effort committed to monitoring and control
and use of EVM as a tool for monitoring and steering a project to better
performance. Its skills and adoption among Project managers in Nigeria appear
low, even in the face of tight project constraints, erratic inflation and increasing
3
global completion in the local market. Studying the application of Project
management techniques, (Blili & Raymond, 1993), asserted that innovative
analysis and forecasting techniques are scarcely applied in small and medium-
scale organisations. This thesis seeks to study the applicability of EVM in
controlling projects in Nigeria. It would consider the method of integrated project
control (if any) among construction managers; it would also seek to determine
the best approach to address the constraints how earned value could be
implemented in construction projects at an organisational level.
1.3 SPECIFIC THESIS OBJECTIVE
This Thesis aspires to provide a framework for project control optimisation
through the delivery of measures and processes that encourages Construction
managers in Nigeria to adopt EVM. The author seeks to study in-depth
theoretical knowledge of this control tool, to the end that he can implement EVM
on projects and Project Management Offices’ processes. The author believes that
systematic implementation accurate monitoring and forecasting tools in a
projectised environment are a value-adding skill modern project managers
should possess.
1.4 BROADER RELEVANCE OF THE THESIS
(De Neufville & Field, 2018) Described a thesis as an opportunity for students to
be creative, to bring together and integrate skills they have acquired to make a
real professional contribution. This infers that it is geared towards not only
nurturing curiosity and becoming experts themselves but also contributing to
the body of knowledge in their chosen fields.
Successful completion of this thesis would likewise provide an opportunity for
interaction and knowledge sharing among professionals from construction
4
industries in developing countries, advanced countries and academic
institutions.
Through developing guidelines and mechanisms for project monitoring and
reporting within project management and EVM framework, the author is keen to
increase project transparency and accountability.
1.5 RESEARCH QUESTIONS
1. What is the impact of EVM on overall construction project performance?
2. What are the constraints to implementing EVM in Construction projects?
3. What is the most effective way to enhance the application of EVM in
construction projects for better performance?
1.6 METHODOLOGY
To realise the objectives of the research, the author conducts an exploratory
research through literature reviews, surveys and focus groups/interviews. The
literature review focused on project management control and earned value
management and its usefulness in construction projects. Survey questionnaires
would be randomly distributed to project managers and focus group/interviews
would be conducted for senior project managers, architects and Engineers.
Results from the analysis of distributed questionnaires would be used to answer
research questions one and two, while interviews would be used to answer
research questions 1 & validate solutions to question 3 that the researcher would
provide.
1.7 THESIS SCOPE
This thesis focuses on EVM from multiple perspectives. These perspectives
represent planning for the use of EVM in projects through the need for flexibility,
standardization, correct reporting, contactor buy-ins and the tools for accurate
performance recording, reporting and analysis.
5
The thesis presents the analysis of questionnaires and interviews will be
conducted with EVM experts.
1.8 EXPECTED RESULTS
This thesis presents earned value method to solve the problem of poor project
control; with emphasis on construction projects. Through research within the
thesis scope, analyses and recommendations are provided on suitable
approaches on how project managers can successfully use EVM at an
organisational level.
6
2 LITERATURE REVIEW
2.1 INTRODUCTION
EVM derives as a tool developed for use during the planning, monitoring and
control phases of projects. Projects, according to (Project management Institute,
2013), follow a 5 phase process from conceptualisation to completion.
Figure 1: project management process. (Eby, 2018)
Achieving the objectives within each of these phases is vital to achieving success
on any project. (Munns & Bjeirmi , 1996) described these processes as essential
to management to achieve project success. (Bower, 2007) mentioned that these
sequential processes need to be followed to achieve project success.
Project endeavours, managed from initiation to completion, can have
complicated interrelationships, processes and restrictions necessary to achieve
its requirements. To achieve success, (Levine, 2002) mentions that It involves
planning for and controlling scope; budget; schedule; quality; risks; human
resources; procurements; and stakeholder communication. These factors
described as knowledge areas in the PMBOK are developed to avoid budget
overruns, projects delays, stakeholder dissatisfaction, among other project
challenges and failure factors. These five phases and knowledge areas are
designed to have defined inter-related processes to guide project managers and
7
teams to plan, deliver, anticipate and control project activities and their
challenges.
There are methods and tools specific to each project process; the choice of the
approach adopted in a process is dependent on the output requirement of that
process. One such method/tool is EVM. EVM is used for operations in the
planning, execution and monitoring & control phases that relate to scope, budget
and schedule knowledge areas. In line with the objectives of project management
to plan and organise activities, EVM can be described as a project manager’s
policing tool. (Turner, 2007) Identified that the purpose of project management
as to foresee challenges to plan for and control project activities to be
successfully delivered despite these challenges.
2.2 HISTORICAL BACKGROUND
EVM was developed in the 1960s by the US Department of Defence as a financial
tool to measure defence acquisition projects. Project deviations were corrected
using pre-established control baselines of interrelated cost and schedule
indicators. When introduced, it was known as schedule/cost system criteria
(SCSC) but later renamed as earned value analysis. Before its introduction,
schedule and costs measuring tools and reports were used discretely or
independent of each other. A significant limitation of this method is that they
failed to estimate planned costs against actual costs spent to complete real work.
(Chen, 2008) Mentioned, actual costs do not reflect actual accomplishment on
projects. Understanding how efficiently costs were being utilised with relation to
task progress and completion was the motivation behind why EVM was
developed.
Over the following decades, “EVM use spread to other US government agencies
such as the United States Department of Energy, NASA and US Defence
Acquisition Department etc.” (Khamidi, Khan, & Idrus, 2011). It also proved
popular among project stakeholders in the private sector. Liable to terms of an
agreed contract, “contractors are faced with challenges within or outside their
8
control. It is, therefore, crucial for contractors to monitor potential cost overruns
and delays in project execution” (Khamidi, Khan, & Idrus, 2011). (Fleming &
Koppelman, 1998), put forward that EVM is now a necessary tool being used to
determine the value of work achieved when planning payments to contractors
whose jobs are paid for in phases.
(VanderVeen, 2018) also, put forward that EVM is also being used as an
instrument to motivate and boost the morale of the project team when a project
is shown to be ahead of schedule or under budget or both. Literature shows that
while EVM was birthed to address shortfalls in measuring efficient government
project spending, its use has broadened to private projects and is being utilized
to provide an expanding spectrum of human resource and procurement
solutions key to every stakeholder involved in a project. “EVM was developed to
monitor the performance of a project, created from the needs of its own project
EVM era 1
(1956-1967)
•Need for a tool better that PERT/cost
•Development of Work breakdown structure
•Development of cost/schedule control systems criteria
EVM era 2
(1967-1983)
•Over implementation led to resistance from project managers and government agencies
•C/CSCS became dismissed as a financial control tool only for financial analysts
•taught in project management programs for AEC industry
EVM era 3
(1983-1991)
•Began being used by project managers and executives
• Inclusion in the first PMBoK by PMI
•Was included in project procurement criteria
•Development and use of Micro frame progam manager (MPM) which included EVM
EVM era 4
(1992-2002)
• Adoption of more flexible regulations
Adoption in more industrialized nations like Australia , UK and other european countries
• Renamed earned value management system
• Increased reasearch and closer integration & expansion of EVM into Project management methodologies
• Became a compulsory tool across all US Government agencies
Private sector adotion
• EVM calculations integrated into management tools like MS Project and MS Excel
EVM era 5
(2002-2008)
•EVM receives increased attention in Publicly listed companies in the USA in response to Sarbanes-Oxley Act of 2002
EVM era 6
(2008-Present)
•EVM is used as a program management tool in facilities integrated program managemnt
Figure 2: EVM historical timeline. Elaborated from (College of performance management, n.d.)
9
members and more specifically of the members of the project management and
its stakeholders” (Ammari, 2017).
With adoption in construction, manufacturing, oil & gas, IT, infrastructure and
similar industries, EVM is a multi-disciplinary project control tool. To this end,
it has earned recognition among project management professional bodies. Since
its first introduction in 1987, EVM is included in the PMI’s PMBoK guide; which
is a collection of processes; guidelines, best practices and required standards for
project managers in the USA. PRINCE 2, a UK developed project management
methodology built on product-based planning, uses EVM at different levels
ranging from overall project level detail down to activity level detail.
EVM has also picked the interested of researchers, scientists and professional
institutions. An international e-materials search on Metropolia UAS MetCat done
on July 23, 2018, using the search word ‘earned value’ yielded 390, 983 results
with a content type distribution illustrated with the graph below;
Figure 3: Graphical representation of the Body of Knowledge search results. (Author)
A similar search done by (Thomas, 2015) across eight cross-disciplinary
databases gave 145 full-texts, 65 were conceptual, 70 were empirical, and 10
could not be distinguished unambiguously. He presented the distribution of his
results in the chart below:
0 50,000 100,000 150,000 200,000 250,000
1
62329321667041,7122,9795,007 143,784 236,773
EVM document type
E-article Newspaper article
Text resource Review
Website Reference entry
Conference proceeding Other
Book Dissertations
Book chapters
10
Figure 4: Graphical representation of the Body of Knowledge search results. Source: (Thomas, 2015)
From the chart above, it can be seen that as is the reason for the thesis, EVM is
historically most popular in the construction industry.
It is important to note that during its early years in the 1970s and early 1980s,
EVM is documented to have faced challenges of adoption by project managers.
As mentioned by (Fleming & Koppelman, 2010), the general criteria set for EVM
was resisted and sometimes ignored by project managers in both government
and the private industries. In its early days as cost/schedule control systems
criteria (C/SCSC), it was widely misunderstood as a mere a financial control tool
with perplexing definitions and should only concern accountants and analytical
specialists. Perceived to be overly prescriptive criteria and confusing, it was
unsuccessful on many commercial projects (Fleming & Koppelman, 2006)
2.3 EVM AND PROJECT MANAGEMENT: CONCEPTUAL CONNECTIONS
As already established, EVM is a well-known methodology in project
management and in construction. The primary motive of having a project
management team dedicated to a construction project is to have it deliver all
project requirements on schedule, within budget and achieve stakeholder
11
satisfaction. The success of project managers is highly dependent on their choice
and level of expertise of methodologies they apply to their tasks. (Lehtonen &
Martinsuo, 2006); Methodologies provide more predictable project success than
projects that do not use one. Methodologies adopted in the executing and
monitoring and control phases of project management are processes that use
project success baselines, project data and skills of a project team to produce
output information necessary to enhance ongoing project performance. It is
therefore crucial for the purposes of achieving project success, to have these
three factors harmonized for best results.
