we are using GPT4 model just able to perform till the 2nd step and not beyond that. We are using function calling. It retrieved all the required data to do step 4,5,6,7,8 but not able to perform 4, 5, 6, 7, 8 steps.
Prompt: what is the sales performance for product Claire at Region level
Answer: Executing the following steps to get the sales performance for product Claire at Region level: 1. Get the time periods for 1st to 9th week previous weeks from current week.
2. Calculate the sum of value Actual Shipments Quantity, Demand plan, prior year shipments from 1st weeks to 9th weeks values for each "Regio
3. Calculate percentage change in growth of demand plan for 9 weeks trend of Actual Shipments Quantity, Demand plan for each “Region”.
4. Calculate percentage change in growth of prior year shipment for 9 weeks trend of prior year shipments, Actual Shipments Quantity, of each "R
5. Calculate percentage change in growth of demand plan, Calculate percentage change in growth of prior year shipment for 4 weeks trend and
6. Get the actual shipment Quantity for the time of “year value” of current week at “Region” level.
7. Calculate the proportion of each region for year value of current week.
8.
Let’s start with step 1.
Executing step 1: Get the time periods for 1st to 9th week previous weeks from current week.
Answer: The time periods for the 1st to 9th week previous weeks from the current week are as follows:
- 2023_FEB_W04
- 2023_FEB_W03
- 2023_FEB_W02
- 2023_FEB_W01
- 2023_JAN_W04
- 2023_JAN_W03
- 2023_JAN_W02
- 2023_JAN_W01
- 2022_DEC_W05
Next, I will calculate the sum of Actual Shipments Quantity, Demand plan, and prior year shipments from the 1st week to the 9th week for each "Re
growth of demand plan and prior year shipment.
Executing step 2: Calculate the sum of Actual Shipments Quantity, Demand plan, and prior year shipments for each “Region” for the given time pe
Answer: The values for Actual Shipments Quantity, Demand Plan, and Prior Year Shipments for product Claire at Region level for the given time pe
Actual Shipments Quantity:
East:
2022_DEC_W05: 886,858
2023_JAN_W01: 737,719
2023_JAN_W02: 907,609
2023_JAN_W03: 738,567
2023_JAN_W04: 758,621
2023_FEB_W01: 776,014
2023_FEB_W02: 856,556
2023_FEB_W03: 752,911
2023_FEB_W04: 717,052
Central:
2022_DEC_W05: 868,816
2023_JAN_W01: 805,473
2023_JAN_W02: 888,576
2023_JAN_W03: 772,487
2023_JAN_W04: 720,353
2023_FEB_W01: 804,405
2023_FEB_W02: 820,634
2023_FEB_W03: 723,235
2023_FEB_W04: 751,849
North:
2022_DEC_W05: 1,239,691
2023_JAN_W01: 1,151,375
2023_JAN_W02: 1,214,535
2023_JAN_W03: 1,108,563
2023_JAN_W04: 1,136,462
2023_FEB_W01: 1,234,097
2023_FEB_W02: 1,345,869
2023_FEB_W03: 1,147,045
2023_FEB_W04: 1,096,903
South:
2022_DEC_W05: 806,471
2023_JAN_W01: 764,741
2023_JAN_W02: 839,371
2023_JAN_W03: 697,660
2023_JAN_W04: 754,164
2023_FEB_W01: 757,257
2023_FEB_W02: 880,079
2023_FEB_W03: 746,351
2023_FEB_W04: 716,773
West:
2022_DEC_W05: 859,750
2023_JAN_W01: 780,489
2023_JAN_W02: 734,215
2023_JAN_W03: 713,048
2023_JAN_W04: 763,390
2023_FEB_W01: 811,296
2023_FEB_W02: 897,485
2023_FEB_W03: 761,184
2023_FEB_W04: 748,485
The result have been retrieved from the Plan: ALL PRODUCTS, Formset: IBP-GenAI, Worksheet: New Forecast Review, Table: NewTable0, and K
The dimensions and their names used for the query were:
PRODUCT: Claire
TIME: 2023_FEB_W04, 2023_FEB_W03, 2023_FEB_W02, 2023_FEB_W01, 2023_JAN_W04, 2023_JAN_W03, 2023_JAN_W02, 2023_JAN
LOCATION: East, Central, North, South, West
Demand Plan:
East:
2022_DEC_W05: 832,781
2023_JAN_W01: 798,434
2023_JAN_W02: 789,545
2023_JAN_W03: 777,670
2023_JAN_W04: 762,211
2023_FEB_W01: 803,448
2023_FEB_W02: 789,240
2023_FEB_W03: 765,476
2023_FEB_W04: 780,663
Central:
2022_DEC_W05: 843,890
2023_JAN_W01: 815,669
2023_JAN_W02: 820,756
2023_JAN_W03: 757,935
2023_JAN_W04: 751,085
2023_FEB_W01: 808,978
2023_FEB_W02: 832,045
2023_FEB_W03: 756,059
2023_FEB_W04: 748,812
North:
2022_DEC_W05: 1,206,232
2023_JAN_W01: 1,192,995
2023_JAN_W02: 1,186,109
2023_JAN_W03: 1,168,217
2023_JAN_W04: 1,148,961
2023_FEB_W01: 1,184,568
2023_FEB_W02: 1,187,696
2023_FEB_W03: 1,152,050
2023_FEB_W04: 1,152,314
South:
2022_DEC_W05: 821,827
