pISSN: 2723 - 6609 e-ISSN: 2745-5254
Vol. 5, No. 5 Mei 2024 http://jist.publikasiindonesia.id/
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2383
Application of Big Data and Analytics to Increase
Competitive Advantage
Eko Siswo Adi Sahputra
, Ikhsan Nendi
Politeknik Siber Cerdika Internasional, Indonesia
Keywords: Big Data,
Analytics, Competitive
In the digital era, the volume of data continues to increase
rapidly, big data and analytics are important tools for
companies to utilize the data and increase competitive
advantage. The purpose of this research is to find out how
big data and analytics can be applied to increase
competitive advantage. This research uses qualitative
research methods. The data collection technique in this
research is a literature study. The data that has been
collected is then analyzed in three stages, namely data
reduction, data presentation and conclusion drawing. The
results showed that big data and analytics are important
tools for companies to increase competitive advantage in
this digital era including through personalization of
customer experience, operational optimization, and
business strategy development. The implementation of big
data and analytics is expected to have an impact on
companies so that they can make better decisions, develop
new products and services, improve operating efficiency,
and strengthen relationships with customers.
Technological developments have been a key driver of change in the business
world, changing the way organisations operate and interact with customers. This
phenomenon brings about a major transformation in the way businesses are managed,
this is because with more and more companies switching to digitally managed business
models. Along with the acceleration of digitalization flows, companies not only rely on
technology infrastructure to run operations, but also use technology as a tool to
understand and respond to market dynamics more quickly and effectively (Manik,
The main impact of digitizing businesses is a drastic increase in the volume of
data generated every day. Every transaction, customer interaction, or operational
activity generates a digital footprint that creates big data (Awali, 2020). Big data is a
term used to describe the large volume, speed, and diversity of data generated by
multiple sources and channels, including business transactions, IoT sensors, social
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Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2384
media, and more. These data have unique characteristics referred to as "3V", namely
volume (large amounts of data), velocity (the speed at which data is created and
exchanged), and variety (diversity of data formats and types) (Lubis & Hayadi, 2022).
The characteristics of big data can also be expanded to "5V" by adding value
(usability and relevance) and veracity (level of trust and accuracy of data). This large-
scale data often cannot be processed using traditional tools and techniques, thus
requiring innovative approaches and specialized technologies to utilize it effectively
(Alyasiri &; Ali, 2023). These changes pose new challenges for companies but also
open up new opportunities. On the one hand, companies must address challenges related
to data management, analysis, and protection. On the other hand, large volumes of data
also provide great potential to generate valuable insights into customer behavior, market
trends, and business opportunities that have not been revealed before.
Previous research by (Nugrahanti, Sudarmanto, Bakri, Susanto, & Male, 2023)
examined the effect of the application of big data technology, auditor independence, and
the quality of financial reporting on the effectiveness of the audit process, the results
showed that the integration of Big Data technology substantially had a positive effect on
audit effectiveness. Although auditor independence is generally maintained, concerns
arise regarding the provision of non-audit services. The quality of financial statements
remains high, increasing audit effectiveness. The interplay of these factors underscores
the complexity of auditing in Jakarta's manufacturing sector. The implications
emphasize the adoption of strategic technology, the protection of auditor independence,
and a continued focus on the quality of financial reporting.
Another study by (Sirait, 2016) examined the implementation of big data
technology in Indonesian government institutions, the results showed that four
institutions studied, three of which were the Government Procurement Policy Institute
(LKPP), the Directorate General of Taxes of the Ministry of Finance, and the Geospatial
Information Agency (BIG) were at the pre-adoption stage, referring to the TDWI Big
Data Maturity Model. While the Bandung City Government can be categorized as being
at the corporate option stage. Regarding the challenges in the adoption of Big Data
technology in the Indonesian government, 5 things can be concluded, including data
availability, government data standardization, data privacy, HR competence, and
supporting infrastructure.
The novelty of this research is from the object of his research, namely the
implementation of big data and analytics to increase competitive advantage that has
never been studied before. This research can contribute to the development of business
theory by broadening understanding of the role of big data and analytics in creating
competitive advantage. This can help in the development of a more complete and
detailed theoretical framework for understanding how information technology affects
business strategy and company performance. The purpose of this study is to find out
how big data and analytics can be applied to increase competitive advantage.
