Supply chain is a bridge between demand and supply. It conveys the demand to the supply point and delivers the quantity to the demand point. It is a network, that facilities the functions of procurement of materials, transformation of these materials into intermediate and finished products and the distribution of these finished products to customers. The Bullwhip Effect represents the information distortion in a Supply chain. It represents the phenomenon where orders to supplier tend to have larger variance than sales to the buyer. The customer demand is distorted. This demand distortion also propagates to upstream stages in an amplified form in the supply chain. The demand forecasting is one of the key-factors to influence the bull-whip effect. Winter__ampersandsignlsquo;s Triple Exponential smoothening model is applied to forecast the future demand. The purpose of this study is to analyze the impact of exponential smoothing parameters on the bullwhip effect for Supply Chain Management (SCM). A simulation model is developed to determine the Forecasted demand and bullwhip ratio value. Further, accuracy of Forecasting alculated by the Winter__ampersandsignlsquo;s model is examined by applying Tracking Signal Technique. A sensitivity analysis is done to experiment with the different values of parameters in the forecasting technique. It is found that longer lead times and poor selection of forecasting model parameters lead to strong bullwhip effect in SCM. The optimized values of parameters help to reduce the bullwhip ratio. The most significant managerial__ampersandsignnbsp; mplication of this study lies in applying best forecasting technique with accuracy testing of forecasting model, to mitigate the bullwhip effect. The managers are suggested to utilize the best exponential smoothing by selecting lower values for alpha and beta and a mid-value for gamma to keep the bullwhip ratio low, besides the forecasting accuracy.