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Littlefield Technologies Game 2

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Littlefield Technologies Game 2 Strategy – Group 28 1. CUSTOMER ORDERS AND ORDERS WAITING FOR MATERIAL: When considering the demand level and changes, we would configure a time series of that data using short range forecasting. Time series are important because they are often the drivers of decision models. Trend projection and regression analysis models will be used to forecast the future demand as the growth of the demand increases at a lower level, increases to a higher level, and then decreases over the course of the project. The following equation applies to this analysis:

Regression Analysis ŷ = a + bx

After using the first 50 days to determine the demand for the remainder of the project, we can then determine the average daily demand for raw material kits by dividing the total of the forecasted demand by the life of the project (365 days). This calculation will give us the average number of daily orders and thus the average number of raw material kits needed, assuming the ratio of 1:1 between receivers and raw material kits remains constant. The calculation can be expressed as: Average daily demand for raw material kits = ∑demand n

As the demand for orders increases, the reorder point and reorder quantity will also need to be increased. As the demand for orders decreases, the reorder point and reorder quantity will need to be adjusted accordingly. To estimate the standard deviation of demand, the following formula would be used:

Where x is the value of demand and is the daily average value of demand, and N is the number of days in the project. The standard deviation will show how accurate the demand for the project was forecasted. A high standard deviation signals inaccurate data, while a low standard deviation indicates fairly reliable data. To estimate the standard deviation of lead time, the following formula is

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