BIG DATA ANALYTICS IN ENHANCING LOGISTICS EFFICIENCY AT THE INDEPENDENT ELECTORAL AND BOUNDARIES COMMISSION OF KENYA
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Abstract
The logistics operations of the Independent Electoral and Boundaries Commission (IEBC) in Kenya are critical to ensuring the successful conduct of elections, involving complex processes such as the distribution and management of electoral materials across the country. However, these operations are often challenged by inefficiencies, delays, and logistical mismanagement. This study examined the impact of big data analytics on enhancing logistics efficiency at the IEBC, focusing on integration with logistics systems, and decision-making enhancement. Grounded in Information Processing Theory (IPT), and Supply Chain Management (SCM) theory, the study aimed to provide a comprehensive understanding of how advanced data-driven strategies can optimize logistics performance in the public sector, specifically within electoral processes. A census sampling technique was employed, targeting the 60 supply chain personnel within the IEBC, including the head of Supply Chain, County Supply Chain Assistants, and other senior officers responsible for logistics functions. Data were collected using structured questionnaires and interviews, providing both quantitative and qualitative insights into current logistics practices and the integration of big data analytics. Descriptive and inferential statistical methods, including regression analysis, were used to analyze the data, highlighting the relationships between the identified variables and logistics efficiency. The findings revealed significant positive relationships between the independent variables and logistics efficiency, with regression coefficients of β = 0.355 for integration with logistics systems, and β = 0.432 for decision-making enhancement. The study concluded that leveraging integrating real-time data into logistics systems, and promoting data-driven decision-making are crucial for optimizing logistics performance. Recommendations include providing continuous training for logistics personnel, and fostering a culture of data-driven decision-making to achieve higher levels of efficiency and responsiveness in IEBC’s logistics operations.
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