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\begin{document}

\title{Project Delay And Cost Overrun In Software Industry In The Kingdom Of
Saudi Arabia: The Powerful Role Of Gqm}



\author[1]{Ahmad Abdullah Alghamdi N}%
\author[1]{Wajdi Al Jedaibi}%
\affil[1]{Abdullah}%


\vspace{-1em}



  
  \date{June 13, 2024}


\begingroup
\let\center\flushleft
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\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
\textbf{Background:} Given the enormous impact that the software
industry has on so many facets of our lives today, software projects are
extremely important. Digital transformation is driven across industries
by software developments. They facilitate the utilisation of technology
by organisations to optimise operations, augment productivity, and
provide inventive products and services. To be competitive and adjust to
the quickly changing market dynamics of today's world, companies must
undergo digital transformation by making full use of software projects.
\textbf{Objectives:} The main aim of the current study is to determine
the main causes of project delay and cost overrun in software projects,
identify the effects of project delay and cost overrun on software
projects, and define the role of cost estimation models in overcoming
project delays and cost overruns in these projects. \textbf{Results and
conclusions:}The researcher reviews the literature on causes behind
delay and cost overrun and describes the role that can be played by cost
estimation models in that process. In light of the reviewed literature,
the researcher reaches certain recommendations for the software
industry.%
\end{abstract}%



\sloppy


\emph{ART I C L E}

\textbf{Project Delay And Cost Overrun In Software Industry In The
Kingdom Of Saudi Arabia: The Powerful Role Of Gqm}

\textbf{Ahmad Abdullah N Alghamdi\textsuperscript{1} Dr. Wajdi Al
Jedaibi\textsuperscript{2} Prof.Abdullah S. Almalaise
Alghamdi\textsuperscript{3}}

\textsuperscript{\textbf{1}analghamdi@stu.kau.edu.sa}

\textsuperscript{\textbf{2 Waljedaibi@kau.edu.sa}}

\textsuperscript{\textbf{3 aalmalaise@kau.edu.sa}}

\textbf{Abstract} \textbf{Background:} Given the enormous impact that
the software industry has on so many facets of our lives today, software
projects are extremely important. Digital transformation is driven
across industries by software developments. They facilitate the
utilisation of technology by organisations to optimise operations,
augment productivity, and provide inventive products and services. To be
competitive and adjust to the quickly changing market dynamics of
today's world, companies must undergo digital transformation by making
full use of software projects.\textbf{Objectives:} The main aim of the
current study is to determine the main causes of project delay and cost
overrun in software projects, identify the effects of project delay and
cost overrun on software projects, and define the role of cost
estimation models in overcoming project delays and cost overruns in
these projects.\textbf{Results and conclusions:}The researcher reviews
the literature on causes behind delay and cost overrun and describes the
role that can be played by cost estimation models in that process. In
light of the reviewed literature, the researcher reaches certain
recommendations for the software industry.\textbf{KEYWORDS} Project
Delay - Cost Overrun - Software Industry - Cost Estimation Models

\textbf{INTRODUCTION}

Software is generated using programming languages, which can take
several forms. To be successful, a software project must be finished on
schedule and under budget, with all features and functionalities as
originally stated. However, some software projects fail for a variety of
reasons, and some are even terminated before they are done (Kamuni,
2015). The delay in software projects is considered one of the most
important causes of companies incurring high costs and losses that may
cause the failure of many systems. Timely project delivery is crucial to
avoid negative circumstances associated with delay (Lopes \& Ma\selectlanguage{ngerman}ñas,
2013). Project delays have negative impacts on cost overruns, project
quality, and stakeholders' satisfaction (Khalid et al., 2022). Accurate
time, effort, and cost estimation are crucial issues for a software
project's success (Chirra \& Reza, 2019). Prediction of a software
project's development effort, timeline, and cost is the goal of
estimation to avoid any delay (Laqrichi et al., 2015; Leung \& Fan,
2005; Mahboob et al., 2017). That is to say, Cost overruns and timing
delays in software development are regularly occurred. Software cost
estimation models and software complexity metrics measures are two
prevalent methodologies used by the industry to decrease the recurrence
of these difficulties.

