Develop a forecast for FY2020 using the two forecasting methods currently employed by the company. (ROUND UP to the next whole number) Comment on which of the forecasts is likely to be more appropriate to support decisions based on your assessment of forecast accuracy from Q1. Based upon this, identify which forecast method that you will use going forward with the project.

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Here is the missing information.

Product Orders (Demand) Information The company provides you with the following information for the past two fiscal years: FY 2018 Demand Characteristic Annual demand, units Average weekly demand, units Variance of weekly demand, units 18,000 375 FY 2019 20,000 417 100 90 Product Forecasting Information Throx uses two main forecasting methods based on annual data to predict orders for the following year, a weighted moving average and exponential smooth They provide you with the following information about forecasts for FY 2018 and FY 2019: Weighted Moving Exponential Year Demand Average Forecast Forecast 2018 18,000 18,200 18,780 2019 20,000 18,400 18,078 Weighted Moving Average uses W, = 0.6 and W-1=0.4. Exponential Smoothing uses a = 0.9. B D E F G H 1 Year Demand WMA Forecast Error Abs error Abs % error Exponential forecast Error Abs error Abs % error 2 2018 18000 18200 -200 200 1.11% 18780 -780 780 4.33% 3 2019 20000 18400 1600 1600 8.00% 18078 1922 1922 9.61% 4 5 For WMA For Exponential 6 MFE = 700 MFE = 571 7 MADE 900 MAD= 1351 8 MAPE= 4.56% MAPE= 6.97% 9 B F G H 1 Year 2 2018 3 2019 Demand 18000 20000 D E WMA Forecast Error Abs error 18200 =B2-C2 =ABS(D2) 18400 =B3-C3 =ABS(D3) Abs % error Exponential forecast Error Abs error Abs % error =(E2/B2) 18780 =B2-G2 =ABS(H2) =12/B2 = (E3/B3) 18078 =B3-G3 =ABS(H3) =13/B3 4 5 For WMA 6 MFE = =AVERAGE(D2:D3) 7 MAD= =AVERAGE(E2:E3) 8 MAPE= =AVERAGE(F2:F3) For Exponential MFE = =AVERAGE(H2:H3) MAD= =AVERAGE(12:13) MAPE= =AVERAGE(12:13) Both forecast models, both of them under forecast demand, are insufficient. The WMA model is slightly superior because its margin of error is 4.6 percent, which is smaller than the Exponential prediction model, but both models are not ideal for decision making. PLEASE LEAVE A LIKE, IT HELPS ME A LOT. THANKS