In addition to requiring good skills from the project manager and pre-determined
project baselines, EVM analyzes quantitative data generated on ongoing projects
to support project review and forecasting among project stakeholders. The
essence of EVM is to accurately and early as possible, draw attention to trends
that could have negative impacts the project success. In other words, it is can
be described as a risk assessment tool. Through measuring the occurrence and
risks of cost overruns and schedule delays, output figures from EVM present
project teams with information in order to maintain or improve project efficiency.
Management is able to forecast cost and time trends based on the actual
performance of the project and obtain crucial information about future costs and
time shifts due to delays (Ammari, 2017).
Another key concept the use of EVM is accurate record keeping. EVM establishes
a single management control system providing reliable data (kshirsagar &
Konnur, 2017). EVM requires the analysis of historical data and current project
data collected at time intervals or milestone achievements to present reliable
information for project control measures. By doing so, it strongly encourages the
project team to actively collect and archive project information in a central
project or program database. By encouraging record keeping and organized
information database systems for every project and program, archived and
historical data from previous projects can be extracted by a project team as
inputs to plan with better accuracy, schedules, costs and procurements on
similar projects. Through collecting data, its use can go beyond monitoring and
12
controlling current projects to be vital information repository for the planning
phase of future projects in an organization (Villafiorita, 2014).
An ancillary concept associated with EVM is the Kaizen theory. Kaizen means an
improvement in Japanese. Kaizen requires constant assessment and
readjustments to allow improvements and better efficiency. (Badgujar, Konnur,
& Landage, 2016) informed that utilization of earned value technique for project
control results in better assessment of schedule and budget requirements.
“Productivity can be improved by taking regular feedbacks of cost and schedule
performance”. The frequent feedback required with the aim of enhancing
efficiency in budget and schedule performance through the EVM process is
central for encouraging a Kaizen culture among the project team.
(Haupt, 2017), mentioned that for EVM to achieve suitable outcomes, project
managers and contractors should have a good working relationship and often
communicate each other’s project analysis. This can be inferred as a
collaborative two-way communication approach. It is therefore ideal for both
parties to agree on how information is reported in status, progress, trend, Earned
value and forecast reports. EVM, thus, pushes for effective information exchange
using a clearly understandable Project assessment and reporting system.
A connection can be made between EVM and project team motivation on projects.
EVM provides information about performance which can be used as the basis
for the organisational application of well-known motivation theories. Basic
performance measurements of work efficiency, cost efficiency and variances can
provide an empirical source to support two of the six major factors proposed by
Herzberg’s two-factor theory that motivate employees (Herzberg, 1968). The
project members are, therefore, able to motivate themselves with a sense of
achievement and expect positive recognition for this achievement if EVM
measurement results indicate a positive performance. Similarly, in a reward-
based project environment, adopting the philosophy of Taylorism theory for
financial rewards to motivate project team members, EVM performance results
will provide justification for reward decisions.
13
It appears through a review that the application of EVM either adopts or supports
a number of broader project management concepts. Adopting Integrated project
management concept, risk management, constant assessment and
improvement, records keeping, KPIs, team motivation, and so on all fall within
the traditional practice of project management. Through monitoring and
enforcing the project schedule, cost and scope baselines, EVM is able to directly
influence the project team to perform a comprehensive spectrum of parallel
project management functions.
2.4 EVM INDEXES, PERFORMANCE ANALYSIS AND FORECAST
2.4.1 Primary EVM Indexes
Several EVM metrics and terminologies exist, that could be cumbersome and off-
putting (Christensen, 1999), Earned value management metric measurements,
however, are all done in monetary terms (Prasad, Rajkumar, & Rastogi, 2006).
There are, however, three basic metrics that all other EVM measurements are
derived from (Christensen, 1999). They are; the budgeted cost of work performed
(BWCP), budgeted cost of work scheduled (BCWS) and Actual cost of work
performed (ACWP). These terms exist under different names in modern project
management books and articles. BCWS and ACWP are now commonly referred
to as Planned Value (PV) and Actual Cost (AC), respectively. Budgeted cost of
work performed is now referred to as Earned Value (EV).
I. EV is the quantification of the worth of work done to date; in simpler terms,
the value of work done to date (Reichel, 2006). A theoretical description by
(Anbari, 2003), states “When the predefined, tangible criteria for the
milestone are met, the balance of the value associated with the milestone
is earned”. Mathematically, it is derived by multiplying the percentage of
work completed date by the budget allocated to the completion of the work.
It can be expressed at different levels of a WBS and can be represented as
a cumulative or static figures.
14
II. PV is the budgeted cost of work scheduled to have been completed to date.
(Kim & Ballard, 2002) defined it as the sum of all the planned costs in the
project, or any given part of the project, up to the reporting date. It
requires a well-defined and decomposed scope of work (WBS) as well as
allocated schedules and budgets for work packages (Reichel, 2006).
III. AC refers to expenditures that have been incurred in the execution of
project work packages to date. “It is the sum of what has actually been
spent irrespective of what has been planned” (Fleming & Koppelman,
Using earned value management, 2002).
Other measurements in EVM are a derivative of arithmetic relationships among
these metrics mentioned above. These derivative metrics are classified as either
Performance or forecast metrics.
2.4.2 Performance Metrics
I. Schedule Variance (SV)
“SV measures a volume of work done versus the volume of work planned”
(Vanhoucke & Vandervoode, 2006). SV is the variance between Earned
value and the present value done to date. It is a measure of how much
deviation the budgeted cost of work performed is against the budgeted cost
of work scheduled, i.e. a measurement of actual work accomplished in
relation to planned accomplishments. Owing to the fact, its determining
metrics are expressed in monetary value; schedule variance is also
expressed in monetary values. Its Formula is expressed in both equations
below;
SV = EV-PV
SV = BCWP – BCWS
15
Figure 5: Project Ahead of Schedule using Schedule Variance (Hinze, 2007)
A derived positive value indicates that the project is ahead of schedule, a
Zero result indicates that the project on schedule and should the value be
negative, it is an indicator that the project is behind schedule. (Biafore,
2007) suggests a risk scale for schedule variances after a project is
determined to be behind schedule:
• Less than 5% shows a low risk but may be an early warning of
potential problems.
• Between 5% and 10% shows a moderate risk and should demand
control actions from the project team.
• Greater than 10% shows high risk and demands that demands swift
and major control actions from the project team.
Percentage schedule variation is derived by
(SV/BCWS) ×100
II. Cost variance (CV)
CV measures the deviations in the budget or cost planned (Yismalet &
Patel, 2018). It is the variance between earned value and actual costs. It
measures the deviation of the budgeted cost of work performed and the
actual cost of work performed, i.e., a measurement of the actual project
16
expenditure in relation to planned costs to date. It is expressed in
monetary values. Its formula is expressed in both equations below;
CV = EV – AC
CV = BCWP – ACWP
Figure 6: Project over Budget using Cost Variance (Hinze, 2007)
A derived positive value as similar to Schedule various indicates project
spending is healthy and under budget. A Zero result shows that spending
is precise as planned while a negative value indicates the project is over
budget. Risk limits differ on different projects. Projects having narrow
profit margins have lower thresholds for minor variances than those with
higher margins. Some projects having a cost variance of three per cent
would signal significant risks that demand immediate control actions
while other projects may manage this deviation as low risk. These different
perceptions may depend on factors such as geographical economy of a
project and access to finance.
III. Schedule performance index (SPI)
“Schedule performance index measures schedule efficiency and is
expressed as a ratio of earned value to planned value” (Project
management Institute, 2013). This ratio measures the efficiency of task
17
completion rates in relation to the overall schedule of a project. Its formula
is expressed in both equations below;
SPI = EV/PV
SPI = BCWP/BCWS
An SPI value more than 1 indicates that more work has been completed
than planned, a zero value indicates work completion progressing as
planned and a negative SPI indicates that more work was planned to have
been completed than work actually completed. Control measures adopted
for undesirable SPI are similar to those earlier expresses for schedule
variance.
IV. Cost performance index (CPI)
“Cost performance index measures cost efficiency of budgeted resources,
and it is expressed as a ratio of earned value to actual costs” (Project
management Institute, 2013). This ratio measures the efficiency of costs
already consumed by a project in relation to the overall budget of the same
project. Its formula is expressed in both equations below
CPI = EV/AC
SPI = BCWP/ACWP
A CPI value greater than 1 indicates cost underruns to date. A zero value
indicates a project consumes cost exactly as planned while a negative CPI
indicates more cost overruns in a project. Its control measures are similar
to the control measures for cost variance.
V. Critical ratio (CR)
CR combines both the cost performance index (CPI) and schedule
performance index (SPI) to represent the project status. This indicator seeks
to draw parallels from both the CPI and the SPI in order to provide an overall
indication of a project’s health. The formula is given below;
CR = CPI * SPI
Its interpretation is the same as its indices. A value greater than 1 indicates
good project performance and values lower than 1 indicates poor project
performance
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2.4.3 Forecast metrics
These are the metrics a project team monitors and analyses in order to influence
the future behaviour of projects in order to reach its schedule and cost baselines
as efficiently as possible. They are;
I. Budget at completion (BAC)
This is the total budget for every work package scheduled within a project.
It is a monetary expression of the total planned value expected after the
completion of a project. It is derived by the summation all of periodic or
milestone planned values.
II. Estimate at completion(EAC)
This is the expected cost of completion of a project based on cost
performance to date. It is derived by multiple formulas which depend on
the reason the EAC is being generated. When an event occurs, or a future
event that will significantly affect the BAC is anticipated or planned, the
BAC must be reviewed to reflect the changes to the BAC. It is derived by
adding the Actual cost of work performed till date to the sum of the
planned values of work packages left to complete the project. It is derived
from the formula below;
EAC = ACWP + ETC
ETC (estimate to completion) is the additional sum required to complete
the project, i.e., the sum of planned values of work packages left to
complete the project.
An alternative approach to deriving the EAC of a project is to assume that
current spending efficiency to date will continue until the end of the
project. This approach fixes the current CPI to date as the expected
performance for the BAC. It is expressed in the formula below
EAC = BAC / CPI
Where the CPI is 1 or greater, the EAC would be equal to or less than the
BAC respectively. CPIs lower than 1 will equate a higher EAC than the
BAC.
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A third approach is to assume that the CPI will not reflect future cost-
efficiency. Future costs are expected to perform as planned. The actual
cost of work performed and the budgeted cost of work performed is used
as an independent variable. This approach is expressed in the formula
below
EAC = AC+ (BAC – BCWP)
A fourth approach is deriving the cost estimate required to complete a
project within its planned schedule with current costs efficiency. By
including the critical ratio, the overall health of the project to date is taken
into account in relation to ACWP and BCWP.
