Urban Run Athletic Wear Case Study Essay

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Case Study: Bram-Wear 1. Is seasonal exponential smoothing the best model for forecasting Urban Run athletic wear? Why? I think that seasonal exponential smoothing is not the best model to be used for forecasting for the Urban Run athletic wear. This is because it is utilized for off-seasonal time arrangement demonstrating no deliberate pattern, this implies the technique properties exponentially lessening weights as the information ages. By doing this, most recent information is given moderately more weight than past information. 2. Explain what has happened to the data for Urban Run. What are the consequences of continuing to use seasonal exponential smoothing? What models would you use? Generate a forecast for the 4 quarters of the 4th year using your model. Determine your forecast error and the inventory consequences. The information for Urban Run athletic has been smoothened utilizing the strategy, yet it winds up giving the wrong …show more content…

327) It is undetermined in being able to use the forecast method due to the fact that there is not data to compare it to. Furthermore, in this case, there cannot be any ramification to the inventory that can be identified. 3. Is exponential smoothing with trend the best model for forecasting five-pocket cargo jeans? Why? I feel that exponential smoothing is a direction that is not the right strategy to use to figure for five-pocket load jean. This is on the grounds that the conjecture levels of stock are elevated to high. This misinforms the clients of the data and they wind up having an excessive amount of stock in inventory. The simple moving average technique is the strategy I would utilize (Reid and Sanders, 2013, p. 291). Demand for 5-Pocket Cargo Jeans Year 1 Demand Year 2 Demand Month Janurary 36 98 February 42

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