Hello, i am very basic with formulas and VBA and i am trying to evaluate data based on material number date and location. i want to group all the same material number then if the product is in location "A Pick Line" or "A Tygard" look at all the age dates to make sure all those locations have the oldest product and if they don't then highlight that cell red. Material is column G, Location is column W, and date is column R. Any help is greatly Appreciated
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Plant | Location | Warehouse | Storage Bin | Sequence | Count Order | Material | Material Description | Stock type | Batch | Physical Count | Base Unit of Measure | Full(s) | Loose | Pallet Qty | Counter | Inventory Doc | BBE Date | Date | Time | Days Diff | Under 90 Days | Product Location |
1 | 0001 | B002 | 5 | 1316 | 100278 | Product 1 | 1 | DSDP046 | 540.000 | CS | 5.000 | 20.000 | 104.000 | 8/12/2019 | 12/3/2018 | 4:24:26 AM | 213 | No | A Pick Line | |||
1 | 0001 | J2013 | 2 | 818 | 100278 | Product 1 | 1 | DSDP046 | 104.000 | CS | 1.000 | 0.000 | 104.000 | 8/12/2019 | 12/3/2018 | 3:56:44 AM | 213 | No | North Warehouse | |||
1 | 0001 | C2008 | 6 | 2728 | 100278 | Product 1 | 1 | DSDP046 | 2,184.000 | CS | 21.000 | 0.000 | 104.000 | 8/19/2019 | 12/3/2018 | 5:41:29 AM | 220 | No | North Warehouse | |||
1 | 0001 | J2015 | 3 | 828 | 100278 | Product 1 | 1 | DSDP046 | 832.000 | CS | 8.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 3:57:18 AM | 227 | No | North Warehouse | |||
1 | 0001 | F2010 | 4 | 1302 | 100278 | Product 1 | 1 | DSDP046 | 2,704.000 | CS | 26.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 4:23:49 AM | 227 | No | North Warehouse | |||
1 | 0001 | C3020 | 3 | 1842 | 100281 | Product 2 | 1 | DSDP046 | 624.000 | CS | 6.000 | 0.000 | 104.000 | 2/4/2019 | 12/3/2018 | 4:54:45 AM | 24 | Yes | North Warehouse | |||
1 | 0001 | C3010 | 4 | 1892 | 100281 | Product 2 | 1 | DSDP046 | 104.000 | CS | 1.000 | 0.000 | 104.000 | 2/4/2019 | 12/3/2018 | 4:57:01 AM | 24 | Yes | North Warehouse | |||
1 | 0001 | A1008C | 2 | 1226 | 100281 | Product 2 | 1 | DSDP046 | 235.000 | CS | 2.000 | 27.000 | 104.000 | 2/11/2019 | 12/3/2018 | 4:19:38 AM | 31 | Yes | North Warehouse | |||
1 | 0001 | C2010 | 5 | 2736 | 100281 | Product 2 | 1 | DSDP046 | 1,248.000 | CS | 12.000 | 0.000 | 104.000 | 2/11/2019 | 12/3/2018 | 5:41:52 AM | 31 | Yes | North Warehouse | |||
1 | 0001 | A1002C | 3 | 1290 | 100287 | Product 3 | 1 | DSDP046 | 34.000 | CS | 0.000 | 34.000 | 104.000 | 8/5/2019 | 12/3/2018 | 4:23:11 AM | 206 | No | North Warehouse | |||
1 | 0001 | A1002C | 2 | 1264 | 100287 | Product 3 | 1 | DSDP046 | 573.000 | CS | 5.000 | 53.000 | 104.000 | 8/12/2019 | 12/3/2018 | 4:21:46 AM | 213 | No | North Warehouse | |||
1 | 0001 | C2020 | 4 | 2786 | 100287 | Product 3 | 1 | DSDP046 | 1,664.000 | CS | 16.000 | 0.000 | 104.000 | 8/12/2019 | 12/3/2018 | 5:44:42 AM | 213 | No | North Warehouse | |||
1 | 0001 | ST02 | 1 | 19 | 100722 | Product 4 | 1 | DSDP046 | 104.000 | CS | 1.000 | 0.000 | 104.000 | 12/3/2018 | 3:10:53 AM | |||||||
1 | 0001 | B035 | 10 | 1661 | 100722 | Product 4 | 1 | DSDP046 | 538.000 | CS | 5.000 | 18.000 | 104.000 | 8/26/2019 | 12/3/2018 | 4:43:50 AM | 227 | No | A Pick Line | |||
1 | 0001 | LY | 3 | 120 | 100722 | Product 4 | 1 | DSDP046 | 208.000 | CS | 2.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 3:22:33 AM | 227 | No | A Tygard | |||
1 | 0001 | LY | 4 | 357 | 100722 | Product 4 | 1 | DSDP046 | 48.000 | CS | 0.000 | 48.000 | 104.000 | 8/26/2019 | 12/3/2018 | 3:31:20 AM | 227 | No | A Tygard | |||
1 | 0001 | H2014 | 5 | 932 | 100722 | Product 4 | 1 | DSDP046 | 728.000 | CS | 7.000 | 0.000 | 104.000 | 8/19/2019 | 12/3/2018 | 4:03:08 AM | 220 | No | North Warehouse | |||
1 | 0001 | G2021 | 7 | 1230 | 100722 | Product 4 | 1 | DSDP046 | 3,224.000 | CS | 31.000 | 0.000 | 104.000 | 8/19/2019 | 12/3/2018 | 4:19:43 AM | 220 | No | North Warehouse | |||
1 | 0001 | E2015 | 12 | 3765 | 100722 | Product 4 | 1 | DSDP046 | 1,664.000 | CS | 16.000 | 0.000 | 104.000 | 8/19/2019 | 12/3/2018 | 10:25:33 AM | 220 | No | North Warehouse | |||
1 | 0001 | G2022 | 6 | 1126 | 100722 | Product 4 | 1 | DSDP046 | 1,768.000 | CS | 17.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 4:14:03 AM | 227 | No | North Warehouse | |||
1 | 0001 | E2021 | 8 | 1514 | 100722 | Product 4 | 1 | DSDP046 | 2,600.000 | CS | 25.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 4:34:39 AM | 227 | No | North Warehouse | |||
1 | 0001 | E2023 | 9 | 1522 | 100722 | Product 4 | 1 | DSDP046 | 2,912.000 | CS | 28.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 4:35:07 AM | 227 | No | North Warehouse | |||
1 | 0001 | D2021 | 11 | 1673 | 100722 | Product 4 | 1 | DSDP046 | 4,784.000 | CS | 46.000 | 0.000 | 104.000 | 8/26/2019 | 12/3/2018 | 4:44:31 AM | 227 | No | North Warehouse |