EAC = ACWP + (BAC – BCWP) / (CPI * SPI)
III. To complete performance index (TCPI)
This is the cost efficiency required to complete outstanding project work
packages with the remaining budget. This assumes no additional budget
is available to the project. It is derived through the equation below
TCPI= (BAC – BCWP) /(EAC-ACWP)
The value derived from this equation indicates the CPI that must be
achieved to remain within the BAC. It is useful in determining the
feasibility of achieving the BAC by factoring the amount of work left to
completed and remaining budget available.
IV. Variance at Completion (VAC).
This is a forecast to determine if a project would be over budget or under
budget at completion. It is the variance between BAC and EAC. It
measures the deviation of the expected project cost at completion from the
budgeted cost of all work scheduled in the project. It is derived from the
equation below;
VAC = BAC – EAC
Positive values indicate that the project will be completed under budget
while a negative value indicates the project would be finished over budget.
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Table 1: Summary of metrics, measurements and interpretation. Revised from (Prasad ,
Rajkumar, & Rastogi, 2006) 1
1 More EAC formulas added by the author
Basic measurement metrics
Performance metrics
Forecast metrics
Expenditures that have been incurred
in the execution of project work
packages till date
Budgeted cost of work
performed(BCWP)
Earned Vaue(EV)
Planned Value(PV)
Budgeted cost of work
scheduled(BCWS)
Actual costs (AC)
Terminology Formula Interpretation
The costs initially budgeted for all work
completed up to the reporting date
% project complete x
budget
Description
Quantification of the worth of work
done till date
It measures the deviation of the
budgeted cost of work performed
against the budgeted cost of work
scheduled
Schedule variance (SV)
Cost variance (CV)
SV = EV-PV
It measures the deviation of the
budgeted cost of work performed
against the actual cost of work
CV = EV – AC
CV = BCWP – ACWP
CPI = EV/AC
SPI = BCWP/ACWP
This ratio measures the efficiency of
costs already consumed by a project in
relation to the overall budget of the
same project
Greater than 1= Project is under
budget, equal to 1= project is on
budget, less than 1= Project is over
budget
This is the total budget for every work
package scheduled within a project
Estimate at completion
(BAC)
Σ PV
Σ BCWS
Greater than 1= Project is performing
better than planned, equal to 1= project
is performing as planned, less than 1=
Project is underperforming
CR=SPI x CPIMeasures the overall health of a project
according to its planCritical ratio (CR)
EAC = ACWP + ETC
EAC = BAC / CPI
EAC = AC+ (BAC – BCWP)
Actual cost of work
performed(ACWP)
EAC = ACWP + (BAC –
BCWP) / (CPI * SPI)
Cost performance index
(CPI)
SPI = EV/PV
SPI = BCWP/BCWS
Greater than 1= Project is ahead of
schedule, Equal to 1= project is on
schedule, less than 1= Project is behind
schedule
A ratio that measures the efficiency of
task completion rates in relation to the
overall schedule of a project
Schedule performance
index (SPI)
Positive= Project is ahead of schedule,
Neutral= project is on schedule,
Negative= Project is behind schedule
Positive= Project is under budget,
Neutral= project is on budget, Negative=
Project is over budget
SV = BCWP – BCWS
VAC must be greater than or equal to
zero for the project to be healthy
TCPI less than 1 = more funds and less
work; It is easier to complete the project
ETC=EAC-ACWP
expected difference between the a
project's budget and total actual costs at
completion
Variation at completion
(VAC)
VAC= BAC-EAC
Estimate to completion
(ETC)
Additional budget required to complete a
project
EAC must be equal to or less than the
BAC for the project to be healthy
TCPI equal to 1 = Just enough funds to
complete the project
TCPI greater than 1= funds are less
than work left. It is difficult to complete
the project
TCPI= (BAC – BCWP)
/(EAC-ACWP)
Cost efficiency required to complete a
project with no additions to the BAC or
EAC
To completion
performance index (TCPI)
This is the expected cost of completion of
a project based on cost performance till
dateEstimate at completion
(EAC)
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Table 2: EVM measurement scenarios and corrective actions. (Prasad , Rajkumar, & Rastogi, 2006)
Redeploy resources to other future
Ahead of Schedule /On Schedule
Corrective Actions
Ensure that Quality is further improvedProductivity higher than estimated
Possible Causes
More resources deployed than necessary
Original planned schedule was very
conservative
Review planned schedule and sustain
performance
Behind Schedule
Use Productivity tools, Retrain resources; get Excessive Rework
Lack of Scope Clarity
Unclear Roles and responsibilities
Skilled resources not available in time
Scope creep is absorbed
Discuss with end users
Clearly define and communicate Responsibility
Try for better skilled resources; invest in
Define scope change process; raise Change
Scope Creep absorbed
Redeploy resources from less to more critical
tasks
Productivity lower than estimated; Wrong
estimates
Closer interactions with team to resolve their
issues; change the team if necessary
Involve senior management team from client's
side to resolve issues
Define scope change process; raise Change
Resources lack requisite skills
Over Budget
Train them; or possibly replace them
Introduce automation/ reusable components;
invest in training
Low productivity of resources
Improve planning and review; Identify team
issues and resolve them
Low utilization (high idle time) of
resources
Under Budget / On Budget
Ensure Quality is not suffered
Ensure cost efficiency does not lead to delay
Delay is caused by client's processes or
indecision
Low utilisation of budgeted resources
Celebrate- for contributing to higher profit
margin to company
Re-estimate remaining Tasks; off-load
resources to other projects
Process automation/ Tools deployed
Original Estimates were on higher side
Lower cost resources deployed
More team productivity than estimated
Use Productivity tools, retrain; get clear
specifications; motivate team
Excessive re-work
Try monitoring the Off-shore- On-shore ratio;
or have right mix of resources
Costlier resources deployed
Improve planning process, re-deploy idle
resources if possible; train for future needs
Unplanned resources deployed
Involve senior management team from client's
side to resolve issues
Delay caused by client's processes
Re-estimate the remaining work and ask for
change request
Incorrect original project Effort estimates
Reduce avoidable Direct, Indirect, Fixed, and
Variable costs
Costly delivery process
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2.5 EVM, PROJECT DELIVERY AND CONSTRUCTION PERFORMANCE
(Humphreys & Associates, 2012) stated that EVM is a concept that improves
project visibility and accountability. The decision to use EVM forces upfront
planning and a disciplined approach to management standards. It is primarily
hinged on the premise of comparing work completed against efforts and
resources spent- it seeks visibility and accountability of value of money spent till
date in and assesses the most efficient approach to future spending. Many works
of literature confirm this benefit that EVM presents. With an increased focus on
planning, periodic project progress measurement, it is assumable that
construction performances are improved with the use of EVM. Construction
performance here refers to the delivery of construction projects on schedule, on
budget and the planned scope of work.
As already previously established, the premise of improved construction
performance stems from higher visibility of project activities progress in order to
make control decisions. In a few case studies of real-life projects, problems have
been found in the ability of EVM to accurately visualize project progress. In a
case study of a 26 floor, 20547.72 SQM business tower, (Candidi, Heineck, &
Neto, 2014) demonstrated that the use of EVM was unsuitable for their
construction site. One major reason presented in their report is that forecasting
variability was high. Predication variability was high for both project cost and
duration. They went on to posit that with too much doubtful information, undue
pressure may be put on project managers as they would try to reschedule work
in response to the discomforting forecasts. Also highlighted were disparages
between cost-based monitoring and man-hours based measurements of physical
work. The author believes that these disparages were as a result of EVM taking
into account direct and indirect project costs while man-hours measurement
considering only direct costs of activities. To conclude their report, they suggest
that EVM is best suited for financial progress evaluation as regards project
performance. To obtain better schedule visibility for accountability, they propose
exploring methods to combine the theories of EVM and lean construction.
23
(Tzaveas, Katsavounis, & Kalfakakou, 2010) Case studied the infrastructure
project ‘Egnatia Odos’, an EU priority highway project of 682km stretching
across Greece. They demonstrated conclusions similar to the ones highlighted
in the previous paragraph. However different to the earlier mentioned case study,
earned schedule (ES) technique was tested alongside EVM. ES was determined
to give better schedule visibility and accurately forecast project schedule
performance. EVM was determined to be reliable for measuring schedule
performance only up until roughly 50% project completion. They also make the
conclusion that EVM’s assessment of schedule performance in their case study
was reliable in detecting underperformances early on in the project.
In an ERP project for a large university in Asia, (Prasad, Rajkumar, & Rastogi,
2006) used EVM to steer a project back to within its schedule baseline. EVM was
effectively used to control scope creep and changes that were negatively affecting
the project schedule. Through offering visibility of the schedule slippage arising
from poor scope management, stakeholders were more disciplined with scope
changes and the project was delivered on time. Despite delivering the project
slightly over budget, they conclude that the intervention of EVM had a generally
positive impact but recommended better stakeholder management and project
communication infrastructure for better use of EVM in the future.
(Valle & Soares, 2004) in a paper reviewing their use of EVM on the Monica
Theme Park project in Rio de Janeiro, referred to project management without
the use of EVM as blind management. Using EVM to deliver the project on time
and within budget, they made the following conclusions:
I. EVM very Sensitive for scope changes and need to be managed
carefully.
II. EVM reports allowed for easy and fast identification of planning and
reporting mistakes.
III. Reporting systems provided consistency in the analysis that provided
support for decision-makers.
IV. EVM assisted during scope change management. It helped keep an eye
on the final budget of the project when analysing providing alternatives
24
to decide on what activities to reduce specifications to save money in to
accommodate cost overruns in other activities.
They gave a comprehensive list, enumerated below, as necessary to
successfully implement EVM in projects
I. Obtain top-level organization commitment with EVM
II. EVM education and training for all project team members
III. Well defined scope, detailed and identified, with proper WBS and
packages
IV. Scheduling and budgeting according to the WBS
V. Clear Project Responsibility Tables with corresponding descriptions of
such responsibilities
VI. Clear flowchart of activities showing their relationship with project
stakeholders
VII. A Cost and Schedule Control System having a database and data
collection procedures
VIII. Suitable reports related to EVM, well planned, analyzed and distributed
IX. Procedures to consistently analyse and validate information being used
X. Lessons Learned - continuous improvement process.
XI. Changing the name of SPI to progress performance index
With a majority perception from the above cases that EVM helps partially or
sufficiently improve project visibility and performances, there is a common
theme of the need to pay attention to its schedule measuring and forecast
function. Also, to be considered are combining its use with other project
management tools, having a supporting organization/project structure, proper
scope decomposition and management, sound reporting systems amongst
others. With the plethora supporting requirements needed, it is reasonable to
assume that that the contribution of EVM to project performance can only be
exploited if it is adequately implemented. This is aligned with a study by
(Thamhain , 1998), who after analyzing the perceived value of 29 project
25
management tools and techniques; including EVM, concluded that project
performance is conditional and dependent on how project managers integrate
them into their work processes and need organizational acceptance. With
acknowledged positive contribution to project cost visibility but apathy due to
potential faults in schedule monitoring, it is comprehensible why EVM was
classified as a project management tool with a higher than average level of
potential to improve the performance of projects but with a lower average level
of use. This was in a survey by (Besner & Hobbs, 2006) comparing the perceived
value of different project management tools among project managers. Some
shortcomings of EVM will be discussed later in this chapter.
