Forecasting Methods for Demand Prediction in 2017

Forecasting

Forecast
Two methods of data visualization for predict the demand in 2017 are:
i) Trend Analysis:
Periods Year Month
Deman
d
1 2014 January 233.00
2 February 223.00
3 March 208.00
4 April 195.00
5 May 197.00
6 June 196.00
7 July 212.00
8 August 219.00
9 September 225.00
10 October 219.00
11 November 196.00
12 December 230.00
13 2015 January 266.00
14 February 256.00
15 March 241.00
16 April 228.00
17 May 230.00
18 June 229.00
19 July 245.00
20 August 252.00
21 September 258.00
22 October 252.00
23 November 229.00
24 December 263.00
25 2016 January 334.00
26 February 324.00
27 March 309.00
28 April 296.00
29 May 298.00
30 June 297.00
31 July 313.00
32 August 320.00
33 September 326.00
34 October 320.00
35 November 297.00
36 December 331.00

37 2017 January 326.91
38 February 333.16
39 March 339.05
40 April 344.17
41 May 348.45
42 June 352.61
43 July 356.46
44 August 360.95
45 September 365.67
46 October 370.61
47 November 375.06
48 December 377.90
Effectiveness: Trend analysis is not so effective in predicting data which is increasing and
decreasing over the months. As the result shows that demand in 2017 is continuously increasing
from January to December; while past data clearly shown that demand is not constantly
increasing. It has up downs in demand from January to December in each year. Hence, this
method is not effective and can only be used where only increasing trended data is available or to
find the result of only one month.
ii) Regression Analysis:
X - Mx Y - My (X - Mx)2 (X - Mx)(Y - My)
-17.5 -24.4167 306.25 427.2917
-16.5 -34.4167 272.25 567.875
-15.5 -49.4167 240.25 765.9583
-14.5 -62.4167 210.25 905.0417
-13.5 -60.4167 182.25 815.625
-12.5 -61.4167 156.25 767.7083
-11.5 -45.4167 132.25 522.2917
-10.5 -38.4167 110.25 403.375
-9.5 -32.4167 90.25 307.9583
-8.5 -38.4167 72.25 326.5417
-7.5 -61.4167 56.25 460.625
-6.5 -27.4167 42.25 178.2083
-5.5 8.5833 30.25 -47.2083
-4.5 -1.4167 20.25 6.375
-3.5 -16.4167 12.25 57.4583
-2.5 -29.4167 6.25 73.5417
-1.5 -27.4167 2.25 41.125
-0.5 -28.4167 0.25 14.2083
0.5 -12.4167 0.25 -6.2083
1.5 -5.4167 2.25 -8.125