Answer the following questions on the Case Study 1) Mower sales forecast a. Deve

Question

Answer the following questions on the Case Study

1) Mower sales forecast

a. Develop mower sales (of the company) forecast for NA region (only) for January-March, 2015.

b. Indicate which method you have used, and explain why? What is the margin of error?

c. What are your observations on the nature of mower sales NA region?

NOTE:

It is not required to paste the spreadsheets into the case study report (but if you could show me one will be perfect!)

Instead, summarize the results in the form of table.

For example, different methods and associated MAPE, forecasts and other details.

Here's the data set

Mower Unit Sales
Month NA SA Europe Pacific China World
Jan-10 6000 200 720 100 0 7020
Feb-10 7950 220 990 120 0 9280
Mar-10 8100 250 1320 110 0 9780
Apr-10 9050 280 1650 120 0 11100
May-10 9900 310 1590 130 0 11930
Jun-10 10200 300 1620 120 0 12240
Jul-10 8730 280 1590 140 0 10740
Aug-10 8140 250 1560 130 0 10080
Sep-10 6480 230 1590 130 0 8430
Oct-10 5990 220 1320 120 0 7650
Nov-10 5320 210 990 130 0 6650
Dec-10 4640 180 660 140 0 5620
Jan-11 5980 210 690 140 0 7020
Feb-11 7620 240 1020 150 0 9030
Mar-11 8370 250 1290 140 0 10050
Apr-11 8830 290 1620 150 0 10890
May-11 9310 330 1650 130 0 11420
Jun-11 10230 310 1590 140 0 12270
Jul-11 8720 290 1560 150 0 10720
Aug-11 7710 270 1530 140 0 9650
Sep-11 6320 250 1590 150 0 8310
Oct-11 5840 250 1260 160 0 7510
Nov-11 4960 240 900 150 0 6250
Dec-11 4350 210 660 150 0 5370
Jan-12 6020 220 570 160 0 6970
Feb-12 7920 250 840 150 0 9160
Mar-12 8430 270 1110 160 0 9970
Apr-12 9040 310 1500 170 0 11020
May-12 9820 360 1440 160 0 11780
Jun-12 10370 330 1410 170 0 12280
Jul-12 9050 310 1440 160 0 10960
Aug-12 7620 300 1410 170 0 9500
Sep-12 6420 280 1350 180 0 8230
Oct-12 5890 270 1080 180 0 7420
Nov-12 5340 260 840 190 0 6630
Dec-12 4430 230 510 180 0 5350
Jan-13 6100 250 480 200 0 7030
Feb-13 8010 270 750 190 0 9220
Mar-13 8430 280 1140 200 0 10050
Apr-13 9110 320 1410 210 0 11050
May-13 9730 380 1340 190 0 11640
Jun-13 10120 360 1360 200 0 12040
Jul-13 9080 320 1410 200 0 11010
Aug-13 7820 310 1490 210 0 9830
Sep-13 6540 300 1310 220 0 8370
Oct-13 6010 290 980 210 0 7490
Nov-13 5270 270 770 220 0 6530
Dec-13 5380 260 430 230 0 6300
Jan-14 6210 270 400 200 0 7080
Feb-14 8030 280 750 190 0 9250
Mar-14 8540 300 970 210 0 10020
Apr-14 9120 340 1310 220 5 10995
May-14 9570 390 1260 200 16 11436
Jun-14 10230 380 1240 210 22 12082
Jul-14 9580 350 1300 230 26 11486
Aug-14 7680 340 1250 220 14 9504
Sep-14 6870 320 1210 220 15 8635
Oct-14 5930 310 970 230 11 7451
Nov-14 5260 300 650 240 3 6453
Dec-14 4830 290 300 230 1 5651

Explanation / Answer

Data given in question is vert scattered . It took 1 hour only to tabulaize.

a. Develop mower sales (of the company) forecast for NA region (only) for January-March, 2015.

Answer :

b. Indicate which method you have used, and explain why? What is the margin of error?

Answer : Moving Aveage method is used

c. What are your observations on the nature of mower sales NA region?

Answer :

% contribution of NA to world

If we see abiove % of conribution , its very much clear that majority of the sale is from NA region.So cpmaoany needs to focus more on NA region.

Month NA SA Europe Pacific China World Jan -10 6000 200 720 100 0 7020 Feb-10 7950 220 990 120 0 9280 Mar-10 8100 250 1320 110 0 9780 Apr-10 9050 280 1650 120 0 11100 May-10 9900 310 1590 130 0 11930 Jun-10 10200 300 1620 120 0 12240 Jul-10 8730 280 1590 140 0 10740 Aug-10 8140 250 1560 130 0 10080 Sep-10 6480 230 1590 130 0 8430 Oct-10 5990 220 1320 120 0 7650 Nov-10 5320 210 990 130 0 6650 Dec-10 4640 180 660 140 0 5620 Jan-11 5980 210 690 140 0 7020 Feb-11 7620 240 1020 150 0 9030 Mar-11 8370 250 1290 140 0 10050 Apr-11 8830 290 1620 150 0 10890 May-11 9310 330 1650 130 0 11420 Jun-11 10230 310 1590 140 0 12270 Jul-11 8720 290 1560 150 0 10720 Aug-11 7710 270 1530 140 0 9650 Sep-11 6320 250 1590 150 0 8310 Oct-11 5840 250 1260 160 0 7510 Nov-11 4960 240 900 150 0 6250 Dec-11 4350 210 660 150 0 5370 Jan-12 6020 220 570 160 0 6970 Feb-12 7920 250 840 150 0 9160 Mar-12 8430 270 1110 160 0 9970 Apr-12 9040 310 1500 170 0 11020 May-12 9820 360 1440 160 0 11780 Jun-12 10370 330 1410 170 0 12280 Jul-12 9050 310 1440 160 0 10960 Aug-12 7620 300 1410 170 0 9500 Sep-12 6420 280 1350 180 0 8230 Oct-12 5890 270 1080 180 0 7420 Nov-12 5340 260 840 190 0 6630 Dec-12 4430 230 510 180 0 5350 Jan-13 6100 250 480 200 0 7030 Feb-13 8010 270 750 190 0 9220 Mar-13 8430 280 1140 200 0 10050 Apr-13 9110 320 1410 210 0 11050 May-13 9730 380 1340 190 0 11640 Jun-13 10120 360 1360 200 0 12040 Jul-13 9080 320 1410 200 0 11010 Aug-13 7820 310 1490 210 0 9830 Sep-13 6540 300 1310 220 0 8370 Oct-13 6010 290 980 210 0 7490 Nov-13 5270 270 770 220 0 6530 Dec-13 5380 260 430 230 0 6300 Jan-14 6210 270 400 200 0 7080 Feb-14 8030 280 750 190 0 9250 Mar-14 8540 300 970 210 0 10020 Apr-14 9120 340 1310 220 5 10995 May-14 9570 390 1260 200 16 11436 Jun-14 10230 380 1240 210 22 12082 Jul-14 9580 350 1300 230 26 11486 Aug-14 7680 340 1250 220 14 9504 Sep-14 6870 320 1210 220 15 8635 Oct-14 5930 310 970 230 11 7451 Nov-14 5260 300 650 240 3 6453 Dec-14 4830 290 300 230 1 5651 Jan -15 7550 283 1149 173 1.88 9150 FEB-15 8000 310 1250 180 2.5 9500 MAR-15 8500 325 1325 200 4 10200

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