Application of Big Data and Analytics to Increase Competitive Advantage
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2385
Research Methods
This study used qualitative research methods. Qualitative research is a scientific
research method that aims to understand social phenomena deeply and thoroughly. This
research focuses on an in-depth understanding of the perspectives, experiences, and
contexts experienced by a particular individual or group. The qualitative approach uses
non-numerical data, such as interviews, observations, and text analysis, to explore
qualitative aspects of the research subject (Kusumastuti &; Khoiron, 2019). The data
collection technique in this study is a literature study. The process of literature study
involves searching, collecting, and reading various literature sources, such as scientific
journals, books, theses, conferences, and other articles relevant to the research topic.
Once the relevant literature is gathered, researchers then analyze and synthesize the
information found to gain a comprehensive understanding of the topic. The data that has
been collected is then analyzed in three stages, namely data reduction, data presentation
and conclusions.
Results and Discussion
Developments in information and communication technology have changed the
way of communication, especially in the dissemination of information. Initially, the
method of communication and information distribution was only limited to written
media (paper, letters) and electronic media (radio, television, and telephone), so that the
information circulating was still very limited, both from the scale of information
circulating and the area that could be reached, especially in cross-country information
distribution. People in one country cannot easily obtain and access information related
to other countries, and vice versa. The development of the internet in the era of
advanced technology allows the circulation of information that is increasing, fast, and
almost unlimited by space and time (Kusumasari &; Rafizan, 2017). Through
information technology, trillions of bytes of data are created every day from a variety of
sources, such as from social media, video surveillance, and smart grids. This sea of data
leads to one terminology, namely big data (PG, 2018).
Big data is the latest technology that is currently considered effective for
processing and analyzing data, both structured and unstructured, has a very large
volume, variety, and velocity which is used as a competitive advantage for companies
(Rahman, 2017). Big data is a new and important technological development that allows
the storage and integration of very large volumes of data from various sources
(Ferdiansyah & Nasution, 2023). Big Data Analytics refers to technologies that are
largely based on data mining: text mining, web mining, process mining, audio and video
analysis, statistical analysis, network analysis, social media analytics, and web analytics
(Batko & Ślęzak, 2022).
Big data analytics has emerged as an important tool to support managerial
decision making. Before the invention of computers, humans' ability to store and
process data was very limited. Nowadays, big data analytics has emerged as one of the
most important factors for generating deep insights and understanding for decision
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Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2386
making. Due to the important role of big data analytics in organizations, scholarly
attention has focused on exploring the relationship between big data analytics and
decision-making performance in companies with ever-evolving markets (Nugraha,
Ritchi, & Adrianto, 2023). Laney in (Efgivia, 2020) states that it is universally accepted
in three dimensions or ''3V'' big data, namely variety, volume, and velocity. Variety is a
type of data that is collected and generated. Volume refers to the amount of data
produced by Perpusnas. While the velocity (speed) of data growth is being created.
Big Data has support in the form of: 1) Accurate, in the form of information data
sought by searching for the source itself. 2) Accessible, is the database power of a data,
where a data requires storage itself and then collected, when it has been collected the
data can be managed. 3) Analysis, in the form of data information to be sought, by
searching for data information by analyzing, can be in the form of predictive analysis,
exploratory analysis, regression analysis, data mining and perspective analysis. 4)
Application, in the results of the analysis that has been done, a data requires software
and hardware devices to provide analysis services, this method can make it easier for
companies to carry out an analysis service for central government agencies or forums as
well as regions, the mining, aviation, and health industries (Syira et al., 2023).
Data sources for Big Data can be structured databases or unstructured data. The
benefits of Big Data technology have been widely felt in various sectors. Companies
engaged in the business sector can utilize valuable information generated by Big Data to
optimize the decision-making process, so that the target of maximizing profit can be
achieved. Meanwhile, institutions engaged in public services can use information output
from Big Data to maximize the level of service satisfaction to their clients / customers
(Duha, Fajriyah, Setiawan, & Dewi, 2022).
The application of big data in the business world is very important because the
form of data that exists in a business is unstructured so that with the existence of big
data data can be used for operations and business development. If a company does not
adopt the technology, then gradually the company will be left behind. In the business
world, the most important thing about data is not about its quantity, but how it can be
managed and utilized to develop an ongoing business (Erislan, 2024).
