BUSINESS PROJECT MANAGEMENT AND ITS RELATION
TO LONG-TERM PROJECT SUCCESS
I. INTRODUCTION
Background and Relevance of the Research
As a result of significant economic pressure as well as the growth of
globalized markets, many companies are faced with the challenge of
reducing both the development time and price of products or services while
simultaneously improving their quality. Clearly, there are notable
advantages to being the first company to bring a new product, innovation, or
service to the market. However, doing so requires an effective and efficient
development and realization process. By developing such a process, the
product life cycle shortens, thus allowing the first firm in the market to earn
money on that product for a longer period of time.
Because of these issues, markets are becoming more competitive.
Competition has led some firms to squeeze others out of the market. Some
firms cease to be economically viable, thereby making room for other firms
to secure a greater number of market shares. Others feel compelled to react
to these circumstances in the short term and increase both the effectiveness
and efficiency of each business-related activity in the longer term. To do so,
firms are forced to undergo a strategic and operational transformation;
otherwise, their ability to compete and to survive will be compromised.
Companies that are able to successfully implement these changes, therefore,
tend to achieve an advantage over the companies that fail in this regard. This
competitive advantage could be in the form of cost leadership or innovative
products or services.
Given this, the main objective of every firm should be to survive and
to gain a competitive advantage in the market in which they operate. This
can only be achieved through continuous product improvement, optimization
of applied technologies and organizational processes, and effective and
efficient realization of changes combined with a maximum level of
flexibility in implementing these changes.
Project completion
with PM
Completio n date
Problem
identification
Measures for problem solution
Time
Problems escalation
Project completion
without PM
Planning and
co -ordination
expenditure
Figure 1. Implementation projects with and without PM (Hab &
Wagner, 2006)
To successfully operate in such turbulent market cycles, companies must
implement effective project management to ensure the success of their
endeavors (see Figure 1). Kerzner emphasized the importance of project
management, stating that “success in project management is often a
reflection of the organization’s ability to respond quickly and effectively to
changes in the marketplace” (Kerzner, 1987, p. 36). The response to which
Kerzner referred could be, for example, a shorter time for project realization
or organizational flexibility in reacting when characteristics of the business
environment change As a result of these strengths, project management is
indispensable for most industrial sectors and is employed in a variety of for-
profit and non-profit organizations. The necessity of implementing project
management to succeed in the highly competitive business environment is
recognized by most companies (Sherman et al., 1996). Once project
management is adopted and correctly implemented, the efficiency,
effectiveness, and productivity of the organization increases (Kerzner, 1987).
Because of the positive outcomes associated with it, some companies invest
large amounts of money and resources into employee training and adaptation
of its existing organizational structure to a project management system. In
companies that successfully adapt to this system, project management is
used to achieve the objectives that are derived from the company or
organization strategy. Jugdev and Müller emphasized the strategic role of
project management, stating that “project management can have strategic
value when a clear connection is made between how efficiently and
effectively a project is done and how the project’s products and services
provide business value” (Jugdev and Müller, 2005, p. 19). Therefore, project
management can be considered a management method that contributes value
to the organizations in which it is implemented.
In parallel to challenges posed by increased project complexity, academics
and practitioners are likewise facing a challenge associated with
maintaining a sound base of corresponding management knowledge. To this
end, several studies have been conducted in this field to explore the link
between theory and practice of project management. This has been
performed to identify the gaps between the two and to initiate further
research. Academics and practitioners have thus analyzed how to
successfully manage projects. The results of these efforts have resulted in
regular publications in the International Journal of Project Management by
IPMA (International Project Management Association) and the Project
Management Journal by the Project Management Institute (PMI). Some
organizations publish their findings in independent reports. One such
organization, called The Standish Group, publishes its findings in reports
named “Chaos Reports” (Table 1). According to the 2009 Chaos Report,
32% of IT-projects have been judged to be successful (The Standish Group,
2009). This survey aimed to investigate the factors that lead projects to fail
and how these failures can be reduced or eliminated. The Standish Group
classified projects into three categories:
Table 1. The Standish Group findings over the years
Year Successful (%) Challenged (%) Failed (%)
1994 16 53 31
1996 27 33 40
1998 26 46 28
2000 28 49 23
2004 29 53 18
2006 35 46 19
2009 32 44 24
•Successful project: a project that is completed within time and budget
constraints and meets all predetermined requirements,
•Challenged project: a project that is completed and operational but over
budget, over the time estimate, and offers fewer features and functions
than originally specified, and
•Failed project: a project is canceled during the development phase.
In response to these reports as well as other previous studies, many
practitioners and researchers have attempted to identify the causes of project
failure, the factors that contribute to project success, and which criteria are
appropriate to gauge this success. Atkinson found, for example, that
“[p]rojects continue to be described as failing, despite management. Why
should this be if both the factors and the criteria for success are believed to
be known?” (Atkinson, 1999, p. 337). He further claimed that no
considerable amelioration of project success criteria have been realized in
the last half century.
Because the use of projects to achieve organizational outcomes is
integral for organizational success, the search for factors that contribute to
project success is likewise critical (Söderlund, 2004). In spite of this, some
researchers, academics, and practitioners have argued that there has been
little agreement on what constitutes project success. In response to the
widespread debate surrounding project success, several lists dealing with
factors related to project success have been published. The lack of agreement
on the definition of project success renders the quest to identify the factors
that contribute to successful project implementation moot. Without knowing
what constitutes success, we cannot know what contributes to it.
Regardless of these debates, there is a marked lack of research linking
project success factors and project success criteria. Practitioners are
interested in recommendations for implementing project success factors and
the corrective or preventative actions that should be taken if the project fails
to meet one or more project success criteria. Project management and the
research related to it are therefore, facing severe criticism for not fulfilling
their contributory expectations within the management discipline.
Packendorff (1995), for example, claimed that there has not been sufficient
empirical research in the project management field to determine (a) what
project success is, or (b) how to gauge it.
A recent study conducted by Ahlemann et al. (2012) investigated the
status of project management research in the last five years through a survey
of the International Journal of Project Management from 2006 to October
2010. The goal of this study was to find answers to the following questions:
1. What is the nature of the project-related body of knowledge that can
serve as a foundation for prescriptive project management research?
2. What types of solutions are proposed and enacted for problems related to
projects?
3. What are the methods used to develop solutions for project-related
problems?
4. What evaluative approaches have been proven useful with respect to
method design and testing?
In this study, 422 project management papers were reviewed and
classified into five categories (see Table 2). The majority of the reviewed
papers were descriptive (216 papers, 51.18%), 120 papers (28.43%) were
classified as prescriptive, and only 10 papers (2.37%) dealt with theories in
the project management field. With respect to research types, 57 papers
(47.50%) were method-based, 42 papers (35%) explored conceptual models,
and 18 papers (15%) were geared towards developing a framework (see
Table 3). Only 23 papers (19.17%) of the 120 prescriptive papers had a
sound theoretical foundation (see Table 4). The study also showed that 32
papers (26.66%) did not contain information about the solution development
process (Table 5) and 62 (49.2%) papers reported on research results by
utilizing one or more evaluation methods (Table 6).
Table 2. Paper type (Ahlemann et al., 2012)
Paper type
Descriptive 216 51.18%
Prescriptive 120 28.43%
Other 39 9.24%
Conceptual 37 8.76%
Theory 10 2.37%
Total 422 100%
Table 3. Research type (Ahlemann et al., 2012)
Prescriptive papers: Research type
Method 57 47.50%
Model 42 35.00%
Framework 18 15.00%
Ontology 1 0.83%
Reference model 1 0.83%
System 1 0.83%
Total 120 100%
Ahlemann et al. criticized the maturity of project management, stating
that the “review of the IJPM papers confirms that theoretical work in project
management research is underdeveloped.” and that ”[a]lthough project
management practices have been known for centuries, PM research is still in
its infancy compared to the natural sciences” (Ahlemann et al., 2013, p. 45).
Table 4. Theoretical foundation (Ahlemann et al., 2012)
Prescriptive papers: Theoretical foundation
No foundation: No theory is used to justify the design
decisions
97 80.83%
Fuzzy set theory 5 4.16%
Organization theory 2 1.66%
Theory of constraints 2 1.66%
Arbitrage pricing theory 1 0.83%
Theory of social constructivism 1 0.83%
Contingency theory 1 0.83%
Evidence theory 1 0.83%
Game theory 1 0.83%
Graph theory 1 0.83%
Lifecycle management theory 1 0.83%
Management control theory 1 0.83%
Negotiation analysis theory 1 0.83%
Organizational psychology theory of job performance 1 0.83%
Porter´s generic strategies 1 0.83%
Pragmatic theory of knowledge 1 0.83%
Stakeholder theory 1 0.83%
Theory of convention 1 0.83%
Total 120 100%
Table 5. Methods used for solution development (Ahlemann et al.,
2012)
Prescriptive papers: Methods used for solution development
No details: No details on the solution development process 32 26.66%
Literature analysis 54 45.00%
Mathematical and logical deductions 28 23.33%
Empirical data analysis 25 20.83%
As a result of the efforts of academics and practitioners to improve the
project management field through the development of theories, frameworks,
and models, the project success rate increased from 16% in 1994 to 32% in
2009. Still, it could be argued that there remains a need for more extensive
and practice-oriented research.
Table 6. Evaluation (Ahlemann et al., 2012)
Prescriptive papers: Evaluation
No evaluation: No evaluation method is used to assess the
effectiveness
58 48.33%
Case study (single or multiple) 24 20.00%
Simulation 19 15.83%
Survey 10 8.33%
Expert opinion 9 7.50%
Meta analysis 3 2.50%
Literature review 2 1.66%
Text analysis 1 0.83%
Conclusion
Several studies have dealt with the identification of project success
criteria or causal antecedents to project success. Unfortunately, success
criteria and causal factors have been investigated in isolation; there has been
no conceptual link between the causes of project success and ways to gauge
that success. Therefore, there is little reason to implement assumed factors
that contribute to project success without knowing the intended outputs.
Given this, practitioners are interested in determining which success factors
(activities, process output, behaviors, etc.) will improve particular project
outcomes. Little attention has been paid to the relationship between project
success criteria and project success factors and to how project success
factors can be improved to achieve better project outcomes. In addition,
there has been no empirical differentiation of pastoriented criteria (POC;
related to corrective action plans) and future-oriented criteria (FOC; related
to preventive action plans). For instance, many researchers have stated that
the execution of a project is successful when it is performed within budget,
on time, and with predetermined specification. In this case, there are three
project success criteria that are considered indicative of project success: cost,
time, and specification. Other authors link these three criteria to the main
objectives of project management and argue for their measurement directly
following product handover (Figue. 2).
Figure 2. Typical Sequence of Phases in Project Life Cycle (PMI,
2004) Despite their use for theorizing about project management, all these
criteria are past-oriented. For instance, customer satisfaction, end-user
satisfaction, and long-term objectives, which are all future-oriented, are not
considered. Customer satisfaction must be continuously measured during the
project and the product’s life cycle (Figure 3) to effectively determine how
to positively affect it. End-user satisfaction represents how happy the user is
with the final product or service, so this criterion should also be measured
regularly during the product life cycle. Given all this, it could be argued that
there exists a general lack of applicable project management knowledge for
practitioners. This can be resolved by coordinating with researchers, but
academics and practitioners acting in the project management field do not
speak the same language. Bridging the gap between theory and practice is
integral for improving not only how projects are managed but also how the
success of that management is gauged.
Figure 3. Relationship between the Product and Project Life Cycles
(PMI,
2004)
Research Questions and Model
This study explores the maturity of project management both as a
discipline and as an applicable instrument to facilitate competition in a
highly competitive business environment. It draws on prescriptive research,
empirical data related to project success factors and success criteria, and the
theoretical and methodological project management corpus of literature to:
1. systematically describe the current situation regarding the project
management body of research and its impact on the long-term project
objectives;
2. discover and/or establish the existence of interdependence among project
success factors in salient project management knowledge areas
(integration management, scope management, time management, cost
management, quality management, communication management, risk
management, human resources management, and procurement
management), project management process groups (initiating, planning,
executing, monitoring, and controlling), and project success criteria;
3. examine the relationship between project success factors and project
success criteria; and
4. develop a framework that deals with the operational link between the
success factors identified in project management knowledge areas,
project management process groups, and project success criteria (past-
oriented criteria: POC, and future-oriented criteria: FOC).
Therefore, this study addresses the following questions:
1. What is the role of project management research in helping organizations
to achieve short- and long-term project success?
2. What are the factors of the project management body of knowledge that
contribute to project success?
3. What is the link between project success factors and the short- and long-
term project success criteria?
4. How can project failure be prevented through preventive FOC and how
can possible project failures measured with POC be corrected through
problem solving tools like TOC (Theory of Constraints)?
The guiding research question in this study is the following: Is there a
significant relationship between project management body of knowledge and
long-term project success?. As known testable research questions begin with
one of the two phrases, (a) is there a significant difference between the
variable or attributes of interest; (b) is there a significant relationship
between the variable or attributes of interest. Therefore, the research
question mentioned above is testable.
A research hypothesis is a testable statement of opinion. It is created
from the research question by replacing the words "Is there" with the words
"There is", and replacing the question mark with a period. The hypothesis for
the research questions is:
There is a significant relationship between project management body of
knowledge and long-term project success.
This so-called alternative hypothesis could not be tested directly, because it
cannot be rejected, one may only accept that a relationship exists. Instead,
the hypothesis must be turned into a null hypothesis. The null hypothesis is
created from the hypothesis by adding the words "no" to the statement.
Therefore, the null hypothesis for this study is:
There is no significant relationship between project management body of
knowledge and long-term project success.
The independent factors in this study have been conceptualized as
those elements of project management knowledge areas and the related
project management process groups that can be influenced or implemented
to increase the chance of project success. These factors are described in the
PMBoK Guide 2004. The dependent items in this study were those project
outcomes (project success criteria) that are influenced by the outputs of the
process groups (independent factors) in each subject area within the
knowledge base of project management. These criteria were established
according to researcher experiences in project management and previous
research on the topic.
Figure 4. Research model
Independent Factors: Project Success Factors:
H1-1 Project charter, H1-2 Preliminary project scope statement, H1-3
Updates, H1-4 Project management plan, H1-5 Deliverables, H1-6
Requested changes, H1-7 Implemented change requests, H1-8
Implemented corrective actions, H1-9 Implemented preventive actions,
H1-10 Implemented defect repair, H1-11 Work performance information,
H1-12 Recommended corrective actions, H1-13 Recommended preventive
actions, H1-14 Forecasts, H1-15 Recommended defect repair, H1-16
Requested changes, H1-17 Approved change requests, H1-18 Rejected
change requests, H1-19 Approved corrective actions, H1-20 Approved
preventive actions, H1-21 Approved defect repair, H1-22 Validated defect
repair, H1-23 Deliverables, H2-1 Project scope management plan, H2-2
Project scope statement, H2-3 Work breakdown structure, H2-4 WBS
dictionary, H2-5 Scope baseline, H2-6 Accepted deliverables, H3-1
Activity list, H3-2 Activity attributes, H3-3 Milestones list,
H3-4 Project schedule network diagrams, H3-5 Activity resource
requirements, H3-6 Resource breakdown structure, H3-7 Resource
calendar, H3-8 Activity duration estimates, H3-9 Project schedule, H3-10
Schedule model data, H3-11 Schedule baseline, H3-12 Performance
measurements, H4-1 Activity cost estimates, H4-2 Activity cost estimates
supporting detail, H4-3 Cost management plan, H4-4 Cost baseline, H4-5
Project funding requirements, H4-6 Forecasted completion, H5-1 Quality
management plan, H5-2 Quality metrics, H5-3 Quality checklists, H5-4
Process improvement plan, H5-5 Quality baseline, H5-6 Recommended
corrective actions, H5-7 Organizational process assets, H5-8 Quality
control measurements, H5-9 Validated deliveries, H6-1 Roles and
responsibilities, H6-2 Project organization chart,
H6-3 Staffing management plan, H6-4 Project staff assignments, H6-5
Resource availability, H6-6 Team performance assessment, H7-1
Communication management plan, H7-2 Performance reports, H7-3
Resolved issues, H8-1 Risk management plan, H8-2 Risk register, H8-3
Risk-related contractual agreements, H9-1 Procurement management plan,
H9-2 Contract statement of work, H9-3 Make-or-buy decisions, H9-4
Procurement documents, H9-5 Supplier evaluation criteria, H9-6 Updates,
H9-7 Procurement document package, H9-8 Proposals, H9-9 Selected
sellers, H910 Contract, H9-11 Contract management plan, H9-12
Procurement management plan (update) and H9-13 Contract
documentation
The measurement level of the independent PM process outputs mentioned
above is categorical (ordinal) that use the numeric value from 1 to 5
according to the Likert scale: (1: strongly agree, 2: agree, 3: neither agree
nor disagree, 4: disagree, 5:strongly disagree).
Dependent Project Outcomes – Project Success Criteria:
Budget/cost, schedule, customer , user, stakeholder and project team
satisfaction, strategic contribution of the project, financial, technical and
performance objectives, commercial benefit for contractors and customer,
scope, personal growth, customer approval, profitability, and sales.
The dependent project outcomes mentioned above are categorical (nominal)
that use the numeric value 0 and 1 to stand for No and Yes.
Research Limitation
In this study, the literature review and analysis of existing empirical
data related to project success factors criteria considers all project types (i.e.,
IS/IT projects, construction, new product development). There is a growing
recognition among researchers that most seminal studies on project success
criteria and project success factors use projects in information systems and
information technology (IS/IT) as data. The factors and criteria for project
success strongly depend on project type and industry. Therefore, to explore
the application of problem solving tools like TOC in a more comprehensive
manner, this study pays greater attention to new product development
projects.
Research Structure
The remainder of this paper is structured as follows. Chapter Two
provides an overview of the literature dealing with the project management
body of knowledge. Chapter Three discuss the research methodology and
solution design utilized in this study. Following this, Chapter Four verifies
the research objectives presented in Chapter One through a presentation of
the analysis results. Chapter Five provides an interpretation of these results.
Finally, Chapter Six summarizes the findings of this study and concludes
with recommendations for future research.
II. LITERATURE REVIEW
Projects and Project Management
In recent years, several definitions of the term “project” have been
proposed. Turner defined a project as “an endeavor in which human,
material and financial resources are organized in a novel way, to achieve a
unique scope of work, of given specification, with constraints of cost and
time, so as to achieve a purpose defined by quantitative and qualitative
objectives” (Turner, 1993, p. 8).
Turner’s definition does not consider external constraints such as the
cultural, political, and social environments in which a project is carried out.
Thus, this definition isolates the project’s external factors that could have an
important impact on the project’s implementation. Furthermore, the
“quantitative and qualitative objectives” referenced by Turner leave much
room for interpretation. Similar to Turner, Andersen et al. defined a project
as “unique task; is designed to attain a specific result; requires a variety of
resources; and is limited in time” (Andersen et al., 2009, p. 10).
While several authors conceptualize project as an endeavor, others
view a project as a collective of individuals. Steiner (1969), for example,
defined a project as “an organization of people dedicated to specific purpose
or objective.”
Furthermore, the term “project management” also has a number of
definitions in the literature. The simplest, and arguably the most meaningful,
definition was proposed by Widemann (1995). He stated that “[t]he
underpinning of project management can be characterized as ‘getting things
done’.” (Widemann, 1995, p. 72). However, he added that project
management is also about the “manner of how people do it.” He also stated
that project management involves sub-skills that integrate both “things” and
“people” (Widemann, 1995). This definition also incorporates interpersonal
skill, which is missing in many other definitions.
The Project Management Institute PMI defined project management
as “the application of knowledge, skills, tools and techniques to project
activities to meet project requirements. Project management is accomplished
through the application and integration of the project management processes
of initiating, planning, executing, monitoring and controlling, and closing”
(PMI, 2004, p. 8). PMI also noted that “managing a project includes
identifying requirements, establishing clear and achievable objectives,
balancing the competing demands for quality, scope, time and cost, and
adapting the specification, plans, and approach to the different concerns and
expectations of the various stakeholders”
(PMI, 2004, p. 8).
Project Management Knowledge Areas
The PMI identified nine significant knowledge areas in its Project
Management Body of Knowledge (PMBoK, 2004). These nine knowledge
areas and the related project management process groups are fundamental to
the development of the survey questionnaire used in the research described
here. These knowledge areas are as follows:
1. Project Integration Management includes the processes related to
developing of the project charter, the preliminary project scope statement,
and the project management plan, directing and managing project
execution, monitoring and controlling project work, integrating change
control, and the project closure process (PMI, 2004).
