Analyzing Big Data's Role in Managerial Decision Making: A Report

This report examines the crucial role of big data in managerial decision-making, focusing on two ASX-listed companies: Virgin Australia Holdings Limited and Vintage Energy. It begins by outlining the evolving business environment and the increasing importance of data-driven insights. The report then delves into the analysis of customer behavior, resources (human and financial), and key performance indicators for both companies, illustrating how big data is used to gain insights and improve operational efficiency and financial performance. It also explores the impact of big data on the information provided by management accountants, highlighting the shift towards automated processes and predictive analytics. Finally, the report discusses how big data can enhance management accounting systems, providing greater value to businesses through improved decision-making and strategic support. The report includes examples of how these companies utilize big data to improve their competitive advantage.

Managerial Accounting
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Contents
Introduction.................................................................................................................................................3
Part 1: Role of Big Data in Managerial Decision Making in Virgin Australia Holdings Limited and Vintage
Energy..........................................................................................................................................................3
Outlining the Changes that have taken place in business environment in recent years..........................3
Part 2: Examining the Customers, Resources and key performance indicators of Virgin Australia Holdings
Limited and Vintage Energy.........................................................................................................................4
Analysis of Customer Behavior................................................................................................................4
Resources (Human and Financial Resources)..........................................................................................5
Key Performance Indicators....................................................................................................................6
Part 3: Impact of Big Data on the Information Provided by the Management Accountants.......................7
Part 4: Use of Big Data in Improving the Processes of Management Accounting systems..........................8
Conclusion...................................................................................................................................................8
References...................................................................................................................................................9
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Introduction
This report has been undertaken to develop an understanding into the role of big data in
the managerial decision-making. As analyzed from the given scenario, Mr. Mark Wood, the
CEO of a growing public limited company intends to gain an understanding of the role of big
data for providing guidance to the business managers in decision-making. In this context, the
report conducts an analysis of two selected ASX listed companies in respect of the significance
of big data in supporting the decision-making of business managers the respective firms. This
has been carried out by outlining the changes that have taken place within the business
environment in the recent years. Also, it examines the customers, resources and key performance
indicators of both the companies and provides an explanation of the impact of the information
gained in supporting the decision-making of management accountants. Lastly, it also discussed
the major processes that management accounting systems adopts for creating value for the
selected two companies by the use of big data. The two companies selected for the purpose are,
Virgin Australia Holdings Limited and Vintage Energy. Virgin Australia Holdings Limited is a
holding company that owns and operates Virgin Australian Airlines that is one of the largest
airlines of Australia. Vintage Energy has been established for acquiring, exploring and
developing energy assets within Australia.
Part 1: Role of Big Data in Managerial Decision Making in Virgin
Australia Holdings Limited and Vintage Energy
Outlining the Changes that have taken place in business environment in recent
years
The business organizations are currently emphasizing on improving their competitive
advantage for enhancing their sustainability and thus promoting their long-term growth. The role
of big data is becoming very crucial for businesses nowadays in this context he effective use of
data is becoming the basis for companies to achieve competitive advantage (Jeble & Kumari,
2018). Businesses are largely focusing on gaining insights from the information for making
better and tactful decisions that leads in improving the business growth and development. The
information is gained by the use of both structured and unstructured data that is achieved from
both inside as well as outside from an organization. The big data that includes internal data as
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well as data realized from outside sources such as online and mobile data for making effective
decisions through providing a basis of business managers both statistical and predictive views.
The businesses are largely integrating the use of big data for causing fundamental
changes in the way through which they are competing and operating. The big data can be
regarded as large and complex data sets that include diverse sets of information from different
sources that assist in better decision-making of businesses (Anderson, 2016). The business
organizations are implementing the use of computational techniques for identifying the
significant patterns, trends and relations to develop better strategies for business growth. This
helps in driving business value and has a distinct advantage over the competitors. The increase in
the ability of businesses to store large volume of data with the development of new technologies
is also enable business organizations to easily analyze the diverse set of information. The
extraction of useful and pertinent information from the big data helps the business managers to
make better decisions regarding business growth and development (Muller & Brocke, 2018).
