1. SEASONALITY with a TREND Operations Management Dr. Ron Lembke

2. Seasonality with a Trend Demand goes up and down on a regular, time-based pattern AND demand is on a long-term upward (or downward) trend

3. Trend & Seasonality Deseasonalize to find the trend 1.Calculate seasonal relatives 2.Deseasonalize the demand 3.Find trend of deseasonalized line Project trend into the future 4.Project trend line into future 5.Multiply trend line by seasonal relatives.

4. Washoe Gaming Win, 1993-96 Looks like a downhill slide -Silver Legacy opened 95Q3 -Otherwise, upward trend 1993 1994 1995 1996 Source: Comstock Bank, Survey of Nevada Business & Economics

5. Washoe Win 1989-1996 Definitely a general upward trend, slowed 93-94

6. 1989-2007

8. 1998-2007 Cache Creek Thunder Valley CC Expands 9/11

9. 1997-2012

11. 2013 Forecast using 2003-12 SR Data for LR Seasonal Relatives calculated using 2003-12 data

13. 1.Compute Seasonal Relatives 2003200420052006200720082009201020112012Avg Q1240.1231.6245.8 244.6227.9190.1187.0174.1175.4216.3 Q2259.3259.8269.2269.7273.5237.0211.9198.3192.1183.3235.4 Q3279.8297.4294.8 284.7259.0217.2209.6203.9201.8254.3 Q4246.1259.6257.0257.2246.4206.2186.0175.6175.5166.8217.6 Avg230.9 AvgSR Q1216.30.937 Q2235.41.020 Q3254.31.101 Q4217.60.943 Divide 216.3 by 230.9 = 0.937

14. 2.Deseasonalize YearQuarterGaming WinSeasonal RelativeDeseas 20091 190,098,500 0.937 202,978,936 2 211,913,667 1.020 207,841,838 3 217,227,445 1.101 197,232,693 4 185,971,111 0.943 197,212,207 20101 187,016,132 0.937 199,687,717 2 198,330,968 1.020 194,520,124 3 209,608,491 1.101 190,315,028 4 175,601,589 0.943 186,215,895 20111 174,138,905 0.937 185,937,972 2 192,122,889 1.020 188,431,331 3 203,912,214 1.101 185,143,066 4 175,510,911 0.943 186,119,736 20121 175,417,340 0.937 187,303,030 2 183,305,632 1.020 179,783,494 3 201,825,465 1.101 183,248,392 4 166,760,853 0.943 176,840,777 Divide 198,098,500 by 0.937 = 202,978,936

15. 3.LR on Deseas data Period Deseasonalized 1 202,978,936 2 207,841,838 3 197,232,693 4 197,319,016 5 199,687,717 6 194,520,124 7 190,315,028 8 186,316,749 9 185,937,972 10 188,431,331 11 185,143,066 12 186,220,538 13 187,303,030 14 179,783,494 15 183,248,392 16 176,936,554

16. 4.Project trend line into future

17. 5.Multiply by Seasonal Relatives PeriodQ Linear Trend Line Seasonal Relative Seasonalized Forecast 171 176,330,767 0.937 165,141,344 182 174,654,854 1.020 178,076,517 193 172,978,941 1.101 190,514,933 204 171,303,027 0.942 161,451,313

19. Summary 1.Calculate seasonal relatives 2.Deseasonalize 1.Divide actual demands by seasonal relatives 3.Do a LR 4.Project the LR into the future 5.Seasonalize 1.Multiply straight-line forecast by relatives