Question

The demand for this SKU during the past five years is shown in the table below: Month 2014 2015 2016 2017 2018 Jan 211 244 291 323 328 Feb 338 403 386 478 510 Mar 191 213 335 327 310 192 Apr May 244 278 327 346 138 153 159 211 261 Jun 148 195 209 342 296 Jul 205 231 288 394 205 364 244 327 374 331 Aug Sep Oct 164 337 263 304 305 200 247 280 337 300 Nov 205 234 282 304 322 Dec 229 438 273 357 369 2 Ms. Patel has retained your services to recommend a forecasting methodology to estimate the demand of generic lubricant. Your document should contain: | 1. A forecasting error comparison of these methodologies: • Two-period moving average . Three-period moving average o Single Exponential Smoothing with constants of 0.4 and 0.3 2. A summary of your recommended next steps. Include the Excel file showing all calculations.

Answer 1

1)

comparing Mean absolute error or deviation for various forecasting techniques, details calculation with formula are as state below:

Absolute deviation=Actual- Forecast

MAD=average of all Absolute deviation values

A B K 1 1 B с Ic Month L 2 Year D E F G H D E G H Actual Data Forecasting Absolute Forecasting using 3 Absolute Exponential using 2 period deviation=Actual period moving deviation=Actual- smmothing using moving average Forecast average Forecast alpha 0.4 Absolute deviation=Actual- Forecast K Exponential smmothing using alpha 0.3 Absolute deviation=Actual- Forecast 2 3 3 2014 Jan 211 4 4 2014 211.00 127.00 211.00 249.10 2014 338 191 192 70.80 5 5 66 Feb Mar Apr May 274.50 264.50 191.50 83.50 72.50 261.80 233.48 127.00 58.10 39.67 2014 246.67 54.67 41.48 231.67 7 7 138 53.50 240.33 102.33 78.89 219.77 81.77 2014 2014 216.89 185.33 8 8 148 165.00 173.67 37.33 195.24 47.24 Jun Jul 25.67 45.67 99 205 143.00 159.33 34.60 23.93 2014 2014 181.07 188.25 10 10 244 176.50 17.00 62.00 67.50 60.50 4.00 163.67 Aug Sep Oct 59.76 44.14 11 11 55.75 40.97 164 224.50 199.00 170.40 184.24 208.14 190.49 194.29 204.97 80.33 35.00 4.33 2.33 12 12 200 204.00 9.51 2014 2014 2014 2014 192.68 7.32 13 13 Nov 205 182.00 23.00 10.71 10.12 204.33 202.67 189.67 211.33 194.88 197.91 14 14 229 202.50 26.50 39.33 198.58 30.42 31.09 244 217.00 27.00 32.67 210.75 33.25 207.24 36.76 2015 2015 403 236.50 166.50 226.00 177.00 15 15 16 16 17 17 18 18 178.95 82.63 213 323.50 110.50 79.00 218.27 273.69 255.48 224.05 295.63 262.58 255.15 184.73 60.69 11.48 244 308.00 292.00 286.67 286.67 64.00 2015 2015 2015 2015 42.67 18.58 Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct 19 19 153 228.50 75.50 133.67 102.15 252.04 99.04 20 20 195 198.50 203.33 8.33 222.33 27.33 214.29 206.57 19.29 24.43 21 21 3.50 57.00 114.00 2015 231 197.33 214.13 16.87 33.67 134.00 22 22 327 193.00 216.34 110.66 219.19 107.81 174.00 213.00 279.00 332.00 2015 2015 2015 23 23 337 58.00 251.00 86.00 260.61 251.53 85.47 76.39 44.16 24 24 247 85.00 298.33 51.33 291.16 277.17 30.17