2. Project Scope Management includes the processes related to scope
planning, scope definition, creating work-break-down structure, scope
verification, and scope control processes (PMI, 2004).
3. Project Time Management includes the processes related to defining
project activities, setting the sequencing of project activities, estimating
the needed resources for each activity, estimating the duration that each
activity will take, and creating a time schedule and controlling it (PMI,
2004).
4. Project Cost Management includes the processes of estimating,
budgeting, and controlling the project cost (PMI, 2004).
5. Project Quality Management includes the processes of quality planning
and performing quality assurance and control (PMI, 2004).
6. Project Human Resource Management includes the processes of
organizing and planning the required human resources for project
execution (PMI, 2004).
7. Project Communication Management includes the processes of
communication planning, information sharing, performance reporting,
and managing stakeholders (PMI, 2004).
8. Project Risk Management includes the processes of risk management
planning, risk identification, qualitative and quantitative risk analysis,
risk response planning, and risk monitoring and control (PMI, 2004).
9. Project Procurement Management includes the processes of planning the
scope to be purchased and acquired, contract management, getting
supplier responses, and supplier selection (PMI, 2004).
Project Success and its History
In their retrospective look at project management success, Jugdev and
Müller argued that “our views on project success have changed over the
years from definitions that were limited to the implementation phase of the
project life cycle to definitions that reflect an appreciation of success over
the entire project and product life cycle” (Jugdev and Müller, 2005, p. 19)
(see Table 7).
During Period 1, only the time, cost, and specifications were used to
judge whether a project was successful (Jugdev & Müller 2005). They also
claimed that little attention has been paid to customer contact and long-term
follow-up and troubleshooting (Jugdev & Müller 2005). In this period, the
literature was focused on theory and not on the empirical investigation of
issues related to project management (Belassi & Tukel, 1996).
Table 7. Measuring success across the project and product life cycles
(Jugdev and Müller, 2005)
In Period 2, an additional criterion was included to judge project
success:
stakeholder satisfaction. In addition, several lists related to critical success
factors were published during this period. Unfortunately, these studies were
not organized in a coherent fashion (Jugdev & Müller 2005).
In Period 3, the focus of research related to project management was
on the development and realization of project success-related frameworks. In
this period, it was argued that project success depends on stakeholders and
the collaboration among the involved organizations (Jugdev & Müller,
2005).
During Period 4, the critical success factors lists that had emerged in
Period 2 were enhanced by further integrating criteria like management
support (Jugdev & Müller, 2005). Some of those lists will be discussed in
later chapters.
In the past few decades, project success has been the most widely
discussed topic within the literature on project management. Despite its
popularity, the concept of project success is not a tangible one. Hyväri noted
that “in the project management literature, it is still somewhat unclear what
makes a successful project in general, and, in particular, in the terms of
organizational context of the company or companies involved” (Hyväri,
2006, p. 31). Remenyi and Sherwood-Smith (1999) made a similar remark,
arguing that project success remains a poorly understood concept and
concluded that projects are often undertaken without defining how the
success of these projects will be judged. As a result of the difficulties
associated with conceptualizing project success, it remains subjective and
variable from one person or group to another. Succinctly stated by Freeman
and Beale (1992), “an architect may consider success in terms of aesthetic
appearance, an engineer in terms technical competence, an accountant in
terms of dollars spent under budget, and chief executive officers rate their
success in the stock market”. That which is not defined can be not measured,
and that which can be not measured cannot be monitored, controlled, or
improved.
McCoy (1986) observed that there is neither a generally accepted
definition for project success nor guidelines to measure it. Similarly,
Wateridge (1995) found that there was no agreement on the criteria for
judging project success. Despite these inconsistencies, extant research
indicates that most metrics for success depend on completing the project on
time, within budget, and with the predetermined user requirements and
functionality incorporated into it. Extant research has also indicated that
projects perceived to have failed have used time and budget as the primary
criteria for judging success. Wateridge noted these inconsistencies in
determining project success and concluded that “[t]here does not appear to
be a consensus of opinion among researchers and authors on the criteria for
judging project success and the factors that influence that success”
(Wateridge, 1995, p. 171). To resolve this, prior to the start of a project, the
individuals involved should determine the criteria with which the project will
be judged and identify and implement factors that will contribute to the
project’s success (Wateridge, 1995).
Several researchers have argued that the completion of a project on
time, within budget, and to the customer’s specification may not be
sufficient in determining project success. As such, many have attempted to
identify other criteria that could be used to judge project success as well as
factors relevant to achieving that success. Thus, other lists of project success
criteria and project success factors have been published since the 1980s.
Cleland (1986), for example, suggested a consideration of two views related
to project success: 1) the fulfillment of predetermined technical requirements
on time and within budget, and 2) the achievement of the strategic
objectives. Morris and Hough (1987) similarly argued that although the
completion of a project on time and within budget is important, a project can
still be considered a success if it is completed late or goes over budget.
Correspondingly, when a project meets its time and budget constraints, it
does not automatically indicate success (Anderson & Merna, 2003).
Therefore, time, budget, and specification are only three criteria among
many for judging project success.
Widemann (1995) stated that success is closely related to effective
communication and the quality of the resulting product. Bounds (1998)
argued that a successful project involves staff training and education;
dedicated resources; good tools; strong leadership and management; and
concurrent development of the individual, team, and organization. Given
Widemann’s (1995) and Bounds’s (1998) perspectives, it can be concluded
that project success is also related to cost management, time management,
scope management, quality management, communication management, and
human resources management. These represent six of the nine project
management knowledge areas indicated by the PMI.
Some authors (e.g., Cooke-Davies, 2002; Munns & Bjeirmi, 1996)
question the relationship between project management and project success.
Specifically, they differentiate the objectives of project management that
include the monitoring and controlling of cost, time and progress, and
project objectives, which are oriented towards long-term outputs like return
on investment and market share. Baccarini (1999) echoed this perspective,
arguing that project management success should be secondary to project
success.
One of the objectives of this study is to identify empirically the
elements of project management knowledge areas and related project
management process groups that affect short and long-term project
objectives, and thus, overall project success. The role of project management
is more than controlling of cost, time, and progress. According to Jugdev and
Müller , “if project success is limited to the variables of time, cost, and
scope- and the links to product/service value are missing- then project
management is perceived as providing tactical (operational) value and not
strategic value” (Jugdev and Müller, 2005, p. 19). To avoid this pitfall, this
study will explore the relationships between predictor variables beyond
timeliness, budgetary conformity, and product specificity and incorporate
some of the project management knowledge areas outlined above.
Project Success Criteria
Cooke-Davies described success criteria as “the measures by which
the success or failures of a project or business will be judged” (Cooke-
Davies, 2002, p. 185). Lim and Mohammed defined success criteria as “the
set of principles or standards by which judgment is made and are considered
to be the rule of the game” (Lim and Mohammed, 1999, p. 243). Each
company, enterprise, or organization has its own principles and standards.
The latter of these are developed and implemented by individuals within
those organizations, enterprises, or companies. Each individual has a unique
perspective on things within an organization. Therefore, the judgment of a
project success may differ not only from organization to organization, but
also from project to project and even from one person to another. Because of
these differential perspectives within and between organizations, Freeman
and Beale (1992) proposed that project success be evaluated through
different perspectives or expectations. These expectations can include the
achievement of a predetermined technical performance within time and on
budget, the level of internal or external satisfaction with the project, or the
commercial benefit generated from it (Freeman & Beale, 1992).
In addition to project management constraints (budget, schedule, and
specifications), Morris and Hough (1987) identified another criteria that
contain financial and technical requirements, and contractor’s commercial
performance by which a project success can be judged. However the list
associates project management with meeting budget, schedule, and
specification. Project management consists of nine knowledge areas.
Schedule, cost, and scope management represent just three knowledge areas
of these nine. This begs the question - what are the respective roles of the
remaining areas in achieving project objectives? The answer to this question
will become evident below.
Kerzner defined a successful project as “one which has been
accomplished within time, within cost or budget, at the desired performance
or quality level, within the original scope or mutually agreed upon scope
changes, without disturbing the corporate culture or corporate values, and
with welldocumented post-audit analysis” (Kerzner, 1987, p. 30). Although
this definition is also based on the “iron triangle” of timeliness, cost, and
specificity, new criteria such as performance, quality, and scope are
addenda to these original three. Similarly, Pinto (1989) enhanced the iron
triangle by adding customer satisfaction. He argued that because a project is
normally carried out for an internal or external customer, it is logical to
consider customer satisfaction when judging whether a project is successful.
Shenhar et al. (1997) identified four dimensions for assessing project
success: time, specification, customer requirements fulfillment, and business
performance/future opportunities. Through this definition, Shenhar et al.
extended Pinto’s (1989) widely accepted definition by adding direct
economic and strategic impacts that the project may have on the
organization.
Further, Baccarini (1999) proposed a Logical Framework Method
(FM) for defining project success. He identified four levels of project
objectives: goal, purpose, output, and input. According to Baccarini, project
success consists of two principal components. First, Baccarini argued that a
successful project is managed well by assessing inputs and outputs as well
as focusing on cost, budget, and quality. The second component of project
considers the final product. In this way, project success has predetermined
goals and purposes. With this statement, Baccarini, similar to Munns et al.,
linked the focus of project management to the achievement of cost, time,
and quality goals.
In their study on IT-projects, Agarwal and Rathold (2006) found that
project scope has been identified as the most agreed upon criterion for
determining project success. In fact, it has been described as equal in
importance to cost, time, quality, and customer when judging project
success.
Finally, Thomas and Fernández (2008) conducted an exploratory
study to investigate how 36 companies operating in three Australian
industries define and measure successful IT projects. Their findings
highlighted success criteria like sponsor satisfaction, business continuity,
project team satisfaction, and steering committee satisfaction as important
for project success.
Table 8. Summary of project success criteria
Authors Project Success Criteria
Cleland (1986)
attain technical performance objective on time and within
budget; contribution that the project made to the strategic
mission of the enterprise
Morris and
Hough (1987)
meet financial and technical requirements, meet the
budget, schedule, and specifications, commercial benefit
for contractors, in the event that the project had to be
cancelled, was this decision made reasonably and
efficiently
Kerzner (1987)
been accomplished within time, within cost or budget, at
the desired performance or quality level, within the
original scope or mutually agreed upon scope changes,
without disturbing the corporate culture or corporate
values, and with well-documented post-audit analysis
Pinto (1989)
on-schedule (time criterion), comes in-on budget
(monetary criterion), achieves basically al the goals
originally set for it (effectiveness criterion), and is accepted
and used by the client for whom the project is intended
(client satisfaction criterion)
Freeman and
Beale (1992)
Technical performance, Efficiency of the project
execution, Managerial and organizational implications,
Personal growth, Project termination, Technical
innovations, Manufacturability and business performance
Turner (1993)
achieve its stated business purpose, provides satisfactory
benefit to the owner, satisfy the needs of the owner, users
and stakeholders, meet its pre-stated objectives to produce
the facility, The facility is produced to specification, within
budget and on time and the project should satisfy the needs
of the project team and supporters
Widemann
(1995)
stated that success is closely associated with effective
communication and the quality of the resulting product
Wateridge
(1995)
meet the user requirements and functionality, on time and
to budget
Munns and long-term goals - return on investment, profitability,
competition and market
Bjeirmi (1996) ability); short-term goals - completion to budget, satisfy the
project schedule, adequate quality standards, and meeting
the project goal
Shenhar, Levy and on time and within the specified budget, impact on the
customer and/or the
Dvir (1997) user of the end result, sales, income, and profits, business
results and market share, organizational and technological
infrastructure for the future
Authors
Bounds (1998) staff training and education, dedicated resources, good
tools, strong leadership and management, concurrent
development of the individual, team, and organization
Lim and
Mohamed
(1999)
macro viewpoint (used by users and stakeholders), “does
the original concept tick” and the micro viewpoint used by
developer and contractor
Baccarini
(1999)
successful accomplishment of cost, time, and quality
objectives, effect of the project’s final product
Agarwal and
Rathold (2006)
scope, functionality, customer happiness and satisfaction,
project specific priorities
Thomas and
sponsor satisfaction, business continuity, project team
satisfaction, and
Fernández (2008) steering group satisfaction
Project Success Factors
Cooke-Davies (2002) described success factors as those which
contribute to achieving success on a project. According to Kerzner (1987),
success factors are those elements that must exist within the organization to
create an environment in which projects are consistently managed with
excellence.
Researchers and practitioners in the field of project management have
developed several lists of project success factors and frameworks. Morris
(1998), for example, suggested that the implementation of factors like
Project Success Criteria
communication, conflict, cost, schedule, stakeholders, life cycle, and
technical and risk management could increase the likelihood of a project’s
success.
Although the above three studies are most well-known for defining
project success, several other studies have also attempted to codify these
factors. Below, I review the history of such research in chronological order.
Sayles and Chandler (1971) developed a list of project success factors.
Their list included project manager’s competence, scheduling, control
systems and responsibilities, monitoring and feedback, and continued
involvement in the project.
For Martin (1976), project success depends on the definition of goals,
the selection of a proper project organizational philosophy, the organization
and delegation of authority, the selection of an effective project team, the
allocation of sufficient resources, the provision for control and a mechanism
for information dissemination, and the support of general management.
Cleland and King (1983) considered project summary, operational
concept, top management support, financial support, the successful
implementation of logistics, market intelligence (i.e., successful
identification of customers), project schedules, executive development and
training, manpower, information and communication channels, and project
review as contributory factors of successful project implementation.
In contrast, Baker et al. (1983) identified completely different project
success factors. These included goal clarity and commitment, an on-site
project manager, adequate funding for completion of the project, adequate
project team capability, accurate initial cost estimates, a minimum of start-up
difficulties, adequate techniques for planning and control, and the absence of
bureaucracy.
One year later, Locke (1984) published a list of project success factors that
seemed to be a combination of the findings of Sayles and Chandler (1971),
Cleland and King (1983), Marin (1976), and Murphy and Fischer (1983).
This included making project commitments known, project authority
derived from the top organization level, the appointment of a competent
project manager, established communications, procedures, and control
mechanisms; and regular progress meetings.
Although the above-mentioned lists indicate the variety of
perspectives related to project success, one of the widely cited and accepted
lists was produced by Pinto and Slevin (1987). This list includes project
mission, top management support, project scheduling, client consultation,
competent personnel, technical tasks, client acceptance, monitoring and
feedback, communication, and troubleshooting as factors integral for
successful project implementation.
Another extensive list of project success factors developed by Kerzner
(1987) includes corporate understanding of project management at the
employee, middle management, and top management levels; commitment by
top management to support the project through appropriate managerial
strategies; organizational adaptability that enables companies to react
quickly to the changes in the political, cultural, social, or economic
environments; a resultoriented project manager possessing strong
interpersonal skills; strong commitment to corporate values; appropriate
project manager leadership style; and commitment to planning and
continuous follow-ups of project activities.
The original CHAOS study (1994) identified 10 success factors:
executive support, user involvement, the presence of an experienced project
manager, clear business objectives, a minimized scope, standard software
infrastructure, basic firm requirements, formal methodology, reliable
estimates, and other miscellaneous criteria.
Unlike the aforementioned studies, Belassi and Tukel (1996) argued
that judging a project as a success or failure is not as simple as compiling a
list. Instead, they classified and clustered former published success factors
into four groups to investigate their impact on project outcomes. These
groups included factors related to the project, project personnel,
organization, and external environment.
In her study, Clarke (1999) investigated the changes in projects
observed in a variety of organizations. Through her analyses, she identified
four factors critical to the success of those projects: communication
throughout the project, clear objectives and scope, Breaking large projects
down into sub-projects or work packages and using project plans as working
documents.
Further, Cooke-Davies (2002) also investigated the factors that are
critical to project management success. He identified eight factors:
knowledge of risk management concepts, the assignment of ownership of
risks, a visible risk register, an up-to-date risk management plan,
documentation of organizational responsibilities on the project, a short
duration (fewer than three years), a mature control process for allowing
changes in scope, and the maintenance of the integrity of the performance
measurement baseline. Cooke-Davies (2002) also identified one criterion
that contributes to project success - effective benefits delivery and
management process - and three other criteria that lead to consistently
successful projects - portfolio and program management, clear metrics for
gauging portfolio and project management, and effective means for
experiential learning.
White and Fortune (2002) also conducted empirical research to
identify success factors. They conducted a survey to capture the “real world”
experiences of project managers in order to identify common criteria used
for defining project success and to establish a common list of critical success
factors. In this way, while previous work in this domain simply listed
potential success factors, White and Fortune (2002) sought to summarize this
literature as a means to identify common factors across extant research.
Their findings demonstrated that the classic criteria of timeliness, staying
within budget, and staying within the specification of the customer were the
most referenced criteria to judge a project’s success. However, the authors
also found that a fit between the project and the organization and the
influence of the project on business performance were often cited as
important criteria.
Similarly, Westerveld (2003) developed a Project Excellence Model
(EFQM-model) to link project success criteria with project success factors
using extant research. The model consists of six results areas covering
project success criteria, six organizational areas covering project success
factors, and five project types. Each of the areas in Westerveld’s (2003)
model is detailed below.
•Results areas: Project results (budget, schedule, and quality), appreciation
by the client, appreciation by project personnel, appreciation by users,
appreciation by contracting partners, and appreciation by stakeholders.
•Organizational areas: emphasis on leadership and team, appropriate
policy and strategy, stakeholder management, resources, contracting, and
competent project management (i.e., effective scheduling, budget,
organization, quality, information, and risks).
•Project types: product orientation, tool orientation, system orientation,
strategy orientation, and total project management.
Table 9. Summary of project success factors
Authors Project Success Factors
Sayles and
Chandler (1971)
project manager’s competence, scheduling, control
systems and responsibilities, monitoring and feedback,
continuing involvement and the project
Martin (1976)
define goals, select project organizational philosophy,
organize and delegate authority, select project team,
allocate sufficient resources, provide for control and
information mechanism, require planning and review and
get support from general management
Cleland and
King (1983)
project summary, operational concept, top management
support, financial support, logistic requirements, facility
support market intelligence, project schedule, executive
development and training, manpower and organization,
acquisition, information and communication channels
and project review
Baker, Murphy
and
Fischer (1983)
clears goals, goal commitment of project team, on-site
project manager, adequate funding to completion,
adequate project team capability, accurate initial cost
estimate, minimum start-up difficulties, planning and
control techniques, Task (vs. orientation ) and absence of
bureaucracy
Locke (1984)
make project commitments known, project authority
from the top, appoint competent project manager, set up
communications and procedures, set up control
mechanism (schedules, etc.) and progress meetings
Pinto and
Slevin (1987).
project mission, top management support, project
schedule / plan, client consultation, personnel, technical
tasks, client acceptance, monitoring and feedback,
communication and troubleshooting
Kerzner (1987)
corporate understanding of project management,
commitment by executive management, organizational
adaptability, project managers selection criteria,
leadership style of the project manager, project
committed to planning
Morris and
Hough (1987)
project objectives, technical uncertainty, politics,
community involvement , schedule duration urgency,
financial contract legal problems, Implement problems.
Clarke (1995)
Communication throughout the project, clear objectives
and scope, Breaking the project into “bite sized chunks,
using project plans as working documents
Authors Project Success Factors
Belassi and
Tukel (1996)
project size and value, uniqueness of project activities,
density of project, life cycle and urgency; ability to
delegate authority, ability to trade-off, ability to
coordinate, perception of project manager roles and
responsibilities, competence and commitment (project
manager); technical background, communication skills,
trouble shooting and commitment (project team
members); top management support, project
organizational structure, functional managers’ support
and project champion; political environment, economical
environment, social environment, technological
environment, nature, client, competitors and
subcontractors.
Morris (1998)
controlling, directing, team building, communicating,
cost and schedule management, technical and risk
management, conflict and stakeholders management and
life-cycle management, among others
Bounds (1998)
staff training and education, dedicated resources, good
tools, strong leadership and management, concurrent
development of the individual, team, and organization
Standish Group
(2000)
executive support, user involvement, experienced project
manager, clear business objectives, minimized scope,
standard software infrastructure, firm basic requirements,
formal methodology, reliable estimates, other criteria
Cooke-Davies
(2002)
education on the concepts risk management, assigning
ownership of risks, visible risk register is maintained, up-
to-date risk management plan, documentation of
organizational responsibilities on the project, keep
project (or project stage duration) as far blow 3 years as
possible (1 year is better), allow changes to scope only
through a mature scope change control process, maintain
the integrity of the performance measurement baseline,
effective benefits delivery and management process,
portfolio- and program management, project, program
and portfolio metrics, effective means of “learning from
experience”
White and
Fortune (2002)
on time, to budget and specification, fit between the
project and the organization, the consequences of the
project for the performance of the business
Westerveld (2003)
Project results (budget, schedule and quality);
appreciation by the client; appreciation by project
personnel; appreciation by users; appreciation by
contracting partners; appreciation by stakeholders;
leadership and team; policy and strategy; stakeholder
management; resources; contracting; project
management: (scheduling, budget, organization, quality,
information and risks), product orientation, tool
orientation, system orientation, strategy orientation and
total project management.
