Inventory Aging Report with Adjustment Support (FIFO) - sql

Question

Have a problem to solve in the SQL Server to generate a Inventory aging report using FIFO Based on SKU & Warehouse with adjustment support (incoming (+ve) and outgoing (-ve)). I have attached the schema here.
SKU
TransactionType
WarehouseCode
TransactionDate
Qty
100
IN
WH1
2021-04-30
100
100
IN
WH2
2021-04-30
50
101
IN
WH1
2021-04-30
30
101
IN
WH2
2021-05-01
25
100
OUT
WH2
2021-05-02
30
100
OUT
WH1
2021-05-02
20
100
OUT
WH1
2021-05-04
50
100
OUT
WH2
2021-05-04
20
100
OUT
WH1
2021-05-05
25
100
IN
WH2
2021-05-10
30
100
IN
WH1
2021-05-11
30
101
OUT
WH2
2021-05-12
20
100
OUT
WH1
2021-05-15
30
102
IN
WH2
2021-05-15
25
102
OUT
WH2
2021-05-17
2
102
ADJ
WH2
2021-05-18
5
102
ADJ
WH2
2021-05-18
-1
Based on the above schema structure, i need to develop a inventory aging report based on first in first out (FIFO) and show the remaining qty of each SKU and Warehouse combination and make the previous incoming records remaining quantities as zero.
Expected report format Assuming the report is run on (2021-05-20)
SKU
TransactionType
WarehouseCode
TransactionDate
Qty
Remaining
Aging
100
IN
WH1
2021-04-30
100
0
21
100
IN
WH2
2021-04-30
50
0
21
101
IN
WH1
2021-04-30
30
30
21
101
IN
WH2
2021-05-01
25
5
20
100
IN
WH2
2021-05-10
30
30
11
100
IN
WH1
2021-05-11
50
5
10
102
IN
WH2
2021-05-15
25
22
6
102
IN
WH2
2021-05-18
5
5
3
Got the inventory aging report with SQL window function, need assistance adding support for adjustment.
WITH
cumulative AS
(
SELECT
*,
SUM(CASE WHEN TransactionType = 'IN' THEN Qty ELSE 0 END)
OVER (
PARTITION BY SKU, WarehouseCode
ORDER BY TransactionDate
)
AS qty_in_so_far,
SUM(CASE WHEN TransactionType = 'OUT' THEN Qty ELSE 0 END)
OVER (
PARTITION BY SKU, WarehouseCode
)
AS qty_out_final
FROM
inventory
)
SELECT
*,
CASE WHEN qty_out_final > qty_in_so_far THEN 0
WHEN qty_in_so_far - qty_out_final > qty THEN qty
ELSE qty_in_so_far - qty_out_final END AS qty_final,
DATEDIFF(day, TransactionDate, '2021-05-20') + 1 AS aging
FROM
cumulative
WHERE
TransactionType = 'IN'
ORDER BY
TransactionDate,
SKU,
WarehouseCode
SQL Fiddle for sample schema and query - https://dbfiddle.uk/?rdbms=sqlserver_2019&fiddle=de36b2c43d16a0e1e69dd64561422525

Answer 1

Something like this might do it, for the limited data provided.
The first CTE terms tie the 'ADJ' rows to the corresponding prior 'IN' rows, and later simply SUM those group Qtys to derive final 'IN' rows which have the adjustments applied.
Now we use your original logic (with slight corrections) to handle the rest, no longer needing to worry about adjustments.
Limitation: If adjustment rows exist which completely remove more than the prior "IN" transaction, that will require more logic. Unless you need that, the following should be fine.
Also note: Some of your original "Aging" results (in the question) appear wrong, and are not based on the corresponding "IN" row.
The updated fiddle
WITH cte1 AS (
SELECT i.*
, SUM(CASE WHEN TransactionType = 'IN' THEN 1 ELSE 0 END) OVER (PARTITION BY SKU, WarehouseCode ORDER BY TransactionDate) AS grp
FROM inventory AS i
WHERE TransactionType IN ('IN', 'ADJ')
)
, cte2 AS (
SELECT SKU, WarehouseCode, 'IN' AS TransactionType
, MIN(TransactionDate) AS TransactionDate
, SUM(Qty) AS Qty
FROM cte1
GROUP BY WarehouseCode, SKU, grp
UNION
SELECT SKU, WarehouseCode, TransactionType, TransactionDate, Qty
FROM inventory
WHERE TransactionType = 'OUT'
)
, cumulative AS (
SELECT *
, SUM(CASE WHEN TransactionType = 'OUT' THEN Qty ELSE 0 END) OVER (PARTITION BY SKU, WarehouseCode) AS qty_out_final
, SUM(CASE WHEN TransactionType = 'IN' THEN Qty ELSE 0 END) OVER (PARTITION BY SKU, WarehouseCode ORDER BY TransactionDate) AS qty_in_so_far
FROM cte2
)
SELECT SKU, WarehouseCode, TransactionType, TransactionDate
, qty_out_final, qty_in_so_far, Qty
, CASE WHEN qty_out_final >= qty_in_so_far THEN 0
ELSE qty_in_so_far - qty_out_final END AS qty_final
, DATEDIFF(day, TransactionDate, '2021-05-20') + 1 AS aging
FROM cumulative
WHERE TransactionType = 'IN'
ORDER BY TransactionDate, SKU, WarehouseCode
;
The result:
SKU
WarehouseCode
TransactionType
TransactionDate
qty_out_final
qty_in_so_far
Qty
qty_final
aging
100
WH1
IN
2021-04-30
125
100
100
0
21
100
WH2
IN
2021-04-30
50
50
50
0
21
101
WH1
IN
2021-04-30
0
30
30
30
21
101
WH2
IN
2021-05-01
20
25
25
5
20
100
WH2
IN
2021-05-10
50
80
30
30
11
100
WH1
IN
2021-05-11
125
130
30
5
10
102
WH1
IN
2021-05-15
2
29
29
27
6
100
WH1
IN
2021-05-16
125
160
30
35
5