QAB020X604S Dissertation: Big Data Analytics in Business Innovation

This dissertation investigates the significance of big data analytics in business management and innovation, highlighting its role in uncovering customer preferences, hidden correlations, and market trends. It emphasizes the importance of big data analytics for informed decision-making and competitive advantage. The research explores the impact of big data analytics capabilities on organizational innovation, the importance of absorptive capacity, and the function of absorptive capacity in shaping the relationship between big data analytics and business innovation. The study uses a meta-analysis methodology, drawing from various web pages, peer-reviewed journals, and organizational reports to examine the research questions and hypotheses related to the impact of big data analytics on business management and innovation.

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SIGNIFICANCE OF BIG DATA ANALYTICS IN BUSINESS MANAGEMENT AND
INNOVATION
Executive Summary
Big data analytics describes a complex procedure of assessing vast and extensive
variety types of facts. Big data analytics aims to unearth the concealed facts (Evelles,
Fukawa & Swayne, 2016). The facts may include customer preferences, hidden
correlations and market trends. It is one of the most significant tools that organisations
should have to assist the managers to make informed decisions. Big data is an
expression that is used to make a distinction amid the new type of data and the old
structured form of data. An organisation cannot rely only on its information from the
internal sources, and it must explore the external environment and gather data that will
be used to make critical and innovative decisions (Evelles, Fukawa & Swayne, 2016).
A vast number of research studies have given an attempt to provide the connotation of
the word big data. It is described with three "Vs" (Bhatnagar & Kurnar, 2015). There is
need to utilize other resources such as Big Data infrastructure to reap the benefits of big
data analytics (Chen & Zhang, 2014). The use of big data analytics can help a business
flourish in the market. As a result, there is the creation of employment opportunities
which leads to an improvement in the living standards of people in various countries
(Rajaraman, 2016). The paper begins with an introduction, followed by research rational
and research questions. A review of literature is then conducted followed by
methodology, ethical considerations and study limitations are presented.

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Table of Contents
Executive Summary.....................................................................................................................................1
The significance of Big Data Analytics in Business Management and Innovation........................................3
Chapter 1: Introduction...............................................................................................................................3
1.1 Introduction.......................................................................................................................................3
1.2 Research Topic...................................................................................................................................4
1.3 The Significance of the Research Topic..............................................................................................4
1.4 Rationale of the Research Project......................................................................................................5
1.5 Research Questions...........................................................................................................................6
1.6 Research aim and Objectives.............................................................................................................7
General Research Question.....................................................................................................................7
Specific Research Questions....................................................................................................................7
1.7 Research Hypothesis.........................................................................................................................7
2.0 Literature Review..................................................................................................................................8
2.1 Role of external data in innovation for products and services.........................................................10
2.3 Big data playing its role in keeping business from jumping to conclusions.....................................11
2.4 Role of big data in identifying patterns, correlations and trends.....................................................12
2.5 Role of big data in using to conduct predictive analytics.................................................................12
2.6 Big Data plays the role of considering the downsides of analytics..................................................13
2.7 Big Data and big data analytics........................................................................................................13
Chapter 3: Research Methodology............................................................................................................16
3.0 Methodology.......................................................................................................................................16
3.1 Research philosophy........................................................................................................................16
3.2. Data collection................................................................................................................................16
3.3 Research Design...............................................................................................................................17
3.4 Data Analysis...................................................................................................................................17
3.5 Importance of the study..................................................................................................................17
3.6 Ethics...............................................................................................................................................18
3.7 Limitations.......................................................................................................................................19
3.8 Chapter Summary............................................................................................................................19

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Chapter 4: Findings and Analysis...............................................................................................................20
CHAPTER 6: CONCLUSION.........................................................................................................................24
6.1 Conclusion.......................................................................................................................................24
6.2 Recommendation:...........................................................................................................................24
Reference List............................................................................................................................................26

