Calculate Profit Based on First-In, First-Out Pricing - mysql

Question

Say I have purchase and sales data for some SKUs:
po_id | sku | purchase_date | price | qty
----------------------------------------------
1 | 123 | 2013-01-01 12:25 | 20.15 | 5
2 | 123 | 2013-05-01 15:45 | 17.50 | 3
3 | 123 | 2013-05-02 12:00 | 15.00 | 1
4 | 456 | 2013-06-10 16:00 | 60.00 | 7
sale_id | sku | sale_date | price | qty
------------------------------------------------
1 | 123 | 2013-01-15 11:00 | 30.00 | 1
2 | 123 | 2013-01-20 14:00 | 28.00 | 3
3 | 123 | 2013-05-10 15:00 | 25.00 | 2
4 | 456 | 2013-06-11 12:00 | 80.00 | 1
How can I find the sales margin via SQL, assuming they are sold in the order they were purchased? E.g, the margin for sku 123 is
30*1 + 28*3 + 25*2 - 20.15*5 - 17.50*1
with 2 purchased at 17.50 and 1 purchased at 15.00 left unsold.

Answer 1

Good question. The approach that I'm taking is to calculate the total sales. Then calculate cumulative purchases, and combine them with special logic to get the right arithmetic for the combination:
select s.sku,
(MarginPos - SUM(case when s.totalqty < p.cumeqty - p.qty then p.price * p.qty
when s.totalqty between p.cumeqty - p.qty and p.qty
then s.price * (s.totalqty - (p.cumeqty - p.qty))
else 0
end)
) as Margin
from (select s.sku, SUM(price*qty) as MarginPos, SUM(qty) as totalqty
from sales s
) s left outer join
(select p.*,
(select SUM(p.qty) from purchase p2 where p2.sku = p.sku and p2.sale_id <= p.sale_id
) as cumeqty
from purchase s
)
on s.sku = p.sku
group by s.sku, MarginPos
Note: I haven't tested this query so it might have syntax errors.

Answer 2

setting ambient
declare #purchased table (id int,sku int,dt date,price money,qty int)
declare #sold table (id int,sku int,dt date,price money,qty int)
insert into #purchased
values( 1 , 123 , '2013-01-01 12:25' , 20.15 , 5)
,(2 , 123 , '2013-05-01 15:45' , 17.50 , 3)
,(3 , 123 , '2013-05-02 12:00' , 15.00 , 1)
,(4 , 456 , '2013-06-10 16:00' , 60.00 , 7)
insert into #sold
values(1 , 123 , '2013-01-15 11:00' , 30.00 , 1)
,(2 , 123 , '2013-01-20 14:00' , 28.00 , 3)
,(3 , 123 , '2013-05-10 15:00' , 25.00 , 2)
,(4 , 456 , '2013-06-11 12:00' , 80.00 , 1)
a sqlserver solution should be...
with cte_sold as (select sku,sum(qty) as qty, SUM(qty*price) as total_value
from #sold
group by sku
)
,cte_purchased as (select id,sku,price,qty
from #purchased
union all select id,sku,price,qty-1 as qty
from cte_purchased
where qty>1
)
,cte_purchased_ordened as(select ROW_NUMBER() over (partition by sku order by id,qty) as buy_order
,sku
,price
,1 as qty
from cte_purchased
)
select P.sku
,S.total_value - SUM(case when P.buy_order <= S.qty then P.price else 0 end) as margin
from cte_purchased_ordened P
left outer join cte_sold S
on S.sku = P.sku
group by P.sku,S.total_value,S.qty
resultset achieved
sku margin
123 45,75
456 20,00
same result for sku 123 example in the problem description...
30*1 + 28*3 + 25*2 - 20.15*5 - 17.50*1 = 45.75

Answer 3

This is really horrible since it changes a MySQL variable in the queries, but it kind of works (and takes 3 statements):
select
#income := sum(price*qty) as income,
#num_bought := cast(sum(qty) as unsigned) as units
from sale
where sku = 123
;
select
#expense := sum(expense) as expense,
sum(units) as units
from (select
price * least(#num_bought, qty) as expense,
least(#num_bought, qty) as units,
#num_bought := #num_bought - least(#num_bought, qty)
from purchase
where sku = 123 and #num_bought > 0
order by po_id
) as a
;
select round(#income - #expense, 2) as profit_margin;

Answer 4

This is Oracle query but should work in any SQL. It is simplified and does not include all necessary calculations. You can add them yourself. You will see slightly diff totals as 17.50*3 not 17.50*1:
SELECT po_sku AS sku, po_total, sale_total, (po_total-sale_total) Margin
FROM
(
SELECT SUM(price*qty) po_total, sku po_sku
FROM stack_test
GROUP BY sku
) a,
(
SELECT SUM(price*qty) sale_total, sku sale_sku
FROM stack_test_sale
GROUP BY sku
) b
WHERE po_sku = sale_sku
/
SKU PO_TOTAL SALE_TOTAL MARGIN
---------------------------------------------------
123 168.25 164 4.25
456 420 80 340
You can also add partition by SKU if required:
SUM(price*qty) OVER (PARTITION BY sku ORDER BY sku)