Project Management Application of the Theory of Constraints
With the advent of optimized production timetables scheduling software in
1979, the basis for Goldratt and Cox’s Theory of Constraints (TOC)
emerged. Since its inception, TOC has been developing and has been
integrated into different fields like project management and problem solving.
Watson et al. (2007) segmented the evolution of TOC into five eras:
1. 1979–1984: The Optimized Production Technology Era - the secret
algorithm
2. 1984–1990: The Goal Era - articulating drum-buffer-rope scheduling
3. 1990–1994: The Haystack Syndrome Era - articulating the TOC
measures
4. 1994–1997: The It’s Not Luck Era - thinking process applied to various
topic
5. 1997–2004: The Critical Chain Era - TOC project management
The Five Focusing Steps
According to Goldratt (1990), the Theory of Constraints is based on
five steps:
1. Identify the system’s constraints: In this step, an individual should
determine the constraints that have a negative impact on system
performance. In discussing project schedules, the primary constraint is
the completion of the longest chain of dependent project activities that
would fulfill both precedence and resource constraints. This also refers to
bottlenecking resources that are assigned to different projects or project
activities.
2. Decide how to exploit the system’s constraint: With respect to time
management, this step implies that the primary objective should be to
increase the efficiency of project execution on the whole as a means to
ensure that the activities in the critical chain are well performed and
without delay.
Figure 5. The Five Focusing Steps and Application of the Critical
Chain
3. Subordinate: This step refers to the avoidance of allowing non-critical
project activities to negatively influence critical activities for the project.
Non-critical resources should be made available when they are needed.
4. Elevate the system’s constraints: If the intended performance is not fully
achieved after executing the steps outlined above, additional resource
must be allocated.
5. Go back to step1: If intended performance is achieved, return to step 1 to
improve the process further.
Resource Constrained Project Scheduling
Resource scheduling includes the assignment of resources to project
activities or project activities to resources. This process supports schedulers
making decisions about the workload and available resources. There are two
different aspects to be considered in the scheduling process. The constraint
could be time or resources or both.
Time-constrained project: The project must be accomplished in a fixed time
line, using reasonable and justifiable level of resources. In this case the time
is critical and not the resources. “Time-constrained resource scheduling
assumes that time constraints are fixed, and seeks to resolve capacity
overloads by manipulating the timing of activities within their total float, and
without affecting the initial project completion time.” (Abeyasinghe et al.,
2001).
Resource-constrained project: The project must be accomplished in a
reasonable and justifiable time line, using predefined and fixed level of
resources. In this case the resources are critical and not the time. “Resource-
constrained scheduling accepts the priority of fixed resource availability,
and permits not only sequencing and float times to be altered, but (if
necessary) the project duration to be increased beyond the initial non-
constrained project duration.” (Abeyasinghe et al., 2001).
Critical Path Method (CPM) and Project Evaluation and Review Technique
(PERT) are doubtless the most popular scheduling procedures used since
1959. CPM scheduling helps project managers and project schedulers to
ensure the project completion in time and on budget. However these
Techniques are activities-time-based and do not consider the resources
required to execute those project activities. In others words these scheduling
methods are not appropriate for addressing issues related of resources
utilization and availability. Thus, they consider the existence of infinite
resources and therefore the possibility of adding resources to activities to
reduce their duration. Yet in real project environment, resources are limited.
For this reason, scheduling projects without considering resources
requirements is out of touch with project reality. The shortcoming of these
two techniques has been discussed in several previous studies (e.g. Wiest
1967, Cooper 1976). Researchers have recognized this limitation and
therefore they are spending lot of efforts in developing others methods and
approaches to solve the project scheduling under consideration of resources
constraints. The most known two approaches are (a) optimization by
mathematical programming techniques, and (b) heuristic techniques.
Mathematical optimization methods define the resource-constrained project
scheduling problem as a mathematical programming problem (linear
programming, enumeration, tree search, and branch and bound) to identify
the best solution. Yet, this approach is not applicable for large-scale projects.
Heuristic methods are the most used and applicable methods for solving the
resource-constrained project scheduling problems. Based on the PERT/CPM
schedule analysis heuristics examine the project activities in periods in
which the resource level is exceeded and allocated the scarce resource to
them according the following rules among others:
•Earliest start prioritization: As soon as possible
•Latest start prioritization: As late as possible
•Earliest finish prioritization: Finish as soon as possible
•Latest finish prioritization: Finish as late as possible
•Activity duration: Shortest task first
•Activity duration: Longest task first
•Greatest resource utilization: Most resources first
•Job slack: Minimum slack first
•Most critical followers
•Most successors
Critical chain project management (CCPM) distinguishes between
critical and non-critical resources assigned to projects. Therefore, CCPM
focuses on the effective and efficient management of critical resources
during the planning of projects. Watson and his associates (2007) stated that
there are three main differences between CPM, PERT, and CCPM in terms
of assigning task
durations, the utilization of buffers, and the avoidance of resource conflict.
For the manufacturing sector, task duration estimates depend on
several factors. The availability of materials, workers, and tools, for
example, can drastically alter how long the task will take. The insertion of a
margin for error into the estimate seems to be a general practice; estimates
typically reflect a 90%– 95% confidence rate at which the task will be
executed within the suggested time frames (Watson et al., 2007). As such, a
safety time is built into each project activity (Figure 5). In reference to the
CPM or PERT approach, Jyh-Bin stated that “[o]ne of the pitfalls is the
unrealistic activity duration that combines proper duration and redundant
safety time. With inflated duration, a project manager cannot control the
schedule because project participants are reserving their safety time” (Jyh-
Bin, 2007, p. 25). Unfortunately, this redundancy has yet to be resolved. In
fact, since the introduction of the critical path method, no significant
improvements have been made to it (Shou & Yeo, 2000). Shou and Yeo
(2000) further argued that existing problems like late project completion,
cost overruns, and the need to cut specification are the principal reasons for
the development of the critical chain project management approach.
The critical chain approach is more geared towards changing the
behavior of project members so that realistic estimates of activity durations
are made. To ensure meeting the project completion date, the critical chain
method typically uses an activity duration estimate with 50% confidence
with margins for error placed at the end of the project (Figure 5).
Figure 6. Comparison between Critical Chain and PERT/CPM
The critical chain project management approach is designed to reduce
project duration time by accounting for constraints on resources. It considers
not only the overall project but also the component projects that are likewise
constrained by time, cost, and scope. This CCPM approach, thus, uses three
different buffers. First, CCPM incorporates a project buffer to ensure the
project’s completion date. Second, it incorporates a feeding buffer to protect
the critical chain against negative influences of other activities or non-critical
chains. Finally, it uses a resource buffer to protect the project’s completion
time in the event of resource conflicts (see Figure 5).
In his book, Critical Chain, Goldratt (1997) argued for the application of the
Theory of Constraints to project management. He stated that the root cause
of failure to meet project completion dates is the inefficient utilization of the
margin time built into the activities’ duration estimates. He further argued
that the estimates used in CPM and PERT to cover uncertainties in projects
are overdrawn. Both PERT and CPM have been criticized by several authors
because of the integration of safety times into each project activity,
regardless of whether the activities are on the critical path or not. In contrast,
critical chain project management allows for the aggregation of safety times
at the end of the project, resulting in not only on-time completion of the
project but also a reduction in the time it takes to complete.
Another pitfall associated with CPM or PERT is referred to as
“Student Syndrome” (Goldratt, 1997). With CPM or PERT, the knowledge
that safety times are built into each project activity provides incentive for the
worker to avoid starting his/her assigned activities on time. With critical
chain project management, however, project personnel and the customer
agree and commit to only the project completion date. Due dates of single
activities (and in some cases, milestones) are removed. Another issue that
has been addressed by CCPM is the reduction of the work in process (WIP).
In the field of project management, WIP reduction involves scheduling the
execution of some activities in a project as late as possible.
By adopting a CCPM approach, a project manager or scheduler can
identify activities that require more attention and avoid delays in project
completion. Therefore, the project manager should keep a track of the
project as a complete system and not as a series of singular activities. This
makes the completion date the most important date related to the project.
Milestone achievements should be considered only if mandated by the
customer.
Given the clear benefits of CCPM, Newbold (1998) offered several
steps for its successful implementation. These steps include first setting clear
project objectives, including the development of a project plan. This also
includes deducing the project completion date from the master plan provided
by the customer and disseminating it to project personnel. Second, a project
manager should determine the customer requirements and define the
activities designed to meet them. These activities should then be delegated.
Third, it is imperative to identify the logical relationship between activities
and requirements, such as start-to-start, start-to-finish, finish-to-start, and
finish-to-finish activities. This will facilitate the reduction or elimination of
simultaneous activities. Fourth, a project manager should estimate the
resources that are required, the duration of the activities to be performed, and
the costs based on his/her experience on previous projects. Fifth, one should
calculate the critical chain schedule, accounting for time buffers. Sixth, the
project manager should evaluate the schedule according to the project
objectives set in step one. Finally, if the schedule meets the internal and
external requirements, the process is complete. If not, the manager must
revisit this process to improve project performance.
The TOC Thinking Processes
The second TOC approach that will be discussed in this chapter is
entitled “TOC: Thinking Process.” It includes logical guidelines on how to
manage changes in a firm’s operational environment. The main points to be
addressed
include what to change, what to change into, and how to bring about this
change.
The TOC thinking process is based on two logical levels (see Figure
7): 1) sufficient cause or effect-cause-effect logic, which includes the current
reality tree (CRT), future reality tree (FRT), and transition tree (TT); and 2)
necessary condition logic, which is used by the evaporating cloud (EC) and
prerequisite tree (PRT) to identify all obstacles that prevent the system from
achieving the objectives (Scheinkopf, 1999).
According to Dettmer (1997), the Current Reality Tree CRT logically
represents the current state of a given system, organization, or process as a
means to:
•clarify thought and allow for the understanding of complex systems;
•identify non-conformities, which are called undesirable effects (UDEs);
•execute a root cause effect analysis and identify the major factors that
cause UDEs;
•identify which factors are controllable and which are not;
•separate uncontrollable factors and address them to improve the system;
and identify quick changes that have a significant impact on the system
as a whole.
Figure 7. The TOC thinking process application tools (Watson et
al.,
2007)
The evaporating cloud EC addresses the second question (i.e., what to
change to) and can be used to reduce or eliminate of the impact of UDEs.
According to
Dettmer (1997), the evaporating cloud EC intends to:
•confirm the existing non-conformities;
•identify the non-conformity or conflict that causes a major problem;
•eliminate this non-conformity or conflict without compromise;
•define solutions, including a “win-win” approach; and
•define new solutions to problems and explain their existence and the
related conflicting relationship.
The Future Reality Tree FRT represents the next step of the TOC
thinking process and focuses on the effectiveness of solutions to be
implemented.
According to Dettmer (1997), the FRT is designed to:
•justify the effectiveness of the new solution before its implementation;
•identify any negative side-effects that could be produced after its
implementation;
•investigate any additional problems or side effects caused by the
implementation of the new change and define new preventive actions
accordingly;
•support the decision making process; and facilitate initial planning.
The fourth step in the thinking process is the prerequisite tree (PRT).
It deals with the process of implementing solutions that are developed in the
previous steps. Dettmer (1997) explained that the PRT is used to:
•identify any hindrances that could have a negative effect on the
achievement of the objectives;
•investigate how to overcome these hindrances or minimize their impact;
•structure the actions to be implemented for the achievement of the
objectives; and
•support localization of actions even if the steps to achieve an objective
are
unknown.
The Transition Tree TT has nine basic purposes (Dettmer, 1997).
These purposes are to:
•serve as a detailed structure method for the implementation process;
•ease orientation through the change process;
•identify deviation during the implementation process;
•integrate modifications if necessary;
•communicate the purpose of each action;
•realize the ideas generated in the EC or FRT;
•achieve the subordinate targets defined in the PRT;
•develop tactical action plans; and
•ensure that no undesirable effects occur.
III. RESEARCH METHODOLOGY AND DESIGN
Introduction
According to Clifford Woody, research involves defining and
redefining problems, formulating hypothesis or suggested solutions,
collecting, organizing and evaluating data, making deductions and reaching
conclusions, and finally, carefully testing those conclusions to determine
how they relate to the formulated hypotheses. Given this, a well-designed
research methodology is a powerful, multi-phase tool for exploring research
questions. To conduct a strenuous, empirical investigation of the issues
described in the previous chapters, I considered several options for
conducting my research.
Given the utility of primary data for examining the hypotheses
described above, this study includes a web survey in addition to archival
research. To be familiar with effective methods for developing and
conducting a survey, the researcher took part in several webinars on the
topic. For the statistical data evaluation methods (described below), the
researcher participated in several statistics courses at the University of
Louisville and underwent training in the use of SPSS software (Statistical
Package for the Social Sciences).
Objectives of the Study
To achieve the project objectives, predetermined long and short-term
purposes, and the business sustainability of an organization the utilization of
project management is indispensable. Several studies have concluded that
project management contributes only to the achievement of short-term
project objectives like cost, schedule, and quality. These three criteria
represent just a small part of the goals that companies intend to achieve
though the execution of their projects. In addition to cost, time, and quality
management, this project incorporates another six knowledge areas that were
described in Chapter One. Therefore, the main objectives of this study were
to (a) identify the role of project management body of knowledge in
achieving long-term project success; (b) identify factors of the project
management body of knowledge that contribute to long-term project success;
(c) identify the link between project success factors and long-term project
success criteria, and (d) develop a framework that could prevent project
failure through preventative FOC (Future-Oriented Criteria), measure
possible project failure through POC (Past-Oriented Criteria), and correct the
failure using problem solving tools like TOC (Theory of Constraints).
Research Hypotheses
The guiding research question for the proposed study was: What is the
relationship between long-term success and the project management body of
knowledge represented in nine knowledge areas: integration management,
scope management, time management, cost management, quality
management, communication management, risk management, human
resources management, and procurement management? The following
hypotheses have been used to test the research question:
H1: There is no significant relationship between long-term project success
and project integration management.
H2: There is no significant relationship between long-term project success
and project scope management.
H3: There is no significant relationship between long-term project success
and project time management.
H4: There is no significant relationship between long-term project success
and project cost management.
H5: There is no significant relationship between long-term project success
and project quality management.
H6: There is no significant relationship between long-term project success
and project human resources management.
H7: There is no relationship between long-term project success and project
communication management.
H8: There is no significant relationship between long-term project success
and project risk management.
H9: There is no significant relationship between long-term project success
and project procurement management.
Research Design
A research design refers to the controlled organization of conditions
for data collection and analysis in a way that aims to combine relevance to
the research purpose with economy in procedure (Selltiz et al., 1962). This
study is a quantitative descriptive inquiry designed to explore whether a
relationship exists between long-term project success and the project
management body of knowledge. According to Kothari (2004), descriptive
research can include surveys as well as other forms of empirical inquiry.
Ultimately, the goal of such research is to describe a situation as it currently
exists. He further argued that the researcher has little control over the
variables in this method; he is only able to report what has happened.
Descriptive research, then, includes comparative and correlational methods.”
In the following section, the research design for this study is
summarized. First the sampling methods and the observation conditions are
discussed, following that; the statistical methods and tools used for the data
analysis are described.
Sampling Design
The study population consists of members of the German Chapter of
the Project Management Institute, a finite sampling pool. Each member
represents a sampling unit. random sampling technique have been used to
select those members of the German Chapter of the PMI that (a) have PMI
certification, or (b) are involved with projects, (c) have a particular function
(project manager, project team member, project coordinator, steering
committee member, etc.), and (d) belong to a particular industry
(information technology, construction, engineering, etc.)
This way a sample of people involved in projects in different business
areas and different industry sectors has been selected. The data about factors
of the project management knowledge areas and the related project
management process groups that contribute to project success were gathered
from project managers, team members, and people that were or are involved
in project work.
Random Sampling Method
PMI is the world’s leading not-for-profit membership association for the
project management profession, with 450,713 PMI-members and 239,965
chapter members and credential holders in more than 185 countries. Four
main chapters, Munich, Frankfurt, Berlin /Brandenburg and Cologne,
represent the PMI in Germany that includes 6,524 PMI-members in which
2,931 are chapter members (PMI, 2013). The survey could not be posted
directly on the PMI.org site because of changed policies. Therefore, the
researcher contacted members via Xing / PMI-Forum.
Random sampling has been used to select the participants because
doing so eliminates bias, thereby allowing sampling error to be estimated
(Kothari, 2004). Further, this method ensures that each member of the
German Chapters of the PMI has an equal chance of being used in the
sample. The link to the survey was sent to 1,047 PMI-members via the Xing-
Forum/PMI, who are involved in project management and/or earned a
project management
certification
Data Collection Method
Generally speaking, two types of data can be collected to answer
research questions: primary data and secondary data. According to Kothari
(2004), primary data is original information collected for the first time.
Secondary data, in contrast, is information that has been previously
statistically analyzed. In this study, secondary data have been obtained
through a review of journals, books, magazines, dissertations, and other
sources. These data were discussed in Chapter Two.
Although secondary data can be used to explore a number of research
questions, Kothari (2004) and others have proposed questionnaires,
interviews, and direct observation as integral means for collecting data.
Therefore, in addition to the secondary data used for this study, primary data
were collected via questionnaires placed on Qualtrics.com. Qualtrics is a
web based researchsurveying software. It enables users to do any kind of
online data collection and analysis including market research, customer
satisfaction and loyalty, product and concept testing, employee evaluations
and website feedback. The Qualtrics Research Suite is a top choice of
academics. Therefore, quantitative statistical analysis performed with
Qualtrics is cited in a number of professional and academic journals and
books. Qualtrics.com complies with the United States
(U.S.) and European Union (E.U.) Safe Harbor Framework and the U.S. and
Swiss Safe Harbor Framework, set forth by the U.S. Department of
Commerce. This ensures the protection of any primary source data collected
for this study.
The questionnaire (Appendix A) included statements and questions on
the following topics. For all project-related demographic questions the
researcher assumes that the repondents are referring to their last project:
•Gender and age of the respondent
•Work and project management experience and the last project completed
•Average budget size of the respondent’s projects
•Project functions
•Project types and industries
•Project durations and customer types (i.e., internal or external)
•Size of the project teams
•Types of project management certification
•Types of project management software used
•Respondent’s opinion regarding criteria for project success measurement
•The frequency of specified project-related symptoms at the respondent’s
organization
•Respondent’s opinion regarding the contribution of the PM-initiating
process outputs to project success
•Respondent’s opinion of agreement regarding the contribution of the
planning-processes outputs to project success
•Respondent’s opinion regarding the contribution of the executing-
processes outputs to project success
•Respondent’s opinion regarding the contribution of the monitoring- and
controlling-processes outputs to project success
Statistical Design
IBM SPSS Statistics Package was used for data analysis. The
Qualtric.com program allows data exportation to SPSS, so transfer of data
from the data collection tool to the data analysis tool was a relatively easy
endeavor. The collected data have been edited, coded, classified, and
tabulated prior to quantitative analysis (Table 10). The data analysis itself
includes descriptive analysis. The hypotheses have been tested to indicate
whether a relationship exists between the long-term project success (i.e.,
project success criteria: dependent project outcomes) and the project
management body of knowledge
(i.e., project success factors: independent factors) using chi-square tests and
Fisher's exact tests. This study seeks to reject those hypotheses at the (p
< .05) level. The chi-square metric has been chosen to test the hypotheses
based on the fact that (a) the non-parametric test is based on frequencies and
not on parameters like mean and standard deviation that are unavailable, (b)
there is no need for assumptions regarding the type of the population and
parametric values, and (c) non-parametric tests are appropriate for
application to ordinal or nominal scales. In cases where the chi-square
assumptions were not met, thus more than 20% of the cells have expected
count less than five, Fisher's exact test has been used for the independence
investigation.
The basic computation of Chi-Square is as follows:
where observedij is the observed frequency of the cell in the ith row and jth
column and expectedij is the expected frequency of the cell in the ith row and
jth column.