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The significance of Big Data Analytics in Business Management and Innovation
Chapter 1: Introduction
1.1 Introduction
Big data analytics describes a complex procedure of assessing vast and
extensive variety types of facts. Big data analytics aims to unearth the concealed facts
(Evelles, Fukawa & Swayne, 2016). The facts may include customer preferences,
hidden correlations and market trends. It is one of the most significant tools that
organisations should have to assist the managers to make informed decisions. Big data
is an expression that is used to make a distinction amid the new type of data and the old
structured form of data. An organisation cannot rely only on its information from the
internal sources, and it has to explore the external environment and gather data that will
be used to make critical and innovative decisions (Evelles, Fukawa & Swayne, 2016).
However, the data collected from the outside sources are generally in large quantities,
and in different types. This is why there is a need for big data analytics that helps to
analyse the big data and come up with information that is helpful to the organisation.
This research project is a detailed investigation of the significance of Big Data
Analytics in today’s business management and innovation. Major purpose of the paper
is to understand and gain a comprehensible insight regarding how organizations in the
present days are dealing with innovation when managing service and business with Big
Data or how Big Data is helping the businesses today to manage innovation and quality
of service in business. Under general view, it can be mentioned that big data analytics
tend to reveal the hidden patterns, correlations and other significant understanding. So,
due to the advances of technology today, it is quite easy to make analysis of the data
and gain suitable responses on an urgent basis which is slower as well as less efficient
with more traditional business intelligence solution. It is a known fact that each type of
data tend to contain figures, facts and the generate information to take better

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organizational businesses, career as well as regular decisions. Generally, all sort of
data is significant to businesses but when it comes to innovation and creative ideas, big
data helps to enhance innovative as well as creative ideas. It is always important to
develop creative ideas in business to achieve goals and due to this reason big data is
significant to discover the appropriate type of solutions that consumers tend to look for.
1.2 Research Topic
The topic of the research will be an investigation into the significance of big data
analytics in business management and innovation.
1.3 The Significance of the Research Topic
A large amount of data available from external environments is becoming a big
challenge to many organisations in the world today (Hashem et al., 2015). It has
become difficult to make the right choices on the information to use in their decision
making. Big data analytics helps the managers of the organisations to analyse the big
data to come up with well-structured details that can be used in decision making. Big
data analytics also helps the managers to identify hidden information, especially about
other competing businesses.
In today's dynamic business environment, innovation has become a decisive tool
needed by firms to make certain their continued existence in the marketplace. The
owners of business and managers therefore, need to be modernized with the dynamic
technology (Hashem et al., 2015).
They have to ensure that they provide new services, find ways of producing and
introducing new products in the market. The only way that they can do this is by having
the ability to right of entry to both external and internal environment and make analysis
to know the requirements of the market from the organisation.
1.4 Rationale of the Research Project
A vast number of studies show that analysis on the big data have had a strong
bang in increasing the innovation of many firms. Conversely, BDA is not adequate to

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ensure that an organisation experiences increased growth and development (Hazen et
al., 2014). To create big data analytics capabilities in a firm, there are numerous of other
types of resources such BDA infrastructure and BDA personnel that the organisation
needs to employ. Big data analytics capabilities describe the effects that big data
analytics create to a firm's modernization. Also, there are other factors that a company
should consider to ensure big data analytics (Hazen et al., 2014). One of the main
factors is an organisation’s absorptive capacity. This describes the ability of a firm to
acquire, implement and exploit the information acquired to ensure growth and
development of the firm (Hazen et al., 2014). Absorptive capacity helps a company to
gain a competitive advantage against their competitors (Hazen et al., 2014). This
research project aims at investigating the significance of big data analytics in business
management and innovation. The investigator hopes to accomplish the key objective of
the study by: finding out the impact of significant data analytics capabilities on an
organisation's innovation sector; examining the importance of absorptive capacity to
organisations' innovation; investigating on the function played by absorptive capacity in
shaping the association between big data analytics capabilities and improvement sector
of an organisation. Meta-analysis methodology will be used by the investigator to come
up with the relevant information on the study. Various web pages, relevant previewed
journals, and organisational reports will be used to seek more information about the
research topic. To identify the relevant sources, the following keywords will be used:
Innovation, big data, business management, analysis on the big data, ability to absorb
and impacts of big data analytics.
Next, the researcher will identify the superlative references which counterpart the
criteria for inclusion-exclusion. Lastly, there will be monitoring of the prose for chosen
references to search on the significance of analysis of big data in business
management and innovation.
1.5 Research Questions
The objective of the study is to examine the significance of big data analytics in
business management and innovation. The researcher is aggravated by knowing that

