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The 7
th
IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications
12-14 September 2013, Berlin, Germany
Factors Influencing Project Success Criteria
Bassam A. Hussein
Norwegian University of Science And Technology, Trondheim. Norway
Abstract— This paper uses a literature review to present
the risk factors that are most common to project success
criteria through a project’s entire life cycle. Empirical
investigation and statistical analysis examined correlations
between these factors. On the basis of the statistical
correlations found we conclude that there are four factors in
the initiation phase that could lead to the occurrence of
additional risks factors in the implementation and
evaluation phases. These are 1) having an incomplete set of
criteria due to lack of knowledge about project context, 2)
diverse and competing expectations about gains and
benefits, 3) basing the project on unrealistic targets, and 4)
using ambiguous criteria to describe the expected benefits or
gains from the product or the project result. These factors
affect all aspects of management and evaluation. The
presence of these factors is also statistically correlated to the
presence of other factors such as lack of organizational
commitment and weakened alignment to success criteria in
the performing organization and subjective assessment of
the project outcome during evaluation phase.
Keywords—project success; success criteria; project
managaement
I. INTRODUCTION
Research into project success criteria in project
management literature can be grouped into three major
classes.
A. Clusters of success criteria
A class of research that focuses on defining what
constitutes project success includes categories concerning
stakeholders, timeline, project size or type [1-4]. This
research also extends to examining how the perception of
success has changed over the years [5-9]. This section of
research is indeed the most dominant in project
management literature on the subject, and it seeks to
define a clear rational for deciding whether the project
was a success/failure, and to some extent, the degree of
success/failure. It was de Wit [5] who first suggested a
distinction between project success and project
management success. Project success embodies the
perceived value of a project when the result or product is
in operation. Project management success, on the other
hand, is considered the ability to comply with time, cost,
and scope requirements. These triple constraints are
called, in literature, the "golden triangle" and are
concerned with the efficiency of the project organization
[10]. Project management success is also described as a
narrow view of success [11].
Similar distinctions were suggested by Baccarini [3],
who also distinguished between project management
success and product success. Product success measures
the benefits of a project's final product. Lim and
Mohamed [2] made the distinction between micro and
macro success. The micro perspective refers to the
success perceived by the contractor or performing
organization and the developer, during the
implementation phase. The macro perspective refers to
the success appreciated by other stakeholders and users
over the entire project life cycle.
B. The rational fordefining success criteria
The second class of research is less dominant in
project management literature and looks into the
significance of the criteria as a tool for shaping and
managing a project.
According to Christenson and Walker [12] defining
success criteria upfront is helpful to establish agreement
on how and when a project will be evaluated, which helps
create a common vision about the outcome, which is in
itself a significant driver of project management success.
Jugdev and Müller [13] supported this view and
recommended defining a project’s success criteria at the
start as good project management practice.
Creating a common reference point for how projects
will be evaluated is an important factor in aligning the
project team and establishing commitment to the project
objectives. Korzaan [14] showed that commitment to
project objectives has a positive influence on perceptions
of project performance both directly and indirectly
through individual propensities to report project status
information.
Hussein [15] showed that failing to actively using
project success criteria in managing projects can lead to
numerous and frequent change of criteria which in turn
result in poor project performance, frustrations, and even
losses. Poor management leads to poor intermediate
results. Poor intermediate results lead to changing project
priorities and this causes a project to lose focus [17]. A
project’s success criteria are also important for project
risk management. It is now widely accepted that even
moderate levels of risk management planning are
sufficient to increase the chances of project success
C. Risk factors associated with success criteria
The third category of research into success criteria
considers the potential threats and challenges influencing
the initial definition of criteria, as well as the
implementation and evaluation phases. These risk factors,
if not accurately addressed at the start of the initiation
phase, will lead to further complications in the execution
and evaluation phases of the project. The risks found in
project literature include:
• The narrowness of the criteria
Narrow focus refers to selecting a limited set of
criteria that measures the focus on project management
success. A narrow focus may reflect weak alignment
between projects and businesses. Several authors,
however, stressed the importance of regarding projects as
tools for value creation in an organization [21-23]. This
missing alignment may lead to several challenges for the
performing organization during the execution phase such
as lack of commitment, or lack of top management
support which are both important success factors for
projects [24-26].
