Forecasting MethodsDemand forecasting is not an easy task. The market is constantly changing and makes product demand difficult to predict. Therefore, there is no perfect forecast of what products customers will need in the future. However, there are several methods that can mitigate the uncertainty associated with demand forecasting. Since then, forecasting methods or techniques have differed from each other; The goal is to compare and contrast several forecasting methods, and how they are best used by organizations under conditions of uncertainty. One of the forecasting techniques commonly used by organizations is the historical analogy. Chase et al. (2005), define that historical analogy “links what is intended to a similar element” (p. 514). This technique is used when the company plans to launch a new product in the market. Since there is no data available for the new product, organizations try to compensate for the uncertainty by using data from products with similar characteristics. Similarly, market research technique also uses data collection to forecast demand. Data collection is mainly done through surveys and direct interviews. Companies use this technique to be able to offer better products than existing ones. Uncertainty about what customers want or don't like is reduced by collecting data directly from them. It is common for organizations to hire external companies to conduct this survey and provide forecasts. Since external organizations are only dedicated to forecasting activities; they generally provide adequate and accurate information. The collaborative or consensus forecasting technique has several similarities with the historical analogy. In their article, Helms et al. (2000) mentioned that “collaborative forecasting is one of the ways that many companies have found to overcome some of the problems inherent in traditional forecasting and at the same time support their companies' supply chain management initiative . Collaborative forecasting is a method in which knowledge and information that exists internally and externally is brought together into a single, more accurate forecast that has the support of the entire supply chain” (p. 395) . In the consensus method, all members of the supply chain actively participate in developing an adequate forecast. The panel consensus method uses open meetings where all participants provide or exchange ideas. Additionally, instead of relying solely on historical data, the consensus method goes even further..