2023_JAN_W01: 804,491
2023_JAN_W02: 807,199
2023_JAN_W03: 775,932
2023_JAN_W04: 762,952
2023_FEB_W01: 812,096
2023_FEB_W02: 791,097
2023_FEB_W03: 764,163
2023_FEB_W04: 768,601
West:
2022_DEC_W05: 804,630
2023_JAN_W01: 797,229
2023_JAN_W02: 792,481
2023_JAN_W03: 774,317
2023_JAN_W04: 771,780
2023_FEB_W01: 794,071
2023_FEB_W02: 795,523
2023_FEB_W03: 759,208
2023_FEB_W04: 773,355
The result have been retrieved from the Plan: ALL PRODUCTS, Formset: IBP-GenAI, Worksheet: New Forecast Review, Table: NewTable0, and K
The dimensions and their names used for the query were:
PRODUCT: Claire
TIME: 2023_FEB_W04, 2023_FEB_W03, 2023_FEB_W02, 2023_FEB_W01, 2023_JAN_W04, 2023_JAN_W03, 2023_JAN_W02, 2023_JAN
LOCATION: East, Central, North, South, West
Prior Year Shipments:
East:
2022_DEC_W05: 810,162
2023_JAN_W01: 733,564
2023_JAN_W02: 743,227
2023_JAN_W03: 770,399
2023_JAN_W04: 745,572
2023_FEB_W01: 875,460
2023_FEB_W02: 819,782
2023_FEB_W03: 747,631
2023_FEB_W04: 729,869
Central:
2022_DEC_W05: 783,843
2023_JAN_W01: 750,915
2023_JAN_W02: 692,021
2023_JAN_W03: 840,484
2023_JAN_W04: 734,721
2023_FEB_W01: 876,637
2023_FEB_W02: 781,424
2023_FEB_W03: 791,194
2023_FEB_W04: 744,257
North:
2022_DEC_W05: 1,219,082
2023_JAN_W01: 1,131,972
2023_JAN_W02: 1,069,304
2023_JAN_W03: 1,176,431
2023_JAN_W04: 1,063,413
2023_FEB_W01: 1,342,137
2023_FEB_W02: 1,166,473
2023_FEB_W03: 1,096,886
2023_FEB_W04: 1,033,191
South:
2022_DEC_W05: 833,802
2023_JAN_W01: 761,678
2023_JAN_W02: 741,427
2023_JAN_W03: 743,476
2023_JAN_W04: 734,161
2023_FEB_W01: 836,877
2023_FEB_W02: 770,795
2023_FEB_W03: 723,089
2023_FEB_W04: 744,371
West:
2022_DEC_W05: 801,183
2023_JAN_W01: 745,751
2023_JAN_W02: 724,342
2023_JAN_W03: 828,120
2023_JAN_W04: 745,729
2023_FEB_W01: 831,243
2023_FEB_W02: 771,157
2023_FEB_W03: 746,040
2023_FEB_W04: 728,647
The result have been retrieved from the Plan: ALL PRODUCTS, Formset: IBP-GenAI, Worksheet: New Forecast Review, Table: NewTable0, and K
The dimensions and their names used for the query were:
PRODUCT: Claire
TIME: 2023_FEB_W04, 2023_FEB_W03, 2023_FEB_W02, 2023_FEB_W01, 2023_JAN_W04, 2023_JAN_W03, 2023_JAN_W02, 2023_JAN
LOCATION: East, Central, North, South, West
Next, I will calculate the percentage change in growth of demand plan and prior year shipment for 9 weeks trend for each “Region”.
Percentage Change in Growth of Demand Plan and Prior Year Shipments for 9 Weeks Tren
East:
Actual Shipments Quantity (9 weeks total): 7,381,149
Demand Plan (9 weeks total): 7,339,768
Prior Year Shipments (9 weeks total): 6,925,666
% Demand Plan Growth: (\frac{7,381,149 - 7,339,768}{7,381,149} \times 100 = 0.56%)
% Prior Year Shipments Growth: (\frac{7,381,149 - 6,925,666}{7,381,149} \times 100 = 6.17%)
Central:
Actual Shipments Quantity (9 weeks total): 7,235,927
Demand Plan (9 weeks total): 7,184,199
Prior Year Shipments (9 weeks total): 6,854,894
% Demand Plan Growth: (\frac{7,235,927 - 7,184,199}{7,235,927} \times 100 = 0.72%)
% Prior Year Shipments Growth: (\frac{7,235,927 - 6,854,894}{7,235,927} \times 100 = 5.27%)
North:
Actual Shipments Quantity (9 weeks total): 10,536,740
Demand Plan (9 weeks total): 10,526,142
Prior Year Shipments (9 weeks total): 9,898,398
% Demand Plan Growth: (\frac{10,536,740 - 10,526,142}{10,536,740} \times 100 = 0.10%)
% Prior Year Shipments Growth: (\frac{10,536,740 - 9,898,398}{10,536,740} \times 100 = 6.06%)
South:
Actual Shipments Quantity (9 weeks total): 6,844,387
Demand Plan (9 weeks total): 6,806,801
Prior Year Shipments (9 weeks total): 6,178,290
% Demand Plan Growth: (\frac{6,844,387 - 6,806,801}{6,844,387} \times 100 = 0.55%)
% Prior Year Shipments Growth: (\frac{6,844,387 - 6,178,290}{6,844,387} \times 100 = 9.72%)
West:
Actual Shipments Quantity (9 weeks total): 7,156,342
Demand Plan (9 weeks total): 7,116,576
Prior Year Shipments (9 weeks total): 6,893,245
% Demand Plan Growth: (\frac{7,156,342 - 7,116,576}{7,156,342} \times 100 = 0.56%)
% Prior Year Shipments Growth: (\frac{7,156,342 - 6,893,245}{7,156,342} \times 100 = 3.67%)
Next, I will calculate the percentage change in growth of demand plan and prior year shipment for 4 weeks trend and 1 week trend.