The tables used in the test within the chi-square tests are contingency table
or a three by two tables because its relate two categories of data. The rows
include respondent’s opinion regarding the contribution of the PM -
processes outputs to project success (1: strongly agree, 2:agree, 3:neither
agree nor disagree, 4: disagree, 5: strongly disagree). The columns include
their opinion regarding criteria for project success measurement (1: selected,
0: not selected). Each box in the tables is referred to as a cell. Each cell
contains the frequency of the category.
In order to increase the number of cells with expected count more than five,
the categories 1 and 2 have been group to a new category “1: strongly agree/
agree” and 4 and 5 to “3: disagree/ strongly disagree”. Category 3: neither
agree nor disagree becomes category 2
Limitations of the hypothesis testing:
•Hypothesis testing is useful aids for decision-making, but result should
not be used as decision.
•Hypothesis testing do not provide the reasons why does a relation or
association exist between the variables or attributes in consideration.
•The sample size must be large enough in order to increase the reliability
of the drawn statistical inferences based on the independence tests.
•The results of independence tests are based on probabilities and include
uncertainties. When the chi-square or Fisher’s exact test shows that a
relationship is statistically significant, then it simply suggest that, the
relationship is probably not due to the chance.
•Doubtless chi-square test of independence is useful for testing a
relationship or association between the attributes of interest, but it su ers
from several limitations. The test is not a measure of the degree or the
form of relationship between the attributes considered, it indicates only
the significance of the relationship or association between those
attributes.
Table 10. Overview of the statistics
Measurement
Questions level Statistics
Q1. Gender Nominal Frequencies
Q2. Age Scale Frequencies
Q3. Total years' work
experience
Scale Frequencies
Q4. Project work Nominal Frequencies
Q5. Last project completion Scale Frequencies
Q6. Average size of project
budgets
Scale Frequencies
Q7. Function on the project Nominal Frequencies
Q8. Project type Nominal Frequencies
Q9. Project purpose Nominal Frequencies
Q10. Size of project teams Scale Frequencies
Q11. Average duration of
projects
Scale Frequencies
Q12. Business area Nominal Frequencies
Q13. PM experience Scale Frequencies
Q14. PM Certification Nominal Frequencies
Q15. PM-Certification type Nominal Frequencies
Q16. Project Management
software
Nominal Frequencies
Q17. Source of the PM-software Nominal Frequencies
Q18. Project success criteria Nominal Chi-square test of
goodness-of-fit
/ Frequencies
Q19. Symptoms at the
organization
Ordinal Exploratory factor analysis
Q20. PM Initiating Processes Ordinal Chi-square test and
Fisher's exact test of
independence /
Frequencies
Q21. PM Planning Processes Ordinal Chi-square test and
Fisher's exact test of
independence /
Frequencies
Q22. PM Executing Processes Ordinal Chi-square test and
Fisher's exact test of
independence /
Frequencies
Q23. PM M&C Processes Ordinal Chi-square test and
Fisher's exact test of
independence /
Frequencies
Framework Development
A number of papers dealing with the application of the theory of
constraints to project management have been published. These papers
focused only on the critical chain and thus time management as knowledge
area in the project management field. None of these papers addressed the
application of the theory of constraints to the other knowledge areas like
communication management, cost management, quality management,
procurement management and so one.
The following model has been used for the framework development (see
Figure 8).
What to change?
•Identify the core conflict which is responsible for the undesired project
outcomes.
•Identify the core conflict causing the symptoms, or undesired project
outcomes.
•The relationship between the project success factors (elements of the
project management knowledge area and the related project
management process groups) and the project success criteria (project
outcomes) will be investigated empirically.
•Localize the project management knowledge areas.
•Localize the project management process group (initiation, planning,
executing, monitoring and controlling or closing).
•And finally identify the element(s) of the process (factors) causing the
undesired project results.
•Build a current reality tree that confirms the existence of the core
conflict. This will help to understand the existing cause-and-effect-
relationship (Figure 8).
What to change to?
•Identify and break the assumptions that allow the Core Conflict to
persist.
•Construct a Future Reality Tree that lays out the complete solution.
•Resolves all of the undesired project outcomes by making their
opposites, the desired project outcomes.
•Ensures alignment with the project and organization objectives.
•Ensures that no new negative side-effects (Negative Branches) will
occur from implementing the solution.
•Leverages the existing TOC applications that are needed to make the
solution work.
How to cause the change?
•Build a Tactical Objectives Map that charts the overall course for
getting from the current reality to the future reality, where the solution
is fully implemented.
•Create detailed task interdependency diagram, using Transition Trees
(TRTs) when necessary to flesh out crucial actions.
•Transform action plans into a complete project network that can be
effectively managed using project management techniques like Critical
Chain project management.
Figure 8. Framework development
IV. ANALYSIS AND RESULTS
Introduction
The focus of this chapter is analyzing the collected data to determine
whether a relationship exists between long-term project success and the
project management body of knowledge represented in the nine knowledge
areas of integration management, scope management, time management,
cost management, quality management, communication management, risk
management, human resources management, and procurement management.
This study aims to add to the body of knowledge concerning project
management, specifically project success factors and criteria. The study used
a quantitative descriptive approach, and SPSS (Statistical Package for the
Social Sciences) was used to analyze the survey data.
The survey consisted of a random sample of 163 PMI-members with
knowledge of and experience in project management. Random sampling
ensured that each PMI-member had an equal probability of being selected.
All responses to the survey were kept anonymous to protect the respondents’
confidentiality, and, per the University Of Louisville’s Institutional Review
Board (IRB) rules for research ethics compliance, no identifiable information
was collected from the survey instrument, and all data were analyzed in
aggregate with no individual survey respondent identified. The survey
instrument posed questions on the following topics:
•Gender and age of the respondent
•Work and project management experience and the last project completed
•Average budget size of the respondent’s projects
•Project functions
•Project types and industries
•Project durations and customer types (i.e., internal or external)
•Size of the project teams
•Types of project management certification
•Types of project management software used
•Respondent’s opinion regarding criteria for project success measurement
•The frequency of specified project-related symptoms at the respondent’s
organization
•Respondent’s opinion regarding the contribution of the PM-initiating
process outputs to project success
•Respondent’s opinion regarding the contribution of the planning-
processes outputs to project success
•Respondent’s opinion regarding the contribution of the executing-
processes outputs to project success
•Respondent’s level of agreement regarding the contribution of the
monitoring-
and controlling-processes outputs to project success
The link to the survey was sent on October 8, 2013, to 1,047 PMI-members
via the Xing-Forum/PMI. The survey concluded on January 31, 2014, by
which time 199 people had responded, a response rate of 19%. One hundred
and nighty nine (199) participants accessed the survey; one hundred and
sixty three (163) participants completed the survey. Thirty-six (36) of the
respondents who accessed the survey were excluded because their responses
were incomplete.
Therefore, 163 completed surveys were included in the study.
Statistics
Question 1: Gender of the respondents
Of the 163 respondents, 145 (89.0%) were male and 18 (11.0%) female (see
Figure 9).
Figure 9. Gender of the respondents
Question 2: Age of the respondents
Respondents were asked to provide their age. The responses were slotted
into four age groups. As shown in Figure 10, nine (5.5%) respondents were
20 to 30 years old, 60 (36.8%) were 31 to 40 years old, 75 (46.0%) were 41
to 50 years old, and 19 (11.7%) were 50 or older.
145 (89.0%)
(11.0% )18
0 20 40 60 80 100 120 140 160
Male
Female
Frequency
Gender
Figure 10. Age of the respondents
Question 3: Work experience
As shown in Figure 11, the largest contingent of respondents (84; 51.5%)
had worked for between 11 and 20 years, followed by the 41 (25.2%) who
had worked for more than 20 years. Respondents with five or fewer years’
work experience represented less than 5.0% of the total.
Figure 11. Work experience
Question 4: Project work
As demonstrated in Figure 12 all respondents (163; 100%) confirmed their
involvement in project work.
9 (5.5% )
) (36.8%60
) (46.0%75
19 (11.7% )
0 20 40 60 80
20 - 30 years
- 40 years31
- 50 years41
Older than 50 years
Frequency
Age
) (.6%1
7 (4.3% )
(18.4%30 )
(51.5% )84
(25.2%41 )
0 20 40 60 80 100
Less than 2 years
2 - 5 years
- 10 years6
11 - 20 years
More than 20 years
Frequency
Work experience
Figure 12. Project work
Question 5: Last project completion
The respondents were asked to provide the time when the last project was
completed. As shown in Figure 13, the majority of the respondents 161
(98.8%) reported that their last project was finished five years ago or less.
Figure 13. Last project completion
Question 6: Size of project budgets
Respondents were asked to provide the budgets of the projects they have
worked with. As can be seen in Figure 14, the largest group 67 (41.1%)
reported project budgets of more than $1 million and less than $10 million,
followed closely by the 66 (40.5%) with more than $100,000 and less than
$1 million. Only 12.3% of projects had budgets of more than $10 million
163 (100.0%)
)0 (0.0%
0 20 40 60 80 100 120 140 160 180
Yes
no
Frequency
Project work
161 (98.8%)
) (1.2%2
0 20 40 60 80 100 120 140 160 180
Five years ago or less
More than five years ago
Frequency
Last project
completion
and less than $50 million, 4.3% had budgets of less than $100,000, and 1.8%
had budgets of more than $50 million.
Figure 14. Size of project budgets
Question 7: Function on the project
As shown in Figure 15, most respondents (85.3 %) were project managers,
followed by the 4.9 % who were project coordinators, and the 4.3% who
were team members. Seven responses (4.3%) were reported as “Other,”
including the program manager, project executive, and consultant. Of the
total, one was a steering committee member, and another was an advisor.
7 (4. 3% )
) (40.5%66
) (41.1%67
20 (12.3% )
(1.8%3 )
0 20 40 60 80
Less than $100,000
More than $100,000 - Less than $1 million
More than $1 million - Less than $10 million
More than $10 million - Less than $50 million
More than $50 million
Frequency
Size of project budgets
Figure 15. Function on the project
Question 8: Project type
Most respondents worked in information technology 112 (68.7%) and
engineering (14.1%; see Figure 16). The “Other” category, representing
8.6%, included consulting/implementation, education, product development
in telecommunication, consulting, product marketing management, business
application, outsourcing, public infrastructure, publicity agency projects,
capital market IT, and logistics.
139 (85.3%)
(4.9%8 )
7 (4.3% )
1 (0.6% )
(0.6% )1
7 (4.3% )
0 20 40 60 80 100 120 140
Project manager
Project coordinator
Project team member
Steering committee member
Advisor
Other
Frequency
Function on the project
23 (14.1% )
) (1.8%3
112 (68.7%)
) (4.9%8
3 (1.8% )
(8.6%14 )
0 20 40 60 80 100 120
Engineering
Construction
Information technology
Enterprise resource planning
Infrastructure design and development
Other
Frequency
Project type
Figure 16. Project type
Question 9: Project purpose
The participants were asked to provide the client type for their projects.
Approximately one half (49.7%) of the respondents reported working for
external clients, 25.8% worked for internal clients, and 24.5% worked for a
combination of both (see Figure 17).
Figure 17. Project purpose
Question 10: Size of project teams
The respondents were asked to provide the average size of their project
teams. As can be seen in Figure 18, the largest group (52, or 31.9%) reported
a project team size of 21 to 50, followed closely by those (46, or 28.2%)
with 11 to 20 members; 38 respondents (23.3%) had 5 to 10 project team
members. Projects with more than 51 team members represented 12.3% of
the total, and those with less than 5 members, 4.3%.
42 (25.8% )
)81 (49.7%
40 (24.5% )
0 20 40 60 80 100
Internal client
External client
Both
Frequency
Project purpose
Figure 18. Size of project teams
Question 11: Project duration
The respondents were asked to provide the average duration of the last
project. As Figure 19 shows, the largest group (63, or 38.7%) reported a
project duration of 13 to 24 months, followed closely by those (60, 36.8%)
reporting a duration of 7 to 12 months. Durations of fewer than six months
and between 25 and 36 months both represented 9.8% of the total, and
durations more than 36 months represented 4.9%.
) (4.3%7
38 (23.3% )
46 (28.2% )
52 (31.9% )
12 (7.4% )
8 ) (4.9%
0 10 20 30 40 50 60
Fewer than 5
- 105
- 11 20
21 - 50
- 10051
More than 100
Frequency
Size of project teams
Figure 19. Project duration
Question 12: Industry area
Computers and information technology is the most common industry sector
in this sample, as shown in Figure 20, followed by telecommunications,
software development, engineering, and manufacturing.
Figure 20. Industry area
) (9.8%16
(36.8% )60
)63 (38.7%
16 (9.8% )
) (1.8%3
5 ) (3.1%
0 20 40 60 80
1 - 6 months
7 - 12 months
13 - 24 months
25 - 36 months
37 - 48 months
More than 48 months
Frequency
Project duration
a. Dichotomy group t abulated at value 1.
107 (24.5%)
) (3.2%14
) (12.2%53
6 (1.4% )
24 (5.5% )
22 (5.0% )
42 (9.6% )
) (15.4%67
(15.6%68 )
33 (7.6% )
0 20 40 60 80 100 120
Computers / Information technology
Construction
Engineering
Education
Government
Health care
Manufacturing
Software development
Telecommunications
Other
Frequency
Industry area a
Question 13: Project management experience
The respondents were asked to provide their level of experience in project
management (in years). Figure 21 shows that the largest group (62, or
38.0%) reported a project management experience of 6 to 10 years, followed
closely by those (59, or 36.2%) with 11 to 20 years. Respondents with fewer
than five years’ experience represented 19.6% of the total, and those with
more than 20 years, 6.1%.
Figure 21. Project management experience
Question 14: Project management certification
As shown in Figure 22, 86.5% of the respondents had earned a project
management certification, and 13.5% had not.
Figure 22. Project management certification
) (1.8%3
)29 (17.8%
(38.0%62 )
(36.2% )59
10 ) (6.1%
0 20 40 60 80
Less than 2 years
2 - 5 years
6 - 10 years
- 20 years11
More than 20 years
Frequency
Project management
experience
141 (86.5%)
(13.5% )22
0 20 40 60 80 100 120 140 160
Yes
No
Frequency
PM
certification
Question 15: PM certification type
Figure 23 shows that most (137, or 76.1%) reported having earned Project
Management Professional (PMP) certification. The “Other” category
included certifications such as PRINCE2 Practitioner, Certified Scrum
Master, PSM I, PRINCE2 Foundation, IPMA Level C, PMA–Germany,
PRINCE1 Foundation
Level, GPM Level D, MSP program management, Prince2, Management of
Successful Programs (MSP), IPMA D+C+B, PRINCE2, CSM, and P3O.
Figure 23. PM certification type
Question 16: PM software used
Most respondents (146, or 63.5%) used Microsoft Project as their PM
software
(Figure 24). The “Other” category includes software such as ePM, JIRA,
con10, Projektron, Actano RPlan, Primavera, CanDo, Excel, Visio, Merlin,
OmniPlan, and OpenProj.
a. Dichotomy group tabulated at value 1.
) (0.6%1
137 (76.1%)
(1.1%2 )
6 (3.3% )
2 ) (1.1%
32 (17.8% )
0 20 40 60 80 100 120 140
Certified Associate in Project Management (CAPM)
Project Management Professional (PMP)
Program Management Professional (PgMP)
PMI Agile Certified Practitioner (PMI - ACP) SM
PMI Risk Management Professional (PMI - RMP)
Other
Frequency
PM certification type a
Figure 24. PM software used
Question 17: Source of the PM software used
As shown in Figure 25, 56.4% of respondents used commercial software,
and 7.4% used their company’s own software. Using a combination of both
was reported by 34.4%. The “Other” category includes self-made and self-
developed software.
Figure 25. Source of the PM software
Question 18: Project success criteria
A chi-square test of goodness-of-fit was performed to determine whether the
project success criteria for judging projects were equally used. Usage of
project success criteria was not equally distributed in the sample (see Figure
26 and
a. Dichotomy group tabulated at value 1.
)3 (1.3%
146 (63.5%)
4 (1.7)
7 (3.0% )
(0.9%2
(0.9% )2
66 (28.7% )
0 20 04 60 80 100 120 140 160
Basecamp
Microsoft Project
Smartsheet
Projectplace
PLANTA Project
2-plan
Other
Frequency
PM software used
)92 (56.4%
12 (7.4% )
)56 (34.4%
3 (1.8% )
0 20 40 60 80 100
Commercial Software
Company's own Software
Combination of both
Other
Frequency
Source fo the PM
software
Table 11).
Figure 26. Project success criteria: Observed frequencies
Table 11. Project success criteria: Chi square test of goodness-of-fit
0 1 Total Chi-square test
Budget / Cost
Schedule
Count
Expected
Count
33
81.5
44
130
81.5
119
163
163.0
2 (1, N = 163) =
57.724, p < .05
2 (1, N = 163) =
130
119
95
25
61
17
20
49
37
33
3
15
52
1
34
34
9
2
0 20 40 60 80 100 120 140
Budget/Cost
Schedule
Customer satisfaction
User satisfaction
Stakeholder satisfaction
Project team satisfaction
Strategic contribution of the project
Financial objectives
Technical objectives
Performance objectives
Commercial benefit for contractors
Commercial benefit for customer
Scope
Personal growth
Customer approval
Profitability
Sales
Other
Frequency
Project success criteria
Customer
satisfaction
Count
Expected
Count
Count
81.5
68
81.5
95
163
163.0
163
34.509, p < .05
2 (1, N = 163) =
4.472, p < .05
Expected
Count
81.5 81.5 163.0
Use satisfaction
Count 138 125
(1, N = 163) = 78.337,
p < .05
Expected
Count
81.5 81.5
Stakeholder
satisfaction
Count 102 61 163
2 (1, N = 163) =
10.313, p < .05
Expected
Count
81.5 81.5 163.0
Project team
satisfaction
Count
Expected
Count
146
81.5
17
81.5 163
163.0
2 (1, N = 163) =
102.092, p < .05
Strategic
contribution of
the project
Count
Expected
Count
143
81.5
20
81.5 (1, N = 163) = 92.816,
p < .05
Financial
objectives
Count 119 49 163
2 (1, N = 163) =
25.920, p < .05
Expected
Count
81.5 81.5 163.0
Technical
objectives
Count 126 37 163
2 (1, N = 163) =
48.595, p < .05
Expected
Count
81.5 81.5 163.0
Performance
objectives
Count 130 33
(1, N = 163) = 57.724,
p < .05
Expected
Count
81.5 81.5
Commercial
benefit for
contractors
Count
Expected
Count
160
81.5
3
81.5 163
163.0
2 (1, N = 163) =
151.221, p < .05
Commercial
benefit for
customer
Count
Expected
Count
148
81.5
15
81.5 163
163.0
2 (1, N = 163) =
108.521, p < .05
Scope
Count 111 51
(1, N = 163) = 21.356,
p < .05
Expected
Count
81.5 81.5
Personal growth
Count 162 1 163
2 (1, N = 163) =
159.025, p < .05
Expected
Count
81.5 81.5 163.0
Customer approval
Count 129 34
(1, N = 163) = 55.368,
p < .05
Expected
Count
81.5 81.5
Profitability Count 139 34 (1, N = 163) = 55.368,
p < .05
Expected
Count
81.5 81.5
Sales
Count 154 9 163
2 (1, N = 163) =
128.988, p < .05
Expected
Count
81.5 81.5 163.0
Question 19: Symptoms at the organization
Exploratory factor analysis was used to measure the symptoms of
organizational or personal factors hampering the proper execution of
projects in the participants’ project environment. Before factor extraction,
the data gathered from 163 respondents were tested for their suitability for
the exploratory factor analysis. As shown in Table 12, the Kaiser-Meyer-
Olkin Measure of Sampling Adequacy was .846, above the recommended .6,
and the Bartlett's Test of Sphericity was significant at p < .05. Principal
component analysis was used for the factor extraction, and a varimax with
Kaiser normalization was employed for the rotation of the 33 items.
Table 12. Kaiser-Meyer-Olkin Measure of Sampling Adequacy and
Bartlett’s Test of Sphericity
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .846
Bartlett's Test of Sphericity Approx. Chi-Square 1,790.125
Df 528
Sig. .000
As shown in Table 13, the cumulative percentage of the variance was 63.4%,
and 10 components (factors) had an eigenvalue > 1. Thus, the 33
questionnaire items were loaded onto those 10 factors.