• Ambiguity
Ambiguity refers to the use of success criteria which
may be differently interpreted [27]. Ambiguous criteria
are also known as soft or subjective criteria [28]. Hussein
[15] gave several examples of ambiguous criteria
including user satisfaction, the quality of being intuitive
in use, user friendliness, ease of use, and safety. This
category of criteria is hard to measure and therefore
control. Time taken to clarify and understand the criteria
may subject them to new interpretation and therefore to
change, and might lead to improper allocation of
resources or to misunderstandings in the performing
organization.
Several authors have already stressed the importance
of measurability of project objectives, through the use of
SMART rule for instance [29]. Ambiguity also influences
the way measurements are conducted after handing over.
The difficulties of how to measure ambiguous criteria
were also taken up in [9]. According to the author,
success and failure are not only subjectively perceived
and constructed by people, but are also entwined in
meaning and action. A symbolic and rhetoric evaluation
of project success and failure was therefore suggested by
[9] to encounter the effect of ambiguity.
• Diversity
The presence of competing and conflicting criteria
due to the diversity of a stakeholder’s interest, power and
influence is another factor that complicates the selection
of success criteria. Westerveld [11] acknowledged the
complications of agreeing on project success criteria not
only because of competing criteria, but also because
judgment is generally made by several and diverse
stakeholders over different periods of time. Diversity
reflects the degree of variation among stakeholders or
within the project scope [30]. The diversity of
stakeholders may involve geographical locations, national
cultures, working practices, awareness of objectives (goal
misperception), and the variety of skills or disciplines that
are used in a project. The challenge that faces projects is
how to accommodate the diverse, and even contradictory,
expectations of all the stakeholders.
• Incompleteness
An additional factor that complicates the definition of
project success criteria is uncertainty, or a lack of full
knowledge about the range of project stakeholders at
start-up [32], or lack of knowledge about the full range of
use of the product or system. This is part of the
fundamental uncertainty that characterizes project
management [33].
• Changes
There is another dimension of uncertainty that might
take place during exaction or at a later stage of the
project. Such as, the impact of changing political factors,
changing owners, changing state regulations, changing
strategy or focus. Other changes may include suddenly
urgent needs that force a project to change priorities or to
add new criteria, or regulations, or new contextual
conditions to meet these urgent needs. These kinds of
changes are inevitable and are a part of the uncertainty in
projects which is often cited as a lack of “true”
knowledge [34].
• Unrealistic targets
Something that leads to the imperfect definition of
success criteria is the (blown optimistic) expectation
regarding the target of, for example, time, cost, or
expected benefits [35]. This may lead stakeholders to
perceive a project that was in fact successful in achieving
near-optimal results as a partial failure. How success is
defined affects the final judgment of success and
failure [36].
• Poor alignment of the performing organization to
success criteria
A lack of alignment with project success criteria in
the performing organization is another risk factor that
might complicate project management. Thomas and
Fernández [37] found that companies with high levels of
confidence in their IT projects not only agreed on a
definition of success and consistently measured success,
they also used the intermediate results actively in
managing projects. This included; 1) the management of
the project according to the agreed definition of success,
2) a willingness to stop projects, 3) accountability for
results, 4) and a connection to learning. They further
found that companies without accountability for results
tended to complete ex-post evaluations inconsistently or
not at all. There also appeared to be a greater tendency
for politically motivated misrepresentations.
Couillard [38] demonstrated through a field study the
correlation between an understanding of project
objectives and effective project risk management.
Hussein [15] provided several examples of how poor
alignment impacts outcome.
! Lack of organizational commitment to project
success criteria
According to Thomas and Fernández [37] companies
who used the criteria effectively were willing to re-direct
project resources based on an a priori understanding of
the relative importance of project success criteria and
were willing to stop projects. This resulted in improved
project management and better use of resources. This
implies that defining proper success criteria or clusters is
simply not enough in order to achieve excellence in
project management [39]. Proper measures in terms of
strategies, rules, resources, and metrics should also
accompany these success clusters. For instance, achieving
a long term and wider benefit requires the strong
involvement of the sponsor or project owner as disclosed
by Munns and Bjeirmi [40]. According to Belassi and
Tukel (1996), when time is important for achieving
project management success, then a project manager’s
skills, and communication between team members
become critical.