25 25 2015 Nov 234 292.00 69.67 39.50 268.12 Dec 438 180.30 26 26 27 27 240.50 336.00 165.33 15.33 257.88 311.92 34.12 180.12 20.92 291 38.82 2015 2016 2016 2016 Jan Feb 28 28 386 364.50 303.67 272.67 306.33 321.00 371.67 337.33 333.00 65.00 305.64 80.36 29 29 335 338.50 36.67 58.00 197.50 45.00 21.50 3.50 82.50 147.50 9.50 21.00 157.00 273.50 257.70 329.82 314.29 342.97 339.78 315.07 252.64 235.19 223.11 71.71 7.97 61.78 156.07 30 30 2016 Mar Apr May Jun 278 360.50 59.33 5.25 53.33 156.33 59.43 31 31 159 306.50 174.00 329.75 331.33 315.33 268.43 250.60 2016 2016 32 32 209 218.50 48.33 43.64 33 33 2016 205 184.00 257.33 215.33 191.00 45.60 Jul Aug Sep 10.33 173.00 34 34 2016 364 207.00 236.92 127.08 35 35 2016 263 284.50 21.50 3.67 275.04 12.04 259.33 277.33 30.19 140.89 16.47 7.12 6.27 5.24 36 36 2016 Oct 280 313.50 33.50 2.67 271.43 37 37 282 271.50 302.33 20.33 Nov Dec 10.50 8.00 279.47 272.88 275.73 278.24 276.14 274.00 276.40 8.57 8.00 3.40 38 38 273 281.00 275.00 2016 2016 2017 2017 2.00 39 39 Jan 323 277.50 278.33 46.86 275.38 47.62 45.50 180.00 Feb 478 298.00 294.89 44.67 185.33 31.00 183.11 40 40 41 41 289.67 292.67 358.00 188.33 19.17 2017 346.17 400.50 402.50 73.50 75.50 327 327 211 368.13 351.68 42 42 2017 376.00 340.42 Mar Apr May Jun 13.42 49.00 166.33 327.00 116.00 377.33 341.81 336.39 41.13 24.68 130.81 52.52 22.49 43 43 44 44 125.39 2017 2017 342 269.00 73.00 288.33 53.67 289.48 298.77 43.23 45 45 276.50 11.50 293.33 310.49 311.74 23.74 2017 2017 2017 Jul Aug Sep 288 374 304 315.00 59.00 280.33 5.33 93.67 30.67 46 46 47 47 301.49 72.51 304.62 69.38 331.00 27.00 334.67 330.50 26.50 325.43 21.43

Oct 337 2.00 15.00 319.90 17.10 339.00 320.50 322.00 338.33 304 34.33 Nov Dec Jan 16.50 36.50 326.74 317.64 357 320.50 42.00 22.74 39.36 5.39 178.77 328 330.50 48 48 2017 49 49 2017 50 50 2017 51 51 2018 52 52 2018 53 53 2018 54 54 2018 55 55 2018 18.00 20.40 38.72 1.90 180.67 2.50 315.00 332.67 329.67 398.33 333.39 319.00 324.40 318.28 329.90 329.33 383.53 361.47 356.83 4.67 180.33 Feb 510 331.23 342.50 419.00 Mar 310 167.50 109.00 64.00 88.33 346 410.00 382.67 Apr May 36.67 127.67 402.74 365.64 357.79 319.07 92.74 19.64 96.79 73.53 15.47 95.83 261 328.00 67.00 388.67 56 56 Jun 296 303.50 7.50 305.67 9.67 23.07 328.08 57 57 Jul 394 278.50 301.00 93.00 309.84 84.16 318.46 2018 2018 12018 2018 32.08 75.54 10.12 331 345.00 115.50 14.00 57.50 14.00 343.51 12.51 58 58 59 59 341.12 Aug Sep Oct 317.00 340.33 305 362.50 35.33 338.50 33.50 338.08 33.08 2018 300 18.00 343.33 43.33 328.16 60 60 61 61 318.00 302.50 25.10 6.94 28.16 2.29 2018 322 19.50 312.00 325.10 315.06 317.84 10.00 Nov Dec 319.71 62 62 2018 369 311.00 58.00 309.00 320.40 60.00 MAD 48.60 MAD 63 63 51.16 MAD 56.79 MAD 59.72 64 64 60.84 54.30

Formula:

А 1 1 B C D B c D JE Year Month Actual Forecasting using 2 Data period moving average F G H G |н Absolute Forecasting using 3 Absolute Exponential deviation=Actual- period moving deviation=Actual- smmothing using Forecast average Forecast alpha 0.4 Absolute Exponential deviation=Actual- smmothing using Forecast alpha 0.3 Absolute deviation=Actual- Forecast 22 3 3 2014 Jan 2014 Feb 4 4 5 5 66 211 338 191 192 138 148 7 7 88 2014 Mar 2014 Apr 2014 May 2014 Jun 2014 Jul 2014 Aug 2014 Sep 2014 Oct 2014 Nov 2014 Dec 2015 Jan 2015 Feb 2015 Mar 2015 Apr 2015 May 2015 Jun 2015 Jul 2015 Aug 2015 Sep 2015 Oct 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 205 244 164 200 205 1229 244 =AVERAGE(D3:04) =ABS(D5-E5) |=AVERAGE(D4:05) =ABS(D6-E6) =AVERAGE(D5:06) =ABS(D7-E7) =AVERAGE(D6:07) =ABS(D8-E8) =AVERAGE(D7:08) =ABS(D9-E9) =AVERAGE(D8:09) =ABS(D10-E10) =AVERAGE(D9:010) =ABS(D11-E11) =AVERAGE(D10:011) =ABS(D12-E12) =AVERAGE(D11:012) |=ABS(D13-E13) =AVERAGE(D12:013) =ABS(D14-E14) =AVERAGE(D13:D14) =ABS(D15-E15) =AVERAGE(D14:D15) =ABS(D16-E16) =AVERAGE(D15:016) |=ABS(D17-E17) =AVERAGE(D16:017) =ABS(D18-E18) =AVERAGE(D17:018) =ABS(D19-E19) =AVERAGE(D18:019) |=ABS(D20-E20) |=AVERAGE(D19:D20) =ABS(D21-E21) =AVERAGE(D20:D21) =ABS(D22-E22) =AVERAGE(D21:D22) =ABS(D23-E23) =AVERAGE(D22:D23) |=ABS(D24-E24) =AVERAGE(D3:05) =ABS(D6-66) =AVERAGE(D4:D6) =ABS(D7-G7) =AVERAGE(D5:07) |=ABS(D8-G8) =AVERAGE(D6:08) =ABS(D9-69) =AVERAGE(D7:09) |=ABS(D10-G10) =AVERAGE(D8:010) =ABS(D11-611) =AVERAGE(D9:011) =ABS(D12-G12) =AVERAGE(D10:012) =ABS(D13-G13) =AVERAGE(D11:013) =ABS(D14-G14) =AVERAGE(D12:014) =ABS(D15-G15) =AVERAGE(D13:D15) =ABS(D16-616) =AVERAGE(D14:016) =ABS(D17-G17) =AVERAGE(D15:017) =ABS(D18-G18) =AVERAGE(D16:D18) =ABS(D19-G19) =AVERAGE(D17:D19) =ABS(D20-G20) =AVERAGE(D18:D20) =ABS(D21-G21) =AVERAGE(D19:D21) =ABS(D22-G22) |=AVERAGE(D20:D22) =ABS(D23-G23) |=AVERAGE(D21:D23) =ABS(D24-G24) 211 =ABS(D4-14) =(0.4*D4)+(0.6*14) =ABS(D5-15) =(0.4*D5)+(0.6*15) =ABS(D6-16) =(0.4*D6)+(0.6*16) =ABS(D7-17) =(0.4*D7)+(0.6*17) =ABS(D8-18) =(0.4*D8) +(0.6*18) =ABS(D9-19) =(0.4*D9)+(0.6*19) |=ABS(D10-110) =(0.4*D10)+0.6*110) =ABS(D11-111) =(0.4*D11)+(0.6*111) =ABS(D12-112) =(0.4*D12)+(0.6*112) =ABS(D13-113) =(0.4*D13)+(0.6*113) =ABS(D14-114) =(0.4*D14)+(0.6*114) =ABS(D15-115) I=(0.4*D15)+(0.6*115) =ABS(D16-116) =(0.4*D16)+(0.6*116) =ABS(D17-117) =(0.4*D17)+(0.6*117) =ABS(D18-118) =(0.4*D18)+0.6*118) =ABS(D19-119) =(0.4*D19)+(0.6*119) =ABS(D20-120) =(0.4*D20)+(0.6*120)=ABS(D21-121) =(0.4*D21)+0.6*121) =ABS(D22-122) 1=(0.4*D22)+(0.6*122) =ABS(D23-123) =(0.4*D23)+(0.6*123) =ABS(D24-124) 211 =ABS(D4-K4) =(0.3*D4)+(0.7*K4) =ABS(D5-K5) =(0.3*D5)+(0.7*K5) |=ABS(D6-K6) =(0.3*D6)+(0.7*K6) |=ABS(D7-K7) I=(0.3*D7)+(0.7*K7) =ABS(D8-K8) =(0.3*D8)+0.7*K8) =ABS(D9-K9) =(0.3*D9)+(0.7*K9) |=ABS(D10-K10) =(0.3*D10)+(0.7*K10) =ABS(D11-K11) =(0.3*011)+(0.7*K11) =ABS(D12-K12) =(0.3*D12)+(0.7*K12) |=ABS(D13-K13) I=(0.3*D13)+(0.7*K13) =ABS(D14-K14) =(0.3*D14)+(0.7*K14) =ABS(D15-K15) =(0.3*D15)+(0.7*K15) =ABS(D16-16) =(0.3*D16)+(0.7*K16) =ABS(D17-K17) I=(0.3*017)+(0.7*K17) =ABS(D18-K18) =(0.3*D18)+(0.7*K18) |=ABS(D19-K19) =(0.3*D19)+0.7*K19) |=ABS(D20-K20) I=(0.3*D20)+(0.7*K20) =ABS(D21-K21) =(0.3*D21)+(0.7*K21) =ABS(D22-K22) =(0.3*D22)+(0.7*K22) =ABS(D23-K23) =(0.3*D23)+(0.7*K23) =ABS(D24-K24) 403 213 244 153 195 231 327 337 247

