1. Demand Forecasting for Tahoe Salt. Use Excel to work through the static forecasting for the Tahoe Salt problem (4th Edition, Chapter 7) Your results should match the given solution

Since there are an even number of period, I will have to find the average of two averages corresponding with periods 1-4 and 2-5. Example De-seasonalized Data Period 3: Ð2.5/= (8000+13000+23000+34000)/4 = 19500, Ð3.5/= (13000+23000+34000+10000)/4= 80000

Ð3/= (80000+19500) = 49750. The formula for this methodology is the following: Ðt/= [Dt-(p/2)+Dt+(p/2)+2]/2P. In excel use the following formulas to calculate the de-seasonalized data = (((SUM (Dt-2: Dt+1)/4) +(SUM (Dt-1: Dt+2)/4))/2) For Example: for period 8 = (((SUM (D7:D10)/4) +(SUM (D8:D11)/4))/2)

Results Column 5:

Run the Regression provided by Excel Solver to come up with the following Data

T: Trend = 524: Level = 18348.99

Regressed Equation: Regressed Demand = 18348.99+524t. Plugging =18439+A2*524 into Excel and copying down the Regressed Data column to apply the regression equation to all actual demand points results in the following:

Results Column 6:

Determine the Seasonal Factors. Formula: St = Dt/Ðt/. Results:

Each seasonal factor is summed up with its corresponding factor in each season cycle. For example: Since their cycles are divided up into quarter the formula will result: Savg1 = (S1+S2+S3)/4, Savg3 = (S3+S7+S11)/4



Johnson, Tara (2018). How the Amazon Supply Chain Strategy Works? Tinuiti.

Krajewski, L., Ritzman, M., Malhotra, N (2006). Operations Management: Processes and Value Chains. (8th edition). Prentice Hall.

Liker, J.K. (2005). The Toyota Way and Supply Chain Management”, Presentation for OESA Lean to Survive Program, The University of Michigan

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