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. https://tinuiti.com.
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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