Demonstrate how to perform forecasting using data-statistics

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Your boss comes in “with their hair on fire”, and says, “just came from a staff meeting and the CEO announced the building next door is coming available at a really good price per square foot.” He needs you to tell him if the forecasted demand for the next 36 months is high enough that we may need some of the new space. He follows up with, “If we miss this opportunity, and later we figure out that we need more space then the only option is to rent space in another building about 5 miles away at almost double the price per square foot”. As the operations manager, the last thing you want to do is to split your staff across two different buildings. That is going to be a staffing and scheduling headache, not to mention morale will take a hit. Do you shoot from the hip and tell your boss, “no doubt, forecasted demand indicates we can use the space”, or do you say, “let me run the forecast and get back to you later today”? Which response has the most risk? Are you willing to bet your job on your answer? Forecasting is both an art and a science. In the assignments for Unit 2 you will get the opportunity to practice forecasting by solving end of chapter problems and completing a linear trending assignment. In order to determine if it makes sense to rent additional space, it will be important to assess the level of operational efficiency of existing processes associated with the delivery of products to consumers. Improving process efficiencies could result in a reduction in labor requirements. Maybe the company can support greater demand with a leaner labor force. In this unit, in addition to applying forecasting models to scenarios, you will also gain a more in-depth understanding of the concept and practices used to create efficient organizations. Unit Learning Outcomes Develop a plan for forecasting impacts to an organization’s bottom line. (CLO 1, 2, 4, and 7) Demonstrate how to perform forecasting using data and statistics. (CLO 4 and 5) Identify trends and patterns in data as they apply to forecasting. (CLO 1, 3, 5, and 7) Develop a data collection plan that will permit the creation of an accurate and reliable forecasting model. (CLO 3, 4, and 5.

Reference no: EM132279524

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