In Big Data, data is too big and too fast or does not fit into the conventional
database architecture structure. So to get value from data, technology must be used to
extract and obtain more specific information. Cloud technology is needed because Big
Data needs to be supported by a strong server with a large storage area and easy to
develop (Hapsari, 2020). Big data brings transparency and more accessible data. This
has never happened before, many businesses that rely on proprietary data as a
competitive asset are threatened. Many new businesses are starting to offer data and
analytics services in almost every domain, they help other businesses to grow faster and
smarter, for example, manufacturing businesses integrate data collected from production
floors and other sources, collecting data from suppliers from all over the world (Shahid
& Sheikh, 2021). The five ways to utilize Big Data according to McGuire et al. (2012)
are as follows.
Application of Big Data and Analytics to Increase Competitive Advantage
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2387
1. Big Data can provide significant value by making information transparent. There is
still a lot of information that has not been recorded in digital form, for example data
that is on paper, or is not easily accessed and searched through the network. We
found that up to 25 percent of efforts across multiple knowledge worker workgroups
consisted of searching for data and then transferring it to another (sometimes virtual)
location. These efforts are a significant source of inefficiencies.
2. As organizations create and store more transactional data in digital form, they can
gather more accurate and detailed performance information on everything from
product inventory to sick days, uncovering variability and improving performance. In
fact, some leading companies are using their ability to collect and analyze big data to
conduct controlled experiments to make better management decisions.
3. Big Data allows for narrower customer segmentation so that products or services can
be tailored more precisely.
4. Sophisticated analytics can significantly improve decision-making, minimize risk,
and uncover valuable insights that may still be hidden.
5. Big Data can be used to develop next-generation products and services. For example,
manufacturers use data obtained from sensors embedded in products to create
innovative after-sales service offerings such as proactive maintenance to avoid
failures in new products.
The purpose or main thing of this Big Data phenomenon is, there is a very
exponential growth of data and information, speed in data accretion (volume), and
increasingly varied content of the data that has the potential to create new challenges,
new opportunities, and new sales or marketing strategies. This indicates that optimal
data processing in a big data warehouse will be able to maximize the company's goals in
winning the competition (Mantik & Awaludin, 2023). Competitive advantage is an
advancement of a process or value that a company is able to create for its buyers. Not
only that, but competitive advantage is also something that can make a company gain
more advantages compared to the advantages of competitors / competitors (Khasanah &
Hudaya, 2024).
Big Data solutions are ideal when all or most of the data needs to be analyzed or
when data sampling is not as effective as larger data sets. By using Big Data and
leveraging its benefits, a company can gain a huge competitive advantage and stay
ahead of its competitors. Big Data offers much greater growth potential to businesses
than traditional technology, although it is still poorly understood. Companies that are
still far from this concept can make their competitors, who have understood the
importance of Big Data faster, gain a leading position in the market. Organizations
should not underestimate the importance of this concept (Kubina, Varmus, & Kubinova,
Thus, the application of big data becomes one of the main things in increasing
competitive advantage for companies. Big data has the ability to process large-volume,
diverse, and high-speed data, allowing companies to gain in-depth knowledge about
customers, markets, and business operations. By utilizing Big Data effectively,
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Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2388
companies can create significant added value and gain a sustainable advantage in
market competition. Therefore, big data is not only a technology but also a vital strategy
for achieving business success in this digital era.
Big data and analytics have a crucial role for companies in increasing competitive
advantage in this digital era. One of the main ways in which this happens is through
personalization of customer experience, which allows companies to better understand
customers' individual preferences and needs as well as tailor their services or products
more precisely. In addition, big data and analytics are also used to optimize company
operations, enabling the identification of areas that can be improved in business
processes to achieve greater efficiency. In addition, companies are also using big data
and analytics to develop smarter and more responsive business strategies, by analyzing
market trends, consumer behavior, and internal data to inform strategic decisions.
Therefore, by effectively applying big data and analytics, companies are expected to
make better decisions, produce innovative new products and services, improve
operational efficiency, and strengthen connections with customers, all of which
contribute to increasing their competitive advantage in an increasingly changing and
competitive market.
Application of Big Data and Analytics to Increase Competitive Advantage
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2389
Awali, Husni. (2020). Urgensi pemanfaatan e-marketing pada keberlangsungan UMKM
di Kota Pekalongan di tengah dampak Covid-19. BALANCA: Jurnal Ekonomi Dan
Bisnis Islam, 2(1), 114.