2.6 PROCUREMENT AND EVM
Cost and Schedule planning: Procurement “is a systematic process of acquiring
goods, services and other facilities to ensure high standards of management for
controlling the project” (Simm & Masters, 2003). It is now evident that EVM is
concerned with the accurate planning and control of cost and schedule
performances on a project. The controlling of the cost and schedules can be
achieved through project procurement, and it is supportive to EVM for
measuring the performance of the project (Lee, 2004). “The delivery dates for
equipment and materials and the work completion dates for contracted works
are placed on the project schedule” (Watt, n.d.). She goes to state that the
eligibility of suppliers is determined by the capacity to perform the work to meet
project requirements. One of such capacities is being able to meet schedule
requirements of the project schedule, and another is cost requirements. In order
to support large, complex projects, late delivery of materials and services
required for critical path activities must be avoided as much as possible using
the procurement contracts.
Procurement contracts can also be a tool for early detection of future schedule
or cost problems on a project. (Watt, n.d.) suggests that the project team, through
procurement documents, can determine the feasibility of particular services or
26
materials being available when they are needed; and thereof taking control
decisions from the planning phase. In an illustration, a project team may decide
to choose to transport critical activity materials by sea cargo rather than air
freight should it be realised that cost saving could be realized without delaying
the arrival of these materials and impacting the schedule negatively. This
illustration could be vice-versa.
It is paramount that procurement contracts support the cost and schedule
guides of the EVM curve and the EVM curve is a reflection of the contracts
attributed to each activity in the project. The implication is that should
procurement not be efficient in the acquisition of goods and services, efficient
prosecution of project activities become challenging, leading to exposure to
project cost overruns and schedule delays and inevitably, EVM will report
inefficiencies during project execution.
Costs and Schedule monitoring & reporting: To ensure a project plan is developed
with the necessary data to facilitate reporting Earned Value analysis during the
execution phase, it is essential that in addition to the project plan, contracts
explicitly state the required baselines and system of reporting before being
approved. Schedules should have a work breakdown structure for activities.
Activities within the work breakdown structure should show allocated resources
and times when they will be started completed. Having a resource loaded
schedule prepared, facilitates the generation of the project’s S-curve. The S-curve
can thus serve as a reference baseline to measure contract performance in terms
of cost, rate of project consumption and time (EVM). Having a resource loaded
schedule included in contracts also serves the purpose of showing the
interdependence of activities and resources in a construction project (Sears,
2008). Showing interdependencies assists the Project management team to
determine the feasibility of the overall project schedule and cost baselines on the
S-curve. On projects, determining real progress for work packages can be
difficult, but is crucial for ensuring earned value analysis is accurate and
meaningful (Lukas, 2012).
27
In reporting systems, contracts need to express the method of measuring
progress and performance. While multiple approaches to performance
measurements exist, a suitable reporting method should be decided on, taking
into consideration, the complexity of activities and dependencies within the
project, type of data to be collected and among other project-specific factors.
Accurate reporting systems, according to (Lukas, 2002, Cited in Lukas 2012)
include:
I. Units completed: Used for simple, measurable work where each
activity consume equal effort.
II. Incremental milestones: Progress is reported only through sequential
completion of set milestones.
III. Start to finish: Suitable for capturing the only the start and
endpoints of activities and nothing in between. Progress is measured
either with 0/100 rule, 50/50 rule or 20/80 rule for slightly longer
duration tasks.
Other contract reporting mechanisms exist in the event that no empirical
information is available.
IV. Expert opinion: Relies heavily on the subjective opinion of the
reporting person and hence a potential source of disagreement.
V. Level of effort: Assumes that EV=PV as completion of such activity
is solely dependent on the level of effort imputed.
In practice, however, project managers are likely required to use one or both of
the following methods
VI. Combination techniques: Adopted for complex work, interrelated
activities with different progress measuring systems occurring over
extended periods.
VII. Weighted Units: Adopted for works that occur over extended periods
with multiple subtasks having different measuring units. Monetary
values or level of effort of each subtask is weighted and then
28
converted to a single measuring unit reflecting percentage
completion of its summary activity.
It is crucial that the most suitable reporting system be adopted for each project
activity. For instance, floor tiling can be measured and reported using units
completed as it easily measurable in terms of a wall or floor area completed.
Concrete placement can only be measured with a start to finish system. It is
logical to measure overall projects efficiency using weighted units. Inaccurate
progress reporting can prevent detection of early warning signs and thus must
be avoided (Sadhu, 2015).
2.7 EVM AND PROJECT MANAGEMENT INFORMATION SYSTEMS
Software and Project management information systems (PMIS) were
introduced to assist project managers to perform their tasks better. They are
aimed at increasing the efficiency of project managers. They are used across
all phases; in the case of EVM, from the planning phase up until closing.
(Gartner Research Group, 2008) mentioned that the use of PMIS does not
guarantee project success, but they are still instrumental in the construction
industry and become mandatory in most construction projects.
According to (Kraemer, 2018), Software and their database systems can assist
project managers to gather, organize, store, analyze and generate reports on
data obtained from projects. With these, project managers can keep track of
the schedules and cost of project activities and likewise follow up on control
decisions. Leveraging on this, EVM has become more effective with better
monitoring and oversight possibilities. When high-quality software and
information management systems are used correctly (Raymond & Bergeron,
2008) posit that the chances of project success can be increased as much as
75%.
Project management software was first introduced in 1977 when the software
companies of Oracle and Artemis were founded and two years later in 1979,
the introduction of Scitor. The software offered during this period were mostly
29
used for major Government projects, and it was not until the 80s and 90s; a
period that experienced the introduction of personal computers and
networked facilities did project management software become easily accessible
and widely available (Azzopardi, n.d.). In 2010, software having cloud-based
functionalities were introduced, allowing projects to be implemented through
virtual teams working remotely (Yves, 2017). He goes on to mention that the
current era of ‘the internet of things’ is driving the demand and supply of
tailor-made software solutions for organizations and projects.
Numerous software are available on the market today that can support the
use of EVM on projects. These software are diverse and heavily fragmented.
Some focus on schedule; others focus on business intelligence, while others
focus on cost. According to Pinnacle management, to have comprehensive
software support for EVM, an Earned Value Management System (EVMS) has
to be set up. An EVMS integrates schedule, cost and business intelligence
software engines into a unified system using individual working parts that
collectively complement each other to support and enhance the use of EVM.
Some popular software engines integrated into EVMS listed by Pinnacle
management include Microsoft Project, Primavera P6, Deltek open plan,
Safran and Artemis for scheduling; Deltek Cobra, EVMSforProject and
Hexagon for costs; and finally Encore Empower, Deltek Winsightand Deltek
PM compass for business intelligence. The vast array of software options and
the need to integrate them together in order to support EVM effectively is an
indication of the dependence project managers and controllers have on
information technology infrastructures for their specialized duties. This is
mostly driven by the need to improve work productivity on complex projects,
filter for relevant information needed run projects easily, communicate with a
large number of stakeholders, managing remote teams, improve project skills
maturity amongst other reasons.
30
Figure 7: EVMS system2. Revised from (Brunton, 2016)
2.8 CRITICISMS/LIMITATIONS OF EVM
Numerous literature review suggests that project managers struggle with
adopting the EVM method. As mentioned earlier in this chapter, (Fleming &
Koppelman, 2006) stated that in its earliest form, EVM confused project
managers with complicated terminologies and never understood the real benefit
it offered in the field of project management. Despite several re-iterations,
simplified definitions, inclusion in most Project management Institutional
training programs, (Thamhain , 1998) mentions the following problems project
teams face with adopting EVM. They are;
I. EVM is perceived as a threat owing to its demand for transparency,
II. Integration of EVM into business processes is low
III. implementation is expensive, time and effort-intensive.
In using the EVM tool, a report by (Lukas, 2012), he listed the following as
common mistakes that influence the ineffectiveness of EVM. They are;
2 Business intelligence added by the author.
31
I. No documented requirements;
II. incomplete requirements;
III. WBS not used
IV. Incomplete WBS
V. Plan not integrated (WBS-Schedule-Budget)
VI. Incorrect Schedule and/or budget
VII. Change management not used or ineffective
VIII. Cost collection system inadequate
IX. Negative management influence and/or control.
In his report, he explains the dangers of not having a planned value derived from
a well-defined scope and WBS; which serves as the PMB, would lead to a healthy
project that does not deliver on project quality requirements. This is supported
by (Kopelman & Fleming, 1999) where it is suggested that the absence of a work
breakdown structure may lead to inaccurate data in relation to costs and
timeframe of the project as a whole. (Lukas, 2008) also indicates the danger of
relying solely on project invoices to calculate AC. Projects often have invoices
that lag behind their corresponding work, which can cause misleading
calculations. In another explanation, he expresses concern regarding
uncontrolled scope creep and effective change control processes. Scope creep
easily influences the schedule and cost baselines of a project without being
captured in the scope of work planned. To avoid reporting false overruns for
activities on which contingencies are spent, but covered with a risk budget, he
counsels change management to update the baselines of the project to reflect the
changes since contingencies are still within the project cost baseline.
(Howes, 2000) suggested concerns regarding absolute dependence on EAC
values. He explains that project works in the future may be entirely unrelated
for project work completed up until the time of forecast assessment. He
determines that future performance is not automatically an indication of past
cost performance. While the author agrees to the logic regarding this theory, he
does not concede the fact that EAC forecasts are misleading. Multiple formulas
exist for estimating this metric and only those that make use of the CPI as an
32
input factor in calculating the EAC are prone to be misleading. (Howes, 2000)
also posits SV does not take into consideration, sufficient relevant information
in its calculation. He explains that SV does not incorporate time or logical
sequence of activities in the future when forecasting. He describes SV as a
scheduling metric based entirely on cost performance. This is especially
problematic when through the calculation of the SV and SPI, an accumulation
of ahead of schedule non-critical activities eclipse critical activities running
behind schedule. EVM does not distinguish or prioritize schedule performance
of critical or near-critical activities which bear higher risks of influencing project
failure. To conclude, he proposed an alternative tool he calls the Work Package
Method (WPM) where he separates a project into a series of discrete work
packages. He splits work packages that are unconnected through time or
sequence. (Valle & Soares, 2004) recognising deficiencies in schedule measuring,
proposed that the name should be changed to progress performance index and
not left as SPI. They suggest that changing the name serves to portray better the
scope of data the metric calculates.
