The Impact of Data Analytics Adoption on Job Roles and Skill Requirements in MSMEs: Development of Conceptual Model

Abstract

The adoption of data analytics by Micro, Small, and Medium Enterprises (MSMEs) has become critical for enhancing decision-making processes, improving operational efficiency, and remaining competitive in the digital economy. This study explores the impact of data analytics adoption on job roles and skill requirements within MSMEs. Specifically, it examines how traditional roles like marketing, finance, and operations are transforming to include data-driven decision-making responsibilities. The study highlights emerging roles such as data analysts and business intelligence specialists, as well as the increasing demand for technical skills like data literacy, programming, and machine learning. However, MSMEs face challenges in adopting data analytics, including resource constraints, skill gaps, and cultural resistance. To address these issues, this study employs a qualitative method approach, primarily explorative study. The research develops a conceptual model that outlines the interplay between data analytics adoption, job role transformation, skill development, and organizational adaptation. This model provides insights into how MSMEs can strategically manage the transition to a data-driven culture, overcoming key barriers to successfully integrating analytics into their operations

Keywords

• Data Analytics Adoption
• MSMEs
• Job Roles
• Skill Requirements
• Data-Driven Decision-Making
• Technical Skills