Assessing the Effects of Data Analytics on Operational Efficiency among Small Scale Manufacturing Enterprises in Lusaka

Author(s): Lusale Shabwalala and Dr. Kelvin Chibomba (PhD)

Abstract:

Small and Medium scale Enterprises (SMEs) play an important role in promoting inclusive growth in the contemporary economy of Lusaka. The aim of the study was to investigate the factors influencing the growth of Small and Medium Enterprises via use of Data Analytics.
The study employed a descriptive research design to achieve the objectives. The following were the research objectives:
i) To identify the types of data analytics tools and practices used among small-scale manufacturing enterprises in Lusaka. 
ii) To examine how data analytics are integrated into decision-making processes among small-scale manufacturing enterprises in Lusaka. 
iii) To explore the perceptions and experiences of small-scale manufacturing enterprises with data analytics on operational efficiency in Lusaka 
iv) To establish challenges faced by small-scale manufacturing enterprises in implementing data analytics on improving efficiency in Lusaka. The study used a questionnaire to collect the required data. The data collected was coded, quantified and analysed quantitatively and qualitatively. Quantitative data was analysed by the use of STATA, Excel. The study recommended the following ways: 
The study concludes that data analytics adoption among SMEs remains very low, and this significantly limits their ability to operate efficiently and make timely, informed decisions. The dominance of manual record-keeping systems and experience-based decision-making suggests that SMEs are missing opportunities to reduce downtime, enhance productivity and streamline operations. Where basic analytics tools such as Excel are used, evidence shows improved production planning and reduction in operational delays, indicating that even simple tools can produce measurable benefits
i) SMEs should begin by incorporating low-cost tools such as Excel, Google Sheets or free statistical packages.
ii) Training programs should be introduced to equip SME managers and staff with basic data management and analysis skills.
iii) SME owners and leaders should be sensitized on the value of data in enhancing decision-making and reducing inefficiencies.
iv) SMEs can adopt a phased approach to technology adoption, beginning with spreadsheets and gradually moving toward dashboards, automated reporting tools and business intelligence software such as Power BI.
v) SMEs should institutionalize periodic review of production, sales and inventory data

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Pages: 200-219     |    3 View     |    0 Download