p–ISSN: 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

Email: [email protected]

, [email protected]

*Correspondence

ABSTRACT

Keywords: Big Data,

Analytics, Competitive

Advantage.

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.

Introduction

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,

2023).

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.

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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,

2015).

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.

Conclusion

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

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