Big Data-Driven Decision Making and AI: Business Performance Analysis

This report delves into the transformative impact of big data and artificial intelligence (AI) on organizational performance, focusing on how these technologies drive data-driven decision-making and strategic planning. The study investigates the role of big data in enhancing operational and financial efficiency, examining its influence on business transformation at a global scale. It explores how organizations can leverage their data to gain a competitive advantage, develop new products and services, and expand into new markets. The report outlines a framework for analyzing the efficiency of data-driven decision-making and AI, including research design, philosophy, type, approach, data collection, and analysis methods. Furthermore, it highlights the potential of big data and AI to improve financial and operational performance, offering insights into how organizations can develop effective strategies. The dissertation structure is also provided, which includes an introduction, literature review, methodology, findings, analysis, and conclusion with recommendations.

Big Data-Driven Decision Making and Artificial
Intelligence:
That Could Leverage Organisation’s Data to
Improve the Operational and Financial
Performance

Table of Contents
CHAPTER 1: INTRODUCTION....................................................................................................1
1.3 Research Question and Objectives........................................................................................3
1.4 Framework and analysis........................................................................................................4
1.5 Contribution of research........................................................................................................5
REFERENCES................................................................................................................................7

CHAPTER 1: INTRODUCTION
The main purpose of research is to analyze role of big data and artificial intelligence in
strategic decision making of organisation. In recent times, many new technologies has emerged
which is been used by businesses. In that big data is has enabled in gathering and storing data
and information. It has benefited in making strategic decisions through which their financial and
operational efficiency is improved. Also, many studies on big data is been conducted on its
impact, benefits or challenges faced by business. But in this study it is been evaluated about how
use of big data can influence organisation operational and financial performance. Alongside it,
introduction chapter includes elements identified below :-
 Defining research problem
 Identify aim and objective of study
 Research questions
1.1 Problem description
In recent times, information technology is been used in all businesses. It has allowed in
gathering of data and information. Technological advancement has resulted in transforming
business operations and functions. It has also created a great impact on human life as well. The
frequent development in technology and use of computers is bringing major changes in business
performance. Now, organisations are able to use of advance IT tools and equipments in many
functions. However, IT has provided vast number of opportunities for business to grow and
develop. It has given many advantages in decision making, maintaining quality, use of data and
information, etc. IT is used in many sectors such as education, retail, construction, etc.
Moreover, by using computer system processes, communication and many other things are
improved. In similar way big data is also a technology used by business. It stores large data sets
which can be easily analyzed. The data is stored in real time which provides change in trends by
giving outputs.
Big data is used by small and large organisations. It has integrated overall business data
into centralised one. With this it has become easy to develop strategies and take effective
decision. The emergence of big data in business has solved many complex problems. The
collection of data gives an insight on what changes may occur, market trends, economic stability,
etc. Big data is much more rather than technology. Today, companies are able to gather large
amount of data and analyze them. It has benefited firms to gain competitive advantage, develop
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new products and services, increase customer base, expand in new markets, etc. In big data, data
mining is also new concept used to filter data. By this it organisation select only that data which
is useful. Apart from it, there are many advance systems installed to store, segregate, process,
data. So, accumulating of large amount of info supports in effective decision making and
improving business performance. It also assists in controlling and regulating business activities
and moving forward in right direction. In addition to it, short and long term goals are set by
organisation to enhance their efficiency.
With help of big data, data analytics is used to process data and obtain relevant outcomes.
Here, AI is implemented in data analytics which makes it simplifies information.
But there is negative impact of big data on business as well. Some small businesses are
not able to maintain such big records. Big Data and artificial intelligence have emerged in terms
of decision making and strategic planning (Wellin, 2016). A detailed analysis conducted to
overview business opportunities using artificial intelligence can help in evaluation of different
types of complex business equations and transactions for better use and determination.
BDAI (Big Data and Artificial Intelligence) is an analytical framework that helps in
examining the complex business data and equations for better use. Decision-making process
majorly depends upon accurate figures and aspects related to operations and functions. Various
information tools and systems are used in this context related to analysing the financial stability
and functions for more effective and efficient manner.
Background of the organization
Samsung, IBM, HSBC financials are organizations using the Big Data analytical
organization to improve the internal business models and performance levels. The preventable
aspects and considerable changes mainly associated with ambitious and consisting changes with
the leading creations and challenges. Leading organizations are tracking their performance and
improving the financial capacity to complete the advanced innovative approaches and tools. This
is mainly created with the management and control with completing the data with general
decentralized with the approach. Organizations sometimes share their information and details
with other organizations and entities to improve business relations. Data sharing and cross-
business networking also get impacted due to this function and the insight support of analytical
strategy at the corporate level.
