This scenario is about Burns Auto Corporation (BAC), an automobile dealership company with a major regional presence that is operating in a highly competitive environment and is contending with uncertainty regarding the accuracy of its sales forecasting (Scenario OneBurns Auto Corporation: Read Me First). In order to align with the "turn and earn" approach soon to be implemented by auto manufacturers, BAC needs to reassess their current sales forecasting methods. They need to consider appropriate variables (e.g.: household income, interest rates, sticker prices, seasonal promotions, and gas mileage), collect sales figures from dealerships, and align data against other variables in order to build this model.
The leaders of BAC are presented with three (or possibly more) different statistical models in which to use to forecast sales (Week Four scenario, U of P). BAC already has a very good understanding of forecasting, to the point where theirs is almost a direct opposite problem than that of USA World Bank. USA World Bank did not know enough about statistically driven decisions whereas BAC knows enough to have brought in consultants who have presented three potentially good forecasting models in which to choose. Focusing in on the correct model is their immediate situation.
The forecasting models BAC are considering include correlation and regression analysis, time series analysis, sensitivity analysis, and game theory as methods to improve their future car sales decision making.
BAC needs to ensure that they are identifying appropriate variables and they need to decide whether to use a top-down or an individual dealership approach in which to conduct data analysis. They also need to be certain they are not making a risky, expensive decision based on only two years of difficult inventory management and sales forecast problems.
BAC has employed the help of two different... [continues]
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