The bullwhip effect (BWE) is a challenging phenomenon in supply chains that cause variability to flow from the lowest to the highest echelon which lowers efficiency. Irregular order sizes across multiple suppliers can cause bullwhip effect in a food supply chain. This study investigates the presence of the BWE and employs a Design of Experiment (DOE) approach to mitigate its impact. Focusing on a case study involving key suppliers, the research quantifies the main interaction effects of supplier and production variables on BWE. The DOE methodology highlights critical factors such as supplier-level adjustments and production configurations, identifying optimal strategies to minimize variability. Unlike conventional approaches that heavily rely on forecasting or demand information sharing, this study proposes determining optimal level of order sizes to minimize variability in supply chain. By isolating and testing factor interactions, the research provides a robust framework for addressing variability without the complexities of advanced forecasting methods. The minimum value of the bullwhip effect was obtained by calculating the main and interaction effects of high and low values of the supply of three major raw materials. Thus, this study provides scope for future research upon these findings by integrating forecasting and real-time analytics for a more comprehensive solution.