234 438 291 386 335 278 159 209 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 33 34 34 35 35 36 36 37 37 38 38 39 39 40 40 41 41 42 42 43 43 44 44 45 45 46 46 47 47 2015 Nov 2015 Dec 2016 Jan 2016 Feb 2016 Mar 2016 Apr 2016 May 2016 Jun 2016 Jul 2016 Aug 2016 Sep 2016 Oct 2016 Nov 2016 Dec 2017 Jan 2017 Feb 2017 Mar 2017 Apr 2017 May 2017 Jun 2017 Jul 2017 Aug 2017 Sep 205 364 263 280 282 273 323 1478 =AVERAGE(D23:D24) =ABS(D25-E25) =AVERAGE(D24:D25) =ABS(D26-E26) I=AVERAGE(D25:026) =ABS(D27-E27) =AVERAGE(D26:D27) =ABS(D28-E28) =AVERAGE(D27:D28) =ABS(D29-E29) =AVERAGE(D28:D29) I=ABS(D30-E30) =AVERAGE(D29:D30) =ABS(D31-E31) |=AVERAGE(D30:D31) =ABS(D32-E32) =AVERAGE(D31:D32) =ABS(D33-E33) =AVERAGE(D32:D33) =ABS(D34-E34) =AVERAGE(D33:D34) |=ABS(D35-E35) =AVERAGE(D34:D35) =ABS(D36-E36) =AVERAGE(D35:D36) |=ABS(D37-E37) =AVERAGE(D36:D37) =ABS(D38-E38) |=AVERAGE(D37:D38) =ABS(D39-E39) =AVERAGE(D38:D39) =ABS(D40-E40) =AVERAGE(D39:D40) =ABS(D41-E41) =AVERAGE(D40:041) =ABS(D42-E42) =AVERAGE(D41:042) |=ABS(D43-E43) =AVERAGE(D42:D43) =ABS(D44-E44) =AVERAGE(D43:044) =ABS(D45-E45) =AVERAGE(D44:045) |=ABS(D46-E46) |=AVERAGE(D45:046) |=ABS(D47-E47) =AVERAGE(D22:D24) =ABS(D25-G25) =AVERAGE(D23:D25) =ABS(D26-G26) =AVERAGE(D24:D26) =ABS(D27-G27) |=AVERAGE(D25:D27) =ABS(D28-G28) =AVERAGE(D26:D28) =ABS(D29-G29) =AVERAGE(D27:D29) =ABS(D30-G30) =AVERAGE(D28:D30) =ABS(D31-G31) =AVERAGE(D29:D31) =ABS(D32-G32) =AVERAGE(D30:D32) =ABS(D33-G33) =AVERAGE(D31:033) =ABS(D34-G34) =AVERAGE(D32:D34) =ABS(D35-G35) =AVERAGE(D33:D35) =ABS(D36-G36) =AVERAGE(D34:D36) =ABS(D37-G37) =AVERAGE(D35:D37) =ABS(D38-G38) =AVERAGE(D36:D38) =ABS(D39-G39) =AVERAGE(D37:D39) =ABS(D40-G40) =AVERAGE(D38:D40) =ABS(D41-G41) =AVERAGE(D39:041) =ABS(D42-642) =AVERAGE(D40:042) =ABS(D43-443) =AVERAGE(D41:043) =ABS(D44-G44) =AVERAGE(D42:D44) =ABS(D45-G45) =AVERAGE(D43:045) =ABS(D46-646) =AVERAGE(D44:046) =ABS(D47-G47) =(0.4*D24)+(0.6*124) =ABS(D25-125) =(0.4*D25)+(0.6*125) =ABS(D26-126) I=(0.4*D26)+(0.6*126) =ABS(D27-127) =(0.4*D27)+(0.6*127) =ABS(D28-128) =(0.4*D28)+(0.6*128) =ABS(D29-129) =(0.4*D29) +(0.6*129) =ABS(D30-130) =(0.4*D30)+(0.6*130) =ABS(D31-131) =(0.4*D31)+(0.6*131) =ABS(D32-132) =(0.4*D32)+(0.6*132) =ABS(D33-133) =(0.4*D33)+(0.6*133) =ABS(D34-134) I=(0.4*D34)+(0.6*134) =ABS(D35-135) =(0.4*D35)+(0.6*135) =ABS(D36-136) =(0.4*D36) +0.6*136) =ABS(D37-137) =(0.4*D37)+(0.6*137) =ABS(D38-138) =(0.4*D38)+(0.6*138) =ABS(D39-139) =(0.4*D39)+(0.6*139) =ABS(D40-140) =(0.4*D40)+(0.6*140) =ABS(D41-141) =(0.4*D41)+(0.6*141) =ABS(D42-142) =(0.4*D42)+(0.6*142) =ABS(143-143) =(0.4*D43)+(0.6*143) =ABS(D44-144) =(0.4*D44)+0.6*144) =ABS(D45-145) 1=(0.4*D45)+(0.6*145) =ABS(D46-146) =(0.4*D46)+(0.6*146) =ABS(D47-147) =(0.3*D24)+(0.7*K24) =ABS(D25-K25) =(0.3*D25)+(0.7*K25) =ABS(D26-K26) =(0.3*D26)+(0.7*K26) =ABS(D27-K27) I=(0.3*D27)+(0.7*K27) =ABS(D28-K28) =(0.3*D28)+(0.7*K28) =ABS(D29-29) =(0.3*D29)+(0.7*K29) =ABS(D30-K30) =(0.3*D30)+(0.7*K30) =ABS(D31-K31) I=(0.3*D31)+(0.7*K31) =ABS(D32-K32) =(0.3*D32)+(0.7*K32) =ABS(D33-K33) =(0.3*D33)+(0.7*K33) =ABS(D34-K34) =(0.3*D34)+(0.7*K34) =ABS(D35-K35) I=(0.3*D35)+(0.7*K35) =ABS(D36-K36) =(0.3*D36)+(0.7*K36) =ABS(D37-37) =(0.3*D37)+(0.7*K37) =ABS(D38-K38) =(0.3*D38)+(0.7*K38) =ABS(D39-K39) I=(0.3*D39)+(0.7*K39) =ABS(D40-K40) =(0.3*D40)+0.7*K40) =ABS(D41-641) =(0.3*D41)+(0.7*K41) =ABS(D42-K42) =(0.3*D42)+(0.7*K42) =ABS(D43-K43) I=(0.3*D43)+(0.7*K43) =ABS(D44-K44) =(0.3*D44)+(0.7*K44) =ABS(D45-K45) =(0.3*D45)+(0.7*K45) =ABS(D46-646) =(0.3*D46)+(0.7*K46) =ABS(D47-K47) 327 327 211 342 288 374 304