\textbf{STATEMENT OF THE PROBLEM}

To determine how much time and effort software projects will take, cost
estimation of software projects is a crucial activity in the software
process development cycle. However, there are very few relevant studies
evaluating software cost estimation in developing nations, especially in
the Kingdom of Saudi Arabia. On one hand, Saudi Arabia is one of the
nations that has used cost estimation techniques (Gumaei et al., 2015),
which means that the current investigation into the causes of inaccurate
cost estimations of projects in this country's software development
companies is spurred by this issue. On the other hand, information and
communication technology (ICT) projects, especially software projects
still have high failure rates in the Kingdom of Saudi Arabia (Ebad,
2018).

Some researchers confirm that 44\% of software projects cost more and
take longer than anticipated (Laqrichi et al., 2015). The problem lies
in the fact that little focus has been placed on how project management
techniques and instruments have affected the frequency of project delays
in the Kingdom (Alotaibi et al., 2015). In addition, there is a paucity
of studies that have dealt with the use of software project management
tools in Saudi Arabia (AlMobarak et al., 2013). Despite the use of the
most up-to-date tools and techniques, numerous studies show that
software projects still fail (Mohabuth, 2017). Software project cost
estimation is a crucial management task. Despite research endeavours,
the precision of estimation tools does not appear to be improved
(Magazinius \& Feldt, 2011). Given the prevalence of software in today's
products, the large proportion of software projects that fail to meet
their deadlines, and the importance of product launches for the
financial viability of the product, further research into the problem is
needed (Rahikkala et al., 2016).

\textbf{QUESTIONS OF THE STUDY}

The questions of the study can be reviewed as follows:

\begin{enumerate}
\tightlist
\item
  What are the main causes of delays in software projects?
\item
  What are the effects of project delay and cost overrun on software
  projects?
\item
  What is the role of cost estimation models in overcoming project
  delays and cost overruns?
\item
  \textbf{OBJECTIVES OF THE STUDY}
\end{enumerate}

The objectives of the study can be reviewed as follows:

\begin{enumerate}
\tightlist
\item
  Determine the main causes of project delay and cost overrun in
  software projects.
\item
  Identify the effects of project delay and cost overrun on software
  projects.
\item
  Define the role of cost estimation models in overcoming project delays
  and cost overruns in software projects.
\item
  \textbf{SIGNIFICANCE OF THE STUDY}
\end{enumerate}

Cost estimation is still a difficult problem that motivates scholars to
look into and try out different strategies and approaches. To
efficiently manage project budgets, foresee risks, make educated
decisions, and control costs, companies can benefit greatly from the
insights and guidance offered by cost estimation models. They provide
the cornerstone for proactive cost management, which helps businesses
better handle project delays and overruns. In the current study, the
researcher will try to shed light on the causes of project delay and
cost overrun and how to overcome these challenges using cost estimation
models.

\textbf{DEFINITIONS OF THE STUDY}

\textbf{Delay}

A delay is a time overrun or an expansion of the project's completion
timeline (Hamzah et al., 2011). The researcher procedurally defines it
as the inability to deliver a software project on time. It is a critical
issue to be discussed in software projects because of its negative
effects on cost estimation.

\textbf{GQM}

The Goal/Question/Metric (GQM) approach is a measurement model that
allows quantitative evaluation of goal achievement within projects
(Khamis \& Aljedaibi, 2016). The researcher procedurally defines it as
one of the best tools to manage the measurement process, especially when
dealing with complex or overlapping variables.