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there is narrow study on how firms should exploit analysis of big data to achieve its
benefits on the business' profitability in the market the vast amount of information from
the external sources is becoming confusion to many companies when it comes to
making critical decisions. Organisations should adopt the use of big data analytics as
one of the most vital resources that can help create a competitive force against their
competitors. Studies have shown that despite the intense competition and many
challenges in the business world today, many firms have been able to ensure their
survival in the market (Gunesekaran et al., 2017). Most of these firms have been able to
adopt big data analytics that has helped them on how to deal with various challenges
that exist in the competitive world of business today.
Nevertheless, big data analytics is not sufficient for organisations to guarantee
big data capabilities in improving the innovation sector (Gunasekaran et al., 2017).
Organisations need to utilize other resources such as BDA technology and personnel.
Other factors such as the absorptive capacity of the firm should be considered to
enhance the capability of the organisation in exploiting big data analytics. Therefore,
this study aims at examining the impact of absorptive capacity on the organisation’s
modernization. Also, the research also objects at the discovery of the function of
absorptive capacity in shaping the affiliation amid the impacts of analysis of big data
and a firm’s modernisation.
1.6 Research aim and Objectives
This research aims to investigate the significance of Big Data Analytics in leading and
managing business innovatively. Following are the key objectives to meet the stated
aims.
 To critically investigate the impact of big data analytic capabilities on an
organization’s innovative managerial initiatives
 To identify the importance of absorptive capacity in organization’s
innovative business
 To analyse the future role of Big Data analytics in business

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General Research Question
What is the significance of big data analytics in business management and innovation?
Specific Research Questions
1. What is the impact of big data analytics capabilities on an organisation's
innovation sector?
2. What is the importance of absorptive capacity in the organisation's innovative
sector?
3. What is the function of absorptive capacity in shaping the affiliation amid big data
analytics capabilities and business innovation?
1.7 Research Hypothesis
H0-Big Data Analytics have no impact on business management and innovation
H1- Big Data Analytics have impact on business management and innovation

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2.0 Literature Review
A vast number of research studies have given an attempt to provide the
connotation of the word big data. It is described with three "Vs" (Bhatnagar & Kurnar,
2015). The first "V" is used to describe the volume of the big data. It is said to be in
huge, and it comes from different types of sources both internal and external. The
second "V" is used to describe the variety of big data. Studies show that it is of a vast
number of varieties and it ranges from structured data to unstructured data. This is one
of the main reasons why it creates a big challenge for firms when it comes to making
critical decisions. The third "V" represents the velocity of the big data. This refers to the
speed at which big data is produced, analysed and interpreted.
Big data need to be analysed to be of importance to the organisations. This is
where big data analytics arises. It involves a complicated procedure for assessing
enormous amounts of big data originating from diverse sources to expose the unseen
facts (Akter et al., 2016). The information may include consumer preferences, unknown
correlations, information about competitors and market trends. Besides, big data
analytics helps in unveiling information about what happened in the past and what is
happening today in the market (Akter et al., 2016).
This information is used by the managers and the owners of the business to
predict what will happen in the future and the possible outcomes. According to the
studies, there are three types of data analytics: Descriptive data analytics, predictive
data analytics, and prescriptive data analytics. Descriptive data analytics involves data
analysis on the occurrences that occurred in the past.
Predictive data analytics requires analysis of data to predict what is probable to
occur in the coming days (Ji-Fan Ren et al., 2017). Prescriptive data analysis involves
analysing various types of data from different sources to help the organisation make
informed decisions to achieve its goals in the future.
Besides, there is a vast number of big analytics tools that a firm can employ.
Some of them are extracted information load, Hadoop distributed file systems and Data
warehouse tools (Ji-Fan Ren et al., 2017). There is a need for organisations to know the

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meaning of big data and big data analytics to achieve the big data analytics capabilities
in improving their innovation sector. Many firms have been struggling to make decisions
with the wide variety of data from both external and internal sources (Kwon, Lee & Shin,
2014). This data may lead to wrong decisions that may lead to the failure of the
business. Organisations need to create a competitive advantage against their
competitors and increase their efficiency for them to survive in the business
environment.
Conversely, an organisation cannot achieve the capabilities of big data analytics
without using other resource. There is need to utilize other resources such as Big Data
infrastructure to reap the benefits of big data analytics (Chen & Zhang, 2014). Big data
analytics infrastructure may include infrastructure that is composed of information
technology which helps the sectors of the company to work as a team to attain the main
objective of the business. Also, BDA personnel expertise is another type of big data
analytics infrastructure. These include the knowledge, professional skills, and familiarity
with big data analytics (Cheng & Zhang, 2014). A firm can attain big data analytics
capabilities if it is able to combine all the required resources to create a competitive
advantage.
The absorptive capacity of a firm is increased by its ability to apply big data analytics in
its decision-making process. The ability of an organisation to acquire information,
analyse it, interpret and utilize it to improve the firm is known as absorptive capacity
(Kwon, Lee & Shin, 2014). There are two types of absorptive capacity: Potential
absorptive capacity and realised absorptive capacity.
Potential absorptive capacity refers to the process of acquiring information from external
sources, interpreting and analysing the obtained data (Jin et al., 2015). Realised
absorptive capacity involves the ability of a company to bring the newly received data
and the old information together. It also requires implementation of the acquired
knowledge and exploiting it to create a competitive advantage that can help ensure its
survival in the competitive market (Jin et al., 2015). Absorptive capacity is one of the
critical tools for achieving big data analytics capabilities by an organisation.

