Modeling and Analyzing of Financial Data within Digital
Transformation Era and its Impact on Balanced Scorecards
Utilizations: A Theoretical Review
SULAIMAN WESHAH
Accounting and Accounting Information Systems
Al-Balqa Applied University
Amman University College for Financial and Managerial Sciences
JORDAN
Abstract: - The present theoretical review outlines the interaction between digital transformation and financial
data modeling and the use of Balanced Scorecards in improving strategic management in organizations.
Considering the context of rapid technological processes and the growing influence of international competition,
the principle question of this work is how current management accounting methods, most of which are inspired
by digitization, shift the theoretical perspective of how organizations use (BSCs) for strategic forecasting and
performance assessment.
By conducting a thorough review of the literature within the realms of management accounting, information
systems, and strategic management, this theoretical review identifies the main trends, the rationale, and the
challenges behind the use of (BSCs) and digitization. The current finding indicates that the implementation of
digital technologies into the process of financial data modeling substantially increases the potential of (BSCs) by
offering real-time, useful information for strategic decision-making. At the same time, the implementation
process raises a set of challenges, such as security issues, hefty financial investments into technological
infrastructures, and human factors of organizational change. Despite these hurdles, the potential benefits of
digitally-enhanced (BSC) framework-such as improved decision-making accuracy, strategic agility, and
operational efficiency-underscore the importance of adopting a holistic approach to digital transformation in
strategic management practices.
This review calls for a balanced perspective that considers both the technological and cultural dimensions of
implementing digital innovations within (BSC) frameworks. It concludes with recommendations for future
research, emphasizing the need for empirical studies to validate theoretical insights presented and explore the
practical implications of digital transformation organizations-BSCs effectiveness in diverse organizational
context.
Key-Words: - Financial Data Modeling, Digital Transformation, Balanced Scorecard (BSC), Management
Accounting, Financial Engineering.
Received: April 28, 2023. Revised: May 9, 2024. Accepted: June 15, 2024. Published: July 17, 2024.
1 Introduction
Management accounting is concerned with the
provision of information; it serves the management
of the enterprise in: setting objectives, planning;
achieving them; monitoring and evaluating their
implementation; and industrial sector accounting
focuses on an information system for the collection,
compilation, analysis and storage of data in a
coherent and sequenced manner, with a view to
providing quantitative information of both types:
financial and non-financial, based on the nature of the
company's needs, to assist its management in
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Volume 2, 2024
planning, oversight and sound decision-making,
making it part of the company's Integrated
Management Information System (IMIS) [11].
Given the world ' s intense competition and openness
in global markets, many companies have resorted to
modern management accounting methods; they
provide time, effort and cost in providing timely
information to decision makers. Business
organizations, especially industrial organizations, are
living in a working situation that is experiencing
rapid changes as a result of rapid technological
development. They must direct their efforts to keep
pace with the constantly evolving process by linking
performance to modern technological developments
and adopting modern management methods that
reduce production costs without compromising their
quality. One of the most important of these methods
to be addressed in this study is: graceful accounting,
a system of costs based on time-oriented activities
and balanced scorecards (BSC).
Balanced Scorecards (BSC) as a managerial
accounting method became an effective and powerful
tool that can provide and support the organizations
performance [24].
The new digital era, such as ERPs and cloud
accounting, needs to take into consideration the
modern techniques and the new forms of integrations
between these modern techniques to utilize them
inside new ways to create new data and information
support decision-making process [21].
The method of the analysis of an econometric model
of the impact and elasticity of human resources
outflow and remittance to economic growth in
Ukraine by [17] reveals the interaction and influence
of remittances on economic activity and inflation of
the country, as well as capital investment. This
research also shows how it is possible to use financial
modeling to develop BSCs further, making them
more valid and up-to-date in strategic planning terms.
Such a measure is relevant due to the need to develop
adaptive strategies given that modern financial
markets present a wide range of phenomena for
which traditional strategies tend to be insufficient.
Therefore, such integrated approaches are essential
for strengthening the stability of socioeconomic
systems from extreme stressors.
This study highlights the modelling and analysis of
financial data and their impact on promoting the use
of balanced performance cards in industrial firms.
2 Literature Review and
Theoretical Background
Data modeling and analytics is the process of
preparing and designing models that include pre-
defined vocabulary within precise sequences that are
used as a database to support the operations and
activities carried out by the organization. Thus, this
stage enabled the auditor to store, update, modify,
and retrieve the data that was prepared through the
model used [9].
