# Category Archives: Rule of 40

## How Quickly Should You Grow to Key ARR Milestones? The Rule of 56789

Question:  what do you call a 10-year old startup with \$10M in ARR?

When you make a list of key SaaS metrics, you’ll rarely find age listed among them.  That’s correct in the sense that age by itself tells you little, but when size is measured against age, you get a rough measure of velocity.

It’s a lot like people.  Tell me you can play Mozart’s Piano Concerto No. 23 and I’ll be impressed [2].  Tell me you can play it at age 12, and I’ll think you’re an absolute prodigy.  Tell me you have \$10M in ARR after 10 years and I’ll be impressed [3].  Tell me you have it 3 and I’ll run for my checkbook.

All this begs the question of growth velocity:  at what age is a given size impressive?  Towards that end, and working with my friends at Balderton Capital, I’ve come up with what I’m calling the Rule of 56789.

• 5 years to break \$10M
• 6 years to break \$20M
• 7 years to break \$50M
• 8 years to break \$75M
• 9 years to break \$100M

Concretely put, if you walk through the doors to Balderton’s London offices with \$54M in ARR after 7 years, you’ll be in the top quartile of those who have walked before you.

Commentary

• I’m effectively defining “impressive” as top quartile in the Balderton universe of companies [4].
• Remembering 56789 is easy, but remembering the milestones is harder.  Once you commit the series {10, 20, 50, 75, 100} to memory, it seems to stick [5].
• Remember that these are milestones to pass, not ending ARR targets, so this is not equivalent to saying grow 100% from \$10M to \$20M, 150% from \$20 to \$50M, and so on.  See note [6] before concluding {100%, 150%, 50%, 33%} is an odd growth trajectory.
• For example, this is a 56789-compliant growth trajectory that has no whipsawing in growth rates.

Three Situtions That Break The Rule
Rules are made to be broken, so let’s talk about three common situations which confound the Rule of 56789.

• Bootstraps, which are capital constrained and grow more slowly.  Bootstraps should largely ignore the rule (unless they plan on changing their financing strategy) because they are definitionally not trying to impress venture capitalists [7].
• Platforms, that require years of time and millions of dollars before they can go to market, effectively resetting the starting clock from company inception to beta product release [8].
• Pivots, where a company pursues strategy A for a few years, abandons it, and takes some salvage value over to a new strategy B. This effectively resets the starting clock from inception to pivot [9].

Alternative Growth Velocity Rules
Let’s compare the trajectory we showed above to similar one generated using a slightly different rule, which I’ll call the 85% Growth Retention Rule, which says to be “impressive” (as defined above), you should:

• Pass \$1M in ARR at a high growth rate (e.g., above ~180%)
• Subsequently retain 85% of that growth rate every year

I view these as roughly equivalent rules, or more precisely, alternate expressions of nearly the same underlying rule.  I prefer 56789 because it’s more concrete (i.e., do X by Y), but I think 85% growth retention is somewhat more general because it says no matter where you are and how you got there, try to retain 85% (or more) of your growth rate every year.  That said, I think it stops working at 8-10 years because the asymptote on great company growth is somewhere around 40% [10] and some would argue 60% [11].  It also fails in situations where you need to reaccelerate growth.

There’s one well-known growth velocity rule to which we should also compare.  The triple/triple/double/double/double (T2D3) rule, which says that once you hit \$2M in ARR, you should triple to \$6M, triple again to \$18M, then double three times to \$36M, \$72M, and \$144M.

Let’s compare the 56789 and the 85% Growth Retention rules to the T2D3 rule:

Clearly T2D3 is more aggressive and sets a higher bar.  My beef is that it fails to recognize the law of large numbers (by failing to back off on the growth rates as a function of size across considerable scale), so as an operator I’m more intuitively drawn to the 85% Growth Retention rule.  That said, if you want to be top 5% to 10% (vs. top 25%), then go for T2D3 if you can do it [12].  You’ll clearly be creating a lot more value.

I like all of these rules because they help give you a sense for how quickly you should be getting to a certain size.  Growth conversations (e.g., trying to get a CRO to sign up for a number) are never easy.  Rules like these help by providing you with data not about what the average companies are doing, but what the great ones are.  The ones you presumably aspire to be like.

The limitation, of course, is that none of these rules consider the cost of growth.  There’s a big difference between a company that gets to \$100M in 9 years on \$100M in capital vs. one that does so on \$400M in capital.  But that’s why we have other metrics like cash conversion score.  Different metrics measure different things and these ones are focused solely on size/growth vs. age.

A big tip of the hat to Michael Lavner at Balderton Capital for working with me on this post.

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Notes

[1] See the definition of small business, which is somewhat broader than I’d have guessed.

[2] Even though it’s only classified as “less difficult” on this rather amazing scale from less difficult to difficult, very difficult, extremely difficult, ridiculously difficult, and extraordinarily difficult.  (Perhaps CEO’s can use that scale to classify board members.)

[3] It’s not as if just anybody can do either.  Founding a company and building it to \$10M is impressive, regardless of the timeframe.

[4] Balderton universe = European SaaS startups who wanted to raise venture capital, who were sufficiently confident to speak with (what’s generally seen as) a top-tier European firm, and who got far enough into the process to submit performance data.

