EARNED VALUE MANAGEMENT AND FORECASTING TO IMPROVE COST PREDICTABILITY IN SAUDI INDUSTRIAL PROJECTS

Cost predictability in industrial projects depends on recognizing the financial consequences of incomplete work before expenditure makes them unavoidable. Earned value management provides a common basis for comparing authorized scope, accomplished work, and incurred cost, but its indicators do not automatically produce a credible estimate at completion. This structured narrative review examines the conditions under which earned value information can support cost forecasting in Saudi industrial delivery.It combines research on earned value systems, statistical forecasting,organizational maturity, and regional construction risks with authoritative estimating guidance. The synthesis develops a proposed forecasting process that separates baseline authorization, performance measurement, remaining-work estimation, uncertainty assessment, and management approval. A worked example shows that identical reporting inputs can generate substantially different completion estimates when assumptions about future efficiency change. The analysis argues for reconciliation between index-based forecasts, bottom-up estimates, and appropriate historical comparisons, with particular attention to procurement, commissioning, scope change, and accounting cut-offs. Forecast quality should be evaluated through preserved historical predictions,consistent scope, and separate measures of error and directional bias.