The Impact of Data Analytics on the Manufacturing Industry (Business & Marketing Coursework)

The Impact of Data Analytics on the Manufacturing Industry
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The Impact of Data Analytics on the Manufacturing Industry
The manufacturing industry has experienced some major changes in recent years due to the digital revolution that has characterised industry 4.0. Global competition has created the need for efficiency, customer-focus, and automation in the value chain (Teslya & Ryabchikov, 2017). The manufacturing value chain is highly dependent on data and the digital transformation has allowed the industry to obtain and use vast information to improve their processes and make better decisions. This paper aims at analysing the impact of data analytics on the manufacturing industry as well as the future opportunities and challenges associated with the use of data analytics in this industry.
Industry Background
Over the years, the manufacturing industry has undergone some key developments through major industrial revolutions. According to Teslya and Ryabchikov (2017, p.321), the industry has transitioned from manual work to the use of machines in production during the 1760-1849 industrial revolution. It then experienced some major changes during the digital revolution when the use of information technology and robots become part of the production process. In the past, the manufacturing industry has not always been customer-focused due to the nature of the existing business models. The traditional business models focused on mass production at low prices, yet times have changed and customers want individualized products (Nayyar & Kumar, 2020). These changes have been facilitated by improved connectivity and advances in technology. It was also greatly focused on the products while ignoring the services aspect of manufacturing. According to Nayyar and Kumar (2020, p.198), the traditional business models in the manufacturing industry are characterised by challenges such as a lack of individualized mass production at low prices, networking and automation issues, value chain fragmentation, and a lack of flexibility in producing personalized products and services. However, in the age of industry 4.0, the manufacturing industry has made certain changes to realign their value chain with current changes in technology and customer demands, including changing their business models. Industry 4.0 is the most recent industrial revolution which has not only improved efficiency and automation but also enhanced sustainability in the value chain (Garcia-Muina et al. 2020, p.1). Also, this revolution has allowed companies in the manufacturing industry to obtain data in a timely manner, thus enhancing the decision-making process.
The Impact of Data Analytics
Data analytics involves the analysis and use of large datasets in making decisions. To understand the impact of data analytics in the manufacturing industry, it is important to understand the role of data in the industry. Manufacturers understand the importance of data, more so in the age of information technology. Prior to the first industrial revolution, the data obtained in the manufacturing process was lost easily since there were no effective ways of documenting the information other than through human experiences (Tao et al. 2018, p.2). However, the data collected at that time is still useful today in manufacturing jewelry and other luxury products. After the first industrial revolution, data collected was better documented in logbooks, charts, and instructional materials (Tao et al. 2018, p.2). It was also better utilized, although it was still managed manually by people rather than computers. The usefulness of data became evident in the information technology era where sales, customer, inventory, supply chain, and other types of data were stored in computers (Tao et al. 2018, p.2). This made it easier for manufacturers to effectively m...