New take on the Oomph factor

Stock investing is a complex art and one needs to consider various macro and micro-factors and compare them with other possible choices to make a decision to own one. There are lot of well-known metrics like P/E ratio, P/S ratio, EV/Sales etc for such comparisons.

In Saul’s land, the focus is on owning the best of the best in terms of growth. However, I needed a more nuanced measure than just revenue growth to select among the best out there. While valuation is considered as a second rung, at the end of the day, a comparative measure could be useful to normalize different stocks into a single measure. And, it could used as a facet of evaluating and choosing where to invest.

Before attempting to do so, let it be known that map is not territory. A stock’s essence could never be reduced to a formula/ratio. However, that doesn’t preclude us coming up with one as long as we’re acutely aware of our folly and treat it just as it is - a different albeit imperfect way to compare stocks.

This formula is heavily influenced by previous work on Oomph factor as discussed in this board.

Now, the main and most important factor that go into this formula.

Revenue (top-line) growth is one of hardest things to manipulate and has stood test of time (Saul, Peter Lynch etc) as a primary factor in achieving compounded absolute returns. Growth especially when it’s persistent acts in an exponential pattern.

For example,

At 20% growth, $1000 → $1200 → $1440 → $1728 → $2073 after 4 years.
At 50% growth, $1000 → $1500 → $2250 → $3375 → $5062 after 4 years.
At 80% growth, $1000 → $1800 → $3240 → $5832 → $10497 after 4 years.
At 100% growth, $1000 → $2000 → $4000 → $8000-> $16000 after 4 years.

As you see, just after 4 years, there’s massive (aka exponential) growth from starting to the end revenue especially as the growth rates goes up… Since stock prices follow revenue, this should result in out-sized stock price gains as well.

However, the market realizes this as well and typically gives high valuation to such prospects.

The principal question to answer then is how growth should be factored into a ratio. Using straight forward growth multiplier only differentiates between a 20% grower to a 100% grower linearly by 80%. Thus, missing the exponential nature of the growth.

Hence, in this formula, I propose to take 4 year compounded rate as a multiplier. At 4 years, it gives enough time based growth factor to distinguish the high growth stocks but discounts any further growth that happens after that. The discount is needed as we have no way of predicting long into the future and hence not willing to pay more premium.

Now, our formula stands at (1+growth rate)^4.

Another important factor along side revenue is gross margin. When we think of revenue, its really the gross profit. A high gross margin business is more valuable than that of a low margin. Hence, we bring this as an additional factor.

Now, our formula stands at (1+growth rate)^4 * gross margin.

At the expense of making this ratio more complex, I am introducing another factor called “Rev Surety” which is between 1 and 10… This is a major factor that differentiates a SaaS to a non-SaaS business. I consider the usage-based SaaS even more stickier than the regular SaaS and hence high values for a company like SNOW.

Now, our formula stands at (1+growth rate)^4 * gross margin * rev-surety-factor.

This is what I call o4 short for OOmph4.

DBNRR is basically growth a company gets from existing customers with churn taken into consideration. SaaS has high growth because of this stable revenue that comes with growth (have your candy and eat it too :). However, this factor is already part of the revenue growth (DBNRR + new customer revenue) and thus not directly used in this formula.

Now, PSo4 is a way to compare P/S ratio with the o4 factor.

Here are certain companies and their corresponding OOmph, Oomph4 and Pso4 values.

| Ticker | P/S | Growth Rate | Margin | Rev Surety | OOmph | P/S to Oomph | OOmph4 | Pso4 |
| MNDY   |  41 | 91%         | 90%    |          9 |   3.3 |         12.5 |  10.78 |  3.8 |
| UPST   |  13 | 90%         | 60%    |          5 |   2.2 |            6 |   3.91 |  3.3 |
| ASAN   |  41 | 72%         | 90%    |          9 |   2.7 |         15.4 |   7.09 |  5.8 |
| AMPL   |  33 | 74%         | 71%    |          9 |   2.1 |         15.4 |   5.86 |  5.6 |
| SNOW   |  81 | 100%        | 75%    |         10 |     3 |           27 |     12 |  6.8 |
| CRWD   |  31 | 57%         | 79%    |          9 |   1.9 |         15.9 |   4.32 |  7.2 |
| DDOG   |  52 | 75%         | 78%    |          9 |   2.4 |         21.8 |   6.58 |  7.9 |
| ZS     |  57 | 75%         | 80%    |          9 |   2.5 |         23.3 |   6.75 |  8.4 |
| MDB    |  40 | 57%         | 70%    |          9 |   1.7 |         23.2 |   3.83 | 10.5 |
| NET    |  64 | 54%         | 79%    |         10 |   1.9 |         34.2 |   4.44 | 14.4 |

Some commentary:

Between SNOW and MDB, OOmph4 is 3.14 times bigger which I believe is closer to reality. However, using OOmph factor, the difference is only 1.76 times. And, SNOW is a better investment at PSo4 6.8 vs 10.5 for MDB. Of course, MDB has been a great investment due to its continuous revenue growth acceleration.