(Ghorbani, 2017) draws attention to the unreliability of schedule performance
measurements beyond two-thirds of the project. She further explains that
schedule slippages are difficult to detect as project activities begin to wind down.
This is because SPI is based on the premise that at the end of projects, SPI is
equal to 1 irrespective of the time they are completed. For this, it is possible to
have a healthy SPI of 1, even beyond the planned completion date of a project as
long as all scheduled activities are registered as completed. Citing references
from the United States Department of Defence guidelines, she suggests that EVM
should not be used as the only measuring tool to assess project schedule status.
While numerous works of literature suggest that EVM implementation is
expensive and data gathering is time-consuming, (Custer, 2009), dismisses these
this criticisms citing that information gathering and reporting already
continuously carried out for legacy reasons and that the data need for EV
calculations already exists in cheaply available software. He posits that the
demand for automation of the entire EVM (EVMS) is the reason for high
33
implementation costs. Citing that data in estimating scheduling and financial
software are adequately organised to suit their individual functions, he suggests
that key or relevant information can be extracted and compiled in EVM formats
and then stored in into an EVM repository that can be set up on inexpensive
database systems; making reference to Microsoft Excel spreadsheets as one of
such databases. The author expresses caution towards this approach. This is
because this process has attempted to reduce the cost of implementation, but
brings additional work of extracting and organising data from and between
software and database systems. Data extraction can only be done by a person
with adequate training and experience in order to be able to identify and correlate
multi-dimensional data from different software stored in different metadata
formats. This may ultimately result in project team training costs or slower
reporting. This could be in contradiction to (Gershon, 2013), that emphasizes
the importance of good and punctual information for EVM to work correctly.
34
3 METHODOLOGY
3.1 INTRODUCTION
(Potter, 1996) defines methodology as methods and processes used to gather,
analyze, and present information to reach a set-out objective; it describes how
specific tools can be adopted to achieve the aforementioned. The literature review
from chapter two has presented the theoretical background that is used to
answer the research questions one and two, while this methodology presents the
approach to answer question one and validate the author’s proposals in this
thesis.
This chapter describes and discusses; the research design, sample size and
selection, the data collection methods used and their corresponding data
collection instruments, data management and analysis procedure as well as
steps that will be taken to ensure validity and reliability during the study and
measurement of variables.
3.2 RESEARCH PHILOSOPHY AND DESIGN
Research philosophy reflects the development of knowledge and the nature of
knowledge; it explains the thought process of the author and how it affects the
way research has been carried out (Saunders, Lewis, & Thornhill, 2009).
According to (Sekaran, 2003) a research design shows the details of the study in
relation to the purpose of such study, types of investigation, and the extent of
author interference, measurement and measures, unit of analysis, sampling
design, data collection method and data analysis, are integral to research design.
This research is approached mainly in two ways; inductive and deductive. The
inductive approach aligns with qualitative techniques while deductive approach
aligns with quantitative methods.
To analyse the best way to enhance the adoption of EVM, Interpretivism method
is adopted. This is owing to its philosophy that individuals are different, complex
and interpret the same objectivity in varying ways. It is established on
35
observation, opinions and concepts. Interpretivism acknowledges that research
takes place in a complex and dynamic and unique environment (Saunders,
Lewis, & Thornhill, 2009). (Collyer & Warren, 2013) established projects occur
in dynamic environments, hence the suitability of Interpretivism.
Instruments
I. Interviews: For this, semi-structured interviews are to be conducted. This
is to allow respondents to give untethered opinions regarding the subject
matter, which may also be influenced by lived experiences, feelings and
attitudes. While responses may be perceived as generalised, (Saunders,
Lewis, & Thornhill, 2009) posit that the qualitative approach does provide
an interpretive understanding of a phenomenon within a particular
context - in this case, the interviewee. Supported by (Creswell, 2014),
understanding of an individual’s lived experience is vital understanding
the psychology of a research problem. In addition, Interviews offer the
author the opportunity to adapt questions, clarify the questions by using
the appropriate language, clear doubts and establish rapport and probe
for more information (Sekaran, 2003)
II. Surveys: Measuring the attitudes and constraints of implementing EVM,
quantitative analysis is adopted. For this, a questionnaire is the tool for
information gathering. Questionnaires are one of the most popular means
of collecting data, and questionnaires are often closely associated in
conjunction with research (Rowly, 2014). “They are a valuable method of
collecting a wide range of information from a large number of individuals,
often referred to as respondents” (Menta & Roopa, 2012). The advantage
of using a questionnaire is that it offers the author statistically relevant
data to make logical inferences from.
36
3.3 SAMPLE POPULATION
A population of 100 respondents is expected for this survey. Respondents will
have formal education in project management or a similar field. Some
respondents would also hold project management certifications by either PMI,
Prince2, IPMA or have at least three years’ experience. This satisfies the condition
that respondents have either received formal project management training or
have sufficient professional experience or have both in order to be familiar
enough with the subject matter.
The questionnaire has three parts. The first part seeks to profile the respondents’
level of education, experience and role within their organisation. It is intended to
ensure that only responses from respondents who meet the above-mentioned
criteria are recorded. Part B measures respondents’ level of knowledge and
experience in respect of the subject matter “Earned Value Management”. Part C,
leveraging on opinions in addition to experience and knowledge, measures
responses to factors the author believes can assist the organisational/project
implementation EVM. Part C is measured with a Likert scale.
3.4 SAMPLING PROCEDURE
Random sampling is used leveraging on the local PMI chapter and LinkedIn
communities of practice for project managers. Communities of practice are
online forums with members having specific work roles in common. The
motivation of communities of practice is to master their discipline, learn about
the speciality, and solve problems together (Garfield, 2016). They achieve this
through creating dialogue, ideas exchange, information and advice sharing as
well as providing answers to questions posed by other members. Communities
of practice offer the author, the advantage of agglomerating project managers
from more geographical locations into a virtual pool of knowledge area-specific
respondents; thus providing access to a broader collection of project managers
as well as doing so quickly and inexpensively. Questionnaires would also be
distributed among project managers within the Author’s network.
37
3.5 VALIDITY AND RELIABILITY OF THE RESEARCH INSTRUMENT
3.5.1 Validity
To certify validity, the questionnaire is developed and given to two judges to
review each question’s relevance to the study. This is to achieve a consensus
estimate, as suggested by (Stemler, 2004). A consensus estimate measures the
extent to which experts agree with the development of the questionnaire. To
measure this, a content validity index will be derived by dividing the number of
validated questions by the total number of questions. (Amin, 2005), posits that
a figure not less than 0.7 is sufficient for a validity test.
3.5.2 Reliability
To certify the reliability of the questionnaire, a pre-test was done on ten
respondents who did not participate in the final survey. Their responses were
analysed using Cronbach’s Alpha Reliability Coefficients function contained the
statistical package for social scientists (SPSS) computer program. A Cronbach’s
alpha reliability coefficient of above 0.7 will be acceptable (Sekaran, 2003).
N %
Cases Valid 10 100.0
Excludeda 0 .0
Total 10 100.0
Reliability Statistics
Cronbach's
Alpha
N of
Items
.729 5
3.6 DATA ANALYSIS TECHNIQUE
3.6.1 Analysis of quantitative data
Data analysis from the survey is carried out using SPSS. Frequency counts and
percentages are used to analyse the respondents’ demographic characteristics,
38
and the mean and standard deviation will be used to analyse the spread of the
average opinion of respondents.
3.6.2 Analysis of qualitative data
Owing to the fact that the author was unable to find a suitable EVM expert who
was willing to be interviewed within the limited time-frame allowed for the
preparation of this thesis, although planned, no interviews were conducted.
Consequently, no qualitative analysis is done.
3.7 MEASUREMENT OF VARIABLES
Data on the respondent’s views and opinions about EVM will be obtained using
scaled variables from a self-developed questionnaire. A five-point Likert scale of
a= strongly agree b= agree, c= neutral d= disagree and e= strongly disagree is
used to collect respondents’ experience and opinions regarding the proposed
factors.
39
4 DATA ANALYSIS
4.1 INTRODUCTION
In this chapter, the results of the research and analysis are presented in
tables. The main objective of the survey is to measure different soft factors
proposed as influential to a project or organisational implementation of EVM.
While very limited literature exists regarding soft factors that may influence
EVM, the author adapts the presentation of (Mullaly, 2018) where he lists
different possible orientation type roles that PMOs may choose to pursue in
order to adapt to different alternative futures. In addition, the author also
takes into consideration, literature reviews and discussions in different EVM
communities of practice on LinkedIn. These factors include;
I. Flexibility to scope changes
II. Manipulations and error reporting
III. control & standardization
IV. Punishment contractors
V. IT project support
4.2 QUESTIONNAIRE RETURN RATE
The survey had a target sample size of 100 formally trained or experienced or
both; project managers, team members, portfolio managers and project
consultants. Seventy-three replies were received and accepted, which is a 73%
response rate. While this falls slightly short of the 75% response rate
recommended by (Babbie & Mouton, 2001), the time restriction regarding
submission of this dissertation did not permit more waiting time to receive more
responses to reach this threshold.
4.3 QUESTIONNAIRE ANALYSIS
Part A of the questionnaire intended to find out the profile details of the
respondents. Features include their role in their organisation, size of their
40
organisation, level of education and project management related experience.
Results are listed below:
I. Respondents’ job roles
Frequency Percentage
Project Manager 33 44.4
Team member 24 33.3
Portfolio Manager 0 0
Consultant 16 22.2
Total 73 100
From the responses, most of the respondents are either project managers or team
members. These groups account for close to 80% of respondents. This can
suggest that survey respondents are either directly involved in executing and
reporting projects or those who take responsibility for delivering them. A small
population of respondents are consultants.
II. Staff size of respondents’ organisations
Frequency Percentage
0 – 10 people 17 22.2
10 – 49 people 24 33.3
50 – 249 people 8 11.1
Over 250 people 24 33.3
Total 73 100
Two-thirds of respondents work in organisations having less than 250 members
of staff. The European Commission classifies these firms as Small and Medium-
sized enterprises. SMEs are more likely to carry out their projects with a close,
personal and professional relationship. For example, having a closer relationship
with clients for requirements gathering and also may have contractors they are
41
comfortable working with. They may be better suited to capturing client’s
baselines and communicate better with their contractors.