Other reported factors include a lack of ranking
among the criteria [41], and lack of a process or scheme
for measuring the achievement of long term objectives
after handing over [42].
II. RESEARCH OBJECTIVES
The literature review has shown that there are several
identified risk factors that contribute to poor management
and complications during identification, management and
evaluation of project success criteria. These factors are
shown and classified in three project phases;
initiation/planning, implementation and evaluation as
shown in Table I. The review has also shown that project
success criteria can be broadly grouped into two
categories; 1) criteria that describe important constraints
to which project organization must adhere during
execution. This includes, for example, criteria of time,
cost, safety, and scope/specifications. This is called
project management success criteria. 2) criteria that
identify the impact of the project results (the product) on
the end-users/ business/the performing
organization/communities. Examples of this category
include criteria involved with operational requirements,
user satisfaction, and ease of use, profitability, market
share, learning, and competence development, as shown
in Table II.
The goal of this paper is three fold; 1) to investigate
the correlation between the type of success criteria
selected and the occurrence of the risk factors presented
in Table I. 2) to examine correlations between these the
identified risk factors in each phase and risk factors in
other phases. 3) through regression analysis we intend to
most predominant risk factors in the initiation/planning
phase that impact other factors in the implementation and
evaluation phase. Answering these questions might help
project practitioners gain a better understanding about the
choices that are made during the planning and initiation
phases and to help them to better address significant risk
factors in a proper way from the start of the project.
TABLE I. RISK FACTORS INFLUENCING PROJECT SUCCESS
CRITERIA ALONG LIFE CYCLE PHASES
ID
number
Risk factor influencing the criteria
Phase
1
Use of unrealistic targets
(conservative or optimistic)
Initiation/planning
2
Use of ambiguous/soft criteria
Initiation/planning
3
Narrow focus (covering only project
management success)
Initiation/planning
4
Diversity (balancing conflicting or
competing criteria)
Initiation/planning
5
Lack of ranking among the criteria
Initiation/planning
6
Incompleteness (missing or omitted
criteria)
7
Lack of organizational commitment
(in the form of resources, support to
achieve the objectives)
Implementation
8
Lack of alignment in the preforming
organization
Implementation
9
Changing context
Implementation
10
Lack of scale of measurements
Evaluation
11
Subjectivity of measurement
Evaluation
12
Lack of long-term scheme for
measurement after handing over
Evaluation
TABLE II. BROAD CLASSIFICATION OF PROJECT SUCCESS
CRITERIA IN LITRATURE
Type
Examples
1- Project management success
Time, cost, scope
2- Project/ product success
Impact on (users, clients,
business, community)
III. METHOD
For this study, a web-based survey was devised and
sent to around 800 respondents worldwide. The survey
can be reviewed at [43]. The survey was anonymous, but
respondents had the opportunity to leave their contact
information if they were willing to discuss the results of
the survey with the author. Seventy-nine respondents
returned valid responses and six expressed willingness to
take part in in-depth interviews. In this paper we mainly
focus on the results obtained by the web survey.
Descriptive and analytical statistics will be used to
interpret the results. The reliability test for the
questionnaires gave a coefficient of 0.833 suggesting
high reliability. Respondents were asked to recall their
last project, or a project that they have thorough
knowledge about, and answer several questions. The
presentation of the results and the analysis of these
questions will be the subject of forthcoming papers. In
this paper we present the results obtained from two
questions.
Q1: Respondents were asked to select, from the
options given, the categories of project success criteria
that had been defined up front?
Q2: Respondents were asked to select, on a scale from
1 to 5, the degree to which they believed each of the risk
factors shown in Table 1 had encountered in their project,
where 1 means rarely and 5 means frequently.
The survey therefore collected information about the
observed occurrence of the risks and not about the
respondent’s opinion of the risk itself.
IV. FINDINGS
The results of the computed mean and median for
each factor is shown in Table III.
TABLE III. MEAN AND MEDIAN OF EACH FACTOR.
