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The term demand estimation consists of two words: demand and estimation. Demand refers to the degree of want or requirement of a firms product by the external market. On the other hand, estimation implies to predict or project. Therefore, demand estimation is a technique that forecasts the need for a product based on previous market conditions. The technique is important in planning future business activities. In a competitive market, a firm must optimize its operations to remain profitable. For example, company A will suffer a loss if it manufactures 500 items, yet the demand for the product is only 300. The resources used to produce the excess 200 will have been wasted. Hence, estimation enables managers to make decisions that mitigate risks and result in profits. Furthermore, executives can make viable capital investments depending on the accuracy of the forecasts. In 2001, Nike reported a $100 million loss related to poor demand estimation. Prior to the forecasting failure, the sportswear company had installed a $400 million supply chain management system (ERP) from i2 to replace its existing SAP system. The company also instituted a policy requiring retailers to place orders 9 months before the delivery date. However, an overestimation or underestimation in demand led to a huge loss. Particularly, Nike rushed i2 to modify the software using demand analytics that was poorly forecasted. A speedy programming process resulted in a system with errors and bugs (Leshinsky, 2008). Consequently, thousands of demand forecasts were erroneous and drove the wrong decisions. Although the i2 system was a pilot approach, it ended up being a plunge approach whereby the business adopted an entirely new operating system. To prevent the loss, the firm should have used a systematic integration process to replace its SAP system with the new ERP software.