It is the process of planning and visualizing the entire
methodology of collecting an organization’s data,
from its inception and updating to the process of
storing it. It focuses on transforming raw data into
structural, often visual, representations that help
analysts extract more meaningful insights from the
data. Data analysis is the process of examining,
interpreting, transforming, and migrating. ; It aims to
extract useful information for internal and external
performance goals. Accordingly, data analysis sets
the model in motion. To benefit from data and obtain
valuable information that helps in the process of
rationalizing and making appropriate decisions.
With emerging electronic formats and innovative
financial reporting processes, accounting
requirements and systems in practice have evolved in
line with the accounting system. With internet
technology advances, online accounting, audit, and
analysis capabilities have increased, and new systems
have been introduced. The improvement has been
activated from conventional paper-based practices
and has focused on accelerating the production of
accounting and reporting [1] The convergence and
transformation of accounting and the Internet of
Things (IoT), cloud computing, big data, and the
digital economy have led to significant improvement
and necessary reforms. However, there is inadequate
awareness of the application of FinTech in
accounting and finance research. This may cause
losses in experience.
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Employers cannot assign conventional audit and
evaluation methodologies to the digital world.
Conventional procedures cannot effectively
scrutinize digital accounting data. This research
suggests that the application of accounting and
management big data, monetary and non-monetary
information, and interdisciplinary big data return
falls into the barrier. With a digital gain from the
internet industry and transactions, exploration of
FinTech's intrinsic value or relevant questions,
FinTech can disperse serious under-allocation,
diverting concerns regarding misuse and deixis in
accounting management. With technological
development and moral justification, FinTech's
comprehension extends, and its appropriation
supersedes the objectives of living agile-business
evolution while preserving associated moral
promises [10] and [16].
[26] Concluded that accounting studies have begun
to address digital transformation since 2017, and the
number of studies has increased, especially in
security and blockchain/big data subjects. However,
while digital transformation studies in information
systems have focused on digital/social media,
automation programmes, the environmental
regulations of digital platforms and the value of the
company, we do not find similar accounting patterns.
A balanced scorecards (BSC) is a control
methodology that provides a comprehensive
measure; on how the organization progresses towards
its strategic objectives through performance
indicators, which serve as golden threads, for five
dimensions or perspectives: the client and interested
parties dimension, the financial dimension, the focus
of management performance processes within the
organization, the post-growth and learning
dimension, and the social dimension. Each dimension
has a different weight and importance for the
organization, and the institution does not rely on a
single measure of performance -- for example,
financial, but on different measures that balance
financial and non-financial measures.
[20] mentioned that risk management is a necessary
mechanism for reducing volatility and ensuring
financial protection in a more and more unpredictable
world, which includes natural disasters, economic
crises, and other incidents. Financial engineering
allows to collectively scatter risks by concluding
hedges, and although it creates risks and problems for
individual portfolios, it significantly strengthens the
financial system as a whole.
(BSC) is a management system aimed at translating
the organization ' s strategic objectives into a set of
organizational performance targets that are
measured, monitored and, if necessary, changed; to
ensure that the organization ' s strategic objectives are
met; and one of its main assumptions is that the
financial accounting standards traditionally followed
by the organizations to monitor their strategic
objectives are insufficient to keep the institutions on
track, and the financial results highlight what has
happened in the past and not where the business is
going or should be going.
Data modelling is the first step in electronic
transformation, where it encodes and arranges
analogue information in electronic form; for storage,
operation and electronic transmission, which means
moving from analogue duties to electronic duties,
thus creating common denominators between
existing duties to work with information technology,
and the auditor must evaluate appropriate control
methods; to prevent change in data: by
misrepresentation, sabotage, deliberate deletion or
total elimination of data, achieved through pre-
emptive electronic surveillance programmes,
allowing access only to the authorized group of
personnel [5]; [8] and [2]. The concept of data
analysis refers to the transformation of primary data
into a clear, applicable and measurable vision, which
includes a set of techniques used in the knowledge
and analysis of the operational mentality of the
Organization, working to find solutions to problems
using data. The process of data analysis is aimed at
demonstrating the nature of the organizations
activities, promoting business growth, and
developing and providing modern decision-making.
