dc.description.abstract | Kazi Farms Limited, a leading FMCG and agriculture business in Bangladesh, faces challenges
in finding qualified blue-collar workers due to the country's expanding economy and agriculture
sector. To ensure a competent workforce, the company needs to address gaps in technical
expertise and educational attainment. The findings of the study may influence business
procedures in Bangladesh, contribute to our knowledge of talent management in the FMCG and
agricultural industries, and create new opportunities for attracting and keeping skilled workers.
The hiring process is managed by a central HR department. The primary objective of this report
is to offer insights into the talent acquisition processes for non-management positions and
provide a strategic analysis of critical roles within Kazi Farms Limited. Utilizing a mixed methods approach of qualitative research, including Focus Group Discussions (FGD) and Key
Informant Interviews (KII), the research delved into the intricacies of talent acquisition for non management positions and provided a strategic analysis of critical roles within the company.
After conducting FGD and KII sessions, the data were analyzed thematically and developed
strategies to build a talent pool for critical roles.
The analysis was based on a theme and the information was presented in a clear and succinct
manner through the data categorization, which was subsequently utilized to generate insights and
recommendations that could be implemented. After the analysis, several strategies were made
under several critical positions to attract, hire and retain them through better benefits and
continues development with the help of training. The recommendations provide a solid
foundation for interventions to improve critical roles efficiency, address skill gaps, refine talent
management strategies, and prioritize employee well-being, ensuring sustained success in a
dynamic business landscape. With every aspect considered, the analysis will be a useful tool for
individuals seeking to use the information to make data-driven decisions. | en_US |