III. Respondents’ level of education
Frequency Percentage
Bachelors 8 11.1
Masters or higher 48 66.7
PM certification 17 22.2
None 0 0
Total 73 100
All respondents reported having some level of project management education.
More than 80% of respondents reported having an education. This fulfils the
requirement for participating in the survey; hence, no one was excluded. More
than 80% reported specialised or advanced levels of education. It is therefore
assumable that most of the respondents have an appreciable knowledge of
project control, which may include some proficiency in EVM.
IV. Respondents’ Project management experience
Frequency Percentage
0 – 3 years 17 22.2
3 – 5 years 32 44.4
5 – 7 years 24 33.3
Over 7 years 0 0
Total 73 100
In addition to the level of education, the number of years of experience plays
adds to the level of knowledge of project managers. Close to 80% of respondents
42
have at least three years of project management practice suggesting moderate
knowledge to make informed or semi-informed opinions regarding the subject
matter area.
Part B of the questionnaire is intended to profile the knowledge and experience
of the survey respondents, specifically in EVM.
V. Respondents’ level of knowledge of EVM
Frequency Percentage
Elementary 32 44.4
Working Knowledge 41 55.6
Expert 0 0
No knowledge 0 0
Total 73 100
With all respondents’ reported having project management education and
varying years of experience, some knowledge of EVM is to be reasonably
expected. However, reported knowledge among respondents appears almost split
between working knowledge and elementary knowledge. Only 5% separates the
two knowledge classifications. No expert knowledge was reported. This validates
numerous literature stating that the knowledge and adoption of EVM among
project managers remain limited. This will significantly hamper a quicker rise to
the performing level of project teams in the process posited by (Tuckman, 1965).
VI. Respondents’ method of tracking projects
Frequency Percentage
EVM alone 0 0
Network-based
techniques
16 22.2
Combination of both 41 55.6
43
None 16 22.2
Total 73 100
A little above half of the respondents reported having used EVM, albeit only in
combination with other schedule tracking tools. This as well means that slightly
less than half of respondents have never used EVM in professional practice.
While its use with other schedule tracking tools is advised by (Ghorbani, 2017),
use among respondents on their projects is still low, even thirteen years after
(Besner & Hobbs, 2006) made this statement.
VII. Respondents’ experience with EVM
Frequency Percentage
Positive 41 55.6
Neutral 0 0
Counter productive 0 0
Never used 32 44.4
Total 73 100
All respondents that indicated past or current use of EVM unanimously confirm
that their experience with EVM is positive. It is also curious that despite this
acknowledged advantage that EVM presents both by respondents and numerous
literature, slightly less than half of the respondents reported never used it. The
author considers 44% non-use an unusually high percentage for a tool with
confirmed benefits in controlling projects.
Part C of the survey intends to indirectly measure the factors enumerated at
the beginning of this chapter
Using a five-point Likert scale was applied to survey responses; 1 representing
“strongly agree” to 5 representing strongly disagree. Using this ranking scale, a
mean value and standard deviation of each factor were derived as part of the
analysis. From the linguistic coding of the questionnaire, a mean closer to 1 and
44
2 suggests that the measured principle in current practice, negatively influences
the sample population’s use, knowledge or opinion of EVM. A mean closer to 4
and 5 suggests vice-versa. The table below shows the response of survey
respondents.
VIII. Standardisation of respondents’ project organisation
Frequency Percentage
Fully standardised 8 11.1
Partially standardised 41 55.6
Not standardised 24 33.3
Total 73 100
The data suggests close to 90% of respondents reported partial or no
standardisation of processes in their organisation. With this, according to
(Monteiro, Santos, & Varajao, 2016), respondents may face difficulties
implementing project management tools and methodologies aimed at improving
efficiency and effectiveness.
IX. Poor Stakeholder
participation
Valid 73
Missing 0
Mean 2.14
Median 2.00
Mode 2
Std. Deviation .346
Range 1
45
Frequency Percentage
Strongly agree 0 0
Agree 63 85.7
Neutral 10 14.3
Disagree 0 0
Strongly disagree 0 0
Total 73 100
As already posited by (Prasad, Rajkumar, & Rastogi, 2006), poor stakeholder
involvement causes poor scope management. Should there be constant moving
baselines regarding project scope; that always influences schedule and cost, the
use of EVM may become defeated and unnecessary. This is because EVM is more
worthwhile where there is a relatively constant long-term baseline to measure.
With a long-term baseline, control decisions can be taken with better confidence
and made for the long-term benefit and stability of a project. With 85% of
respondents suggesting poor stakeholder participation, it is reasonably certain
that not all requirements in the project baseline would be captured during the
initial and planning phases. While better stakeholder management has been put
forward by earlier literature, additionally, the author suggests that the
implementation of EVM should include measuring the flexibility of a project to
accommodate changes essential to deliver quality success. This, in combination
with changing stakeholder requirements; analysed later in this chapter, are
proposed as two factors to consider for considering scope flexibility.
46
X. Error reporting
and data
manipulation
N Valid 73
Missing 0
Mean 2.27
Median 2.00
Mode 2
Std. Deviation .692
Range 2
Frequency Percentage
Strongly agree 0 0
Agree 63 85.7
Neutral 0 0
Disagree 10 14.3
Strongly disagree 0 0
Total 73 100
If linked to the almost 90% reported partial and or no form of standardisation, a
connection with error reporting and data manipulation can be assumed. While
the mean of this factor is closer to two, a standard deviation bordering between
one and two standard deviations of the mean suggests that opinions are more
spread out regarding this factor, especially when the only other response is a
disagreement. Still, 85% of respondents agree that data presented for EVM
analysis may be unreliable. It is imperative that this problem; which would
further be discussed in chapter 5, be addressed to protect the integrity of results
derived from earned value management analysis.
47
XI. Changing client
expectations
N Valid 73
Missing 0
Mean 2.29
Median 2.00
Mode 2
Std. Deviation .456
Range 1
Frequency Percentage
Strongly agree 0 0
Agree 52 71.4
Neutral 21 28.6
Disagree 0 0
Strongly disagree 0 0
Total 73 100
Project management methodologies do not only encourage capturing
requirements before commencing execution of a project but also acknowledge
and encourage stakeholders to change the scope of a project if those changes are
necessary for end satisfaction and acceptance. As is common practice, it is
expected that as high as 70% of respondents would agree to this factor. Unlike
poor stakeholder management mentioned earlier, changes may not necessarily
be as a result of poor requirements gathering; changes may arise from
uncertainties in the planning process, thus are unable to be accurately
incorporated into project performance baseline. Traditional project management
allocates contingencies and management reserves for these risks and
uncertainties. (Lukas, 2008) Advice that projects’ EVM curve be plotted
excluding these reserves and only be updated when these set-aside funds are
48
spent. The problem here again is that these funds need to be measured to
monitor their trends and efficiency. Knowing their trends and efficiency can be
instrumental in determining if a project is flexible enough to accommodate any
future change request. Information gotten from this may help in prioritising
change requests. Flexibility is discussed in chapter 5.
XII. IT Project Support
N Valid 73
Missing 0
Mean 2.00
Median 2.00
Mode 2
Std. Deviation .764
Range 2
Frequency Percentage
Strongly agree 21 28.6
Agree 31 42.9
Neutral 21 28.6
Disagree 0 0
Strongly disagree 0 0
Total 73 100
This is the only measured factor that had some respondents report strongly
agree, albeit only 29% reporting this. EVMS was introduced in chapter 2.
However, EVMS can be fragmented and expensive to set-up. Being an
unavoidable expense to be incurred, it is paramount that the choice of engines
running within the EVMS is optimised as much as possible to suit individual,
49
organisational objectives. This is because the author believes organisations differ
in size, project management skill maturity, project team network, among other
factors.
XIII. Punishment tool
N Valid 73
Missing 0
Mean 2.56
Median 2.00
Mode 2
Std. Deviation .726
Range 2
Frequency Percentage
Strongly agree 0 0
Agree 42 57.1
Neutral 21 28.6
Disagree 10 14.3
Strongly disagree 0 0
Total 73 100
Dividing opinions and with an appreciable population neutral, is expanding the
use of EVM to include contractor appraisals. There still exists a dichotomy of
motivation to implement EVM between contractors and project managers. (Song
& Shalini, 2009) stated that contractors do not consider the contract type when
deciding to implement EVM while clients are more inclined to readily adopt EVM
in cost plus fee contracts. (Nkiwane, Meyer, & Steyn, 2016) Reported the cynic
attitude contractors to hold towards using EVM for controlling fixed-price
50
contracts on milestones-based payment contracts because they are usually not
familiar with the tool. The author believes that for impartiality and transparency
in the project environment, EVM needs to be equally understood and bought-in
to by all concerned stakeholders. There are also numerous influencing issues to
consider when demanding strict accountability from project contractors that
would be discussed later.
51
5 RECOMMENDATIONS AND CONCLUSION
5.1 FLEXIBILITY TO SCOPE CHANGES
Real-life projects and Modern project management methodologies accept and
encourage scope changes, especially if such changes are necessary for crucial
project success. Existing literature on EVM suggests the proper control
processes for scope changes and discourages scope creep. (Lukas, 2008) wrote:
“Change management must be addressed in the project plan, and includes the
procedure for handling scope and variance changes, the forms to record and
evaluate change requests, the review and approval process for changes, and the
process to ensure changes are incorporated into the current plan, so the earned
value calculations remain relevant.”
(Totin, 2012) Mentioned the following terminologies for project controllers to be
aware of when involved with Earned value. The author believes these terms are
necessary to be understood for EVM to remain relevant despite scope changes.
They are:
Original Contract Value
This the planned cost of construction. Depending on the type of delivery method,
it may be synonymous with the contractor’s bid price. The author believes this
is likewise synonymous with planned value and budget at completion value
Approved Changes to Date
This is the sum of all changes that result in money added to the contract. Since
these changes are crucial for project success, (Lukas, 2008) suggests the original
EVM baselines should be updated with the time and cost additions from these
changes. The sum of these costs (approved changes + original contract value),
becomes the “committed contract value”. Aligning with Lukas’s posit, the author
52
believes the committed contract value should become the revised EVM cost
baseline.
Contract Time
This is the initial amount of time planned to complete the project.
Days Added
This is the amount of time added to the contract necessary to execute work as a
result of changes. This should, in addition to contract time, should become the
new schedule baseline.
