Question

Use Excel to calculate the values to fill in the empty boxes. Feel free to add additional tables and calculations as
needed. Please use the assignment 1 discussion board to ask questions. Once completed, save this file and
upload it in Canvas.
Historical Demand Data 2012 to 2016:
The table reproduced below is the demand data for a company (aggregated) for the previous five years.
	2012	2013	2014	2015	2016
Q1	11632	15034	16117	15565	16470
Q2	22509	26824	24169	20151	42858
Q3	21646	13314	14505	13392	19278
Q4	11355	10698	11176	10613	13934
Annual Demand	67,142	65,870	65,967	59,721	92,540
Average Quarterly Demand	16,785.50	16,467.50	16,491.75	14,930.25	23,135.00
Forecasting Using Moving Average Methods
Using the historical demand data above, you are to determine the total annual demand forecast for 2016 and 2017 using:
Ø the three-period moving average forecasting method
Ø the three-period weighted moving average method with weights of .6, .3, and .1					use .6 for most recent period				(Use .6 for most recent period)
Enter your forecast results in the following tables.
2016 Annual Forecast Using a Moving Average	2016 Annual Forecast Using a Weighted Moving Average			2017 Annual Forecast Using a Moving Average	2017 Annual Forecast Using a Weighted Moving Average
63,852.67	62209.7			72742.67	80037
Calculate a Time Series Linear equation using the all of the above demand data:
Using the historical demand data for 2012 through 2016, create a linear equation with the year as the independent variable and the annual volume as the dependent variable.
	(Excel can be quite useful here, consider the Slope and Intercept functions)
Enter your linear equation in text from here:					y = a + bX
Calculated 2017 Annual Forecast from Linear Equation:						x=2017
Forecasting Using an Exponential Smoothing Method and Seasonal Factors:
Using the historical demand data for 2012 through 2016 given on the first page you are to:
Ø Using the exponential smoothing forecasting method with an alpha value of 0.7, forecast the total annual demand for 2017. Start your forecast calculations with the total annual demand for 2012 and a starting forecast for 2012 that is the
	same as the 2012 total annual demand. After you have the annual forecast for 2012, use the average seasonal factors determined in the first part above to calculate the quarterly demand forecasts for 2017.
Ø Determine the average seasonal factors for each quarter. Remember that you will first need to calculate the total annual demand and then average quarterly demand for each year of data as shown in lecture.
Ø Determine the MAD, CFE, and MAPE errors between the annual forecast values using exponential smoothing for 2013 to 2016 and the actual annual demand data for 2013 to 2016. Enter the values in response to the three questions below.
	2012	2013	2014	2015	2016	2017
Actual Annual Demand	67,142	65,870	65,967	59,721	92,540							alpha=	0.7
Forecasted Annual Demand	67,142	67142	66251.6	66052.38	61620.414
Forecast Error		-1,272	-285	-6,331	30,920
Values	Seasonal Factor for each Quarter	2017 Quarterly Forecast		Index	2012	2013	2014	2015	2016
Quarter 1	0.89			Q1	0.69	0.90	0.96	0.93	0.98
Quarter 2	1.63			Q2	1.34	1.60	1.44	1.20	2.55
Quarter 3	0.98			Q3	1.29	0.79	0.86	0.80	1.15
Quarter 4	0.69			Q4	0.68	0.64	0.67	0.63	0.83
Totals	4.19
What is the MAD value for the exponential smoothing forecast? Answer =
What is the CFE value for the exponential smoothing forecast? Answer =
What is the MAPE value for the exponential smoothing forecast? Answer =
Forecasting using trend with regression:
Calculate forecasts for 2017, 2016 and 2015 using a linear regression of the previous three actual demand values.
	(Hint: You will need to calculate three different linear equations.)
	2012	2013	2014	2015	2016	2017
Actual Annual Demand	67,142	65,870	65,967	59,721	92,540			slope	-587.5
Forecasted Annual Demand	67,142	67,142	66,252	66,052	61,620			intercept
Forecast Error				-6,331	30,920
What is the MAD value for the trend with regression forecast? Answer =
What is the CFE value for the trend with regression forecast? Answer =
What is the MAPE value for the trend with regression forecast? Answer =

Answer 1

Formulas:

A10 =AVERAGE(C6:E6)

B10 =E6*0.6+D6*0.3+C6*0.1

E10 =AVERAGE(D6:F6)

F10 =F6*0.6+E6*0.3+D6*0.1

B13 =ROUND(INTERCEPT(B6:F6,B1:F1),2)&" + "&ROUND(SLOPE(B6:F6,B1:F1),2)&"X"

D15 =-8921657.8+4464.7*2017

C20 =B20+(B19-B20)*$F$17 copy to C20:F20

C21 =C19-C20 copy to C21:F21

C22 =ABS(C21) copy to C22:F22

C23 =C22/C19   copy to C23:F23

E25 =AVERAGE(C22:F22)

E26 =SUM(C21:F21)

E27 =AVERAGE(C23:F23)

B33 =-8921657.8+4464.7*B31 copy to B33:F33

C34 =C32-C33 copy to C34:F34

C35 =ABS(C34) copy to C35:F35

C36 =C35/C32 copy to C36:F36

E38 =AVERAGE(C35:F35)

E39 =SUM(C34:F34)

E40 =AVERAGE(C36:F36)