Effect of Project Planning Practices on Performance of Projects: A Case of Rwanda Dairy Development Project in Ruhango District, Rwanda

Effect of Project Planning Practices on Performance of Projects: A Case of Rwanda Dairy Development Project in Ruhango District, Rwanda

Umuhire Mahoro Gisele and Jean de Dieu Dushimimana
University of Kigali
https://orcid.org/0009-0009-1983-5570
Email: umuhiregisele25@gmail.com

Abstract: This study examined the effect of project planning practices on the performance of the Rwanda Dairy Development Project in Ruhango District, Rwanda. The specific objectives were to assess the effect of resources planning, operational planning, and monitoring and evaluation planning on project performance. The study was guided by Resource-Based View Theory, Systems Theory, and the Logical Framework Approach. A descriptive and correlational research design was adopted using quantitative and qualitative approaches and primary and secondary data. The target population comprised 365 individuals directly involved in the planning and implementation of the Rwanda Dairy Development Project, from whom a sample of 191 respondents was selected using Slovin’s formula. Stratified random sampling and simple random sampling were applied to select participants. Primary data were collected using structured questionnaires, while secondary data were obtained through documentation review. Data were analysed using SPSS version 27 through descriptive statistics, bivariate correlation, and multiple linear regression. The regression findings showed that resources planning was the strongest predictor of project performance (B = 0.521, t = 10.633, p = 0.000), followed by operational planning (B = 0.223, t = 4.956, p = 0.000) and monitoring and evaluation planning (B = 0.196, t = 3.769, p = 0.000). The study concluded that structured planning across resources, operations, and monitoring and evaluation significantly enhances project performance. It recommends establishing a centralized digital resource registry to improve material inventory and vehicle allocation.

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