Non profit organizations, advocacy groups and
community based organizations often advocate for
education policy issues, like funding, culturally
sensitive curricula and inclusive practices [18].
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In todays changing business landscape incorporating
technologies has become essential for organizations
aiming to stay competitive.
This incorporation, referred to as transformation
involves adopting digital tools and technologies to
enhance business processes improve decision making
and foster innovation. In the field of management
digital transformation has brought about changes in
how financial data is gathered, analyzed and used to
support strategic decision making. Thus, this
literature review reflects the analysis of
transformation in intersection with financial data
modeling and analysis, and the use of Applied
scorecards BSC, as strategic management tools.
The Resources Based View (RBV) framework
suggests that a firms competitive advantages arise
from its combination of resources and capabilities.
In the realm of transformation and financial
management the Resource Based View (RBV) theory
suggests that organizations can achieve an edge by
utilizing digital technologies to improve their
financial capabilities. This includes enhancing data
analytics skills utilizing time data and streamlining
decision making processes [4].
Theories centered around technology driven
innovation highlight the significance of progress, in
fostering innovation and competitiveness. In the field
of management innovations like AI powered
analytics blockchain based financial transactions and
automated financial processes empower
organizations to make informed decisions on a large
scale [22].
Frameworks for strategy execution underscore the
importance of flexibility and agility in implementing
initiatives within rapidly evolving environments.
When employing scorecards an adaptive approach
involves monitoring and adjusting performance
metrics based on up, to date financial data and market
trends. This enables organizations to effectively
respond to emerging opportunities and challenges
[13].
Embracing advancements, in management includes
utilizing technologies like data analytics, artificial
intelligence (AI) machine learning (ML) and cloud
computing to simplify financial procedures and
derive valuable insights, from financial information.
Studies by [15] and [6] emphasize the importance of
digital transformation in enhancing the efficiency and
effectiveness of the financial operations, enabling,
real-time data analysis consider as a base to enhance
and improve the forecasting accuracy.
Financial data modeling and analysis play crucial
role in supporting the process of decision-making
inside- organizations, while the traditional financial
models are being augmented or replaced by more
sophisticated data-driven approaches that leverage
advanced analytics techniques. [14] highlights the
significance of predictive modeling and data
visualization techniques in extracting actionable
insights from financial data, thereby enabling
informed decision-making.
Balanced scorecards (BSCs) are a management tool
that helps organizations turn their vision and strategy
into goals and performance measurements, from
various viewpoints, such, as financial, customer
service, internal processes and learning and growth.
While (BSCs) have been widely adopted across
various industries, their effectiveness relies on the
quality of data used measures business environment.
[12] and (Rappaport, 2017) mentioned the
importance of aligning (BSCs) inside organizational
goals and ensuring the relevance and accuracy of
performance metrics.
Traditional scorecards utilize Key Performance
Indicators (KPIs) with a balanced ratio representing
different functions such as customers, internal
business processes, financials, and viewpoints of
each KPI. Each organization has its unique KPI ratio
representation based on the company's vision.
However, recent research shows that this traditional
approach does not satisfy performance management
needs. Most organizations have tried financial scores
and HR scores in addition to the traditional score.
Unfortunately, it has only shown improved employee
productivity in a few organizations. The reason for
this is that this method does not cater to innovative
technology development. Today, the seeds sown for
the digital era have started to show their roots in areas
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such as big data, cloud storage, blockchain
technology, IoT, and AI. These technologies
transform organizations and make businesses more
evolved and transformed [3].
Balanced Scorecard (BSC) is a strategic management
performance tool to identify the green zones among
all functions widely used across the globe. It is used
to evaluate company performance and compare it
with similar industries and world-leading industries.
In the current digital era, advanced data collection
models depend on big data, blockchain, and financial
API. They provide BSC visualizations and prescribe
alignment activities [7]. It is interesting to analyze
and compare the score of performance management
and the organization's tendency to utilize score
metrics in financial data, traditional methods, and
digital transformation improvement [19].
3 Methodology
To have a clear perception of the impact of financial
data modeling on BSCs adoption through the digital
transformation, the research included the whole
theoretical review techniques. The purpose of the
study is to synthesize the cuurent literature.