Issue or factor influencing success criteria
Median
Mean
Use of unrealistic targets (conservative or
optimistic)
3
3.21
Use of ambiguous / soft criteria
3
3.04
Narrow focus (covering only project
management success)
3
3.04
Diversity (balancing conflicting or
competing criteria)
3
3.09
Lack of ranking among the criteria
3
3.38
Incomplete (missing or omitted criteria)
3
3.19
Lack of organizational commitment (in the
form of resources, support to achieve the
objectives)
3
3.09
Lack of alignment in the preforming
organization
3
3.13
Changing context / uncertainty
3
3.41
Lack of scale of measurements
3
3.11
Subjectivity of measurement
4
3.37
Lack of long-term scheme for
measurement after handing over
4
3.34
According to the data shown in the table there are 6
factors that were encountered more frequently, as
reported by the respondents.
These factors are; in the initiation phase, 1) the use of
unrealistic targets (mean value: 3,21) and 2) lack of
ranking among the identified criteria (mean value: 3.38),
3) frequent changes to success criteria (mean value 3.41),
4) incomplete (mean value 3.19), 5) subjectivity of
measurements (mean value: 3.37), and 6) lack of method
to measure long-term success (mean value: 3.34). The
table also shows that the median of both last factors is 4.
The study also collected data from respondents about
the type of criteria used in their projects and the results
are shown in Table IV.
A median test using the grouping variable (Type of
success criteria) was also performed. The objective of
the test was to determine whether the distribution of each
factor across the grouping variable (Type of the criteria)
is the same. The frequency table for the median test is
shown in Table V. The table shows that the distribution
of (unrealistic target) is the same across the grouping
variable. This means that the type of criteria selected has
no impact on the occurrence of this factor. On the other
hand, distribution of (narrow focus) is not the same
across the grouping variable. The number of cases that
are higher than the median for Type 1 criteria are higher
than the number of cases for Type 2. This indicates that
the occurrence of (narrow focus) is evidently more
frequent when Type 1 criteria are selected. Two factors
(lack of ranking) and (incomplete) are frequent when
Type 1 criteria are selected. On the other hand,
(contextual changes), (lack of alignment in the
performing organization), and (lack of organizational
commitment) are more frequent when Type 2 criteria are
selected. Other factors remain unaffected by the grouping
variable.
TABLE IV. FREQUENCY TABLE OF TYPE OF CRITERIA
Type
Frequency
Percent
Type 1) Only Project management success
criteria
23
29.1
Type 2) Only Project success related criteria
30
38.0
Both Type 1 and Type 2
26
32.9
TABLE V. FREQUENCY TABLE FOR THE MEDIAN TEST.
Factor
Type 1
Type 2
None realistic target
> Median
8
12
<= Median
15
18
Ambiguous
> Median
8
15
<= Median
15
15
Narrow focus
> Median
15
7
<= Median
8
23
Diversity
> Median
8
15
<= Median
15
15
Lack of ranking
> Median
12
11
<= Median
11
19
Incomplete
> Median
12
12
<= Median
11
18
Lack of organizational
commitment
> Median
6
12
<= Median
17
18
Lack of alignment in the PO
> Median
6
14
<= Median
17
16
Changes
> Median
11
15
<= Median
12
15
The data was examined for statistical correlations
between the factors. A linear regression test was also
conducted to single out the most important predictors of
each factor. The significant correlations and the linear
regression test are summarized in Table VI. Only
significant correlations at the 0.01 level (2-tailed) are
shown.
The results obtained show, for instance, that in the
initiation/planning phase the presence of (use of
ambiguous criteria) is significantly correlated with the
presence of three factors; 1) diversity, 2) lack of
knowledge about stakeholders resulting in an incomplete
set of criteria, 3) and the presence of unrealistic targets
(overblown or pessimistic).
