Ingevulde oefeningen supply chain management les 06

X Y
Date Day Pizzas Forecast How much pizzas will be sold on 1/8/2016 ???
5/1/2016 1 329
5/2/2016 2 357
5/3/2016 3 351
5/4/2016 4 346 1. plot data
5/5/2016 5 342
5/6/2016 6 344
5/7/2016 7 356
5/8/2016 8 357
5/9/2016 9 368
5/10/2016 10 367
5/11/2016 11 351
5/12/2016 12 343
5/13/2016 13 340
5/14/2016 14 358
5/15/2016 15 343
5/16/2016 16 363
5/17/2016 17 364 2. Vailidate data en eliminate outliers
5/18/2016 18 353
5/19/2016 19 363
5/20/2016 20 341
5/21/2016 21 351 3. we kiezen voor forecast methode TREND
5/22/2016 22 350
5/23/2016 23 379
5/24/2016 24 378
5/25/2016 25 369
5/26/2016 26 345
5/27/2016 27 368
5/28/2016 28 348
5/29/2016 29 366
5/30/2016 30 368
5/31/2016 31 376
6/1/2016 32 351
6/2/2016 33 365
6/3/2016 34 375
6/4/2016 35 360
6/5/2016 36 369
6/6/2016 37 377
6/7/2016 38 370
6/8/2016 39 359
6/9/2016 40 364
6/10/2016 41 355
6/11/2016 42 375
6/12/2016 43 360
6/13/2016 44 389
6/14/2016 45 396
6/15/2016 46 377

,6/16/2016 47 368
6/17/2016 48 363
6/18/2016 49 378
6/19/2016 50 379
6/20/2016 51 376
6/21/2016 52 383
6/22/2016 53 368
6/23/2016 54 365
6/24/2016 55 373
6/25/2016 56 371
6/26/2016 57 383
6/27/2016 58 385
6/28/2016 59 393
6/29/2016 60 373
6/30/2016 61 382
7/1/2016 62 370
7/2/2016 63 386
7/3/2016 64 378
7/4/2016 65 399
7/5/2016 66 387
7/6/2016 67 388
7/7/2016 68 384
7/8/2016 69 383
7/9/2016 70 394
7/10/2016 71 385
7/11/2016 72 398
7/12/2016 73 404
7/13/2016 74 381
7/14/2016 75 395
7/15/2016 76 401
7/16/2016 77 401
7/17/2016 78 384
7/18/2016 79 412
7/19/2016 80 413
7/20/2016 81 394
7/21/2016 82 397
7/22/2016 83 396
7/23/2016 84 386
7/24/2016 85 397 b0
7/25/2016 86 417 b1
7/26/2016 87 416
7/27/2016 88 397
7/28/2016 89 403 4. we testen de betrouwbaarheid van de forecest
7/29/2016 90 392
7/30/2016 91 408
7/31/2016 92 403 5. Farecast uitvoeren
8/1/2016 93 405

,on 1/8/2016 ???


Pizzas
450
400
350
300
250
200
150
100
50
0
0 10 20 30 40 50 60 70 80 90 100




thode TREND