Improving Forecast Accuracy as an Effort to Enhance Business Performance

Abstract

This research investigates the role of forecasting accuracy in improving business performance. Forecasting has become a critical managerial tool in dynamic business environments where demand fluctuations and market uncertainty often challenge strategic decision-making. The main objective of this research is to empirically test whether higher forecasting accuracy contributes significantly to enhancing business performance. A quantitative approach was employed using survey data collected from firms in hospitality and the food and beverage industries. Data were analyzed using Structural Equation Modeling – Partial Least Squares (SEM-PLS) to examine the relationships among data quality, forecasting techniques, forecasting accuracy, and business performance. The findings indicate that forecasting accuracy mediates the effect of data quality and forecasting methods on business performance. Furthermore, the study concludes that big data capabilities and structured budgeting significantly improve forecast accuracy, with big data being the most influential factor, while competitive intensity does not exert a significant direct impact. Importantly, forecast accuracy itself strongly and positively affects business performance, underscoring its role as a critical mediator between organizational capabilities and performance outcomes. The study contributes to the literature by providing empirical evidence on the mediating role of forecasting accuracy and offers practical implications for managers to design more accurate forecasting systems that support sustainable business growth.