Existing literature, however, is silent regarding monitoring the ability of a project
to be flexible to scope changes. This is amongst other factors, mostly dependent
on cost. Projects have a limited management reserve set aside for unknown risks
such as scope changes. These changes can only be possible if contingency funds
are left to accommodate these changes. For this reason, management reserves
need to be monitored just as carefully as the project cost baseline. For this, the
author proposes a different S-curve to be plotted for the management reserves.
This will show early on; how much reliance is put on these management reserves.
This can be a basis for revisiting the project scope, and costs plan to check for
errors.
Most importantly, this curve will give early warning signs of the project’s future
flexibility to adapt to cost changes, scope creep and scope additions further along
the project duration. The principle is similar to the project’s EVM curve; with
SPIs and CPIs of less than one indicates the project is less flexible to scope
changes or cost overruns. A TCPI greater than one should suggest to the project
team that there is not sufficient management reserve left to accommodate
potential future risks. This would be helpful, especially in the case of target price
or Guaranteed maximum price contracts. Owing to the fact that unlike project
direct and indirect costs that are associated with specific project activities
occurring at particular dates, management reserves do not have related tasks. It
53
is therefore proposed that the schedule axis on the s-curve for management
reserves be planned using milestone intervals. This is because milestones are
not project activities themselves but checkpoints that embody completion of
groups of summary activities. Traditionally, they are periods when reviews are
done for completed activities, and risk analysis is done for future activities. It
may be measured with a reserves milestone performance index. With the
management milestone performance index, project teams can have quantifiable
data to demand disciplined and timely scope changes from other project
stakeholders.
5.2 ERROR REPORTING AND DATA MANIPULATION
“The goal is to turn data into information and information into insight.” – Carly
Fiorina, however, Errors using inadequate data are much less than those using
no data at all.” – Charles Babbage
EVM loses its reliability once data analysed is wrong or manipulated. The author
proposes that PMOs in which the following factors exist, bear more risks of
unreliable data.
• Absence of consistency and standardisation,
• Not enough time allowed for data collection,
• Confusion on what and how to measure,
• Punishment oriented monitoring,
• Promotion of individualism, private interests and subjective appraisals,
• Setting vague baselines.
While measuring techniques have been introduced earlier in Chapter 2 of this
research, these techniques are classified in numerous Project management
literature as discrete, apportioned and level of effort.
Of the three, apportioned techniques are subjective opinions and can be sources
of individualism, biased appraisals and difference in reporting styles
54
(communication), especially considering expert judgement. Being only an
estimate, it is effectively a guess subjective to the objectives and knowledge level
of the appraiser or appraising team. The danger this poses is that without
quantifiable data, the status of critical or near-critical activities with very limited
float can be poorly-measured and intentionally or unintentionally
miscommunicated. Accurate work performance insights may be impaired until
it is too late to make control decisions. This effectively defeats the benefit of early
warning signs EVM presents. This can cause loss of control; slipping from
proactive decision making to reactive decision making.
All three categories of measurement reporting may be adversely influenced in
complex projects having a plethora of data that consumes considerable time and
effort for sorting at all times during project execution. Without clear guidelines
on what data is necessary, timeliness requirement of such data, irrelevant and
untimely data presents a risk to the integrity of EVM results.
To alleviate these problems, the author suggests;
Expert judgment measuring and reporting technique should be limited to short-
duration project activities. This is to ensure that warning signs for difficult to
measure activities; which may affect subsequent activities, are detected early.
Despite the reliance on the qualitative judgement of the reporting person or team,
errors can be spotted early if the scheduled finish date is not far from the
reporting date, yet enough work is not perceived as close to completion. This
allows for swift and frequent review of activity performances that are measured
anecdotally. Reducing the duration of activities where possible decreases the
risks from error reporting. The threshold of ‘short duration’ may be decided by
the project team taking into consideration, total project duration, average total
float of each activity and unit of time measurement for activities. The author
strongly advices against any iteration of qualitative measuring for critical and
near-critical activities. Additionally, the author proposes that a project scope
55
should be decomposed to the level where most activities are short to medium-
term in duration.
A second proposal is having a predefined measurement basis for apportioned
reporting. This can be developed by project facilitation or focus groups before the
commencement of the project. This should allow for an all-stakeholder
understood and collaborative rationale for reporting, thus reducing the
possibility of data manoeuvring for personal objectives. A system that objectively
assesses subjective measurements. This may be achieved by taking into account
the completion of lower-level tasks. Lower-level tasks may be assigned weights
that will collectively sum of to the task completion rate of 100%. For a discrete,
level of effort, 0/100 and 50/50 techniques; units of measurement, the
technique to be used and reporting level should be prescribed before the project
commences.
Participating stakeholders may each have consistent internal measuring and
reporting processes, the existence of various techniques means that units,
approach and processes may differ among stakeholders. It is, therefore, once
again, essential to define project-specific measurement techniques or align
processes with that of other stakeholders. This requires repetitive work for each
project. An alternative to this repetitive proposal is to have a comprehensive
legislated, standardised measurement and reporting guideline book that can be
referred to, to form the basis of any project reporting. What the author suggests
here is similar to the German HOAI, which is referenced to for the calculation of
architects and engineers service fees.
For data integrity issues, it is pertinent to EVM that standardised rules for
activity measurement and reporting should be prepared, understood and aligned
among participating stakeholders. This may be gotten by developing an AEC-
EVM general guideline book of standards or best practices or be expressed in
project-specific documents such as contracts and project management manuals.
56
Punishment oriented monitoring would be discussed later in this chapter
5.3 STANDARDIZATION OF PROJECT MANAGEMENT PROCESSES
The most apparent approach to achieving standardisation is the establishment
of a Project management office.
(Monteiro, Santos, & Varajao, 2016) Stated that the Project Management Office
(PMO) “is an organisational structure created in order to promote and improve
project management practice, by adopting appropriate methodologies to achieve
high levels of efficiency and effectiveness”. A PMO performs centralised oversight,
supporting and consulting duties for projects. Various models of how project
management offices should be set up exist; however, the design of each model
depends on the objective of the PMO. However, for alignment with EVM,
controller PMO models are most suited. The models below are listed according
to the services they offer;
I. Supporter model (Desouza & Evaristo, 2006)
Serves as a project administrator, identifying risks, providing project
status, raising possible issues and keeping project records.
II. Supporter model (Unger, Gemünden, & Aubry, 2012)
They provide team training and steer project team members towards
working with Project management standards and methodologies.
III. Information management model (Desouza & Evaristo, 2006)
They track and report the progress of the projects for reviews and
forecasts. They are always well informed of the current status of their
projects
IV. Knowledge management (Desouza & Evaristo, 2006)
They are the source of the best practices, project expertise, training and
mentoring project team.
V. Coaching model (Desouza & Evaristo, 2006)
They are focused on constant improvement through the enforcement of
project management methodologies in an organisation.
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VI. Federated PMO (Gartner Research Group, 2008)
Consists of a corporate PMO and lower-level division PMOs where the
corporate PMO is responsible for methods, training, and tools while the
lower division PMOs are responsible for project reporting, oversight, and
delivery.
VII. Project management Office (Gartner Research Group, 2008)
Seeks to establish a consistent baseline of processes and to use formalised
project tracking and reporting systems.
VIII. Project control office (Crawford, 2010)
This handles large and complex single projects. This PMO is dedicated to
one project at a time.
IX. Controller model (Unger, Gemünden, & Aubry, 2012)
They are responsible for gathering, preparing and providing information
that is required for decision making, as well as proposing corrective
measures.
X. Projectized PMO (Project management Institute, 2013)
They are set up temporarily for the specific purpose of delivering project-
related services in a particular project. The office is disengaged or
reassigned at the completion or termination of a project.
Other models exist; however, the author believes that all models mentioned
above are capable of delivering EVM standardisation. Specific suitability of these
models varies from project to project and organisation to organisation. Some
models are better suited for low project management maturity and others, for
higher-level maturity; some support, train and motivate, others enforce. Choice
of the model to adopt may be decided by determining the level of organisational
or project influence desired; some models deliver monitoring and archiving
services while others hold control and steering authority. A third factor to
consider may be the choice between a temporary, single project focused PMO or
a long-term, multiple project PMO setup.
58
While the premier objective for advocating for a PMO is to have a focal point
providing standardisation, coordination and consistency in project monitoring
and control, organisations with little or no EVM and project control
standardisation should first attempt a hybrid model of ‘training’ and ‘project
specific’ models in order to raise internal proficiency levels. This would involve
the adoption of EVM control methodologies, as well as developing templates for
project control framework.
While the author acknowledges that introducing a PMO would demand effort,
increase overhead costs and cut into profit margins, organisations having many
projects or working on complex projects should have a central project control
office best aligned with their objectives and helps define, optimise, coordinate
and maintain best control practices.
5.4 PUNISHMENT OF CONTRACTORS
Punishment oriented monitoring is one of the challenges to successful project
deliveries.
A potential hindrance to proper use of EVM is the fear of negative consequences
that may arise from control decisions. This may be in the form of claims against
the contractor, and extreme cases, termination of services. While some literature
exists encouraging the use of EVM as a human resources tool, the author
believes that there can exist, a multitude of other reasons why EVM could
indicate poor contractor performance without being the fault of the contractor.
The first, as observed from questionnaire responses and analysed earlier, is the
problem of standardisation. Lack of standardised measuring and reporting, non-
alignment and understanding of reporting processes may lead to a poor
measurement of ACWP and discrepancies from contractor to contractor. A
second factor to consider is that higher competition for contracts leads
contractors to underbid projects in expectations of future income from claims or
submit high risk fast-tracked schedules with very limited float. These can cause
59
an extremely difficult execution of the project. Being a tool that works best having
set reliable and realistic baselines, using EVM as a basis to punish contractors
for unrealistic targets can be unfair.
Another reason to discourage punishment is that external factors beyond the
control of contractors may influence project performance. These factors include
but are not limited to erratic weather, unplanned site conditions, changes in the
regulatory requirement. Without being able to distinguish between internal
inefficiencies and negative external factors influencing poor performance, EVM
is mostly by itself, unable to measure both project performance and contractor
performance.
Punishment causes contractors to hide and try to fix problems that may be a
flaw in the overall project itself and not born as a result of poor contractor
performance. The fright of punishment may also compel contractors to conceal
or manipulate reports such that they can avoid negative scrutiny on their
performance. As is often an area of debate in project management, in the event
of challenges, contractors assume ownership of floats and resource reallocation
to correct their challenges without informing the project owner or his project
manager. The danger this poses is that early warning signs of a faulty plan may
be missed when all focus is placed on only on completing activity and milestones
within their planned budgets. Secondly, as is with the project management iron
triangle, quality may suffer when constant pressure of performance is placed on
schedule and cost performance.