Table 13. Total Variance Explained
Total Variance Explained
Component Initial Eigenvalues Rotation Sums of Squared
Loadings
Total
% of
Variance
Cumulative
% Total
% of
Variance
Cumulative
%
1 8.279 25.086 25.086 3.375 10.227 10.227
2 1.932 5.856 30.942 2.558 7.752 17.979
3 1.815 5.500 36.442 2.455 7.438 25.417
4 1.601 4.850 41.293 2.389 7.240 32.657
5 1.491 4.517 45.809 2.354 7.134 39.791
6 1.391 4.214 50.024 1.961 5.944 45.735
7 1.162 3.521 53.545 1.901 5.762 51.497
8 1.134 3.437 56.982 1.346 4.077 55.574
9 1.100 3.334 60.316 1.298 3.932 59.506
10 1.023 3.099 63.414 1.290 3.908 63.414
11 .947 2.870 66.284
12 .915 2.774 69.059
13 .856 2.593 71.651
14 .806 2.444 74.095
15 .761 2.306 76.401
16 .684 2.073 78.473
17 .635 1.925 80.399
18 .613 1.857 82.256
19 .589 1.784 84.040
20 .556 1.686 85.725
21 .549 1.662 87.388
22 .466 1.413 88.800
23 .459 1.392 90.192
24 .431 1.305 91.498
25 .411 1.246 92.744
26 .384 1.164 93.909
27 .363 1.100 95.009
28 .321 .972 95.981
29 .319 .967 96.948
30 .285 .864 97.812
31 .265 .804 98.616
32 .231 .700 99.316
33 .226 .684 100.000
Extraction Method: Principal Component Analysis.
Seven items loaded onto Factor 1. All these items are related to
behavior and consequences on the project (see Rotated Component Matrix in
Appendix B). This factor was labeled “Project-oriented behavior of people
involved in projects.” Six items loaded onto Factor 2, all related to project
difficulties such as incomprehensible project measurement systems and self-
impeding procedures and policies. This factor was labeled “Self-impeding
organization.” Three items loaded onto Factor 3, all related to the leadership
team and their perceptions of the symptoms that may put the project at risk.
This factor was labeled “Problemsolving oriented leadership.” Five items
Figure 27 . Scree Plot
10 Factors to be retained
loaded onto Factor 4, all related to team accountability and teamwork. This
factor was labeled “Project team related project constraints.” Three items
loaded onto Factor 5; all were related to the project outcomes, cost, scope,
quality, and schedule. This factor was labeled “Project outcomes.” Three
items loaded onto Factor 6, all related to the customer and to missing inputs
for successful project execution. This factor was labeled
“Customer-related project constraints.”
Three items loaded onto Factor 7, all related to the non-availability of
resources such as experts in relevant fields and/or equipment capacities. This
factor was labeled “Resources-related project constraints.”
Question 20: PM initiating processes: contribution to project success
A chi-square test of goodness-of-fit was performed to determine whether
agreement regarding how the outputs of project management initiating
processes contributed to project success was equally distributed. The level of
agreement was not equally distributed in the sample (see Figure 28 and
Table 14).
Figure 28. PM initiating processes: chi-square test of goodness-of-fit
Table 14. PM initiating processes: hypothesis test summary
Hypothesis Test Summary
Null Hypothesis Test Sig. Decision
1
The categories of H1-1 Project
charter occur with equal
probabilities.
One-Sample
ChiSquare
Test
.000
Reject the null
hypothesis.
2
The categories of H1-2 Preliminary
project scope statement occur with
equal probabilities.
One-Sample
ChiSquare
Test
.000
Reject the null
hypothesis.
3
The categories of H1-3 Updates
occur with equal probabilities.
One-Sample
ChiSquare
Test
.000
Reject the null
hypothesis.
Asymptotic significances are displayed. The
significance level is ,05.
Question 21: PM planning processes: contribute to project success
A chi-square test of goodness-of-fit was performed to determine whether
agreement on how the outputs of project management planning processes
144
143
125
14
16
30
5
4
8
H1-1 Project charter
H1-2 Preliminary project scope statement
H1-3 Updates
strongly agree/ agree neither agree nor disagree disagree/ strongly disagree
contribute to project success was equally distributed. The level of agreement
was not equally distributed in the sample (see Figure 29 and Table 15).
Figure 29. PM planning processes: chi-square test of goodness-of-fit
Table 15. PM planning processes: hypothesis test summary
Hypothesis Test Summary
Null Hypothesis Test Sig. Decision
1
The categories of H1-4 Project
Management plan occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
2
The categories of H2-1 Project
scope management plan occur
with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
3
The categories of H2-2 Project
scope statement occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
4
The categories of H2-3 Work
breakdown structure occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
5
The categories of H2-4 WBS
dictionary occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
6
The categories of H2-5 Scope
baseline occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
7 The categories of H3-1 Activity
list occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
8
The categories of H3-2 Activity
attributes occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
9 The categories of H3-3 Milestones
list occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
10
The categories of H3-4 Project
schedule network diagram
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
11
The categories of H3-5 Activity
resources requirements occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
12
The categories of H3-6 Resource
breakdown structure occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
13
The categories of H3-7 Resource
calendar occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
14
The categories of H3-8 Activity
duration estimates occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
15
The categories of H3-9 Project
schedule occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
16
The categories of H3-10 Schedule
model data occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
17
The categories of H3-11 Schedule
baseline occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
18
The categories of H4-1 Activity
cost estimates occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
19
The categories of H4-2 Activity
cost estimates supporting detail
occur with equal probabilities.
One-Sample
Chi-Square
Test
,00
0
Reject the null
hypothesis.
20
The categories of H4-3 Cost
management plan occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
21 The categories of H4-4 Cost One-Sample .00 Reject the null
baseline occur with equal
probabilities.
Chi-Square
Test 0 hypothesis.
22
The categories of H4-5 Project
funding requirements occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
23
The categories of H5-1 Quality
management plan occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
24
The categories of H5-2 Quality
metrics occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
25
The categories of H5-3 Quality
checklists occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
26
The categories of H5-4 Process
improvement plan occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
27
The categories of H5-5 Quality
baseline occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
28
The categories of H6-1 Roles and
responsibilities occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
29
The categories of H6-2 Project
organization chart occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
30
The categories of H6-3 Staffing
management plan occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
31
The categories of H7-1
Communication management plan
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
32 The categories of H8-1 Risk
management
One-Sample .00
0
Reject the null
plan occur with equal
probabilities.
Chi-Square
Test
hypothesis.
33
The categories of H8-2 Risk
register occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
34
The categories of H8-3 Risk-
related contractual agreements
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
35
The categories of H9-1
Procurement management plan
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
36
The categories of H9-2 Contract
statement of work occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
37
The categories of H9-3 Make-or-
buy decisions occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
38
The categories of H9-4
Procurement documents occur
with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
39
The categories of H9-5 Supplier
evaluation criteria occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
40 The categories of H9-6 Updates
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
Asymptotic significances are displayed. The significance level is .05.
Question 22: PM executing processes: contribution to project success A
chi-square test of goodness-of-fit was performed to determine whether
agreement on how project management executing process outputs contribute
to project success was equally distributed. The level of agreement was not
equally distributed in the sample (see Figure 30 and Table 16).
strongly agree/ agree neither agree nor disagree
disagree/ strongly disagree
159
H1-5 Deliverables
H1-6 Requested
changes
H1-7 Implemented change
requests
H1-8 Implemented
corrective actions
H1-9 Implemented
preventive actions
H1-10 Implemented
defect repair
H1-11 Work performance
information
H5-6 Recommended
corrective actions
H5-7 Organizational
process assets
H6-4 Project staff
assignments
4
0 135
18
10 130
25
8 126
34
3 121
38
4 118
40
5
99
96
77
70
107
145
50
14
56 9
16
49
7
17
1
72
75
85
75
72
68
76
16
49
29
16
19
H6-5 Resource availability
H6-6 Team performance assessment
H9-7 Procurement document package
H9-8 Proposals
H9-9 Selected sellers
H9-10 Contract
H9-11 Contract management plan
H9-12 Procurement management plan (up.)
Figure 30. PM executing processes: chi-square test of goodness-of-fit
Table 16. PM executing processes: hypothesis test summary
Hypothesis Test Summary
Null Hypothesis Test Sig. Decision
1
The categories of H1-5 Deliverables
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
2
The categories of H1-6 Requested
changes occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
3
The categories of H1-7
Implemented change requests occur
with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
4
The categories of H1-8
Implemented corrective actions
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
5 The categories of H1-9
Implemented preventive actions
One-Sample
Chi-Square
.00
0
Reject the null
hypothesis.
occur with equal probabilities. Test
6
The categories of H1-10
Implemented defect repair occur
with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
7
The categories of H1-11 Work
performance information occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
8
The categories of H5-6
Recommended corrective actions
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
9
The categories of H5-7
Organizational process assets occur
with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
10
The categories of H6-4 Project staff
assignments occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
11
The categories of H6-5 Resource
availability occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
12
The categories of H6-6 Team
performance assessment occur with
equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
13
The categories of H9-7 Procurement
document package occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
14
The categories of H9-8 Proposals
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
15
The categories of H9-9 Selected
sellers occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
16
The categories of H9-10 Contract
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
17
The categories of H9-11 Contract
management plan occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
18
The categories of H9-12
Procurement management plan
(update) occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
Asymptotic significances are displayed. The significance level is ,05.
Question 23: PM controlling and monitoring processes: contribution to
project success
A chi-square test of goodness-of-fit was performed to determine whether the
agreement on how project management controlling and monitoring processes
outputs contribute to project success was equally distributed. The level of
agreement was not equally distributed in the sample (see Figure 31 and
Table 17).
strongly agree/ agree neither agree nor disagree disagree/ strongly
disagree
H1-12 Recommended corrective actions
H1-13 Recommended preventive actions
H1-14 Forecasts
H1-15 Recommended defect repair
H1-16 Requested changes
H1-17 Approved change requests
H1-18 Rejected change requests
H1-19 Approved corrective actions
H1-20 Approved preventive actions
H1-21 Approved defect repair
H1-22 Validated defect repair
H1-23 Deliverables153
H2-6 Accepted deliverables 147
H3-12 Performance
measurements
H4-6 Forecasted
completion
H5-8 Quality control
measurements
H5-9 Validated
deliveries
H7-2 Performance
reports
H7-3 Resolve
issues
H9-13 Contract
documentation
127
107
131
5 31
18 38
4 28
99
127
133
7 57
11 25
6 24
108
108
105
105
110
9 46
14 41
18 40
8 50
6 47
2 8
3 13
120
103
117
134
7 36
10 50
10 36
4 25 103
120
Figure 31. PM controlling and monitoring processes: chi-square test of
goodness-of-fit
Table 17. PM controlling and monitoring processes: hypothesis test
summary
Hypothesis Test Summary
Null Hypothesis Test Sig. Decision
1
The categories of H1-12
Recommended corrective actions
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
2
The categories of H1-13
Recommended preventive actions
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
3
The categories of H1-14 Forecasts
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
4
The categories of H1-15
Recommended defect repair occur
with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
5
The categories of H1-16 Requested
changes occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
6
The categories of H1-17 Approved
change requests occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
7
The categories of H1-18 Rejected
change requests occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
8
The categories of H1-19 Approved
corrective actions occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
9
The categories of H1-20 Approved
preventive actions occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1The categories of H1-21 Approved
defect repair occur with equal
One-Sample
Chi-Square
.00 Reject the null
0 probabilities. Test 0 hypothesis.
1
1
The categories of H1-22 Validated
defect repair occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
2
The categories of H1-23 Deliverables
occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
3
The categories of H2-6 Accepted
deliverables occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
4
The categories of H3-12 Performance
measurements occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
5
The categories of H4-6 Forecasted
completion occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
6
The categories of H5-8 Quality control
measurements occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
7
The categories of H5-9 Validated
deliverables occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
1
8
The categories of H7-2 Performance report occur
One-Sample
.000 with equal probabilities. Chi-Square Test
Reject the null
hypothesis.
1
9
The categories of H7-3 Resolved
issues occur with equal probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
2
0
The categories of H9-13 Contract
documentation occur with equal
probabilities.
One-Sample
Chi-Square
Test
.00
0
Reject the null
hypothesis.
Asymptotic significances are displayed. The significance level is ,05.
Hypotheses testing
Hypothesis H1
There is no significant relationship between long-term project success and
project integration management.
The independent project management processes outputs are project
charter, preliminary project scope statement, updates, project management
plan, implemented change requests, implemented preventive actions,
implemented defect repair, work performance information, recommended
corrective actions, forecasts, recommended defect repair, approved change
requests, rejected change requests, approved defect repair, and deliverables.
The dependent project outcomes are sales, stakeholder satisfaction, user
satisfaction, financial objectives, commercial benefit for contractors, sales,
customer approval, and personal growth. The entire test summary is shown
in Table 20. Due to the large number of tests, only few are described in this
section. Further tests are shown in Appendices C and D.
A Fisher's exact test of independence was performed to examine
whether there is a relationship between preliminary project scope statement
and stakeholder satisfaction. The results revealed significant evidence of a
relationship (p =.011, 2-sided). Moreover, 89 of the participants who did not
consider stakeholder satisfaction as a project success criterion reported that
preliminary project scope statement contributes to project success, while
only 54 participants selected stakeholder satisfaction as a project success
criterion (see Table 18). The strength of this association is represented by the
coefficient Cramer's V (.236), which indicates a moderate relationship.
Table 18. Crosstab H1-2 Preliminary project scope statement *
Stakeholder satisfaction
Stakeholder
satisfaction
Total
143
143.0
16
16.0
4
4.0
0 1
H1-2 Preliminary
project scope
statement
strongly agree / agree Count
Expected
Count
89
89.5
54
53.5
neither agree nor
disagree
Count 13 3
Expected
Count
10.0 6.0
disagree / strongly
disagree
Count 0 4
Expected
Count
2.5 1.5
Total Count 102 61
Expected
Count
102.0 61.0
163
163.0 Chi-Square Tests
Value df
Asymp.
Sig.
(2-sided)
Exact
Sig.
(2-sided)
Exact
Sig.
(1-
sided)
Point
Probability
Pearson Chi-
Square
9.078a 2 .011 .008
Likelihood Ratio 10.513 2 .005 .007
Fisher's Exact
Test
8.372 .011
Linear-by-Linear
Association
.607b 1 .436 .448 .276 .110
N of Valid Cases 163
a. 2 cells (33.3%) have expected count less than 5. The
minimum expected count is 1.50. b. The standardized statistic
is .779.
Symmetric Measures
Value Approx. Sig. Exact Sig.
Nominal by Nominal Phi .236 .011 .008
Cramer's V .236 .011 .008
N of Valid Cases 163
disagree / strongly
disagree neither
agree nor disagree
strongly agree / agree
4
0
3
13
Stakeholder satisfaction
1 0
54
89
0 20 40 Count 60 80 100
The second Fisher's exact test of independence was performed to
examine whether there is a relationship between project management plan
and stakeholder satisfaction. The results revealed significant evidence of a
H1-2
Preliminary
project
scope
statement
relationship (p =.040, 2-sided). Moreover, 90 of the participants who did not
consider stakeholder satisfaction a project success criterion reported that
project management plan contributes to project success, while only 47
participants selected stakeholder satisfaction as a project success criterion
(see Table 19).
The strength of this association is represented by the coefficient Cramer's V
(.199), which indicates a weak relationship.
A shown in Table 20, the results of the tests revealed significant
evidence of a relationship between the outputs of project integration
management and long-term project success (i.e., project manager
satisfaction, sales, stakeholder satisfaction, user satisfaction, financial
objectives, customer approval, and personal growth). Chi-square values were
greater than the critical value (5.991 by two degrees of freedom), and the p-
values were less than .05 in both the chisquare and Fischer’s exact tests.
Therefore, the null hypothesis that there is no significant relationship
between project integration management and long-term project success was
rejected.
Table 19. Crosstab H1-4 Project management plan* Stakeholder
satisfaction
Stakeholder
satisfaction
0 1 Total
H1-4 Project strongly agree / agree Count 90 47 137 management plan
Expected Count 85.7 51.3 137.0 neither agree nor disagree Count 11 9 20
Expected Count 12.5 7.5 20.0
disagree / strongly disagree Count 1 5 6
Expected Count 3.8 2.2 6.0
Total Count 102 61 163
Expected Count 102.0 61.0 163.0
Chi-Square Tests
Value df
Asymp. Sig. Exact
Sig.
(2-sided) (2-sided)
Exact Sig. Point
(1-sided)
Probability
Pearson Chi-
Square
6.459a 2 .040 .033
Likelihood Ratio 6.414 2 .040 .058
Fisher's Exact
Test
6.102 .040
Linear-by-Linear
Association
5.552b 1 .018 .019 .016 .009
N of Valid Cases 163
a. 2 cells (33.3%) have expected count less than 5. The minimum expected
count is 2.25.
b. The standardized statistic is 2.356.
Symmetric Measures
Value
Nominal by Nominal Phi .199 .040 .033
Cramer's V .199 .040 .033
N of Valid Cases 163
Table 20. Summary hypothesis testing: H1 integration management
Independence Test
Dependent project
Independent factors outcomes
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
H1-1 Project charter Sales
Financial objectives
p = .033
p = .050
H1-2 Preliminary project Stakeholder
satisfaction scope statement
p = .011
H1-3 Updates User satisfaction p = .011
H1-4 Project
management plan
Stakeholder
satisfaction
p = .040
H1-7 Implemented
change requests
Scope
Commercial benefit
for contractors
2 (2, N = 163) =
6.460, p < .05
p = .050
Approx. Sig. Exact Sig.
90
11
1
47
9
5
0 20 40 60 80 100
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H1-4 Project
management plan
Count
Stakeholder satisfaction
1 0
H1-9 Implemented
preventive actions
Schedule
Financial objectives
p
= .007
p
= .004
Commercial benefit
for contractors
p = .043
H1-10 Implemented
defect repair
Schedule
Sales
p
= .019
p
= .030
H1-11 Work
performance
information H1-12
Recommended
corrective actions
Sales p = .046
Customer approval
p = .016
H1-14 Forecasts Performance objectives p = .004
H1-15 Recommended Financial objectives p = .024 defect
repair
H1-17 Approved change Commercial benefit for p = .036 requests
contractors
Scope p = .043
H1-18 Rejected
change requests
User satisfaction 2 (2, N = 163) =
6.490, p < .05
Technical objectives 2 (2, N = 163) =
11.397, p < .05
H1-21 Approved
defect repair
Personal growth p = .049
H1-23 Deliverables Commercial benefit
for contractors
p = .043
Hypothesis H2
There is no significant relationship between long-term project success and
project scope management.
The independent project management processes output analyzed is the
scope baseline. The dependent project outcomes are project team satisfaction
and profitability.
A Fisher's exact test of independence was performed to examine
whether there is a relationship between scope baseline and project team
satisfaction. The results revealed significant evidence of a relationship (p
=.045, 2-sided). Moreover, 114 of the participants who did not consider
project team satisfaction a project success criterion reported that scope
baseline contributes to project success, while only five participants selected
project team satisfaction as a project success criterion (see Table 21) The
strength of this association is represented by the coefficient Cramer's V
(.209), which indicates a moderate relationship.
The second Fisher's exact test of independence was performed to
examine whether there is a relationship between scope baseline and
profitability.
The results revealed significant evidence of a relationship (p =.039, 2-sided).
Moreover, 102 of the participants who did not consider Profitability a project
success criterion reported that scope baseline contributes to project success,
while only 21 participants selected profitability as a project success criterion
(see
Table 22). The strength of this association is represented by the coefficient
Cramer's V (.210), which indicates a moderate relationship.
Table 21. Crosstab H2-5 Scope baseline * Project team satisfaction
Project team
satisfaction
110.2
1 Total
H2-5 Scope
baseline
strongly agree / agree Count
Expected
Count
9
12.8
123
123.0
neither agree nor
disagree
Count 28 8 36
Expected
Count
32.2 3.8 36.0
disagree / strongly
disagree
Count 4 0 4
Expected
Count
3.6 .4 4.0
Total Count 146 17 163
Expected
Count
146.0 17.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi- 7.100a 2 .029 .044
Square
Likelihood
Ratio
6.487 2 .039 .038
Fisher's Exact
Test
5.960 .045
Linear-by-
Linear
Association
3.085b 1 .079 .115 .074 .045
N of Valid
Cases
163
a. 3 cells (50.0%) have expected count less than 5. The minimum
expected count is .42. b. The standardized statistic is 1.756.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .209 .029 .044
Cramer's V .209 .029 .044
N of Valid Cases 163
Table 22. Crosstab H2-5 Scope baseline * Profitability
1 Total
H2-5 Scope strongly agree / agree Count 21 123
114
28
4
9
8
0
0 20 40 60 80 100 120
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H2-5 Scope baseline
Count
Project team satisfaction
1 0
Profitability
0
102
baseline Expected
Count
97.3 25.7 123.0
neither agree nor
disagree
Count 23 13 36
Expected
Count
28.5 7.5 36.0
disagree / strongly
disagree
Count 4 0 4
Expected
Count
3.2 .8 4.0
Total Count 129 34 163
Expected
Count
129.0 34.0 163.0
Chi-Square Tests
Value df
Asymp.
