The challenges and benefits of product data analysis

Abstract

This thesis examines the challenges, benefits, and preconditions of how product data analysis can be successfully implemented within companies. The primary focus of the research is to explore how businesses can manage and leverage product data towards effective decision-making, optimization of operational performance, product quality enhancement, and innovation activity. The research aims to explore the following questions: What are the challenges in product data analysis? What benefits can product data analysis bring to companies? What are the preconditions for product data analysis?

These questions are addressed through a comprehensive literature review and analysis of secondary data, including academic journals, industry reports, and case studies from sectors such as manufacturing, automotive, and e-commerce. The findings point out several significant challenges, such as poor data quality, data integration challenges, security and privacy concerns and resource and skill constrain. At the same time, the study demonstrates the benefits of product data analysis including improved product quality, informed decision-making, operation efficiency and cost reduction, customer experience enhancement and agility and risk mitigation. The research also analyzes essential preconditions, such as data quality assurance, technical infrastructure preparation, and organizational readiness.

This thesis underlines the potential of product data analysis in achieve competitiveness and long-term success in a data-driven business environment.