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1.3 Research Question and Objectives
Aim helps to maintain the flow of information relevant to the subject and helps in
consolidating the business equations for machine learning. The norms mostly help in compiling
the data with technological aspects and generation availability. It is analysed that with the
changing business requirements the objectives of business also have been derived from a
traditional analytical approach to critical thinking. Aims also associated with determining the
challenges and opportunities by collecting information at large business level.
Aim- “To analyse the efficiency of data-driven decision making (DDD’M) and artificial
intelligence in a business organization”
Objective:-
 To analyse the role of Big Data-driven for decision making and strategic planning
 To derive the data under Big Data Artificial Intelligence as per organizational
information
 To determine the use of artificial intelligence in strategic decision making
Research question
For conducting a study it is important to define some research questions so that research
can be conducted. Thus, based on above problem there are two questions which are been taken.
The aim of research is to get an insight about How organizations derive the digital business
transformation through data-driven insight and excellence efficiency to impact strategic
decision making?
Also, the purpose is to evaluate first question and on basis of that to analyze How Big data
and artificial intelligence help to improve the financial and operational performance of an
organization? Thus, it will be answer the above question by making it easy to get desires results.
Furthermore, it by gathering data it aims of study can be attained.
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1.4 Framework and analysis
Framework mainly defines the structural base of research in which the detailed
information of the research is summarised on the basis of results (Chatti and et al., 2012). This
research is formed to leverage the organization's data by utilizing Big Data analytical approach
and artificial intelligence for improving the performance of organizations. For successful
completion of research following framework analytical tools are used below.
Research design: This research is mainly based on the application of descriptive and
theoretical analysis. Key potential factors and principal matters are cited form scholars, books
and authors perspectives. There are a clear representation and justification done subject to using
the Big Data evaluation and management program. Relevancy of concepts and material
information upon data are controlled and operated clearly in this research.
Research philosophy: Numerous figures and facts considered to frame the research more
understandable and ethical. Theoretical concepts and description upon Big Data-driven and
leveraged data within organizations are considered effective for more critical control.
Interpretive philosophies are considered due to the concept of the social environment.
Research type: Quantitative type of research is found in this research because most of the
data are taken in the statistical form. It can be reformed for consolidating the changes and
managing the leverage of data among organizations (Shi and Abdel-Aty, 2015). Results from
critical examination and evaluation moulded to research aim and objectives.
Research approach: This research follows the inductive approach and deductive
approach that helps in determining the concept with compressing the operations. It helps in
collecting the information from the sources form retail, financial and manufacturing industries.
Data collection: Information related to fluctuation in growth rate and other
comprehensive changes are taken from secondary sources. Primary sources of data are collected
by questionnaire method. This is the concept which helps in collecting the methods for deploying
the plans and fluctuations with the provided results.
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Data analysis: Data analysis is the base of the research that helps in understanding the
arguments and justification with justified methodologies and concepts. Statistical analysis and
numeric results are found out in the data analysis part. A complete formation and procedure
mainly remain associated with data analytical part. Data collected from primary sources are
critically examined for getting justified results.
1.5 Contribution of research
This research will help in evaluating how big data can result in business transformation at
global level. Also, it will reflect how business efficiency can be improved through strategic
decision making. Moreover, the study will analyse how Big data and AI can improve financial
and operational performance of firms. Hence, the focus is on big data and business efficiency at
global level. Alongside it, it will enable large MNC to implement big data and in what ways they
can enhance their efficiency. Moreover, it will allow organisation to develop strategies on how
they can use big data and AI in organisation.
The study aims to investigate how big data can influence in positive way on business
efficiency. Also, it will evaluate how decisions and strategies can be formed or developed to gain
competitive advantage. The use of big data and analytics support in decision making. Along with
it, how big data has enabled in generating opportunities for business growth.
Structure of dissertation
The dissertation will consist of mainly six chapters. In first chapter that is introduction it
will describe about background, aims and objectives, scope, etc. of research. In second chapter
literature review is done in which secondary data analysis is done. Here, other author and scholar
view regarding research topic is evaluated from journals, articles, etc. it will include articles and
journals related to use of big data in businesses and how it has transformed their strategic
management.
The third chapter is methodology one in which research methods that will be used in study is
discussed. The fourth chapter is findings in which primary data is gathered.
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The fifth chapter is analysis one which will analyse secondary data with primary one. At last
sixth chapter is conclusion and recommendations which will include detailed conclusion of
dissertation and provide some recommendations.
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REFERENCES
Books and Journals
Chatti, M.A., Dyckhoff, A.L., Schroeder, U. and Thüs, H. (2013) A reference model for learning
analytics. International Journal of Technology Enhanced Learning. 4(5-6). pp.318-331.
Shi, Q., and Abdel-Aty, M. (2015) Big Data applications in real-time traffic operation and safety
monitoring and improvement on urban expressways. Transportation Research Part C:
Emerging Technologies. 58. pp.380-394.
Wellin, M. (2016) Managing the psychological contract: Using the personal deal to increase
business performance. Routledge.
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