Digital project controls can strengthen capital-project decisions when reliable field evidence, commercial records, schedules, and risk assessments are connected through consistent definitions. Software adoption alone does not establish better cost or schedule performance. This integrative review develops a decision-oriented framework for Saudi mining and industrial projects under Vision 2030. Targeted searches of publicly accessible scholarly material inform an analysis of earned value management, forecasting, information governance, and organizational adoption. The proposed framework links data capture, validation, integrated analysis, managerial intervention, and verification of outcomes. It distinguishes reporting speed from forecast accuracy and separates approved scope growth from uncontrolled deviation. An explicitly hypothetical cost-forecast sensitivity exercise demonstrates how assumptions about remaining productivity affect estimated final cost; it is not presented as a Saudi project dataset. Three tables summarize evidence, control measures, and implementation responsibilities, while a conceptual diagram explains the feedback process. The paper proposes a phased pilot and longitudinal evaluation using dated forecasts, baseline histories, and categorized changes. Its contribution is a practical explanation of the conditions under which digital information may improve control decisions. The framework requires empirical validation and cannot establish achieved savings, reduced delays, or sector-wide performance effects.