4 Conclusion
The aforementioned theoretical review identified the
intersection of digital transformation, financial data
modeling and analysis, and the application of
balanced scorecards to make strategic management
within this paper. The review of the literature allowed
the formation of several important implications and
conclusions: on this basis:
1. The use of advanced financial data modeling
enriches BSC-centered decision-making,
while real-time data analysis facilitated by
the adoption of AI, ML, and cloud
computing technologies renders BSC
metrics more accurate and relevant.
2. Digital transformation as a catalyst of BSC
evolution. Finally, the rise of digital
technologies has spurred a reassessment of
traditional BSC practices, and digital tools
for monitoring, accounting, and reporting
financial data have become available for
deploying a more dynamic and agile strategic
management. Consequently, this is part of an
enhanced federal trend for evidence-based
decision-making in the digital era.
3. Implementation challenges. While the
benefits seem quite transparent, the shift to a
digital or BSC-enhanced framework is
always associated with certain factors that
might compromise this process. Specifically,
one should mention data security, while the
increased use of technological solutions
implies substantial investment in this field
and training of the personnel, which is
another limiting factor. Moreover, the issue
of structural resistance remains acute;
therefore, a strategy should encompass a
broader scope.
4. Future prospects and possibilities. In the
future, the dynamic changes in digital
technologies create additional opportunities
to use BSC. For example, the development of
AAR services and novel data analytics
methods that increase transparency,
efficiencies, and strategic fit. In this case,
offsetting organizations would constantly
adjust their strategies to new BSC
conditions.
5. Utilization of Balanced Scorecard; Emerging
technologies such as advanced data analytics
methods offer potential, for enhancing
transparency, efficiency and strategic
alignment further. Companies should stay
flexible in updating their BSC approaches to
capitalize fully on these approaches to a
competitive level.
In conclusion, for future research, it is necessary
to look at how advanced financial data modeling
and advanced analytics, including predictive
analytics and machine learning, might
complement BSC frameworks in strategic
decision-making. Research on the integrated use
of real-time data analytics and BSC metrics and
the influence of digitalization, automation, and
digitization, including AI technology and cloud
computing, should also be prioritized. These
areas may be researched from the perspective of
a case study or empirical experiments.
Furthermore, attention should be paid to the
associated problems of implementing digital
BSC frameworks, along with issues like data
protection, technology funding, and personnel
training.
At the same time, attention should be paid to the
potential of augmented analytics and robotic
process automation on BSC-enhancing analytics,
and a comparative study on strategic adaptation
to new technology would be beneficial to remain
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competitive in the changing technological
environment.
5 Recommendations
1. Integration of expertise of fields to improve
the evolution of Balanced Scorecard : It is
suggested that companies should proactively
create teams consisting of IT experts, data
scientists, financial analysts, and strategic
managers to oversee the integration of digital
transformation implementations into their
Balanced Scorecard framework. This will
ensure that the use of technological innovations
and data analysis tools align with the goals
which lead to a sophisticated and effective use
of the tool. Moreover this team can serve as
mediators, which connects the capabilities
offered by transformation with the organizations
strategic goals to ensure digital transformation
projects become rooted in actual business needs
and strategy.
Moreover, this team can fostering an
environment of continuous learning and sharing
knowledge which will help organizations stay a
head and in parallel with technological trends.
2. Recommendations for Educational
Institutes: there is a significant demand for the
improvement of courses plans for students
studying business, accounting, and finance,
which should be considered in conjunction with
the growing utilization of digital resources. This
advice contained in [25] and [23] are likewise
applicable to these.
3. Recommendations for future research:
there is a clear need for further empirical
research to explore the practical
implementations and outcomes of digitally-
enhanced (BSC) various organizational context.
These future studies need to aim to quantify the
impact of digital transformation on (BSC)
effectiveness and investigate the strategic for
over coming implementation challenges.
6 Final Thoughts
The intersection of digital transformation, financial
data modeling, and (BSC) utilization represents
fertile ground for both academic research’s practical
innovation. As organization navigate the
complexities of the digital age, the findings of this
review offer valuable insights for enhancing strategic
management practices through the integrated use of
digital technologies and (BSC) frame works.
Acknowledgement:
I am grateful for the support and encouragement
received from my college’s dean and department
colleagues, who provided me invaluable feedback
and dissections enrich this theoretical study.
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Contribution of Individual Authors to the
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Policy)
The author contributed in the present research, at all
stages from the formulation of the problem to the
final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The author has no conflict of interest to declare that
is relevant to the content of this article.
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