1. Quantitative Analysis for Business Lecture 10 September 13th, 2010 http://www.slideshare.net/saark/ibm401-lecture-10

2. Example i Data shown is average monthly production of a commodity for the year 1948 – 1958 Construct a 5 year moving average Construct a 4 year centered moving average

3. Example ii Monthly sales of A4 copy paper have been recorded over 12 months (Year 1) Using F0 = 1700, which α do you recommend? α = 0.2 α = 0.5 From selected α, calculate Trend using β = 0.1 and T0 = 100

4. Example ii Supposed sales team has come back with additional data of Year 2 sales, find seasonal index using 4 period centered-moving-average Deseasonalize the data

5. Example ii Using the Forecast method obtained from part 1 of this question, calculate tracking signal of June of year 1.

6. solution

7. Example i 5-year moving average MA5-year = (Ft-5 + Ft-4 + Ft-3 + Ft-2 + Ft-1)/5 4-year centered MA CMA4-year = (0.5*(Ft-2 + Ft+2) + (Ft + Ft-1 + Ft-2))/4

8. Example i 5-year moving average & 4-year centered MA

9. Example ii Determining which α, choose the one with lowest MAD New forecast = Last period’s forecast + (Last period’s actual demand - Last period’s forecast)

10. Example ii

11. Example ii

12. Example ii calculate Trend using β = 0.1 and T0 = 100

13. Example ii

14. Example ii Find seasonal index using 4 period centered-moving-average Use CMA formula Deseasonalizethe data Find seasonal index from CMA st = Actualt / CMAt

15. Example ii – Find CMA and seasonal index

16. Example ii – Find average seasonal index

17. Example ii - deseasonalize

18. Example ii Using the Forecast method obtained from part 1 of this question, calculate tracking signal of June of year 1 RSFE = Ratio of running sum of forecast errors = ∑(actual demand in period i - forecast demand in period i)

19. Example ii – Tracking signal

20. Example ii June, Year 1 Tracking signal