Batko, Kornelia, & Ślęzak, Andrzej. (2022). The use of Big Data Analytics in
healthcare. Journal of Big Data, 9(1), 3.
Duha, Tobias, Fajriyah, Nurul, Setiawan, Wawan, & Dewi, Ernawati. (2022).
Implementasi teknologi big data di era digital. Jurnal Informatika, 1(1), 17.
Efgivia, Mohammad Givi. (2020). Pemanfaatan big data dalam penelitian teknologi
pendidikan. Educate: Jurnal Teknologi Pendidikan, 5(2), 107119.
Erislan, Erislan. (2024). Application of Big Data Analytics for Decision Making in
Digital Marketing. Return: Study of Management, Economic and Bussines, 3(1),
Ferdiansyah, Veri, & Nasution, Muhammad Irwan Padli. (2023). Penerapan Teknologi
Big Data Dalam Pengembangan Database Pendidikan. Jurnal Riset Manajemen,
1(3), 2229. https://doi.org/10.54066/jurma.v1i3.591
Hapsari, Nurul Fikriati Ayu. (2020). Big Data Dan Pemanfatannya Di Perpustakaan.
Jurnal Ilmu Perpustakaan (Jiper), 2(1).
Khasanah, Aniatul, & Hudaya, Robith. (2024). The Effect Of Big Data Application On
Financial Performance: Company Size As A Moderating Variable. Jurnal Aplikasi
Akuntansi, 8(2), 403410.
Kubina, Milan, Varmus, Michal, & Kubinova, Irena. (2015). Use of big data for
competitive advantage of company. Procedia Economics and Finance, 26, 561
Lubis, Muhammad Zulkarnain, & Hayadi, B. Herawan. (2022). Strategi Komunikasi
Krisis Pemerintah Menggunakan Big Data Pada Media Sosial. Journal of
Computer and Engineering Science, 114.
Manik, Esra Imelda Humiras Masro. (2023). Masa Depan Mesin: Peran Utama
Teknologi Cerdas dalam Perkembangan Mesin. WriteBox, 1(1).
Mantik, Hari, & Awaludin, Muryan. (2023). Revolusi industri 4.0: big data,
implementasi pada berbagai sektor industri (bagian 2). JSI (Jurnal Sistem
Informasi) Universitas Suryadarma, 10(1), 107120.
Nugraha, Fauzi Purwa, Ritchi, Hamzah, & Adrianto, Zaldy. (2023). Interaksi Big Data,
Eko Siswo Adi Sahputra, Ikhsan Nendi
Jurnal Indonesia Sosial Teknologi, Vol. 5, No. 5, Mei 2024 2390
Kualitas Data, dan Kinerja Keputusan: Studi Kasus BPJS Kesehatan. Jurnal
Pendidikan Akuntansi & Keuangan, 11(2), 224238.
Nugrahanti, Trinandari Prasetyo, Sudarmanto, Eko, Bakri, Asri Ady, Susanto, Edy, &
Male, Sartina R. (2023). Pengaruh Penerapan Teknologi Big Data, Independensi
Auditor, dan Kualitas Pelaporan Keuangan terhadap Efektivitas Proses Audit.
Sanskara Akuntansi Dan Keuangan, 2(01), 4754.
PG, Dewi Sri Woelandari. (2018). Potential Benefits and Business Value of Big Data
Analytics. Majalah Ilmiah Bijak, 15(2), 106114.
Rahman, Nayem. (2017). Big data analytics for a sustained competitive advantage.
Shahid, Nadeem U., & Sheikh, Nasir J. (2021). Impact of big data on innovation,
competitive advantage, productivity, and decision making: literature review. Open
Journal of Business and Management, 9(02), 586.
Sirait, Emyana Ruth Eritha. (2016). Implementasi teknologi big data di lembaga
pemerintahan Indonesia. Jurnal Penelitian Pos Dan Informatika, 6(2), 113136.
Syira, Syahdina Damayari, Fauzi, Achmad, Woestho, Choiroel, Vilani, Laurencia,
Firmansyah, Prado Dian, Pratama, Demas Rizky, Apriliana, Atun Dwi, Ghaffar,
Naufal Shafly Abdul, & Putri, Dhea Amelia. (2023). Pemanfaatan Big Data dalam
Peningkatan Efektivitas Strategi Komunikasi Marketing Terpadu pada Perusahaan
E-Commerce. Jurnal Ekonomi Manajemen Sistem Informasi, 4(5), 891900.