Disruptive Innovations using Tech-Business Analytics in the Secondary Industry Sector

Authors

  • Sachin Kumar Associate Professor, Dept. of Information Technology, Management Education & Research Institute (MERI), Affiliated to GGSIP University, New Delhi., India Author
  • Hirdesh Sharma Assistant Professor, Dept. of CSE, Dronacharya Group of Institutions, Greater Noida, U.P., India Author
  • Aithal P. S. Director, Poornaprajna Institute of Management, Udupi, India Author

Keywords:

Business Analytics (BA), ICCT underlying technologies, Tech-Business Analytics, TBA, Secondary Industry, Data Science, Big Data Analytics, Research gap in Business Analytics, ABCD Listing, Tech-business Analytics, Service industry, Secondary Industry Sector

Abstract

Purpose: The principal objective is to revolutionize conventional manufacturing and production procedures by utilizing cutting-edge technologies and insights derived from data. In the secondary sector, the incorporation of tech-business analytics promotes competitive advantage, long-term sustainability, and more intelligent decision-making.

Design/Methodology/Approach: Collect information from a range of sources, including sensors, IoT devices, ERP systems, and consumer reviews in production processes. Combine information from several systems and departments into a single platform to guarantee consistency and accuracy in analysis. Utilize methods like AIML, predictive analytics etc.  monitoring to spot trends, inefficiencies, and opportunities. Utilize insights to create innovative solutions that go against the grain, such automated processes, smart factories, or customized production lines. Prior to full implementation, test new models or technologies on a small scale to assess their viability, performance, and return on investment. Successful innovations should be expanded throughout operations, integrated with current systems, and staff members should be trained for adoption. Create feedback loops with analytics to track results and keep improving procedures and inventions. This methodology aligns technology with secondary sector business objectives and guarantees that disruption is data-driven, strategic, and sustained.

Findings/Result: Predictive maintenance and automation greatly cut down on resource waste and downtime. Budget allocation is enhanced and production expenses are reduced through data-driven decision-making. Faster defect detection and repair are made possible by real-time analytics. Agile manufacturing techniques provide more rapid reaction to market demands. Businesses that use tech-business analytics do better in terms of innovation and agility than traditional players. Energy-efficient and environmentally friendly activities are enhanced by intelligent resource management.

Originality/Value: Tech-business analytics-based disruptive developments in the secondary industrial sector are distinctive due to a number of significant variables. These characteristics show that disruptive innovations that use tech-business analytics are not just improvements on existing practices, but are, in fact, new techniques that create value and establish new industry norms.

Type of Paper: Exploratory Research.

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Published

2025-08-06

How to Cite

Disruptive Innovations using Tech-Business Analytics in the Secondary Industry Sector. (2025). Poornaprajna International Journal of Emerging Technologies (PIJET), 2(2), 1-20. http://poornaprajnapublication.com/index.php/pijet/article/view/112

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