\textbf{2. LITERATURE REVIEW}

The IT sector is complicated, which naturally increases the complexity
of initiatives undertaken in this field. Such big initiatives require a
high level of efficiency and activity. These projects are prone to
delays owing to a variety of difficult scenarios and challenges. Despite
considerable scientific research and better management practices,
software projects continue to struggle with a variety of challenges such
as delays, disputes, productivity loss, poor performance, and
coordination. Poor software project performance is a worldwide problem
(Kakaei, 2022).

Software development is divided into stages, each of which necessitates
some work (Verma, 2016). That is to say, certain factors affecting
development processes in software projects can be reviewed as follows
(Tuape \& Ayalew, 2019):

\begin{enumerate}
\tightlist
\item
  \textbf{Organizational factors} : They refer to all factors inside a
  workplace or entity that have an impact on the people, purpose, work
  patterns, culture, leadership, and structure of the specific
  institution.
\item
  \textbf{Business environment factors:} They refer to internal or
  external factors that impact a company's or organization's capacity to
  create and sustain effective customer relationships and are outside
  the organization's control. For example, competitors, customers,
  societal economic trends, government operations, and so forth.
\item
  \textbf{Governance factors:} They refer to the application of all acts
  involved in an organization's management as well as the effort to
  regulate the environment in which the organisation operates via
  continual monitoring and policy. Examples include strategic
  management, operations, quality control, and corporate strategy.
\item
  \textbf{Technical factors:} They are elements that have an impact on
  how an organisation is operated and connected. Tools, processes, skill
  levels, experiences, and business knowledge are employed within the
  context of an organisation.
\end{enumerate}

Developing software, which is one of the IT industry's subgroups, is a
complex process that is difficult to foresee and estimate. Delays are a
key issue in software development. As a result, when these initiatives
run late, clients become dissatisfied. Delay is a typical occurrence in
software projects; thus, it is critical to understand the causes of
delays in these projects and their influence on meeting the objectives
(Kakaei, 2022). Software projects' high risk of cost and schedule
overruns has long been a source of concern for the software engineering
community. One of the challenges in software project management is
making reliable predictions of delays in the context of the constant and
rapid changes inherent in software projects (Choetkiertikul et al.,
2015).

Delays are defined as circumstances that result in an extension of the
period scheduled to complete a project (Alotaibi et al., 2015). A
project delay is an unforeseen and unexpected postponement of a project
due to an incident or occurrence that prevents the project from starting
or continuing. It is the amount of time that causes the project duration
to be extended and the delivery of project goals and objectives to be
disrupted. Project delays can result in a host of issues, some of which
may not be apparent at first. Unexpected delays have a substantial
financial impact on projects. When there is a delay, resources are
squandered, and the company incurs additional costs. Project delays can
also harm your company's reputation among stakeholders and clients.
Delays in one client project might induce delays in other projects by
tying up resources that could be used elsewhere. Delays in projects can
also disrupt the budget, lead the project to deviate from its original
path, and, worst of all, result in missed deadlines (Kakaei, 2022).

In software development projects, delays frequently happen during some
operations. Many software development projects miss their dates because
project delays are not handled effectively (Zhang et al., 2018). In
addition to organisational and managerial issues, several technological
factors contribute to software development delays (Mohabuth, 2017).
Software development projects frequently experience delays due to a
variety of causes, including rework, abandonment, and inaccurate initial
estimates (Zhang et al., 2018).

Delays in software projects are typically caused by earlier phases, such
as inadequate requirement analysis, bad system design, frequent changes
in requirements, or faulty project estimation. Similarly, factors for
integration testing delays include inadequate unit testing, system
architecture, and requirement analysis (Monden et al., 2012). A software
project delay may result in increased costs as well as a reduction in
the scope and quality of product launch activities. Top management,
software managers, and sales and marketing managers must recognise the
extensive consequences of a software project delay and manage the
problem holistically from the perspective of the entire firm, rather
than from the views of particular departments (Rahikkala et al., 2016).

