Oomph Factor--Large Sample Size Review

Hello Fools,

I’m revisiting the Oomph factor that was brought to the board awhile back I believe by Ron (rdutt).

The goal of this post is to share with you some interesting stats when using the Oomph factor over a large basket of stocks. EV/Sales/Oomph (EVSO)

I don’t want to debate the strengths or weaknesses of the factor. I feel the Oomph can be used as a reference point when comparing companies. It’s simple and clean. It’s just one tool out of many that an investor can use. It’s not a magic bullet and it’s not meant to solely base your investing decisions on. Keep in mind this is just a snapshot in time as these figures are constantly changing. Here was the method to my madness.

I took a diverse basket of 46 stocks and applied these parameters to the sample.

• A range of large caps like McDonalds/JNJ, midsized ISRG/WDAY, small BEAT/GPRO
• A range of great companies like Mastercard/TTD and poor ones like Macy’s/Fitbit. There are
companies on this list I would never invest in but I wanted to see how their Oomph factors
compared. The good vs. bad. Let me stress I included BAD COMPANIES on this list.
High growth vs slow
• High margins vs low
• SaaS vs Non-SaaS
• Various sectors like healthcare, software, consumer discretionary/food, media, fintech. Most of
the companies on the list have a “techie” vibe to them even though they might not be pure
software companies. Think of names like Carvana, DexCom, and 2U.
• I added a recurring revenue parameter similar to Saul’s based on a scale of 1 to 20. For
example, if a company like ZS has all recurring revenue they received a 1.2 ranking. On the
other hand, a company without recurring revenue received a 1. TTD, CVNA, etc.

Findings on overall basket of stocks:

Average growth rate 35%

Average gross margins 61%

Average EVSO 10.02

Average YTD returns 43.3%

Findings on Non-SaaS vs Saas:

Average growth rate 29% vs SaaS of 46%

Average gross margins 54% vs Saas of 71%

Average EVSO 9.53 vs SaaS 10.86

Average return YTD 30% vs SaaS 65%

To put things into perspective here are some eye-opening examples of SaaS vs. Non-SaaS EVSO’s.

MongoDB vs. Domino’s Pizza: EVSO of 10 vs 10.5. Returns 113% vs 18%.

OKTA vs. Mastercard: EVSO of 14.1 vs 14.6. Returns 101% vs 40%.

ZS vs Monster Beverage: EVSO of 11 vs 12. Returns of 90% vs 35%.

Now you’re thinking how in the world can you compare SaaS to an energy drink! You must have lost your mind!

Let’s try a few examples within the SaaS segment just to check my sanity. Companies like VEEV, COUP, TEAM all have higher EVSO’s than the two poster child’s of “expensive” stocks. ZS and OKTA.

ZS vs VEEV: EVSO of 12 vs 17.9. Returns of 90% vs 85%.

ZS vs COUP: EVSO of 12 vs 15.7. Returns of 90% vs 94%.

ZS vs TEAM: EVSO of 12 vs 14.6. Returns of 90% vs 48%.

The stocks with the highest EVSO’s produced returns of 71.6% YTD. Avg EVSO of 18.9. 4 of the top 10 have some form of recurring revenue. These high-priced companies include VEEV, COUP, TEAM. OKTA rounds out the top 10. Look at Beyond Meat! EV/S 51.6. EVSO 41.4.

There seems to be a “sweet” spot between an EVSO of 10 and 7. These stocks returned 57.6% YTD. Avg EVSO of 8.6. 9 of 12 have some form of recurring revenue. Companies within this batch have a reasonable EVSO with room for future expansion. This includes TWLO, TTD, PAYC, AYX.

Stocks with the lowest EVSO’s are truly laggards and cheap for a reason. Returns of 6.1%. Avg EVSO of 4.2. DOCU and TWOU fall into this basket of the bottom 15 stocks. Are you paying for great value or under performance?

My objective was to provide some context and perspective by looking at a diverse basket of stocks across different sectors. I may have gotten a little carried away with all of the stats I posted but I hope this information will be helpful or at least interesting to some when looking at the Oomph factor.


