IntroductionAll businesses face the general problem of having to make decisions under conditions of uncertainty. Management must understand the nature of demand and competition in order to develop realistic business plans, determine a strategic vision for the organization, and determine technology and infrastructure needs. To address these challenges, forecasting is used. According to Makridakis (1989), forecasting future events can be characterized as seeking answers to one or more of the following questions: "X What new economic, technical or sociological forces is the organization likely to face in short and long term? term ? „X When might these forces impact the company's objective environment? „X Who is likely to be the first to adapt to each competitive challenge? „X How much change should the company anticipate in both the short term and the long term? ?In this article, I will provide an overview of forecasting methods and compare and contrast these different methods. The article will then focus on how Mattel, one of the nation's largest toy manufacturers, uses demand forecasting under conditions of uncertainty, specifically those related to the structure and pace at which customers request products. What is forecasting? In operations management, demand forecasting is defined as "the business process that attempts to estimate the sales and usage of products so that they can be purchased, stored, or manufactured in advance in appropriate quantities to support the company's value-added activities. » (Ross, 1995). Forecasting is a process that transforms historical time series data and/or qualitative assessments into statements about future events. This process can produce qualitative or subjective projections. Note that no forecasting process can consistently provide perfect forecasts. Any forecast that perfectly estimates subsequent events should raise concern, as this likely indicates irregularities such as “rigging the books” or reporting performance data that shows conformance to plans versus actual events (Makridakis, 1989). Forecasting Methods There are four basic types of forecasting methods: qualitative, time series analysis, causal relationships, and simulation. Qualitative Techniques Qualitative techniques are subjective or judgment-based and based on estimates and opinions (Chase, 2005). These forecasts reflect people's judgments or opinions and suggest likely conditions, such as people's opinions on whether or not it will rain today. These forecasts are preferred when we wish to involve individuals within the organization in a key business process. A potential pitfall of this technique is that some people base their judgments about future events on historical data, which may not provide relevant and sufficiently stable demand patterns to justify their use in forecasting future events...