Sig.
(2-sided)
Exact
Sig.
(2-sided)
Exact
Sig.
(1-sided)
Point
Probability
Pearson Chi-
Square
7.195a 2 .027 .041
Likelihood Ratio 7.414 2 .025 .023
Fisher's Exact
Test
6.190 .039
Linear-by-Linear
Association
2.192b 1 .139 .173 .102 .051
N of Valid Cases 163
a. 2 cells (33.3%) have expected count less than 5. The minimum expected
count is .83.
b. The standardized statistic is 1.481.
Symmetric Measures
Value
Nominal by Nominal Phi .210 .027 .041
Cramer's V .210 .027 .041
Approx. Sig. Exact Sig.
N of Valid Cases 163
The results of the tests, shown in Table 23, revealed significant
evidence of a relationship between the output of the project scope
management (scope baseline) and long-term project success project (team
satisfaction). The p-value in Fischer’s exact test was less than .05. Therefore,
the null hypothesis that there is no significant relationship between project
scope management and long-term project success was rejected.
Table 23. Summary hypothesis testing: H2 project scope
management
Independence Test
Independent factors
H2-5 Scope
baseline
Dependent project
outcomes
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
Project team satisfaction p = .045
Profitability p = .039
102
23
4
21
13
0
0 20 40 60 80 100 120
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H2-5 Scope baseline
Count
Profitability
1 0
Hypothesis H3
There is significant no relationship between long-term project success and
project time management.
The independent project management processes outputs analyzed are
activity list, activity attributes, activity resource requirements, resource
breakdown structure, resource calendar, and project schedule. The
dependents project outcomes are customer satisfaction and sales.
The entire test summary is shown in Table 27. Due to the large
number of tests, only few are described in this section. Further tests are
shown in
Appendices C and D.
A Pearson chi-square test was conducted to examine whether there
was a relationship between activity list and customer satisfaction. The results
revealed a significant relationship (chi-square value = 10.216, df = 2, p
< .05). A significantly larger proportion of the participants who had selected
customer satisfaction as a project success criterion (81) reported that activity
list contributes to project success, while only 47 participants did not consider
customer satisfaction as a project success criterion (see Table 24). The
strength of this association is represented by the coefficient Cramer's V
(.250), which indicates a moderately strong relationship.
A second chi-square test was conducted to examine whether there
was a relationship between resource breakdown structure and customer
satisfaction.
The results revealed a significant relationship (chi-square value = 6.820, df =
2, p < .05 (see Table 25). The strength of this association is represented by
the coefficient Cramer's V (.242), which indicates a moderate relationship.
Furthermore, a Fisher's exact test of independence was performed to
examine whether there is a relationship between project schedule and
customer satisfaction. The results revealed significant evidence of a
relationship (p =.002, 2-sided) (see Table 26). The strength of this
association is represented by the coefficient Cramer's V (.251), which
indicates a moderately strong relationship.
Table 24. Crosstab H3-1 Activity list * Customer satisfaction
Customer
satisfaction
0 1 Total
H3-1 Activity list strongly agree / agree Count 47 81 128
Expected Count 53.4 74.6 128.0
neither agree nor disagree Count 11 12 23
Expected Count 9.6 13.4 23.0
disagree / strongly disagree Count 10 2 12
Expected Count 5.0 7.0 12.0
Total Count 68 95 163
Expected Count 68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
10.216a 2 .006 .005
Likelihood Ratio 10.513 2 .005 .006
Fisher's Exact
Test
10.042 .006
Linear-by-Linear
Association
9.235b 1 .002 .003 .002 .001
N of Valid Cases 163
a. 0 cells (0.0%) have expected count less than 5. The
minimum expected count i b. The standardized statistic is -
3.039.
Symmetric Measures
s 5.01.
Value Approx. Sig.
Exact
Sig.
Nominal by Nominal Phi .250 .006 .005
Cramer's V .250 .006 .005
N of Valid Cases 163
Table 25. Crosstab H3-6 Resource breakdown structure * Customer
satisfaction
Customer satisfaction
0 1 Total
H3-6 Resource
breakdown
structure
strongly agree /
agree
Count
Expected
Count
27
35.0
57
49.0
84
84.0
neither agree nor
disagree
Count 28 28 56
Expected
Count
23.4 32.6 56.0
disagree / strongly
disagree
Count 13 10 23
Expected
Count
9.6 13.4 23.0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Value df
Asymp.
Sig.
(2-sided)
Exact
Sig.
(2-sided)
Exact
Sig.
(1-
sided)
Point
Probability
Pearson Chi-
Square
6.820a 2 .033 .030
47
11
10
81
12
2
0 20 40 60 80 100
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H3-1 Activity list
Count
Customer satisfaction
1 0
Likelihood Ratio 6.854 2 .032 .033
Fisher's Exact
Test
6.819 .031
Linear-by-
Linear
Association
6.364b 1 .012 .015 .008 .004
N of Valid
Cases
163
a. 0 cells (0.0%) have expected count less than 5. The
minimum expected count is 9.60. b. The standardized
statistic is -2.523.
Symmetric Measures
Value Approx. Sig. Exact Sig.
Nominal by
Nominal
Phi .205 .033 .030
Cramer's V .205 .033 .030
N of Valid Cases 163
57
0 20 40 60
Count
disagree /
strongly
disagree
neither agree
nor disagree
strongly
agree / agree
10
28
28
27
Customer
satisfaction
1 0
13
H3-6 Resource
breakdown structure
Table 26. Crosstab H3-9 Project schedule * Customer satisfaction
Customer
satisfaction
0 1 Total
H3-9 Project
schedule
strongly agree / agree Count
Expected
Count
60
63.8
93
89.2
153
153.0
neither agree nor
disagree
Count 1 2 3
Expected
Count
1.3 1.7 3.0
disagree / strongly
disagree
Count 7 0 7
Expected
Count
2.9 4.1 7.0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Value df
Asymp. Sig. Exact
Sig.
(2-sided) (2-sided)
Exact Sig. Point (1-
sided) Probability
Pearson Chi-
Square
10.260a 2 .006 .003
Likelihood Ratio 12.725 2 .002 .003
Fisher's Exact
Test
10.435 .002
Linear-by-Linear
Association
8.746b 1 .003 .003 .003 .002
N of Valid Cases 163
a. 4 cells (66.7%) have expected count less than 5. The minimum expected
count is 1.25.
b. The standardized statistic is -2.957.
Symmetric Measures
Value
Nominal by Nominal Phi .251 .006 .003
Cramer's V .251 .006 .003
N of Valid Cases 163
disagree /
strongly
disagree
neither agree
nor disagree
strongly
agree / agree
0
60
1 0
93
7
2
1
Customer satisfaction
0 20 40 60 80 100
Count
As can be seen in Table 27, the results of the tests revealed significant
evidence of a relationship between the outputs of project time management
and long-term project success (i.e., customer satisfaction, sales, stakeholder
satisfaction, user satisfaction, financial objectives, and personal growth).
Chisquare values were greater than the critical value (5.991 by two degrees
of freedom), and the p-values were less than .05 in both the chi-square and
Approx. Sig. Exact Sig.
H3-9 Project
schedule
Fischer’s exact tests. Therefore, the null hypothesis that there is no
significant relationship between project time management and long-term
project success was rejected.
Table 27. Summary hypothesis testing; H3 project time
management
Fischer’s
Dependent project Chi-Square Test Exact Test
Independent factors outcomes (2-sided) (2-sided)
H3-1 Activity list Customer satisfaction 2(2, N = 163) = 10.216, p < .05
Sales p = .038
H3-2 Activity attributes Sales p = .030 H3-5 Activity resource
Sales p = .038 requirements
H3-6 Resource Customer satisfaction 2(2, N = 163) = 6.820, p < .05
breakdown structure
Sales p = .008 H3-7 Resource calendar Performance objectives
2(2, N = 163) = 7.150, p < .05
Hypothesis H4
There is no significant relationship between long-term project success and
project cost management.
The independent project management processes outputs are activity
cost estimates supporting detail and cost baseline. The dependent project
Independence Test
H3 -9 Project schedule Customer satisfaction p = .002
outcomes are customer satisfaction, customer approval, and commercial
benefit for customer.
The entire test summary is shown in Table 30. Due to the large
number of tests, only few are described in this section. Further tests are
shown in Appendices C and D.
A chi-square test was conducted to examine whether there was a
relationship between activity cost estimates supporting detail and customer
satisfaction. The results revealed a significant relationship (chi-square value
= 7.901, df = 2, p < .05). A significantly larger proportion of the participants
who had selected customer satisfaction as a project success criterion (45)
reported that activity cost estimates supporting detail contributes to project
success, while only 18 participants did not consider customer satisfaction as
a project success criterion (see Table 28). The strength of this association is
represented by the coefficient Cramer's V (.220), which indicates a moderate
relationship.
A further Pearson chi-square test was conducted to examine whether
there was a relationship between cost baseline and customer satisfaction. The
results revealed a significant relationship (chi-square value = 6.516, df = 2, p
< .05) (see Table 29). The strength of this association is represented by the
coefficient Cramer's V (.200), which indicates a moderate relationship.
Table 28. Crosstab H4-2 Activity cost estimates supporting detail *
Customer satisfaction
Customer
satisfaction
0 1 Total
H4-2 Activity
cost estimates
supporting
detail
strongly agree / agree
neither agree nor
disagree
Count
Expected
Count
Count
18
26.3
39
45
36.7
42
63
63.0
81
Expected
Count
33.8 47.2 81.0
disagree / strongly
disagree
Count
Expected
Count
11
7.9
8
11.1
19
19.0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
7.901a 2 .019 .020
Likelihood Ratio 8.048 2 .018 .021
Fisher's Exact
Test
7.943 .019
Linear-by-Linear
Association
7.517b 1 .006 .008 .004 .002
N of Valid Cases 163
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 7.93. b. The standardized statistic is -2.742.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .220 .019 .020
Cramer's V .220 .019 .020
N of Valid Cases 163
disagree
/ strongly
disagree
neither
agree nor
disagree
strongly
agree /
agree
8
18
1 0
42
39
45
11
Customer satisfaction
0 10 20 30 40 50
Count
Table 29. Crosstab H4-4 Cost baseline * Customer satisfaction
Customer
satisfaction
0 1 Total
H4-4 Cost baseline strongly agree /
agree
Count 40 72 112
H4-2 Activity cost
estimates
supporting detail
Expected
Count
46.7 65.3 112.0
neither agree nor disagree Count 18 18 36
Expected
Count
15.0 21.0 36.0
disagree / strongly disagree Count 10 5 15
Expected
Count
6.3 8.7 15.0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
6.516a 2 .038 .042
Likelihood Ratio 6.477 2 .039 .045
Fisher's Exact
Test
6.412 .042
Linear-by-Linear
Association
6.464b 1 .011 .014 .008 .004
N of Valid Cases 163
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 6.26. b. The standardized statistic is -2.542.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .200 .038 .042
Cramer's V .200 .038 .042
N of Valid Cases 163
disagre
e /
strongl
y
disagre
e
neither
agree
nor
disagre
e
strongl
y
agree /
agree
5
18
18
1
4
0
0 72
1
0
Customer satisfaction
0 10 20 30 40 50 60 70 80
Count
The results of the tests, presented in Table 30, revealed significant
evidence of a relationship between project cost management outputs (i.e.,
activity cost estimates supporting detail and cost baseline) and long-term
project success (i.e., customer satisfaction and customer approval). Chi-
square values were greater than the critical value (5.991 by two degrees of
freedom), and the pvalues were less than .05 in both the chi-square tests and
Fischer’s exact tests. Therefore, the null hypothesis that there is no
H4-4 Cost baseline
significant relationship between project cost management and long-term
project success was rejected.
Table 30. Summary hypothesis testing; H4 project cost management
Independence Test
Independent factors
H4-2 Activity cost
estimates
supporting
detail
Dependent project
outcomes
Fischer’s
Chi-Square Test Exact Test
(2-sided) (2-sided)
Customer satisfaction
Customer approval
2
(2, N = 163) = 7.901, p < .05
2
(2, N = 163) = 7.419, p < .05
H4-4 Cost baseline Customer satisfaction 2(2, N = 163) = 6.516, p < .05
Commercial benefit for
p = .019
customer
Hypothesis H5
There is no significant relationship between long-term project success and
project quality management.
The independent project management processes outputs are quality
management plan, process improvement plan, recommended corrective
actions, and quality control measurement. The dependent project outcomes
are customer satisfaction, stakeholder satisfaction, strategic contribution of
the project, and
profitability.
The entire test summary is shown in Table 32. Due to the large
number of tests only one test is described in this section. The remaining tests
are shown in Appendices C and D.
A Pearson chi-square test was conducted to examine whether there
was a relationship between quality management plan and customer
satisfaction. The results revealed a significant relationship (chi-square value
= 11.253, df = 2, p < .05). A significantly larger proportion of the
participants who had selected customer satisfaction as a project success
criterion (75) reported that quality management plan contributes to project
success, while only 37 participants did not consider customer satisfaction as
a project success criterion (see Table 31). The strength of this association is
represented by the coefficient Cramer's V (.263), which indicates a
moderately strong relationship.
As shown in Table 32, the results of the tests revealed significant
evidence of a relationship between project quality management outputs (i.e.,
quality management plan and recommended corrective actions) and long-
term project success (i.e., stakeholder satisfaction, strategic contribution of
the project, and profitability. The chi-square values were greater than the
critical value (5.991 by two degrees of freedom), and the p-values were less
than .05. Therefore, the null hypothesis that there is no significant
relationship between project quality management and long-term project
success was rejected.
Table 31. Crosstab H5-1 Quality management plan * Customer
satisfaction
Customer
satisfaction
0 1 Total
H5-1 Quality strongly agree / agree Count
management plan Expected Count
37
46.7
75
65.3
112
112.0
neither agree nor disagree Count 25 17 42
Expected Count 17.5 24.5 42.0
disagree / strongly disagree Count 6 3 9
Expected Count 3.8 5.2 9.0
Total Count 68 95 163
Expected Count 68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
11.253a 2 .004 .003
Likelihood Ratio 11.212 2 .004 .005
Fisher's Exact
Test
11.097 .003
Linear-by-Linear
Association
10.473b 1 .001 .002 .001 .001
N of Valid Cases 163
a. 1 cells (16.7%) have expected count less than 5. The minimum
expected count is 3.75. b. The standardized statistic is -3.236.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .263 .004 .003
Cramer's V .263 .004 .003
N of Valid Cases 163
Table 32. Summary hypothesis testing: H5 project quality
management
Independence Test
Independent
factors H5-1
Quality
management plan
Dependent project
outcomes
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
Customer
satisfaction
Stakeholder
satisfaction
Commercial benefit
for contractors
2 (2, N = 163) =
11.253, p < .05 2 (2, N
= 163) = 6.025, p < .05
p = .050
37
25
6
75
17
3
0 20 40 60 80
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H5-1 Quality
management plan
Count
Customer satisfaction
1 0
H5-4 Process
improvement plan
Customer satisfaction
2 (2, N = 163) =
5.987, p = .05
H5-6
Recommended
corrective actions
Strategic
contribution of the
project
2 (2, N = 163) =
12.456, p < .05
Profitability 2 (2, N = 163) =
6.668, p < .05
H5-8 Quality
control
measurements
Scope 2 (2, N = 163) =
7.540, p < .05
Hypothesis H6
There is no significant relationship between long-term project success and
project human resource management.
The independent project management processes outputs are roles and
responsibilities, staffing management plan, and resource availability. The
dependent project outcomes are stakeholder satisfaction and user
satisfaction.
A Fisher's exact test of independence was performed to examine
whether there is a relationship between roles and responsibilities and
stakeholder satisfaction. The results revealed significant evidence of a
relationship (p =.003, 2-sided). Moreover, 96 of the participants who did not
consider stakeholder satisfaction as a project success criterion reported that
roles and responsibilities contributes to project success, while only 47
participants selected stakeholder satisfaction as a project success criterion
(see Table 33) The strength of this association is represented by the
coefficient Cramer's V (.256), which indicates a moderately strong
relationship.
Table 33. Crosstab H6-1 Roles and responsibilities * Stakeholder
satisfaction
0 1 Total
H6-1 Roles and strongly agree / agree Count
responsibilities Expected Count
96
89.5
47
53.5
143
143.0
neither agree nor Count
disagree Expected Count
5
11.3
13
6.7
18
18.0
disagree / strongly Count
disagree Expected Count
1
1.3
1 .
7
2
2.0
Total Count 102 61 163
Expected Count 102.0 61.0 163.0
Chi-Square Tests
Value df
Asymp. Sig. Exact
Sig.
(2-sided) (2-sided)
Exact Sig.
(1-sided)
Point
Probability
Pearson Chi-
Square
10.711a 2 .005 .003
Likelihood Ratio 10.394 2 .006 .005
Fisher's Exact
Test
10.524 .003
Linear-by-Linear
Association
8.438b 1 .004 .005 .004 .003
N of Valid Cases 163
a. 2 cells (33.3%) have expected count less than
5. The minimu
m expected count is .75.
Stakeholder satisfaction
b. The standardized statistic is 2.905.
Symmetric Measures
Value Approx. Sig. Exact Sig.
Nominal by Nominal Phi .256 .005 .003
Cramer's V .256 .005 .003
N of Valid Cases 163
disagree /
strongly
disagree neither
agree nor
disagree
strongly agree /
agree
1
1 13
47
Stakeholder
satisfaction
1 0
5
96
100
0 20
40
Coun
t
60 80
The results of the tests revealed significant evidence of a relationship
between project human resource management outputs (i.e., roles and
responsibilities and staffing management plan) and long-term project success
(i.e., stakeholder and user satisfaction; see Table 34). The chi-square value
was greater than the critical value (5.991 by two degrees of freedom), and
the pvalues were less than .05 in both the chi-square and Fischer’s exact
tests. Therefore, the null hypothesis that there is no significant relationship
between project human resource management and long-term project success
was
rejected.
H6-1 Roles and
responsibilities
Table 34. Summary hypothesis testing: H6 project human resource
management
Independence Test
Independent factors
H6-1 Roles and
responsibilities
Dependent project
outcomes
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
Stakeholder
satisfaction
p = .003
H6-3 Staffing
management plan
User satisfaction 2 (2, N = 163) =
7.894, p < .05
H6-5 Resource
availability
Budget/Cost p = .000
Hypothesis H7
There is no significant relationship between long-term project success and
project communication management.
The independent project management processes outputs are
communication management plan, and resolved issues. The dependent
project outcomes are customer satisfaction and personal growth.
A chi-square test was conducted to examine whether there was a
relationship between communication management plan and customer
satisfaction. The results revealed a significant relationship (chi-square value
= 8.328, df = 2, p < .05). A significantly larger proportion of the participants
who had selected customer satisfaction as a project success criterion (81)
reported that communication management plan contributes to project
success, while only 45 participants did not consider customer satisfaction as
a project success criterion (see Table 35). The strength of this association is
represented by the coefficient Cramer's V (.226), which indicates a moderate
relationship.
The results of the tests revealed significant evidence of a relationship
between project communication management outputs (i.e., communication
management plan and resolved issues) and long-term project success,
customer satisfaction, and personal growth (see Table 36). The chi-square
value was greater than the critical value (5.991 by two degrees of freedom),
and the pvalues were less than .05 in both the chi-square and Fischer’s exact
tests. Therefore, the null hypothesis that there is no significant relationship
between project communication management and long-term project success
was rejected.
Table 35. Crosstab H7-1 Communication management plan *
Customer satisfaction
Customer
satisfaction
0 1 Total
H7-1 Communication strongly agree /
agree management plan
Count
Expected
Count
45
52.6
81
73.4
126
126.0
neither agree nor
disagree
Count
Expected
Count
17
11.7
11
16.3
28
28.0
disagree / strongly
disagree
Count
Expected
Count
6
3.8
3
5.2
9
9.0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
8.328a 2 .016 .014
Likelihood Ratio 8.252 2 .016 .023
Fisher's Exact
Test
8.171 .017
Linear-by-Linear
Association
7.710b 1 .005 .006 .004 .003
N of Valid Cases 163
a. 1 cells (16.7%) have expected count less than 5. The minimum
expected count is 3.75. b. The standardized statistic is -2.777.