Part 2: Examining the Customers, Resources and key performance
indicators of Virgin Australia Holdings Limited and Vintage Energy
Analysis of Customer Behavior
Virgin Australia Holdings Limited adopts the use of big data for gaining an insight about
the customer needs and preferences. The analysis of the changing consumer preferences and their
satisfaction level with every flight of Virgin Australia is very important to determine its
sustainable growth and development. As such, airlines such as Virgin Australia are largely
focusing towards sting and data mining each and every interaction held with the customers
(Moth, 2013). This is done through the use of feedback received from the online platform such as
social media sites. Also, it is using flight search history of the customers who visits its website
for gaining an analysis of their needs and preferences. Virgin Australia Holdings Limited adopts
the use of both internal and external sources to collect information about the customers and
develop the strategies of future growth and development. The internal sources include
conducting customer survey and external sources include analyzing their responses from the
different online communication channels (Jisana, 2014).
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On the other hand, Vintage Energy operating within the energy sector tends to collect the
information regarding the consumption pattern of energy by the consumers. The major source of
their information for the energy companies is from the use of smart meters that helps in
collection of large volume of data. The energy companies such as Vintage Energy are integrating
the use of big data analytics to identify relevant patterns of customer consumption from the data
collected and thus gaining an insight into their future requirements. The use of emery analytics
can helps in exporting the large volume of data from the standard meters in the standard formats
that can be used by the companies in further decision-making (Stoicescu, 2015).
Resources (Human and Financial Resources)
The major problem that is being faced by large number of airline companies such as
Virgin Australia is recruiting and maintaining talented and skilled workforce to effectively
meeting the changing customer needs and preferences. As such, the airlines are adopting the use
of new tools and technologies to collect information about the potential employees. For example,
LinkedIn and Glassdoor are largely being used by the airlines for gaining an insight into relevant
skills and experience of the potential candidates and recruiting quality workforce. Also, data is
collected through survey responses and social media posts of the present employees to gain an
understanding of their brand loyalty (Ross-Smith, 2017). The collection of such type of big data
helps the airline companies such as Virgin Australia to recruit and maintain quality workforce
having relevant skills and expertise. Virgin Australia is also adopting the use of Artificial
intelligence and machine learning analytics for conducting market and customer analysis and
processing the interpreting the complex financial data for better financial management of the
company. The use of AI has enabled in automating the daily operational processes of the airline
such as answering customer calls. Also, it helps in easy collection of relevant financial data that
helps in driving productivity improvement and also leads to enhanced decision-making (Sumathi,
2017).
On the other hand, Vintage Energy tends to collect large volume of data about the
employees from both inside as well as external sources. The internal sources can include
analyzing employee satisfaction level through surveys while external source include gaining
information about their skills, expertise and needs with the use of online challenges or
interviewing potential candidates. The large volume of data collected can be analyzed with the
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use of predictive analytics and behavior analytics that helps in identifying significant pattern of
employees toward preferring the company for potential employments and also segregating their
relevant skills and expertise(Utilities and Big Data: Using Analytics for Increased Customer
Satisfaction, 2013).
Key Performance Indicators
 Enhancing Operational Efficiency: Virgin Airlines is also adopting the use of leveraging
data to automate its processes and enhancing its overall efficiency. The use of machine
learning by the airline can help in improving its operational efficiency. The machine
learning techniques such as time series and pattern recognition helps in improving the
data mining capabilities of the airline and thus improving the operational efficiency. For
example, the airline has adopted the use of DataRobot’s automated machine learning
technique. This technique is enabling the airline to collect data regarding the customer
preferences towards travel, types of travel they undertake and their price willingness.