The delay in software projects is considered one of the most important
causes of companies incurring high costs and losses that may cause the
failure of many systems. There is a real need to reduce the effect of
delay causes using comprehensive mitigation measures and advanced tools
(Elhusseiny et al., 2021). That is to say, more accurate time and
expense estimates for software projects need to be provided by project
managers and leaders (Zadeh \& Kashef, 2022). Worthy here to mention is
that forecasting the total costs of a software project is extremely
challenging due to the rapid rate of software change (Briciu et al.,
2016). In addition to the lack of accuracy associated with this process.
Without specific objectives and the relationship between goals and
measurements, as well as the interpretation of those measures, an
organisation will not be able to regard the measures as meeting its aims
(Monden et al., 2012).

The evaluation point and the ability to quantify the quantitative
measurements are the most important part of solving this problem.
Understanding the relationships between cause and effect and linking
them to delay times will help to understand the delay and discover its
aspects, causes, and size of its impact in a clear quantitative manner
that can be measured, compared, and followed up on its performance
during the stages of the project. It is essential to note that a key
problem with delay analysis and the costs associated with it emerges
from the absence of a measurement tool or software that is especially
suitable for analyzing, registering, categorizing, and identifying the
sources of delays and their effects on the different aspects of the
project. In addition, using a single software instrument makes it more
difficult and inaccurate (Jalal \& Yousef, 2017).

The last 40 years have witnessed the introduction of numerous cost
estimation models that have been suggested by many researchers.
Algorithm-based models and non-algorithm-based models are the two major
categories (Armario et al., 2012). Although it is common for people to
use software measurement standards, they are not always simple to
implement in a specific environment where the data and context are
different. Without explicit goals and a connection between goals and
measures, an organisation will not have the opportunity to see the
measures as fulfilling its goals (Monden et al., 2012).

In 1984, the Goal-driven measurement, also known as the
Goal-Question-Metric (GQM) was introduced by Dr Victor Basili and his
colleagues (Asghari, 2012). The GQM method is used to explain the
connection between metrics and measurement purposes, which is frequently
the same as the project objective. To ascertain whether the project
objective (measurement purpose) has been attained, questions are
evaluated (Nakai et al., 2014). There are four main phases of the GQM
identified by (Esteves \& Pastor, 2001; Van Solingen \& Berghout, 1999)
as follows:

\begin{enumerate}
\tightlist
\item
  \textbf{The planning phase:} The main goals of the planning phase are
  to gather all the data needed for an effective introduction and to get
  team members ready for a measurement programme. A project plan is a
  crucial product of the planning process.
\item
  \textbf{The definition phase:} The measurement programme is outlined
  (goal, questions, metrics, and hypotheses are defined) and documented
  during this phase.
\item
  \textbf{The data collection phase:} This phase occurs when actual data
  collection takes place to identify the data that is essential for
  analysis and interpretation took place in the following phase.
\item
  \textbf{The interpretation phase:} The interpretation phase is when
  the gathered data is processed in light of the established metrics to
  produce measurement outcomes, which then enable the evaluation of
  target achievement. The four phases can be shown in the following
  figure:
\end{enumerate}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{FIGURE 1} : Phases of GQM

Source: (Van Solingen \& Berghout, 1999).

To make the business goals and strategies clear, the GQM Strategies add
several extensions to the GQM model. Business goals like increasing
customer satisfaction, gaining market share, cutting production costs,
considering the context, and making assumptions are dealt with by
developing strategies. The organisation defines and incorporates
sequences of actions required to complete the goals into strategies to
accomplish a particular aim. Links are made between every objective and
the strategy it promotes. Models that are used to interpret data to
identify whether the predetermined goals at all levels are met are
called interpretation models. Assumptions must be taken into account
while estimating unknowns as they may have impacts on how the results
are interpreted (Basili et al., 2007; Trendowicz et al., 2014).