Symmetric Measures
Value Approx. Sig. Exact Sig.
Nominal by Nominal Phi .226 .016 .014
Cramer's V .226 .016 .014
N of Valid Cases 163
Table 36. Summary hypothesis testing: H7 project communication
management
Independence Test
Independent factors
H7-1
Communication
management plan
Dependent project
outcomes
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
Customer
satisfaction
2 (2, N = 163) =
8.328, p < .05
H7-3 Resolved
issues Personal growth p = .037
Hypothesis H8
There is no significant relationship between long-term project success and
project risk management.
The independent project management process outcome the risk
management plan and the dependent project outcome is profitability.
45
17
6
81
11
3
0 10 20 30 40 50 60 70 80 90
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H7-1
Communication
management
plan
Count
Customer satisfaction
1 0
A Pearson chi-square test was conducted to examine whether there
was a relationship between risk management plan and profitability. The
results revealed a significant relationship (chi-square value = 8.016, df = 2, p
< .05). Moreover, 97 of the participants who did not consider profitability as
a project success criterion reported that risk management plan contributes to
project success, while only 33 participants selected user satisfaction as a
project success criterion (see Table
37). The strength of this association is represented by the coefficient
Cramer's V
(.222), which indicates a moderate relationship.
Table 37. Crosstab H8-1 Risk management plan * Profitability
Profitability
Total
130
130.0
26
26.0
7
7.0
163
163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
8.016a 2 .018 .019
Likelihood Ratio 11.166 2 .004 .004
Fisher's Exact 7.987 .014
0 1
H8-1 Risk
management plan
strongly agree /
agree
Count
Expected
Count
97
102.9
33
27.1
neither agree nor
disagree
Count
Expected
Count
25
20.6
1
5.4
disagree / strongly
disagree
Count
Expected
Count
7
5.5
0
1.5
Total Count 129 34
Expected
Count
129.0 34.0
Test
Linear-by-Linear
Association
7.348b 1 .007 .008 .002 .001
N of Valid Cases 163
a. 1 cells (16.7%) have expected count less than 5. The minimum
expected count is 1.46. b. The standardized statistic is -2.711.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .222 .018 .019
Cramer's V .222 .018 .019
N of Valid Cases 163
The result of the test, shown in Table 38, reveals significant evidence
of a relationship between project risk management outputs (i.e., risk
management plan) and long-term project success (i.e., profitability). The chi-
square value was greater than the critical value (5.991 by two degrees of
freedom), and the p-value was less than .05. Therefore, the null hypothesis
that there is no significant relationship between project risk management and
long-term project success was rejected.
97
25
7
33
1
0
0 20 40 60 80 100
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H8-1 Risk
management plan
Count
Profitability
1 0
Table 38. Summary hypothesis testing: H8 project risk management
Independence Test
Independent factor
H8-1 Risk
management
plan
Dependent project
outcome
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
Profitability 2
(2, N = 163) = 8.016, p < .05
Hypothesis H9
There is no significant relationship between long-term project success and
project procurement management.
The independent project management processes outputs are
procurement management plan, contract statement of work, make-or-buy
decisions, procurement documents, supplier evaluation criteria, updates,
procurement document package, proposals, selected sellers, contract,
contract management plan, and contract documentation.
The dependent project outcomes are customer satisfaction, stakeholder
satisfaction, user satisfaction, commercial benefit for customer, project team
satisfaction, commercial benefit for contractors, financial objectives, and
strategic contribution of the project.
The entire test summary is shown in Table 44. Due to the large
number of tests, only few are described in this section. Further tests are
shown in Appendices C and D.
A chi-square test was conducted to examine whether there was a
relationship between procurement management plan and customer
satisfaction.
The results revealed a significant relationship (chi-square value = 7.716, df =
2, p < .05). A significantly larger proportion of the participants who had
selected customer satisfaction as a project success criterion (53) reported that
procurement management plan contributes to project success compared,
while only 23 participants did not consider customer satisfaction as a project
success criterion (see Table 39). The strength of this association is
represented by the coefficient Cramer's V (.218), which indicates a moderate
relationship.
A second chi-square test was conducted to examine whether there was
a relationship between proposals and customer satisfaction. The results
revealed a significant relationship (chi-square value = 10.845, df = 2, p
< .05) (see Table
40). The strength of this association is represented by the coefficient
Cramer's V
(.258), which indicates a moderately strong relationship.
Table 39. Crosstab H9-1 Procurement management plan * Customer
satisfaction
Customer
satisfaction
1 Total H9-1 Procurement strongly agree / agree Count 23 53 76
management plan
Expected Count 31.7 44.3 76.0
neither agree nor disagree Count 35 32 67
Expected Count 28.0 39.0 67.0 disagree /
strongly disagree Count 10 10 20
Expected Count 8.3 11.7 20.0
Total Count 68 95 163
Expected Count 68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
7.716a 2 .021 .019
Likelihood Ratio 7.812 2 .020 .020
Fisher's Exact
Test
7.761 .019
Linear-by-Linear
Association
5.718b 1 .017 .020 .011 .005
N of Valid Cases 163
0
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 8.34. b. The standardized statistic is -2.391.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .218 .021 .019
Cramer's V .218
N of Valid Cases 163.000
.021
.019
Table 40. Crosstab H9-8 Proposals * Customer satisfaction
Customer
satisfaction
0 1 Total
H9-8
Proposals
strongly agree / agree Count 21 54 75
Expected
Count
31.3 43.7 75.0
neither agree nor
disagree
Count 39 33 72
Expected
Count
30.0 42.0 72.0
disagree / strongly
disagree
Count 8 8 16
Expected
Count
6.7 9.3 16.0
23
35
10
53
23
10
0 20 40 60
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H9-1
Procurement
management
plan
Count
Customer satisfaction
1 0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
10.845a 2 .004 .004
Likelihood Ratio 11.037 2 .004 .005
Fisher's Exact
Test
10.942 .004
Linear-by-Linear
Association
7.916b 1 .005 .005 .003 .002
N of Valid Cases 163
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 6.67. b. The standardized statistic is -2,814.
Symmetric Measures
Value Approx. Sig.
Exact
Sig.
Nominal by Nominal Phi .258 .004 .004
Cramer's V .258 .004 .004
N of Valid Cases 163
The third chi-square test was conducted to examine whether there was
a relationship between selected sellers and customer satisfaction. The results
21
39
8
54
33
8
0 20 40 60
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H9-8 Proposals
Count
Customer satisfaction
1 0
revealed a significant relationship (chi-square value = 11.426, df = 2, p
< .05). A significantly larger proportion of the participants who had selected
customer satisfaction as a project success criterion (50) reported that selected
sellers contribute to project success, while only 18 participants did not
consider customer satisfaction as a project success criterion (see Table 41).
The strength of this association is represented by the coefficient Cramer's V
(.265), which indicates a moderately strong relationship.
The fourth chi-square test was conducted to examine whether there
was a relationship between contract and customer satisfaction. The results
revealed a significant relationship (chi-square value = 10.611, df = 2, p
< .05). A significantly larger proportion of the participants who had selected
customer satisfaction as a project success criterion (74) reported that contract
contributes to project success, while only 39 participants did not consider
customer satisfaction as a project success criterion (see Table 42). The
strength of this association is represented by the coefficient Cramer's V
(.255), which indicates a moderately strong relationship.
The fifth chi-square test was conducted to examine whether there was
a relationship between contract management plan and customer satisfaction.
The results revealed a significant relationship (chi-square value = 11.229, df
= 2, p < .05) (see Table 43). The strength of this association is represented
by the coefficient Cramer's V (.262), which indicates a moderately strong
relationship.
Table 41. Crosstab H9-9 Selected sellers * Customer satisfaction
Customer
satisfaction
0 1 Tota
l
H9-9
Selected
sellers
strongly agree / agree Count
Expected Count
18
28.4
50
39.6
68
68.0
neither agree nor disagree Count 39 37 76
Expected Count 31.7 44.3 76.0
disagree / strongly Count
disagree Expected Count
11
7.9
8
11.1
19
19.0
Total Count 68 95 163
Expected
Count
68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
11.426a 2 .003 .003
Likelihood Ratio 11.706 2 .003 .003
Fisher's Exact
Test
11.554 .003
Linear-by-Linear
Association
10.219b 1 .001 .002 .001 .001
N of Valid Cases 163
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 7.93. b. The standardized statistic is -3.197.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .265 .003 .003
Cramer's V .265 .003 .003
N of Valid Cases 163
Table 42. Crosstab H9-10 Contract * Customer satisfaction
Customer satisfaction
0 1 Total
Expected Count
Chi -Square Tests
18
39
11
50
37
8
0 20 40 60
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H9-9 Selected
sellers
Count
Customer satisfaction
1 0
H9-10 Contract strongly agree /
agree
Count 39 74 113
Expected
Count
47.1 65.9 113.0
neither agree nor
disagree
Count
Expected
Count
26
17.1
15
23.9
41
41.0
disagree / strongly
disagree
Count
Expected
Count
3
3.8
6
5.2
9
9.0
Total Count 68 95 163
68.0 95.0 163.0
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
10.611a 2 .005 .004
Likelihood Ratio 10.535 2 .005 .008
Fisher's Exact
Test
10.405 .004
Linear-by-Linear
Association
4.008b 1 .045 .057 .032 .015
N of Valid Cases 163
a. 1 cells (16.7%) have expected count less than 5. The minimum expected
count is 3.75.
b. The standardized statistic is -2.002.
Symmetric Measures
Value
Nominal by Nominal Phi .255 .005 .004
Cramer's V .255 .005 .004
N of Valid Cases 163
Customer satisfaction
15
1
0 20 40 60 80
Count
Approx. Sig. Exact Sig.
H9-10 Contract
3
6
Table 43. Crosstab H9-11 Contract management plan * Customer
satisfaction
Customer
satisfaction
0
1 Total
H9-11 Contract strongly agree /
agree management plan
Count
Expected Count
18
28.0
49
39.0
67
67.0
neither agree nor
disagree
Count
Expected Count
39
29.6
32
41.4
71
71.0
disagree / strongly
disagree
Count
Expected Count
11
10.4
14
14.6
25
25.0
Total Count 68 95 163
Expected Count 68.0 95.0 163.0
Chi-Square Tests
Asymp. Sig. Exact Sig. Exact Sig. Point
Value df (2-sided) (2-sided) (1-sided) Probability
Pearson Chi-
Square
11.229a 2 .004 .003
Likelihood Ratio 11.464 2 .003 .004
Fisher's Exact
Test
11.317 .003
Linear-by-Linear
Association
5.574b 1 .018 .019 .012 .006
N of Valid Cases 163
a. 0 cells (0.0%) have expected count less than 5. The minimum
expected count is 10.43. b. The standardized statistic is -2.361.
Symmetric Measures
Value Approx. Sig. Exact
Sig.
Nominal by Nominal Phi .262 .004 .003
Cramer's V .262 .004 .003
N of Valid Cases 163
Table 44. Summary hypothesis testing: H9 project procurement
management
Independence Test
Independent factors
H9-1 Procurement
management plan
Dependent project
outcomes
Chi-Square Test
(2-sided)
Fischer’s
Exact
Test
(2-sided)
Customer satisfaction2 (2, N = 163) =
7.716, p < .05
Stakeholder
satisfaction
Technical objectives
2 (2, N = 163) =
10.768, p < .05
H9-2 Contract
statement of work
2 (2, N = 163) =
9.852, p < .05
Scope 2 (2, N = 163) =
8.986, p < .05
H9-3 Make-or-buy
decisions
Commercial benefit
for customer
2 (2, N = 163) =
7.304, p < .05
H9-4 Procurement
documents
Project team
satisfaction
2 (2, N = 163) =
7.673, p < .05
H9-5 Supplier Project team 2 (2, N = 163) =
18
39
11
49
32
14
0 20 40 60
strongly agree / agree
neither agree nor disagree
disagree / strongly disagree
H9-11 Contract
management plan
Count
Customer satisfaction
1 0
evaluation criteria satisfaction 6.505, p < .05
H9-6 Updates Performance
objectives
Scope
2 (2, N = 163) =
9.347, p < .05
H9-7 Procurement
document package
2 (2, N = 163) =
9.487, p < .05
H9-8 Proposals Customer
satisfaction
2 (2, N = 163) =
10.845, p < .05
Commercial benefit
for contractors
p = .026
H9-9 Selected
sellers
Customer
satisfaction
2 (2, N = 163) =
11.426, p < .05
Financial objectives 2 (2, N = 163) =
7.277, p < .05
H9-10 Contract Customer
satisfaction
2 (2, N = 163) =
10.611, p < .05
H9-11 Contract
management plan
Customer
satisfaction
User satisfaction
2 (2, N = 163) =
11.229, p < .05 2 (2, N
= 163) = 6.022, p < .05
H9-12
Procurement
management plan
(update)
Customer
satisfaction
2 (2, N = 163) =
10.321, p < .05
Strategic contribution
of the project
2 (2, N = 163) =
6.307, p < .05
Commercial benefit
for customer
2 (2, N = 163) =
9.301, p < .05
H9-13 Contract
documentation
Strategic contribution
of the project
2 (2, N = 163) =
6.020, p < .05
A shown in Table 44, the results of the tests revealed a significant
relationship between project procurement management outputs (i.e.,
procurement management plan, procurement documents, supplier evaluation
criteria, proposals, selected sellers, contract, , contract management plan, and
contract documentation) and long-term project success (i.e., customer,
stakeholder and project team satisfaction, financial objectives, strategic
contribution of the project). The chi-square values were greater than the
critical value (5.991 by two degrees of freedom), and the p-values were less
than .05 in both the chi-square and Fischer’s exact tests. Therefore, the null
hypothesis that there is no significant relationship between project
procurement management and long-term project success was rejected.
V. DISCUSSION OF RESULTS
A total of 163 participants took the online survey. Eighty-nine percent
are male and 11.0% female. Nearly six percent are between 20 and 30 years
old, 36.8% are between 31 and 40 years old, 46% are between 41 and 50
years old, and 11.7% are older than 50. Their work experience ranges from
less than two years (4.3% of total) to more than 20 (25.2%), but all
respondents (100%) are involved in project work. Project management
experience ranges from fewer than two years (1.8%) to more than 20 (6.1%).
Nearly 87% earned a project management certification, 76.1% earned the
Project Management Professional
(PMP) certification, 1.1% earned the Program Management Professional
(PgMP), 3.3% earned the PMI Agile Certified Practitioner (PMI–ACP) SM,
1.1% earned the PMI Risk Management Professional (PMI– RMP), and
0.6% earned the Certified Associate in Project Management (CAPM).
Eighty-five percent are project managers, 4.9 % are project coordinators, and
4.3% are project team members. Their projects comprise engineering
(14.1%), construction (1.8%), information technology (68.7%), enterprise
resource planning (4.9%), and infrastructure design and development
(1.8%). Nearly 10% of those projects took an average of under six months
(9.8%), and 3.1% of them took more than 48 months. Approximately one
half (49.7%) are working on projects for external clients, 25.8% for internal
clients, and 24.5% a combination of both. The sizes of the project teams
range from fewer than five members (4.3%) to more than 100 (4.9%). The
most common last project completion date was five years ago or less
(98.9%), followed by more than five years ago (1.2%). The sizes of the
project budgets range from less than $100,000 (4.3%) to more than $50
million (1.8%). Their business areas are computers/Information technology
(24.5%), construction (3.2%), engineering (12.2%), education (1.4%),
government (5.5%), health care (5.0%), manufacturing (9.6%), software
development (15.4%), and telecommunications (15.6%).
Project Success Criteria:
According to the survey, the top-nine criteria for judging project
success are budget/cost (79.8%), schedule (73.0%), customer satisfaction
(58.3), stakeholder satisfaction (37.4%), scope (31.9%), financial objectives
(30.1%), technical objectives (22.7%), customer approval (20.9%), and
profitability (20.9%). Schedule, budget/cost, scope, and technical objectives
are short-term or past-oriented criteria (POC). The remaining criteria -
customer and stakeholder satisfaction, financial objectives, customer
approval, and profitability - are long-term or future-oriented criteria (FOC).
These results reveal that five of the top-nine criteria for judging project
success are long-term success criteria and four are short-term success
criteria.
Project Type and Project Success Criteria:
The study reveals that the criteria used to judge project success are
related to project type. For engineering projects, the top three project success
criteria are budget/cost (82.6% within this project type), schedule (78.3%),
and customer satisfaction (56.5). In construction projects, the criteria used
are budget/cost (100%), profitability (66.7%), and schedule (33.3%). In IT
projects, the criteria used are budget/cost (80.4%), schedule (75.9%), and
customer satisfaction (60.7%).
Project Size and Project Success Criteria:
The results reveal that project success depends on project size.
According to the survey, all project sizes use budget/cost as project success
criteria. For projects of more than $50 million, the scope, not the schedule, is
considered the most important criterion of project success. Customer
satisfaction is not used in projects of less than $100,000. Stakeholder
satisfaction is important for projects over $1 million and less than $10
million.
45. Demographic characteristics o (1)
Frequency Percent
Gender
Age
Male
Female
20 - 30 years
145
18
9
89.0
11.0
5.5
31 - 40 years 60 36.8
41 - 50 years 75 46.0
Older than 50 years 19 11.7
Work experience
Less than 2 years
1
.6
2 - 5 years 7 4.3
6 - 10 years 30 18.4
11 - 20 years 84 51.5
More than 20 years 41 25.2
Project work
Yes
163
100.0
No 0 0.0
Last project completion
Five years ago or less
161
98.8
More than five years ago 2 1.2
Size of project budgets
Less than $100,000
7
4.3
More than $100,000 - Less than
$1 million
66 40.5
More than $1 million - Less than
$10 million 67 41.1
More than $10 million - Less
than $50 million 20 12.3
More than $50 million 3 1.8
Function of the project
Project manager
139
85.3
Project coordinator 8 4.9
Project team member 7 4.3
Steering committee member 1 .6
Advisor 1 .6
46. Demographic characteristics o (2)
Frequency Percent
Project type Engineering 23 14.1
Construction 3 1.8
Information technology 112 68.7
Enterprise resource planning 8 4.9
Infrastructure design and
development 3 1.8
Other
14
8.6
Project purpose Internal client 42 25.8
External client 81 49.7
Both 40 24.5
Size of project teams
Fewer than 5
7
4.3
5 - 10 38 23.3
11 - 20 46 28.2
21 - 50 52 31.9
51 - 100 12 7.4
More than 100 8 4.9
Project duration
1 - 6 months
16
9.8
7 - 12 months 60 36.8
13 - 24 months 63 38.7
25 - 36 months 16 9.8
37 - 48 months 3 1.8
More than 48 months 5 3.1
Industry areaa
Computers / Information
technology
107
24.5
Construction 14 3.2
Engineering 53 12.2
Education 6 1.4
Government 24 5.5
Health care 22 5.0
Manufacturing 42 9.6
Software development 67 15.4
Telecommunications 68 15.6
Other 33 7.6
47. Demographic characteristics o (3)
Frequency Percent
PM experience Less than 2 years 3 1.8
2 - 5 years 29 17.8
6 - 10 years 62 38.0
11 - 20 years 59 36.2
More than 20 years 10 6.1
PM certification
Yes
141
86.5
No 22 13.5
PM certification
Certified Associate in Project
1
0.6
typea Management
(CAPM)
Project Management Professional
(PMP)
137 76.1
Program Management Professional
(PgMP)
2 1.1
PMI Agile Certified Practitioner (PMI
- ACP) SM
6 3.3
PMI Risk Management Professional
(PMI -
RMP)
2 1.1
Other 32 17.8
PM software useda
Basecamp
3
1.3
Microsoft Project 146 63.5
Smartsheet 4 1.7
Projectplace 7 3.0
PLANTA Project 2 0.9
2-plan 2 0.9
Other 66 28.7
Source of the
software
Commercial Software
92
56.4
Company's own Software 12 7.4
Combination of both 56 34.4
Other 3 1.8
a. Dichotomy group tabulated at value 1.
Relationship between project integration management and long-term
project success
The results presented in Chapter Four reveal significant evidence of a
relationship between project integration management and long-term project
success.
