International Journal of Progressive Research in Engineering Management and Science
(Peer-Reviewed, Open Access, Fully Referred International Journal)

ISSN:2583-1062
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Paper Details

A study on impact of data-driven HR in Macdonalds India (KEY IJP************761)

  • Shipra Pandey

Abstract

This study examines the impact of data-driven HR practices in McDonalds India, employing a mixed-methods approach to provide a comprehensive understanding of HR management within the multinational fast-food chain. Utilizing secondary data analysis, the research investigates the influence of data-driven HR on employee performance, retention, and satisfaction. Quantitative analysis involves statistical techniques to quantify relationships between data-driven HR practices and key performance indicators, while qualitative methods offer insights into employee perceptions through interviews and thematic analysis. Findings reveal that data-driven HR enhances recruitment, training, performance management, and employee engagement at McDonalds India. Moreover, the study underscores the transformative role of predictive analytics in shaping strategic decision-making and fostering a culture of continuous improvement. By integrating multiple sources of evidence, this research contributes to a deeper understanding of data-driven HRs impact on organizational success and employee well-being in the fast-food industry. The findings of this study illuminate the multifaceted benefits of data-driven HR implementation in McDonalds India. Analysis reveals that the adoption of data analytics tools enables McDonalds to streamline recruitment processes, enhance training programs, and optimize performance management systems. Moreover, the integration of predictive analytics empowers decision-makers to anticipate workforce trends and proactively address organizational challenges. Qualitative insights further underscore the importance of data-driven HR in fostering a culture of transparency, accountability, and employee engagement within the organization.

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