\textbf{Previous Studies}

Bilgaiyan et al. (Bilgaiyan et al., 2017) carried out a systematic
survey of the literature on effort and cost estimation techniques for
software development. The researchers concentrated on studying several
development models to reach an accurate measurement of the effort and
cost of different software projects based on different development
models that can accurately predict delay and calculate the percentage of
misbehaviour in total effort, cost estimation, delivery time forecast,
and budget. This helped projects adapt to changes in a software project
and reach a development model where the customer becomes an active
participant in the development thus changes can occur at any stage of
development and can be dynamic. Accurate measurements of the effort and
cost were able to solve the problems and make the project more flexible
through the application of the genetic algorithm (GA), the improvement
of particle swarming (PSO), the artificial neural network (ANN), and the
fuzzy inference systems (FIS).

Zadeh \& Kashef (Zadeh \& Kashef, 2022) aimed to help the company's
executives and management team provide more realistic time and cost
estimates for future software projects by examining the link between
project complexity and cost/time overrun. The Changepoint database was
used to collect sample data for around 50 projects. Statistical
approaches were used to define and test the two study hypotheses.
Descriptive analysis and regression modelling are part of the
quantitative analysis. The findings of the experiments revealed that
there was a strong positive linear link between project complexity and
cost/time overrun.

Yoon et al. (Yoon et al., 2007) proposed a new effort estimation
methodology aimed at agile and iterative development environments that
were not suitable for description by traditional prediction methods. The
study proposed a detailed development methodology that discussed several
structures of these models and also a large group of augmented
regression models and neural networks based on machine learning and
included a comprehensive case study for Extreme Programming (XP) in two
semi-industrial projects. The results showed that the proposed stepwise
model outperformed traditional estimation techniques significantly in
the early stages of development.

Sharma \& Singh (Sharma \& Singh, 2017) presented a systematic review of
software effort estimation techniques using machine learning. For
software effort estimation, the most common machine learning algorithms
are Artificial Neural Networks, Fuzzy Logic, Genetic Algorithms, and
Regression Trees. The results revealed that the most common methods for
effort estimation, are Line of Code (LOC) and Function Point (FP) for
software metrics.

Choetkiertikul et al. (Choetkiertikul et al., 2019) presented a
prediction model for estimating and evaluating projects based on a novel
combination of two powerful deep-learning architectures: long-term
memory and recurrent highway network. The researchers proposed a
comprehensive dataset for effort-based estimation and evaluation that
studied 313 releases from 16 open-source projects. It also proposed a
comprehensive prediction system based on deep learning for effort
estimation. The results revealed that a large part of these improvements
has been made possible by the use of deep learning architecture LSTM for
modelling textual descriptions.

Kula et al. (Kula et al., 2022) reviewed the problems of late delivery
of projects and the resulting increase in costs and showed that it was a
problem resulting from the failure to estimate effort during project
planning. Despite the complex systems and technologies involved in
software projects, they can be affected by many factors that affect
effort estimation and timely delivery. The researchers also identified
the factors that affected schedule deviations using a multi-method case
study in ING that revealed many organizational, personnel, process, and
technical factors. The researchers then structured the findings into a
conceptual framework representing the influencing factors and their
relationships to on-time delivery. The proposed framework identified and
managed delays and risks and designed automated tools to predict
schedule overruns and manage a software project.

Agrawal \& Chari (Agrawal \& Chari, 2007) focused on multitasking
projects to examine the effects of very large processes on effort,
quality, and cycle time. Using a linear regression model based on data
collected from 37 projects and focusing on program size to determine
effort, cycle time, and quality on average, a set of developed models
was designed that predicted effort and cycle time to be about 12 percent
and defects to about 49 percent of the actual values across
organizations. It compared favourably with widely used estimation
software models such as FPs and COCOMO. The results showed a sharp
decrease in variance in the effort, quality, and cycle time which led to
relative uniformity in the effort, cycle time, and quality.