Stock	Growth	Gross M	Rec. Revenue  Oomph Factor   EV/Sales  EVS/Oomph  YTD Returns
BYND	215%	27%	      1	          1.25	       51.6	    41.4	156.0%
SNAP	39%	32%	      1	          0.62	       13.5	    21.9	140.0%
VEEV	25%	72%	      1.162	  1.31	       23.5	    17.9	85.0%
V 	10%	81%	      1	          0.98	       16.6	    16.9	28.0%
MCD	-4%	52%	      1	          0.56	       9.4	    16.6	17.0%
COUP	39%	68%	      1.18	  1.55	       24.3	    15.7	94.0%
ISRG	15%	70%	      1	          0.93	       13.7	    14.7	7.0%
TEAM	38%	81%	      1.108	  1.71	       25.0	    14.6	48.0%
MA 	9%	97%	      1	          1.15	       16.8	    14.6	40.0%
OKTA	50%	76%	      1.186	  2.03	       28.6	    14.1	101.0%
CMG 	14%	20%	      1	          0.26	       3.6	    13.9	60.0%
PYPL	12%	45%	      1	          0.56	       7.6	    13.5	33.0%
NFLX	22%	37%	      1.2	  0.66	       8.8	    13.3	35.0%
ZM	103%	82%	      1.2	  4.05	       50.0	    12.3	83.0%
ZS	65%	80%	      1.2	  2.61	       31.4	    12.0	90.0%
MNST 	10%	60%	      1	          0.73	       8.0	    11.0	35.0%
DIS	3%	44%	      1	          0.47	       4.9	    10.6	27.0%
DPZ	6%	37%	      1.036	  0.43	       4.6	    10.5	18.0%
MDB	78%	68%	      1.186	  2.56	       25.6	    10.0	113.0%
MTCH 	15%	76%	      1.16	  1.17	       11.5	     9.8	68.0%
AMZN	17%	27%	      1.042	  0.39	       3.7	     9.6	17.0%
TWLO	81%	53%	      1.14	  1.98	       19.0	     9.6	66.0%
WDAY	35%	70%	      1.17	  1.49	       14.3	     9.6	32.0%
SMAR	55%	81%	      1.178	  2.29	       19.9	     8.7	88.0%
TTD	56%	78%	      1	          1.90	       16.2	     8.5	111.0%
PAYC	30%	84%	      1.196	  1.70	       14.3	     8.4	86.0%
ADBE 	25%	86%	      1.18	  1.59	       13.1	     8.2	24.0%
TWTR 	18%	68%	      1.028	  0.97	       7.8	     8.0	32.0%
CVNA	100%	10%	      1	          0.44	       3.4	     7.8	96.0%
AYX	51%	89%	      1.192	  2.42	       18.8	     7.8	63.0%
JNJ	1%	66%	      1	          0.67	       4.7	     7.0	8.5%
WIX	27%	77%	      1.14	  1.42	       9.8	     6.9	60.0%
DXCM 	52%	60%	      1.06	  1.47	       9.5	     6.5	9.4%
DOCU	37%	76%	      1.188	  1.69	       9.9	     5.9	18.0%
BEAT	10%	63%	      1	          0.76	       4.3	     5.7	-18.0%
GRUB	39%	44%	      1	          0.85	       4.6	     5.4	-14.0%
ULTA	10%	36%	      1	          0.44	       2.3	     5.2	36.0%
IRTC 	54%	75%	      1	          1.78	       9.3	     5.2	5.4%
LULU	26%	57%	      1	          0.90	       4.4	     4.9	40.0%
EL 	11%	78%	      1	          0.96	       4.2	     4.4	34.0%
BMY	14%	69%	      1	          0.90	       2.8	     3.2	-11.0%
TWOU	32%	78%	      1	          1.36	       3.9	     2.8	-29.0%
GPRO	20%	33%	      1	          0.48	       0.9	     2.0	34.0%
GOOS	50%	64%	      1	          1.44	       2.3	     1.6	-22.0%
M 	1%	39%	      1	          0.39	       0.6	     1.5	-34.0%
FIT	10%	33%	      1	          0.40	       0.5	     1.1	-17.0%

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I’m a bit confused by some of this data. Are these the current metrics (OOMPH, EV/Sales, Growth % etc…) and the past results (YTD returns)?

If so, wouldn’t it be more effective to show the metrics on 1/1/2019 to see how they predicted the growth of the YTD returns?

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I believe the growth rate for the basket of stocks analyzed is much higher than the S&P’s average and median.
My calculation for the basket mean is 35% compared to the S&P 500 of 25%.
The median of the basket of 26% compared to the S&P 500 of 12%
See https://www.multpl.com/s-p-500-earnings-growth

Current S&P 500 Earnings Growth Rate: 20.49%; Reported Dec 2018
Mean: 24.53%
Median: 12.41%

1 Like

Hi.

Your calculations on oomph was very interesting. I appreciated you calculating in other companies we do not usually invest in. Just the rate of return for the year on each stock I find of value. I do not have the time to look at so many other companies and you have done the work I can not.

I assume Saul liked it!

I would like to see it as it gets updated.

Thanks for posting.

Frank - Boston,Ma

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