Performance Lawn Equipment case study in Business Analytics text by James R. Evans. The problem statement is: "An important part of planning manufacturing capacity is having a good forecast of sales. Elizabeth Burke is interested in forecasting sales of mowers in NA, Eur and Pacific regions as well as industry mower sales to assess future changes in market share. She also wants to forecast future increases in market share. She also wants to forecast future increases in production costs. Develop forecasting models for these data and prepare a formal report of your result with appropriate charts and outputs. Can you assist me with how to go about figuring 1st what model to use and the initial steps needed to solve these problem. I just need a starting point please. This is the model: 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