Question

The following table shows predicted product demand using your particular forecasting method along with the actual demand that occurred:

FORECAST	ACTUAL
1,490	1,540
1,390	1,490
1,690	1,590
1,742	1,640
1,790	1,690

a. Compute the tracking signal using the mean absolute deviation and running sum of forecast errors. (Negative values should be indicated by a minus sign. Round your "Mean Absolute Deviation", "Tracking Signal" to 2 decimal places and all other answers to the nearest whole number.)

Period	Forecast	Actual	Deviation	RSFE	Absolute Deviation	Sum of Absolute Deviation	MAD	TS
1	1,490	1,540
2	1,390	1,490
3	1,690	1,590
4	1,742	1,640
5	1,790	1,690
q2) The tracking signals computed using past demand history for three different products are as follows. Each product used the same forecasting technique. TS 1 TS 2 TS 3 1 ?2.81 1.54 0.16 2 ?2.43 ?0.65 0.45 3 ?1.81 2.01 1.05 4 ?1.21 2.57 1.80 5 ?0.96 ?0.97 1.83 6 ?0.08 ?1.29 2.27 7 0.16 0.71 2.95 8 0.43 ?1.51 3.13 9 1.53 0.45 3.55 10 2.21 2.75 3.75 a. Graph the tracking signals for each product.

Answer 1

PLEASE FIND BELOW ANSWER TO FIRST QUESTION ( QUESTION # A ) :

Period	Forecast	Actual	Error	Running sum of forecast error ( RSFE )	Absolute deviation ( AD)	Sum of absolute deviation	MAD	Tracking signal ( TS )
1	1490	1540	50	50	50	50	50	1
2	1390	1490	100	150	100	150	75	2
3	1690	1590	-100	50	100	250	83.33	0.60
4	1742	1640	-102	- 52	102	352	88	-0.59
5	1790	1690	-100	-152	100	452	90.4	-1.68

Following may be noted :

Error for period t = Actual for period t – Forecast for period t

Absolute deviation for period t = Absolute difference between values : actual for period t and Forecast for period t

RSFE for period t = Sum of forecast errors from period 1 upto period t

Sum of absolute deviation for period t = Sum of absolute deviation from period 1 till period t

Mean absolute deviation ( MAD ) for period t = Sum of absolute deviation values from period 1 to period t / t

Tracking signal for period t = RSFE for period t / MAD for period t