Project charter – Sales: The project charter is a document authorizing a
project within an organization and giving the project manager the necessary
authority to assign project activities to human and/or technical resources.
When the management officializes a project, all involved in that project feel
comfortable because they face fewer problems than they would if they
lacked a project charter; a charter lessens the potential for resistance to
reduce the available resources necessary for a project. Projects are ranked in
a project charter according to key commercial indicators. This ranking
allows top management, stakeholders, sponsors, and project owners to
prioritize projects. As a project charter includes product and service sales,
activities could begin at this stage (i.e., project initiating). A charter’s project
ranking and key commercial indicators could have either a negative or
positive affect on sales; thus, lower priority projects may have less sales than
higher priority ones.
Preliminary project scope and project Management plan – Stakeholder
satisfaction: A preliminary project scope statement defines a project’s
scope. It is used as an agreement between stakeholders about the project’s
scope and objectives. With this document, all stakeholders “speak the same
language.” A preliminary project scope statement setting out the project
requirements and expectations, the criteria for measuring project success,
and product or service objectives that are measurable, attainable, and
realistic, which is then coordinated with a project management plan
including all project planning documents, could contribute to stakeholder
satisfaction.
Implemented preventive actions – Financial objectives: In order to
reduce or eliminate project risks, a project team defines measures during the
product or service development to prevent any non-conformities. The
measures defined depend on the project team’s experience. Simple and
cheap solutions can sometimes be used to reduce or eliminate non-
conformities, but actions required by the customer can be expensive or
impact project profitability or financial objectives (e.g., if customers compel
their suppliers to implement a 100% final visual check before delivering
products, executed by three shifts every day during the product life cycle).
Therefore, preventive actions could help firms achieve their financial
objectives.
Forecasts – Performance objectives: Project managers regularly report
project statuses to the project steering committee. These reports include the
progress of the projects and forecasts. If the latter indicate that the
performance objectives will not be achieved, further intervention from the
management or project steering committee will be needed. Performance
objectives that are definitely not attainable should be reviewed and updated
with the project owner or customer; this can occur in product development
projects, when the product fails to meet customer specifications because the
test values or conditions were exaggerated.
Therefore, forecasting could impact the performance objectives.
Rejected change request – User satisfaction / Technical objectives:
Changes are common during the development phase of a product or service.
Modifying the material of a product by drawing from another one with
higher or lower material characteristics will impact the technical objectives.
Changing the terms or conditions of a service could also contribute to either
the satisfaction or dissatisfaction of the service users.
Relationship between project scope management and long-term project
success
Scope baseline – Project team satisfaction / Profitability: Project
managers track the progress of their projects by using baselines, one of
which is the scope baseline, which measures how far a project is meeting its
project scope objectives. Project teams are often faced with the unofficial
enlargement of an approved project scope, which then requires additional
human and technical resources. Such a circumstance could contribute to
project team dissatisfaction and impact profitability. If the scope remains
unchanged and the project team meets its scope baseline; however, the
project should be achieved.
Relationship between Project Time Management and Long Term Project
Success
Activity list / Activity attributes / Activity resource requirement and
RBS – Customer satisfaction: The project customer pays the costs of
product or service development as a lump-sum or amortized cost in the
product or service unit price. The supplier must justify these costs by
submitting a detailed breakdown based on an activity list that includes the
work to be performed for the project, the resources needed for each activity,
and the responsible people. The customer’s purchasing department needs
this detail to justify the costs internally. When the customer and supplier
sign the contact for the development costs, it can be assumed that both
parties to this contract (the purchasing department on the customer side and
the sales department on the supplier side) are satisfied. Therefore, the
activity list and related activity attributes, the activity resources, and the
derived resources breakdown structure (RBS) could contribute to customer
satisfaction during the negotiation phase and thus impact sales.
Resources calendar – Performance objectives: A resources calendar is
created to show who (i.e., the human resources) or what (i.e., the technical
resources) are assigned to which project activities and when. Human
resources abilities differ from one person to another. An experienced design
engineer needs less time to develop a product than an engineer with less
experience.
Technical equipment and resources also have different capacities, which could
impact the completion date and thus the project schedule. Therefore, the
resources calendar could influence the performance objectives.
Project schedule – Customer satisfaction: Using the project milestones
submitted by the customer, the project manager builds in accordance with
the project team and all involved parties (both internal and external) the
project schedule, which includes a planned start and finish date for each
activity to be performed. Activities are usually scheduled to meet the
customer requirements set for each milestone. Thus, the finishing and
milestone dates must be coherent. In later phases of the project, this schedule
is used to show the progress of the project to the customer or steering
committee; in this case, the schedule includes the percentage of work
accomplished. Using a project schedule to show the customer that the project
is in line with the time requirements and that the project’s activities are all
planned and its resources assigned could contribute to customer satisfaction.
Relationship between Project Cost Management and Long-term Project
Success
Activity costs estimates supporting detail – Customer satisfaction and
approval: As mentioned, the customer pays the costs for development
activities as a lump-sum or amortized cost in the product or service unit
price. During the cost negotiation phase, the customer expects details about
the estimated costs, such as a detailed breakdown and information or
documents supporting the plausibility of the estimation. Once the customer
is satisfied with the cost estimation, the development phase is commercially
approved. Therefore, using activity cost estimates with supporting detail
could contribute to customer satisfaction, the basis of a commercial
partnership. If such satisfaction is achieved, the development cost should be
approved.
Cost baseline – Customer approval: One of the baselines project managers
use to track the progress of their projects is the cost baseline, which
measures how a project is meeting its cost objectives. A project’s target
budget should be maintained. The project manager is responsible for
optimizing activities that could push the project into cost overruns.
Development budgets are sometimes agreed upon with the customer; the
project manager must justify development cost overruns to the steering
committee and the customer. Meeting the cost baseline could contribute to
customer satisfaction and lead to cost underruns, to the commercial benefit
of both customer and supplier. When the customer’s cost expectations are
met, there should be no obstacle to the approval of justified costs.
Relationship between Project Quality Management and Long-term Project
Success
Quality management plan – Customer and stakeholder satisfaction:
Each customer expects his goods or services to be delivered in the right
quantity, on time, and with the agreed quality. A quality management plan
includes documents describing how the quality of goods is assured and
controlled. These documents are created in the product development phase
and used in the realization phase. They cover the whole realization process,
from the inspection of raw materials to the final check before dispatch. Some
automotive suppliers implement additional quality checks at the customer
plant before the products hit the assembly lines to achieve a zero-reject rate
(0 PPM); this is managed quality. A customer who receives only quality
goods will never complain, and all stakeholders will be satisfied. Therefore,
well-managed quality through comprehensive quality management
contributes to customer and stakeholder
satisfaction
Recommended corrective actions – Strategic contribution of the project:
Continuous improvement is a goal-oriented activity within the quality system
that helps organizations and manufacturing companies enhance the quality of
their services or products. The outputs of the continuous improvement process
are effective actions, either preventive or corrective,
recommended for implementation. These actions could affect the entire
organization and represent an overall improvement, which could then have a
significant and strategic effect.
Relationship between Project HR Management and Long-term Project
Success
Roles and responsibilities / Staffing management plan – Stakeholder and
user satisfaction: It is useful to have lists describing everyone involved in a
project, their roles (i.e., the project activities to be performed by each person),
their decision-making authority, and their competencies. These lists show
stakeholders the levels of skills and competencies required by the project and
who is assigned to the project activities. A good fit is required between task
and worker; sometimes, additional competencies must be acquired (e.g.,
through a staffing management plan), or the project will be put at risk.
Therefore, defining the roles and responsibilities concerning project activities,
combined with a staffing management plan, could contribute to stakeholder
and user satisfaction.
Relationship between Project Communication Management and Long-
term Project Success
Communication management plan – Customer satisfaction:
Communication in projects is key - communication in teams, in groups,
between teams and groups, and through internal and external
communication, such as with suppliers and customers. Project management
comprises many processes, each receiving inputs and outputs. One output
could be an input for another process. Therefore, inputs and outputs must be
communicated throughout a project. A project communication plan defines
communication types, when to communicate, who should communicate, and
when the communication should take place (e.g., in monthly project steering
committee meetings or meetings with customers). The format of the
presentation and the topics are often standardized for all projects. Project
managers report the status of their projects monthly, and the customer or
steering committee ideally reacts appropriately when something goes wrong.
Therefore, a communication management plan could contribute to customer
satisfaction
Relationship between Project Risk Management and Long-term Project
Success
Risk management plan - Profitability: A risk management plan is a
predefined procedure for evaluating the probability of events that could have
a negative effect on project outcomes. The evaluation could be monthly,
quarterly, or during each project phase. The risk evaluation should involve
the entire project environment, customers, markets, suppliers, schedule,
economics, human and technical resources, product, process, and quality.
Project managers evaluate a list of categories in detail using a risk topology
according to an internal scale similar to a Likert scale: 1 for no risk, 2 for
low risk, 3 for moderate risk, 4 for high risk, and 5 for very high risk.
Management support is required in high and very high-risk cases. When a
customer changes the scope of an ongoing new product development project,
the development time may be increased as a result, possibly requiring
additional resources and delaying the product’s market entry. Either result
could have a negative effect on project profitability. Thus, managing risk in
preventive and proactive ways is required.
Relationship between Project Procurement Management and Long-term
Project Success
A supplier could also be a customer at the same time. Suppliers can be
customers of sub-suppliers, thus enjoying a customer/supplier relationship
involving management by a supplier management team on one side or
customer management on the other from first contact (i.e., in a project-
related request for a quotation), throughout all project phases and during
product or service
realization, until the contract closure (i.e., end of the product or service life
cycle).
Procurement management plan / Procurement documents / Supplier
evaluation, Supplier selection - Customer, stakeholder, and project team
satisfaction: A procurement management plan is a company’s structured
method of defining and establishing the steps required for managing
purchases and acquisitions in a project. The procurement management plan
ensures that suppliers or sub-suppliers are following the customer’s or end-
user’s policies. Supplier or sub-supplier problems regarding quality,
deliveries, or commercial issues concern stakeholders, who must spend
much time and effort solving the problems. Thus, managing suppliers and
sub-suppliers effectively using a procurement management plan that
complies with customer needs and
evaluates, selects, and rewards suppliers and sub-suppliers who are
competitive in terms of cost and quality could contribute to customer,
stakeholder, and project team satisfaction.
Make-or-buy-decisions – Commercial benefit for customer: Projects
follow make-or-buy procedures to define which services, products,
components, or systems must be acquired externally. Decisions are taken
after the signature of the contract with the customer, project sponsor, or end-
user (if any). These decisions are cost- , quality-, or capacity-oriented. Cost-
oriented decisions can impact the business position of a project positively.
The decision whether to make molding tools and stamped or molded sub-
components in Germany or in low-cost countries like Slovakia or Romania
is significant for a project’s financial objectives. Customers may request cost
or price reductions. Therefore, a make or buy decisions could benefit both
the customer and the supplier.
VI. CONCLUSIONS AND FUTURE RESEARCH
This dissertation set out to investigate the role that the project
management body of knowledge plays in helping organizations and
companies to improve the resulting project outcomes and achieving
predetermined short- and long-term project success. In this final chapter the
following will be reviewed and / or discussed: the research contributions of
this dissertation, the directions for future research, implications and finally
the framework.
One of the more significant findings to emerge from this study is from
the top-nine used criteria for judging project success five of them are long-
term success criteria and four are short-term success criteria. Profitability
could be considered, as strategic objectives, that projects tend to achieve.
Therefore, this finding confirms the suggestion of Cleland (1986) to consider
project success of two views: 1) the fulfillment of predetermined technical
requirements an time and within budget, and 2) the achievement of the
Strategic objectives. The second major finding was that project success
depends on project type and project size, therefore the emphasis of the
project success criteria is different for different project types. For
construction projects, the top-three project success criteria are budget/cost,
profitability, and schedule. For engineering and information technology
projects, the emphasis is different, thus budget/cost, schedule and customer
satisfaction. However, customer satisfaction is not used for judging projects
of size less than $100,000. It seems also that the schedule it not the focus of
project of the size more than $50 million.
These findings confirm the observation of McCoy (1986) that there is
no generally accepted definition for project success and that there is neither a
generally accepted definition for project success nor guidelines to measure.
The study has gone some way towards enhancing our understanding
of the project management body of knowledge represented in the nine
knowledge areas and the related project management process groups. The
empirical findings in this study contribute to existing knowledge in project
success criteria and project success factors by providing an operational link
between these factors, outputs of the project management groups, to the
project outcomes or project measurement criteria. The present study
confirms previous findings that confirmed the role of project management in
achieving long-term project success and contradicts those studies stating that
the role of project management is limited to the controlling of cost, budget
and scope.
Although the study has successfully demonstrated that the project
management body of knowledge contributes to both short-term and long-
term project success, and that the project success depends on the type and
size of the project to be judged, it has certain limitations in terms of the
perspective of different functions in the project management filed. The
sample was representative in term of Knowledge and experience in the
project management field. A large proportion of the participants are project
managers, who are familiar with the project management processes, but the
question regarding which criteria are used to judge project success and
which factors contribute that success, the sample would tend to miss a
representative proportion of participants who are project team members,
project committee members, etc. … in order investigate the interdependence
between the function on the project and the perspective regarding the success
measurement. As stated by Freeman and Beale (1992),
“an architect may consider success in terms of aesthetic appearance, an
engineer in terms technical competence, an accountant in terms of dollars
spent under budget, and chief executive officers rate their success in the
stock market". The population from which the sample was drawn does not
constitute a homogeneous group, therefore a stratified sampling technique
will be recommended for further research in order to obtain a representative
sample.
The strata could be formed on the basis on relevant common characteristics
like:
(a) function on the project; (b) project type; (c) industry; and (d) project
budget.
Contributions
To the best of our knowledge, this study is the first one investigating
the relationships between all outputs of the project management body of
knowledge processes and the project success. Nine knowledge areas
(integration management, scope management, time management, cost
management, quality management, communication management, risk
management, human resources management, and procurement
management), and four project management process groups (initiating,
planning, executing, monitoring, and controlling) have been investigated.
Figure 32. Study Framework
Figure 33 Framework Results
•Favorably empirical contributions that consist of new findings based
on systematically observed data and provide new data to reveal formerly
unknown insights about the project management body of knowledge and
its
relation to short- and long- term success.
•Methodological contribution that support practitioners analyzing and
improving the project outcomes by using the theory of constraints as
problem solving process. It provides an organized and structured view,
how to deal systematically with undesired project outcomes. As example
this process was applied to customer satisfaction (see. Section
Methodological Framework)
•A general classification of the top nine used criteria for judging project
success, (1) budget/cost, (2) schedule, (3) customer satisfaction, (4)
stakeholder satisfaction, (5) scope, (6) financial objectives, (7) technical
objectives, (8) customer approval, and (9) profitability. This classification
provides an organized overview of short-term and long-term criteria for
measuring the project outcomes.
•A specific classification of the top three criteria used to judge project
success in relation to project type. For engineering and information
technology projects, the top three project success criteria are (1)
budget/cost, (2) schedule, and (3) customer satisfaction. In construction
projects, the criteria used are (1) budget/cost, (2) profitability, and (3)
schedule.
•The top criterion used to judge project success in relation to project size.
All project sizes use budget/cost as project success criteria. For projects
of more than $50 million, the scope, not the schedule, is considered the
most important criterion of project success. Customer satisfaction is not
used in projects of less than $100,000. Stakeholder satisfaction is
important for projects over $1 million and less than $10 million.
Future research
Further research needs to examine more closely the links between
project selection criteria and project success criteria. Another possible area
of future research would be to investigate which elements and processes of
the project management body of knowledge are implemented and used in
companies and organizations with the objective to explore the relationship
between their project success rate and those implemented processes.
Implications
The findings of this study have a number of important implications for
future practice and therefore several courses of action will be recommended.
Project success criteria should be defined at the beginning of each project
and should be logically linked to criteria used during the project selection
and the factors that contribute that success. The results of this research
support also integrating a set of project success criteria that are valid for all
projects, thus General Project Success Criteria (GPSC), and project related
success criteria, which are specific to each project (SPSC, specific project
success criteria).
General Project Success Criteria could be e.g. budget/ cost, schedule, scope,
technical performance, etc… and Specific Project Success Criteria could
include such criteria such like market share, strategic contribution of the
project.
Methodological Framework
Doubtless, delivering projects on time, within budget, and within the
predefined scope remains the basic requirement for business and represents
just an “entrance card” into the market. In order to be competitive and
achieve longterm success with projects linked to the company’s or
organization’s strategy; however, the abovementioned three project
achievements are not enough. Achieving more advantages requires a
structured project management that considers projects in their entirety - from
project selection to the end of the product or service life cycle. This is only
realizable if long-term project measurement criteria are implemented and
reported continuously. Based on the findings of this study and the
researcher’s experience in project management, the following are
recommended:
•Develop a set of project selection criteria that enable management and
support during the decision-making process about which projects should be
realized.
•Make sure that the entire organization understands the project selection
criteria.
•Have a project portfolio in the organization and make it known. It helps to
have a one-page (minimum) description of two project selection criteria
that can be used to justify the prioritization of one project or project groups
over others.
•Make the project prioritization known in your organization in order to
avoid resources conflicts.
•Develop a set of criteria supporting project success judgments. It will
outline what should be achieved and when at the beginning of each project.
The criteria should be understandable by the project team and manager and
contain short-term and long-term criteria linked to the organization’s
strategy and long-term goals. The criteria should consider projects in their
entirety and not only criteria like budget, cost, schedule, and scope.
•Make a logical link between the project selection and project success
criteria.
•Identify which factors could contribute to the achievement of project
success, measured by the project success criteria, and link the project
success factors to the project success criteria. The findings of this study
could be used as an orientation.
•Implement, execute, and manage the factors that contribute to project
success.
•Develop a set of criteria by which to judge the risk in the entire project
environment - including customers, markets, suppliers, schedules,
economics, human and technical resources, products, processes, and
quality - and make sure that the project team and project manager are
familiar with the risk evaluation and report.
•“Educate” your customers and support them in defining their expectations,
and try to meet their unwritten expectations.
•Transform the informal communication between the development teams
(i.e., customer and supplier) into a formal communication; any minor or
major changes required by the customer or supplier should be evaluated
technically and economically.
•“Educate” your customers and suppliers about your internal policies.
•Steering committee meetings should be decision meetings and not only
informal meetings.
•Train your staff in project management and inter-personal skills, and train
your project manager in leadership.
The following framework demonstrates the theory of constraints as
problem solving process applied to customer satisfaction (example) (see
Figure
32).
What to change?
•Identification of the core conflict that is responsible for the undesired
project outcomes.
The undesired effect in this case is the dissatisfaction of the customer.
Possible causes could be the quality, the availability, reliability and the
plausibility of one or more of following project management process
outputs:
H3-01 Activity list: output of activity definition process – Project time
management
H3-06 Resource breakdown structure: output of activity resource estimating
process - Project time management
H3-09 Project schedule: output of schedule development process - Project
time management
H4-02 Activity cost estimates supporting detail: output of cost estimating
process - Project cost management
H4-04 Cost baseline: output of cost budgeting process - Project cost
management
H5-01 Quality management plan: output of quality planning process - Project
quality management
H7-01 Communication management plan: output of communications planning
process - Project communication management
H9-01 Procurement management plan: output of plan purchases and
acquisitions process - Project procurement management
H9-08 Proposals: output of request seller responses process - Project
procurement management
H9-09 Selected sellers: output of select sellers process - Project procurement
management - Project procurement management
H9-10 Contract: output of select sellers process - Project procurement
management
H9-11 Contract management plan: output of select sellers process - Project
procurement management
•Build a current reality tree that describes the non-conformities of the
outputs mentioned above and their link to the customer dissatisfaction.
What to change to?
•Identification of actions to improve the quality, availability, reliability and
the plausibility of the outputs. Process und human resources related
actions.
•Construct a Future Reality Tree that lays out the complete solution that:
Resolves the undesired project outcome (customer dissatisfaction)
by making its opposite, the desired project outcome (customer
satisfaction).
Ensures alignment with the project and organization objectives.
Ensures that no new negative side-effects (Negative Branches) will
occur from implementing the solution.
Leverages the existing TOC applications that are needed to make the
solution work, and
How to cause the change?
•Build a Tactical Objectives Map that charts the overall course for getting
from the current reality to the future reality, where the solution is fully
implemented.
•Create detailed task interdependency diagram, using Transition Trees
(TRTs) when necessary to flesh out crucial actions.
•Transform action plans into a complete project network that can be
effectively managed
Figure 34. Theory of constraints applied to customer satisfaction