Bhattacharya \& Neamtiu (Bhattacharya \& Neamtiu, 2011) proposed models
for predicting the time to fix errors that used different features to
report errors such as the number of developers who participated in
fixing the error, the severity of the error, and the number of
corrections. The time it would take to fix was estimated, and from it,
the study was able to build more accurate and more general models to
predict the time to fix errors by using multivariate and univariate
regression testing to test the pre-interpretation significance of the
existing models. The researcher presented a case study of a bug report
from five open-source projects: Eclipse, Chrome, and three Mozilla
project products (Firefox, Seamonkey, and Thunderbird). The results
revealed three unresolved research issues: (1) determining if
prioritising bugs based on bug-opener reputation is advantageous, (2)
defining features that are useful in forecasting bug-fix time, and (3)
developing bug-fix time prediction models that can be evaluated on
real-world data.

Grimstad (Grimstad, (2005, September)) addressed the issue of improving
program cost estimates based on expert judgments and cost uncertainty
assessments through better processes, support processes, and better
learning/training processes. The emphasis was on expert judgment in most
software costing exercises and improving understanding of the causes of
estimation inaccuracies in software development projects. It included
understanding the impact of the activities and phenomena that occurred
before, during, and after the actual development project and examining
how personal experiences affected the estimator when deciding to grade.

Trendowicz et al. (Trendowicz et al., 2014) proposed an integrated
approach to selecting relevant factors affecting software development
productivity. Evaluation of Effort and Delay Factors was used to
identify the most relevant factors affecting software development
productivity by incorporating data analysis and an expert judgment
approach via a multi-criteria decision support technique. The study was
conducted using a process where the researchers presented a different
set of factors compared to individual data and expert-based factor
selection methods. The results showed an improvement in the performance
of effort estimation in terms of accuracy and an improvement in the
estimation performance on the groups of factors that were reduced by the
data-based selection method. It was conducted that expert and data-based
selection methods identified different (only partially overlapping)
combinations of relevant factors.

Abdalkareem et al. (Abdalkareem et al., 2021) addressed the impact of
commits on project delays, where it examined the commits of 58 Java
projects and identified the commits that were explicitly skipped by
developers through manual investigation of 1813 explicit commits and
proposed a prototype of the commit that can be Skip CI. The model used a
rule-based technology that automatically identified which commits to
skip by focusing on unseen datasets extracted from ten projects and
demonstrated that the technology can detect and label skip commits CI.
The number of commits that are needed to run the CI process can be
reduced by 18.16\%. A publicly available prototype tool called
CI-SKIPPER has been developed that can integrate with any git repository
and automatically flag commits that can be skipped.

Lebedeva \& Guseva (Lebedeva \& Guseva, 2020) dealt with the factors of
late delivery of software projects and cost overruns in the software
industry due to deficiencies in estimating effort during project
planning as it affected the estimation of effort and delivery on time,
which affected schedule deviations in software development. A
multi-method case study in ING revealed many organizational, personnel,
process, project, and technical factors that were then quantified and
statistically modelled using software repository data from 185 teams.
Focusing on agent metrics such as project size, number of dependencies,
historical delivery performance, and team knowledge, it also addressed
hierarchical interactions between factors, which in turn influence
technical factors. From it, a conceptual framework was reached that
represented the influencing factors and their relationships to delivery
on time. From it, it was possible to access the identification and
management of delay risks. The researchers also designed automated tools
to predict schedule overruns and developed a relational theory for
software project management.

Chang et al. (Chang et al., 2020) proposed an automatic code review tool
using static analysis with quality evaluation metrics designed
systematically under the GQM methodology and evaluating the three
software quality characteristics of the ISO/IEC52060 standard for
intelligent applications. It was an automatic code review tool for
applications built on an open platform for personal use or public
distribution, as it reviewed the code responsible for detecting
violations of coding standards and ensuring that best practices were
followed. This tool developed a code review model and automatic quality
analysis without the need for human intervention to monitor delay
elements and interpret their cause and proposal for treatment.