SNOW is growing at 43% more than MDB and has higher margin and more stickiness.

MNDY is cheaper comparatively to other stocks. I hypothesize this to newer IPO, not well-known, and in highly competitive enterprise tools space.

Average Pso4 seems to be around 7 as of this writing but again this depends on what P/S multiples market is giving as of today. But, again this tool is a way to measure and compare between multiple investment choices.

Rev surety is - let’s say - more subjective than the revenue growth. Hence, we are injecting quite a bit of subjectivity into the formula. So, be careful and mindful in choosing this value. For example, I have given UPST a value of 5 for Rev Surety but that may be too high of an estimate for you personally - I don’t know. Also, this value can be manipulated for other factors such as moat etc.

Growth Rate used in calculation is itself an art. Should one use YoY growth rate or QoQ sequential growth rate and consideration for growth acceleration and deceleration are some decisions to make.

For P/S ratio, for Sales portion, I used Run Rate Sales which may be quirky if there’s seasonality. Please be mindful of that.

One of my to-do is to sell a portion of my NET and distribute that to SNOW which I don’t own right now.

Hope this is useful.

I am linking to a Google sheet (…) I use to make these calculations.



Sudheer, when coming up with new metric, it would be useful to test it against one of bigger megacaps.

I see Cloudflare will 31x its revenues by 2031 according seekingalpha and is selling for 13.6 times 2025 revenues. when you look at it like this, it looks like a bargain to me today.

Datadog will only do 13.5x revenue by 2031 and is selling for 15.13 times 2025 revenues.

I then look at a bigger cap like nvida is selling for 16.35 times 2025 revenues but will only do 6x revenues by 2031.

upst shows selling for just 4.37 times 2025 revenues. the valuation commanded by fb/goog which will grow their revenue by just 2.59 and 2.94x by 2031. Whereas upst will 3.93x its revenue by 2026. Definitely feels undervalued here at this point.

not many of our companies have revenues projected to 2030/2031 but most are projected to 2025 in seekingalpha. this is why I used 2025 revenue multiple here.

what i am trying to say is we need to consider how is one of stable business valued and see how our hypervalued are valued against them. just like how stock valuations are a direct function of fed model. right now we see all these big tech going up in recent month.

although I don’t have a formula but on a bird eye you should see value is when you tabulate this data.


Consider using DBNRR as your Rev Surety.

I see why the SaaS get a higher rating but there’s nothing objective (that I see) that separates a 9 vs 10 between the various companies… whereas DBNRR is verifiable by all.

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While stocks must be evaluated based on their future performance, it is very hard to foresee and I don’t generally give much credence to estimates that are a few years out. UPST is a good recent and painful reminder that foreseeing even one quarter ahead is perilous. That said, I believe in secular trends and sometimes companies need time to work through and capture these.

So, Pso4 metric as it stands is only based on the present (most recent Q) data. And, implicit in this assumption that the current growth, margin and Rev Surety has certain predictive power. If you strongly believe a company has stronger growth acceleration, you could use Rev Surety as a way to strength its Oomph factor.

And, the way I use Pso4 is to compare our stocks from the perspective of growth/margin/Rev Surety. Values tend to go between 3 to 25. Since this is factor applied to P/S ratios, it also depends on the current market valuations.

From this lens, I use it to compare our stocks and see the spectrum and then try to understand why a stock in not in the middle range.

For example, MNDY and UPST stands out on the lower end (least expensive) and NET on the most expensive side. Then, its a decision to consider other factors to keep/reduce NET and correspondingly, add to MNDY, UPST etc. Regarding NET, I see potential for it to become the fourth cloud to AWS, Azure, GC which could mean consistent and accelerating growth for years to come. However, at 3 times more expensive than MNDY based on this lens, I may choose to allocate capital accordingly.

To the question about DBNRR, it is already part of growth rate and if added again becomes double counted.

Hope this helps and the spreadsheet which is built from reading Quarterly reports. I hope this is not becoming an investing philosophy or portfolio management discussion. Let’s take any further questions to personal replies.