TABLE VI. SIGNFICANT CORRELATIONS AND LINEAR REGRESSION
TEST
Factor
Significant correlation at
the 0.01 level (2 tailed)
Liner regression test
Most important
predictor (importance )
Ambiguous
Diversity .382**
Diversity (.44)
Incomplete (.39)
Unrealistic target (0.17)
Narrow focus
Incomplete 0.298**
Incomplete (1)
Lack of ranking
Incomplete 0.376**
Incomplete (1)
Lack of
organizational
commitment
Use of ambiguous
criteria.402**
Diversity .400**
Incomplete 0.567**
Incomplete (0.61)
Diversity (0.19)
Ambiguous
criteria(0.18)
Alignment in
the performing
organization
Use of unrealistic
targets.346**
Use of ambiguous
criteria.340**
Diversity439**,
Lack of ranking among
the criteria.289**
Incomplete.353**
Use of unrealistic
targets (0.38)
Diversity (0.35)
Ambiguous
criteria(0.12)
Changes
Narrow focus.300**
Diversity .437**
Lack of organizational
commitment.302**
Alignment in the
performing
organization.390**
Diversity (0.44)
Narrow focus (0.35)
Alignment in the
performing organization
(0.2)
Subjective
assessment
Use of ambiguous
criteria.466**
Lack of organizational
commitment.366**
Attitude in the
preforming
organization.360**
Incomplete 0.404**
Use of ambiguous
criteria (0.57)
Incomplete (0.3)
The results also show that the having success criteria
that focuses only on the operational phase can be linked
to uncertainty about the full range of stakeholders or
operational requirements (incomplete). Lack of ranking
could also be attributed to the lack of full knowledge
about the stakeholders and their precise expectations.
In the execution phase, the effect of the risk factors
resulting from the initiation/phase is very evident. For
instance, Table VI shows that the occurrence of (lack of
organizational commitment) is correlated with three risk
factors (incomplete set of criteria, diversity, and
ambiguity). Results may therefore suggest that reducing
the occurrence of these factors or reducing their impact
should also help to increase top management support and
gain better commitment from top management.
Similarly, we may conclude that (alignment in the
performing organization) could also be enhanced by
avoiding or reducing the likelihood of occurrence of the
(use of unrealistic targets), having better methods of
addressing (diversity) in order to balance expectations of
the project. A combination of unrealistic targets,
competing expectations, and ambiguous formulation of
criteria does not contribute to better alignment of the
criteria in the performing organization.
Occurrence of changes during execution phase is
shown to be correlated to (diversity), (narrow focus) and
(lack of alignment in the performing organization). This
might imply that failing to balance diverse and competing
expectations from the start will lead to changes during
execution, and this may lead to further disruption and loss
of focus. The degree of changes that takes place during
the course of the project seems to be correlated with
(narrow focus). The higher the alignment of the project
success criteria with business goals (less narrow) the less
likely that there will be changes to the project.
In the evaluation phase, the use of subjective
evaluation could be attributed to two factors from the
initiation phase: ambiguity and lack of full knowledge
about stakeholders. This is no conclusion but an
observation in fact, the higher the use of ambiguous and
incomplete criteria the more likely that measurement will
also be based on subjective assessment. An inability or
failure to measure long-term criteria seems to be linked to
the subjectivity of measurements, that is, basing the entire
assessment on using rhetoric and subjective interpretation
of the outcome also contributes to failure to measure the
long-term criteria.
V. CONCLUSIONS
The goal of this paper was to conduct an empirical
investigation to examine the correlation between several
risk factors that complicate the definition and
management of project success criteria. On the basis of a
comprehensive literature review twelve different factors
were identified. A survey was then conducted in order to
collect empirical data about the frequency of occurrence
of these factors in real life projects. On the basis of the
statistical correlation we may conclude that there are four
factors in the initiation phase that, if occurring, will lead
to the occurrence of risk factors in the implementation
and evaluation phase. These are 1) having an incomplete
set of criteria, 2) diversity, 3) basing a project on
unrealistic targets, and 4) using ambiguous/no measurable
criteria. These factors affect all aspects of management
and evaluation.
From Table V we can see that the presence of the first
risk factor (incomplete set of criteria) is more evident
when Type 1 criteria are selected. This may suggest that
there is perhaps a need to better understand project
stakeholders who have influence on the project context in
order to ensure that success criteria includes all the
requirements. Diversity, on the other hand, is more
present when selecting Type 2 criteria. This suggests that
efforts should be made to balance stakeholder
expectations of gains or benefits from a project when the
product or service is in operation. The same applies to the
presence of ambiguous criteria, which is more evident
when selecting Type 2 criteria. Measurability of the
benefits or gains expected by the project should be
addressed more carefully.
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