A few gaps can be found in the extensive corpus of research on cost
estimate models and their relevance to project delays and cost overruns.
These gaps point to areas where more investigation and learning can
advance our comprehension of the subject. Although cost estimation
models can be used in a variety of businesses, certain features and
difficulties may exist in other areas that call for cost estimation
techniques unique to that industry. Despite the abundance of cost
estimation models available, a more thorough quantitative assessment and
comparison of these models concerning their precision, dependability,
and suitability is required.

\textbf{3. METHODOLOGY OF THE STUDY}

To achieve the study objectives and answer its questions, the researcher
adopts the quantitative descriptive approach. The researcher has tried
to describe the nature of delays in software projects and the different
reasons behind software project delays and cost overruns to provide a
comprehensive overview of the different factors and methods to overcome
them.

\textbf{4. DISCUSSION}

In the current study, the researcher has tried to shed light on the main
causes of project delay and cost overrun in software projects. The
results revealed that one of the main causes of delays in projects is
poor planning (Esteves \& Pastor, 2001; Solingen \&Berghout, 1999).
Scope creep, frequent revisions, and delays in providing the intended
software solution can be caused by inadequately stated project scope,
ambiguous requirements, and unattainable schedules. Software initiatives
may be delayed by a lack of resources, including trained labour,
technical infrastructure, and tools. Project progress may be slowed by
poor resource allocation, the absence of skilled team members, or
reliance on outside sources. Delays can result from setting unrealistic
timelines or commitments without taking the project's complexity
(Kakaei, 2022), possible hazards, or dependencies into account. Delays
may be caused by complicated technical specifications, technological
limitations, or a lack of experience with new technology (Tuape \&
Ayalew, 2019).

Concerning the effects of project delay and cost overrun in software
projects, the results showed that delays and cost overruns lead to
higher project expenses. Both the project budget and the organization's
overall financial resources are strained by these challenges. Project
delays may cause deadlines to be missed, which could affect the
anticipated dates of delivery or deployment. This may lead to unmet
company goals, lost market opportunities, or dissatisfied clients.
Consistent cost overruns and project delays can damage an organization's
reputation in the marketplace.

In software projects, cost estimation models are essential for
preventing delays and cost overruns. These models assist in precisely
forecasting and controlling project costs, empowering businesses to
decide wisely and take preventative action to reduce risks.
Organizations can create budgets that are more realistic and precise by
employing these models. Precise budgeting lessens the possibility of
cost overruns and the requirement for additional funding by ensuring
that sufficient financial resources are allocated to the project
(Kakaei, 2022).

\textbf{5. CONCLUSION}

In the software sector worldwide, particularly in the Kingdom of Saudi
Arabia, project delays and cost overruns are frequent problems. Rapid
technological improvements are defining features of the software
industry. It can be difficult for enterprises to keep up with these
improvements, which can cause delays in project timeframes and higher
expenses. There is frequently a talent shortage as a result of the
demand for qualified workers exceeding the supply. Due to the
possibility that businesses would need to employ more staff or finance
training initiatives, this could cause delays in the completion of
projects and raise expenses. Software initiatives in Saudi Arabia may be
impacted by the accessibility and dependability of connection and
infrastructure. Project delays may result from infrastructure
constraints or problems with internet connectivity that impede
development and testing.

Organizations can use strong project management techniques, such as
careful planning, risk identification and mitigation, and frequent
monitoring and control, to avoid delays and cost overruns in the
software sector in Saudi Arabia. Investing in programs that improve the
capabilities of the software workforce through training and development
can help expedite project execution and lower the risk of delays.
Organizations can prevent project delays and cost overruns by
proactively addressing possible difficulties through the implementation
of mitigation techniques and thorough risk assessments. Through the use
of these tactics and the resolution of the unique obstacles encountered
by the software industry in Saudi Arabia, businesses can optimize
software project outcomes, curtail expenses, and augment total project
success.

ORCID

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