A tale of 2 formulas: Which one is more efficient?

[RICH937]

A Couple of days ago, @Fluff helped me simplify a formula in a model I have been working on. between my posting the Q, and Fluff's much more elegant solution, I worked out a different simplified solution. To simplify the question, I didn't include that this is part of an 80/20 (Pareto) analysis, and the % values were identifiers for the 80/20 threshold. I now have 2 formulas that work perfectly! What I am wondering is if one of the two is more efficient in its use of excel and my computer's horsepower. Does anyone have an opinion, or a way I can check the efficiency of a formula being used?

I finally got Xl2bb to work, so here's the paste! (whoot! whoot!)

EXCEL HELP2.xlsx
	B	C	D	E	F	G	H	I	J	K	L
1	GOAL:	Identify C+P Count associated with minimum 80|20 % ID for each product in each category.
2
3	CATEGORY (C)	PRODUCT (P)	GROUP (G)	QTY (Q)	RUNNING Q	% RUNNING Q	80|20 % ID	C+P COUNT		FLUFF	RICH937
4	CATEGORY 1	PRODUCT 1	GROUP 1	6,410	6,410	100%	20%	1		YES	YES
5	CATEGORY 1	PRODUCT 3	GROUP 7	9,371	9,371	34%	46%	1		YES	YES
6	CATEGORY 1	PRODUCT 3	GROUP 6	8,445	17,816	64%	16%	2		YES	YES
7	CATEGORY 1	PRODUCT 3	GROUP 5	4,719	22,535	81%	1%	3		YES	YES
8	CATEGORY 1	PRODUCT 3	GROUP 8	2,963	25,498	92%	12%	4		NO	NO
9	CATEGORY 1	PRODUCT 3	GROUP 9	2,159	27,657	100%	20%	5		NO	NO
10	CATEGORY 1	PRODUCT 4	GROUP 11	7,510	7,510	30%	50%	1		YES	YES
11	CATEGORY 1	PRODUCT 4	GROUP 10	5,946	13,456	53%	27%	2		YES	YES
12	CATEGORY 1	PRODUCT 4	GROUP 14	5,537	18,993	75%	5%	3		YES	YES
13	CATEGORY 1	PRODUCT 4	GROUP 1	3,320	22,313	88%	8%	4		NO	NO
14	CATEGORY 1	PRODUCT 4	GROUP 7	3,029	25,342	100%	20%	5		NO	NO
15	CATEGORY 1	PRODUCT 5	GROUP 22	8,211	8,211	69%	11%	1		YES	YES
16	CATEGORY 1	PRODUCT 5	GROUP 16	3,653	11,864	100%	20%	2		NO	NO
17	CATEGORY 2	PRODUCT 2	GROUP 4	9,612	9,612	42%	38%	1		YES	YES
18	CATEGORY 2	PRODUCT 2	GROUP 3	9,486	19,098	83%	3%	2		YES	YES
19	CATEGORY 2	PRODUCT 2	GROUP 2	4,003	23,101	100%	20%	3		NO	NO
20	CATEGORY 2	PRODUCT 4	GROUP 13	9,202	9,202	80%	0%	1		YES	YES
21	CATEGORY 2	PRODUCT 4	GROUP 12	1,592	10,794	93%	13%	2		NO	NO
22	CATEGORY 2	PRODUCT 4	GROUP 15	772	11,566	100%	20%	3		NO	NO
23	CATEGORY 2	PRODUCT 5	GROUP 20	7,440	7,440	30%	50%	1		YES	YES
24	CATEGORY 2	PRODUCT 5	GROUP 17	6,473	13,913	56%	24%	2		YES	YES
25	CATEGORY 2	PRODUCT 5	GROUP 21	3,550	17,463	71%	9%	3		YES	YES
26	CATEGORY 2	PRODUCT 5	GROUP 19	3,512	20,975	85%	5%	4		YES	YES
27	CATEGORY 2	PRODUCT 5	GROUP 18	1,951	22,926	93%	13%	5		NO	NO
28	CATEGORY 2	PRODUCT 5	GROUP 8	1,799	24,725	100%	20%	6		NO	NO
29		FLUFF FORMULA:	IF(I4<=(TAKE(SORT(FILTER($H$4:$I$28,($B$4:$B$28=B4)*($C$4:$C$28=C4))),1,-1)),"YES","NO")
30		RICH937 FORMULA:	IF(G4<=((MIN(FILTER($H$4:$H$28,($B$4:$B$28=B4)*($C$4:$C$28=C4))))+0.8),"YES","NO")
Sheet1

Cell Formulas
Range	Formula
K4:K28	K4	=IF(I4<=(TAKE(SORT(FILTER($H$4:$I$28,($B$4:$B$28=B4)*($C$4:$C$28=C4))),1,-1)),"YES","NO")
L4:L28	L4	=IF(G4<=((MIN(FILTER($H$4:$H$28,($B$4:$B$28=B4)*($C$4:$C$28=C4))))+0.8),"YES","NO")

 

[MARK858]

Using FastExcel v3 (over what is a small data set) there is nothing between them, at a push Fluff's is more often faster over the runs (but not always) but we we are talking in the range of 0.020 milliseconds difference.