304 337 304 357 328 47 47 48 48 49 49 50 50 51 51 52 52 53 53 54 54 55 55 56 56 57 57 58 58 59 59 60 60 61 61 62 62 63 63 64 64 2017 Sep 2017 Oct 2017 Nov 2017 Dec 2018 Jan 2018 Feb 2018 Mar 2018 Apr 2018 May 2018 Jun 2018 Jul 2018 Aug 2018 Sep 2018 Oct 2018 Nov 2018 Dec 510 310 346 261 =AVERAGE(D45:046) =ABS(D47-547) =AVERAGE(D44:D46) =ABS(D47-G47) =(0.4*D46)+(0.6*146) =ABS(D47-147) =AVERAGE(D46:047) =ABS(D48-E48) =AVERAGE(D45:047) =ABS(D48-G48) =(0.4*D47)+(0.6*147) =ABS(D48-148) =AVERAGE(D47:048) =ABS(D49-E49) =AVERAGE(D46:148) =ABS(D49-G49) =(0.4*D48)+(0.6*148) =ABS(D49-149) =AVERAGE(D48:D49) |=ABS(D50-E50) |=AVERAGE(D47:049) =ABS(D50-G50) =(0.4*D49) +0.6*149) =ABS(D50-150) =AVERAGE(D49:D50) =ABS(D51-E51) =AVERAGE(D48:D50) =ABS(D51-G51) =(0.4*D50)+(0.6*150) =ABS(D51-151) =AVERAGE(D50:051) =ABS(D52-E52) =AVERAGE(D49:D51) =ABS(D52-652) I=(0.4*D51)+(0.6*151) =ABS(D52-152) =AVERAGE(D51:052) =ABS(D53-E53) =AVERAGE(D50:052) =ABS(D53-G53) =(0.4*D52)+(0.6*152) =ABS(D53-153) =AVERAGE(D52:053) =ABS(D54-E54) =AVERAGE(D51:053) =ABS(D54-G54) =(0.4*D53)+(0.6*153) =ABS(D54-154) =AVERAGE(D53:054) =ABS(D55-E55) =AVERAGE(D52:054) =ABS(D55-G55) =(0.4*D54)+(0.6*154) =ABS(D55-155) =AVERAGE(D54:D55) =ABS(D56-E56) =AVERAGE(D53:055) =ABS(D56-656) I=(0.4*D55)+(0.6*155) =ABS(D56-156) =AVERAGE(D55:056) =ABS(D57-E57) =AVERAGE(D54:056) =ABS(D57-G57) =(0.4*D56)+(0.6*156) =ABS(D57-157) =AVERAGE(D56:057) =ABS(D58-E58) =AVERAGE(D55:D57) =ABS(D58-658) =(0.4*D57)+(0.6*157) =ABS(D58-158) =AVERAGE(D57:058) =ABS(D59-E59) =AVERAGE(D56:058) =ABS(D59-G59) =(0.4*D58)+(0.6*158) =ABS(D59-159) =AVERAGE(D58:059) =ABS(D60-E60) =AVERAGE(D57:059) =ABS(D60-560) =(0.4*D59)+(0.6*159) =ABS(D60-160) =AVERAGE(D59:060) =ABS(D61-E61) =AVERAGE(D58:D60) =ABS(D61-G61) =(0.4*D60)+(0.6*160) =ABS(D61-161) =AVERAGE(D60:061) |=ABS(D62-E62) =AVERAGE(D59:061) =ABS(D62-662) =(0.4*D61)+(0.6*161) =ABS(D62-162) MAD MAD MAD =AVERAGE(F5:F62) |=AVERAGE(H6:462) =AVERAGE(14:J62) =(0.3*D46) +0.7*K46) =ABS(D47-K47) I=(0.3*D47)+(0.7*K47) =ABS(D48-K48) =(0.3*D48)+0.7*K48) =ABS(D49-549) =(0.3*D49)+(0.7*K49) =ABS(D50-K50) =(0.3*D50)+(0.7*K50) =ABS(D51-651) =(0.3*D51)+(0.7*K51) =ABS(D52-K52) =(0.3*D52)+(0.7*K52) =ABS(D53-K53) I=(0.3*053)+(0.7*K53) ABS(D54-K54) =(0.3*D54)+0.7*K54) =ABS(D55-K55) =(0.3*D55)+(0.7*K55) =ABS(D56-656) =(0.3*D56)+(0.7*K56) =ABS(D57-K57) =(0.3*D57)+0.7*K57) =ABS(D58-K58) =(0.3*D58)+0.7*K58) =ABS(D59-K59) =(0.3*D59)+0.7*K59) =ABS(D60-K60) I=(0.3*D60)+(0.7*K60) =ABS(D61-661) =(0.3*D61)+(0.7*K61) =ABS(D62-K62) MAD =AVERAGE(L4:L62) 296 394 331 305 300 322 369

2)

based on such comparison, we could recommend that forecasting using Exponential smoothing using alpha 0.3 as it has lowest MAD value.