Projects can be delivered according to cost, schedule and quality baselines;
however, they rarely go according to plan for the entirety of their duration. They
always require control decisions that balance scope, cost, schedule and quality
to steer projects back on track. For this reason, the author believes that EVM
should be used only as a compass and not a weaponised project control tool.
Despite the necessity to pursue excellent project performance, the project
environment should be such that contractors are encouraged to report truthfully
and transparently poor project performance, whatever the reason behind it is.
Having this allows all stakeholders to deliver a collaborative control plan that
60
requires collaboration and trust amongst all participating stakeholders. Steadier
long-term control decisions may be developed rather than focusing on firefighting
project management that is more preoccupied with short term results by the
contractor. Principles of alliance contract project delivery method can be adopted
to encourage collaboration and shared problem-solving. For EVM to work
transparently and effectively, it is vital that every project stakeholder sees it as
a tool that supports their work and shares a common desire to deliver a
successful project.
5.5 IT PROJECT SUPPORT
Computers and software are vital tools in modern-day workplaces. Project
management workplaces are no exception to this with software such as Oracle’s
Primavera P6, and MS Project in widespread use in the construction project
management community. These project software help overcome challenges of
traditional project management systems that may be characterised by multiple
unorganised interrelated schedules, graphs and reports. By replacing
inefficiencies of conventional manual methods, the additional general
advantages of project management and control EVMS include; reduction in
computational errors, straightforward and consistent reporting formats,
improved efficiency through reducing the man-hours required for gathering,
analysing and reporting data, leaving project managers more time to focus on
other responsibilities. There must, however, be the awareness that these
advantages come at some costs to the organisation. Purchase of licenses,
integrating different software, and staff training for are often expensive and a
barrier for small-sized organisations. Software available may also not fit the
business processes of the organisation and may require the business processes
to fit the framework of the software instead. This is more a problem for
standardised project management offices. A solution to this problem is to have
customised bespoke made EVMS, which will incur additional costs.
61
Despite the benefits that EVMS brings to project control, modern projects are
growing in complexity and challenging schedules yet demanding higher cost
efficiencies in management infrastructure. It is therefore imperative that to build
an EVMS, the benefits of individual software should be chosen to balance as
much as possible, ease of use by its intended users, organisational standards,
inter-operability and multiple other factors while keeping set-up or use costs as
low as possible.
Figure 8: Engine choice checklist to build an EVMS. Owner's elaboration
Using the figure above, the author suggests a checklist of feasibility and cost-
benefit relationship that can be useful when building an EVMS. Alignment with
organisational standards and policies and user requirements are feasibility
conditions that should be considered, while the cost to the organisation, use,
general requirements and quality are cost-benefit conditions to be assessed.
62
The quality of an EVMS can significantly influence the successful delivery of
projects they are used on. With relevant, consistent and comprehensive reports,
they can assist in making right control decisions, while its interoperability can
improve overall project & portfolio intelligence. User requirements demand that
the engines be adaptive and uncomplicated enough for intuitive use. With these,
project managers would be further encouraged to use and share information on
the EVMS. Projects and portfolios may also have multiple site teams that require
the support of multi-location EVMS as opposed to single-site project teams.
The author acknowledges that smaller sized organisations may be unable to
invest in specialised EVM software irrespective of accompanying benefits,
perhaps as a result of skills maturity or financial constraints. To alleviate these,
simple spreadsheets may be used; as they are mostly cheaply available but
require increased effort. There are large pools of materials and manuals available
on the internet on how to use spreadsheets like Microsoft Excel to calculate EVM
for simple project tasks. However, more complex projects requiring the need to
incorporate combinations of different progress measuring systems for different
activities supervised by a large number of people over extended periods would
require high EVM knowledge and Excel proficiency to write formulas as well as
high levels of synchronisation, collaboration and organization. It would likewise
need the project team to determine the right size that project activities should be
measured. Measuring tasks that are too small will cause a floodgate of
information to be analysed on a limited functionality software. Project activities
that are too big may not be measured early enough to catch early warning signs
that may have negatively impacted on the projects beyond if they had been
detected earlier. More basic software like Microsoft Excel is recommended only
in the event of the following conditions:
I. Project managers have good projects, EVM and spreadsheets maturity.
II. A small-sized project team is involved.
III. The project scope and activity relationships are relatively simple.
IV. The project is short term (1-3) years.
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5.6 CONCLUSION
Factors identified by the author, as factors that are important for the successful
project/organisational implementation of EVM have been discussed earlier.
Recalling, they are flexible to accommodate scope changes, standardisation of
processes, mitigating against manipulation of figures, the punishment of
contractors and use of software support. These factors need to be individually
satisfied and collectively balanced in order to provide an enabling environment
for EVM to be reliable. The ratios to which they are adjusted would be determined
by the type of control decisions expected from the project team. EVM itself is
described as a powerful measuring tool; however, strategic project organisation
influences how it is implemented for measurements.
Strategic project organisation that is more aligned with strictly policing and
controlling a project are more likely to use EVM for a firm and accurate
enforcement of original baselines and processes. They may choose to place a
higher emphasis on standards, consistency, strict accountability, discipline and
prefer specialised software and EVMS. Conversely, they may place a lower
emphasis on flexibility and collaboration. This model is more suitable for project
controllers working on large projects and organisations. It involves assigning
people to pre-determined processes. EVM measurements in this model are
reasonably reliable, limited expected deviations and variances from the EVM
curve, and usually difficult to manipulate. Negatively, it is less useful for
delivering projects with uncertainties.
64
Figure 9: Model 1 to overcome Implementation Constraints of EVM. (Author)
On the other hand, strategic project organisation that is more aligned with
project advocacy and support are more likely to use EVM to inform adaptive
approaches to controlling the project to successful delivery. They may place a
higher emphasis on people’s experiences, and capacity, flexibility to changes,
stakeholder collaboration and may not require standardised software.
Conversely lesser emphasis is placed on consistency, standards, discipline and
processes. Accountability would still be demanded but at higher tolerance for
poor work performance if it guarantees transparency of reporting and highlights
contractor challenges. With fewer regimented processes, frequent deviations
from the EVM curve is reasonably expected; however, the higher likelihood of
collaboration and buy-ins from all participating stakeholders increases the
chance of achieving the baseline targets EVM measures.
EVM for project
Policing and control
Standards
Strict accounta
bility
Consistency
Collaboratio
n
Specialized
software
EVM and
control maturit
y
Flexibility
65
Figure 10: Model 2 to overcome Implementation Constraints of EVM (Author)
Baselines may be adjusted to accommodate changing requirements necessary
for achieving success criteria outside the purview of EVM measurements. This
EVM use model may be better suited for projects with limited stakeholders, not
very complex scope and organisations with developed EVM and project control
maturity.
The models presented above are presented as different environments in which
EVM implementation can be iterated depending on its purpose. The features of
model one may be more embraced by project organisations representing project
clients while project organisation on the side of contractors may find themselves
better suited to model two.
EVM for project
advocacy and support
Collaboration
Flexibility
EVM and control
maturity
Standards
Specialized
software
Consistency
Strict accountability
66
To end this thesis, the author also proposes that university syllabi in the field of
project controls need to be updated. Despite the relative ease of understanding
the classroom version of earned value management, this thesis has shown that
its practice on real projects is low. There should be more in-depth technical
training, software proficiency training and knowledge of organisational
environments influencing project control. Practising organisations need to be
aware of the interrelated factors that must all be individually satisfied and then
collectively balanced to provide an enabling structure for EVM to be reliable, thus
enhancing its application of construction projects.
67
DECLARATION OF AUTHORSHIP
I hereby declare that this Master’s thesis was completed independently and
without the prohibited support of third parties, and that no sources or support
were used other than those listed. All passages whose content or wording
originates from another publication have been marked as such. Neither this
thesis nor any variant of it has previously been submitted to an examining
authority or published.
Signature: ……………………… Date: ………………………………
68
APPENDIX A
EARNED VALUE MANAGEMENT (EVM) RESEARCH QUESTIONNAIRE
I am a Construction and Real Estate Master's degree student from Berlin,
Germany.
This survey is meant for project managers and controllers and is intended to give
the researcher an insight into important, yet often overlooked soft factors to
consider for the accurate use of the EVM tool. The research is purely for
academic purposes and responses would be treated with the highest
confidentiality.
Kindly fill this survey according to your knowledge, experience and opinion.
PART A
1. What is your current role within your organisation?
a. Project manager
b. Project team member
c. Portfolio manager
d. Consultant
2. What is the staff size of the organisation in which you are employed?
a. 0-10 people
b. 10-49 people
c. 50-249 people
d. 250 or more people
3. What is your project management level of education? Multiple answers
can be chosen
a. Bachelor’s degree
69
b. Master’s degree
c. Project management certification, e.g. PMP or Prince 2
d. No project management education
4. How many years’ project management/control related experience do you
have?
a. 0-3 years
b. 3-5 years
c. 5-7 years
d. More than 7 years
PART B
5. How would you rate your knowledge of Earned value management?
a. Elementary
b. Working knowledge
c. Expert
d. No knowledge
6. How do you track and monitor progress on your projects?
a. Earned Value management method
b. Network-based techniques, e.g. CPM or PERT
c. Combination of A & B
d. None of the above
7. To what extent has EVM positively influenced the successful deliveries of
your past projects?
a. Positive
b. Neutral
c. Counterproductive
d. I have never used EVM on Projects
PART C
8. Project management & Control processes are standardised in your
organisation. (evaluating control process aspect)
70
a. Fully standardised
b. Partially standardised
c. Not standardised
9. All stakeholders and departments involved in project control do not
participate in scope and cost planning. Please respond based on your
experience.
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly disagree
10. Project managers and contractors manipulate or do not report
progress measurements properly. Please respond based on your
experience.
a. Strongly agree
b. Agree
c. Neutral
d. Disagree
e. Strongly disagree
11. Work breakdown structures from the planning phase do not
completely represent client expectations at the end of the project. Please
respond based on your experience.
a. Strongly agree
b. Agree
c. Neutral
d. Disagree
e. Strongly disagree
12. Data gathering, collection, storage, and extraction requires
specialised project management software. Please respond based on your
experience.
a. Strongly Agree
71
b. Agree
c. Neutral
d. Disagree
e. Strongly disagree
13. EVM is a strong basis to terminate underperforming project
contractors. Please respond based on your experience.
a. Strongly Agree
b. Agree
c. Neutral
d. Disagree
e. Strongly disagree
72
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