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Moreover, absorptive capacity is also one of the factors that lead to a firm’s
improvement. Modernization involves the introduction of updated goods, systems and
the firm’s structure. (Lazer et al., 2014). Absorptive capacity helps a firm to acquire
information from the external sources, analyse it through big data analytics and exploit it
to come up with informed, innovative business decisions. This shows that the absorptive
capacity has a big role in determining the big data analytics capabilities of a firm with its
innovation.
It has been identified that chief executives are shifting their attention from product
innovation to service innovation due to increasing commoditization of product items and
increasing consumer demands for customized experience of service or product. Hence,
to remain active or continue the service innovation, organizations or the businesses
often rely on big data management. Questions often arise that why it is necessary to
maintain sustainability in innovation in business as there is no good in investing in time,
money, and resources to think tank which cannot do much on producing a steady
stream of innovation on a daily basis. Hence, Lee, Kao and Yang (2014) commented
that it is quite true that every business or marketers need to achieve and maintain a
state of regular as well as consistent innovation.
Provost and Fawcett (2013) also mentioned the fact that several forward thinking
businesses often find that big data tend hold long series of answers to drive innovation
and one major reason for this is that internal data with possibility can drive
organizational innovation. Tiwari, Wee and Daryanto (2018) arguably added the fact
that innovation management is not just coming up with creative ideas. Much of
innovation is just made up of smaller or limited improvements which tend to combine to
create colossal impact. Authors of this study has also given an example that if a
business is able to minimize 10% of overall operation’s waste and make 15% of
enhancement in production time. By reducing or eliminating a bottleneck and
streamlining few process, together it can enhance operations without even
manufacturing single new revolutionary data. This is probably the major power of using
big data in your internal operations. It is certain that small innovations tend to add up to
large improvement.

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2.1 Role of external data in innovation for products and services
Just like the above studies, Braganza et al. (2017) performed a study and mentioned
the fact that big data could not only give answers to the questions regarding the market,
customers, industry and competitors, it has the ability to bringing up a series of other
similar questions that help to set innovation under the path of developing new concepts.
Wolfert et al. (2017) added the fact that big data is known for generating as many or
more questions than it could actually responds. Here, the major fact to be understood is
that while it can be frustrating for teams who are tasked with resolving specific
problems, it could be so much effective for the businesses assigned with innovation
management. Wixom et al. (2014) added the fact that big data has the ability of
delivering some effective revelations which can be used for all sort of ways.
In this context, Gobble (2013) gave an example that it is appropriate to state the fact
commuters who go to work and then routinely get home on time everyday are probable
much more happier than who drive their own cars. Authors of this study has mentioned
the fact that people in Tokyo tend to sleep less compared to the people in other nations
across globe and people living in Texas are more likely to call each other bro and dude.
So, on the basis of such data and information, innovators gain the ability of delving into
such data and discover all sorts of intriguing and fascinating facts. And, the findings
draw the implications that each of these often leads right back to few more questions.
Thus, it is mentioned that this is the major sustenance of a healthy innovation program
in business.
2.3 Big data playing its role in keeping business from jumping to conclusions
According to Ittmann (2015), it might happen that data was considered to be something
often proved to be different than it was actually considered. Authors also gave an
example that there could be sometimes the data which is originally very different from
what organizations conventionally consider to be true. Just like the markets for
desktops, Personal Computer remained stagnant that marketers assumed that this was
going to be an end of desktop computer. According to LaValle et al. (2011), Microsoft
gave a challenge on the fact that when they developed Windows 8, which was a big
disaster or more of a bad marketing initiative. However, in reality the picture is little