Also, the airline is using the past purchases of the customers to gain an insight about their
future needs and demands. Thus, the use of such data mining techniques is help the
airline to a large extent to increase its operational effectiveness by collecting vast volume
of data that helps in improving its operational activities (Bindi, 2017). Similarly, Vintage
Energy tends to drive its operational efficiency through collecting big data regarding all
its different operations and implementing the use of big data analytics tool to identify and
interpreting significant information from it that helps in improved-decision making for
business managers (Utilities and Big Data: Using Analytics for Increased Customer
Satisfaction, 2013).
 Improving Financial Performance: The use of analytics solution for extracting relevant
data from the huge volume of financial data helps the airline to predict the future
financial growth and development of the airline. The extraction of relevant financial data
from the complex big data helps in identifying the key financial performance indicators
such as prediction of total profits to be realized and future sales pattern for the airline
(Noyes, 2014). On the other hand, energy sector companies such as Vintage Energy can
adopt the use of big data to predict the future financial performance and also improve it
through identifying the relevant loopholes. For example, the identification of issues
related to receivable turnover, profitability patterns, sales volume and other financial key
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performance indicators that can be analyzed adequately with the use of big data analytics
tools helps in better decision-making for the business managers (Girouard, 2016).
Part 3: Impact of Big Data on the Information Provided by the
Management Accountants
The present business environment is seeing major changes in the ways in which financial
transactions are captured, recorded, verified and transformed into significant information. The
businesses are increasingly adopting the use of automated processes for recording and carrying
out their complex financial transactions in an easy and quick manner. There is quick collection of
large volume of financial data by the businesses that can be utilized at any point of time by the
business managers for better decision-making (Muller & Brocke, 2018). The current era of big
data and analytical platforms have provided new opportunities for the businesses to use finance
as their strategic partner and drive business growth. The collection of all information related to
an organization such as its customers, employees and other stakeholder needs and wants enables
in developing a bigger picture of an organization (Jeble & Kumari, 2018).
As such, management accountants are required to work in close integration with the
business managers for driving operational efficiency and thus improving the business bottom-
line outcomes. The management accountants’ are required to integrate their accounting
knowledge and skills with the management accounting tools to convert the raw data collected
into predictive insights that helps the business managers to make valuable decisions. For
example, Virgin Airlines is adopting the sue of artificial intelligence and machine learning that
can significantly helps in deriving significant patterns of growth and other important financial
data from the raw data that can be used in making accurate predictions regarding the future sale
volume of the airline. The machine learning analytics is also used by the energy sector
companies such as Vintage Energy that enables in data visualization for the management
accountants and thus developing a strategic decision-support system for the business managers
(Joachim, 2017).
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Part 4: Use of Big Data in Improving the Processes of Management
Accounting systems
The traditional management accounting system sued by Virgin Australia and Vintage
Energy can be significant improved to provide more value to business by the use of big data.
This is because the use of big data would enable in transforming the role of management
accountants into more of a strategic partners (Trifu & Ivan, 2014). As such, it would lead to
transforming the traditional management accounting into a strategic management accounting
process that can effectively help in integrating the financial information with other organizational
data and adequately helps in forecasting by the use of predictive analytics technique of big data
(Savvas, 2010). The strategic improvement in the processes of management accounting system
within the two firms would help in achieving better financial control, increased business
efficiency and better forecasting. The use of automation procedures will effectively help in
recording and verifying complex financial and accounting data that can be accurately interpreted
by the use of big data analytical techniques such as artificial intelligence and machine learning
by the two firms (McGowan, 2013).
Conclusion
It can be inferred from the discussion held that sue of big data is providing to be very
useful for businesses in a competitive business environment to drive their sustainable growth by
creating higher value. The improvement in the operational and financial performance of
businesses is achieved through big data. This is due to enhanced decisions-making of business
managers who tend to adopt the use of big data analytics to identify and interpret significant data
that lead in providing better strategic direction.
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References
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big-data-and-energy-analytics-
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new-content-strategy/
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Muller, O. & Brocke, J. (2018). The Effect of Big Data and Analytics on Firm Performance: An
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