Analysis of factors affecting Efficient Practices and Techniques for Allocating Provisional Sums in Construction Management

Abstract

Cost estimation for electrical services in construction projects remains a critical challenge, particularly in Nigeria, where cost uncertainties in mechanical and electrical (M&E) services lead to budget overruns and project delays. The estimation of provisional sums for electrical installations is often imprecise due to incomplete design specifications, fluctuating market prices, and the absence of standardized estimation frameworks. These limitations impact financial planning, contractor-client relationships, and overall project efficiency. This study aims to analyse effective cost estimation techniques for allocating provisional sums in electrical installations and to identify causal factors affecting their accuracy. Specifically, it seeks to examine current industry practices, analyze the reliability of various estimating techniques, and propose a refined framework for improving cost estimation accuracy in electrical services. A quantitative research design was adopted, utilizing structured questionnaires administered to 83 professionals, including quantity surveyors, electrical engineers, and project managers involved in residential construction projects in Owerri, Nigeria. Simple random and snowball sampling methods were used to ensure a representative sample of experienced professionals. The collected data were analyzed using descriptive statistics. The findings highlight that engineering cost estimating and resource analysis emerged as the most effective methodologies for determining provisional sums. However, factors such as incomplete design details, unclear specifications, and organizational policies significantly impact the accuracy of estimates. The study concludes that improving the proficiency of estimators, integrating modern computational tools, and ensuring complete project specifications can significantly enhance cost estimation accuracy. It recommends the adoption of digital modeling techniques, increased training for cost estimators, and the establishment of standardized guidelines for electrical service cost estimation. These improvements can help mitigate cost-related disputes, optimize budget allocations, and improve overall project outcomes.