[5] I remember it by thinking that since it’s still pretty early days, jumping from \$10M+ to \$20M+ seems more reasonable than from \$10M to \$25M+.

[6] Don’t equate this rule with a growth vector of {100%, 150%, 50%, 33%} in years 5 through 9.  For example, years in which companies break \$10M often don’t conclude with \$10.1M in ARR, but more like \$15M, after having doubled from a prior year of \$7 to \$8M.

[7] The rule would probably be more useful in projecting the future of VC-backed competitor.  (I think sometimes bootstrapped companies tend to underestimate the aggressiveness of their VC-backed competition.)  This could help you say, “Well, in N years, BadCo is likely to be a \$50M business, and is almost certainly trying to be.  How should that affect our strategy?”

[8] That said, be sure you’re really building a mininum viable product and not overengineering either because it’s fun or it allows you to delay the scary of moment of truth when you try to sell it.

[9] Financings after a pivot sometimes require a recapitalization, in which case the company’s entire lifeclock, from strategy to product to cap table, are all effectively reset.

[10] Current median growth in Meritech Public Comps is 32% at median scale \$657M in ARR.

[11] 0.85^10 = 0.2 meaning you’ll cut the starting growth rate by 80% after ten years.  So if you start at 200% growth, you’ll be down to 40% after 10 years with 85% growth retention.

[12] I’ll need to take a homework assignment to figure out where in the distribution T2D3 puts you in my data set.

## Are We Due for a SaaSacre?

I was playing around on the enterprise comps [1] section of Meritech‘s website today and a few of the charts I found caught my attention.  Here’s the first one, which shows the progression of the EV/NTM revenue multiple [2] for a set of 50+ high-growth SaaS companies over the past 15 or so years [3].

While the green line (equity-value-weighted [4]) is the most dramatic, the one I gravitate to is the blue line:  the median EV/NTM revenue multiple.  Looking at the blue line, you can see that while it’s pretty volatile, eyeballing it, I’d say it normally runs in the range between 5x and 10x.  Sometimes (e.g., 2008) it can get well below 5x.  Sometimes (e.g., in 2013) it can get well above 10x.  As of the last data point in this series (7/14/20) it stood at 13.8x, down from an all-time high of 14.9x.  Only in 2013 did it get close to these levels.

If you believe in regression to the mean [5], that means you believe the multiples are due to drop back to the 5-10 range over time.  Since mean reversion can come with over-correction (e.g., 2008, 2015) it’s not outrageous to think that multiples could drop towards the middle or bottom of that range, i.e., closer to 5 than 10 [6].

Ceteris paribus, that means the potential for a 33% to 66% downside in these stocks. It also suggests that — barring structural change [7] that moves baseline multiples to a different level — the primary source of potential upside in these stocks is not continued multiple expansion, but positive NTM revenue surprises [8].

I always love Rule of 40 charts, so the next fun chart that caught my eye was this one.  While this chart doesn’t speak to valuations over time, it does speak to the relationship between a company’s Rule of 40 Score and its EV/NTM revenue multiple.  Higher valuations primarily just shift the Y axis, as they have done here, uplifting the maximum Y-value by nearly three times since I last blogged about such a chart [9].  The explanatory power of the Rule of 40 in explaining valuation multiple is down since I last looked, by about half from an R-squared of 0.58 to 0.29.  Implied ARR growth alone has a higher explanatory power (0.39) than the Rule of 40.

To me, this all suggests that in these frothy times, the balance of growth and profit (which is what Rule of 40 measures) matters less than other factors, such as growth, leadership, scarcity value and hype, among others.

Finally, to come back to valuation multiples, let’s look at a metric that’s new to me, growth-adjusted EV/R multiples.

I’ve seen growth-adjusted price/earnings ratios (i.e., PEG ratios) before, but I’ve not seen someone do the same thing with EV/R multiples.  The basic idea is to normalize for growth in looking at a multiple, such as P/E or — why not — EV/R.  For example, Coupa, trading at (a lofty) 40.8x EV/R is growing at 21%, so divide 40.8 by 21 to get 1.98x.  Zoom, by comparison looks to be similarly expensive at 38.3x EV/R but is growing at 139%, so divide 38.3 by 139 to get 0.28x, making Zoom a relative bargain when examined in this light [10].

This is a cool metric.  I like financial metrics that normalize things [11].  I’m surprised I’ve not seen someone do it to EV/R ratios before.  Here’s an interesting observation I just made using it:

• To the extent a “cheap” PE firm might pay 4x revenues for a company growing 20%, they are buying in at a 0.2 growth-adjusted EV/R ratio.
• To the extent a “crazy” VC firm might pay 15x revenues for a company growing at 75%, they are buying in at a 0.2 growth-adjusted EV/R ratio.
• The observant reader may notice they are both paying the same ratio for growth-adjusted EV/R. Given this, perhaps the real difference isn’t that one is cheap and the other free-spending, but that they pay the same for growth while taking on very different risk profiles.

The other thing the observant reader will notice is that in both those pseudo-random yet nevertheless realistic examples, the professionals were paying 0.2.  The public market median today is 0.7.

See here for the original charts and data on the Meritech site.

Disclaimer:  I am not a financial analyst and do not make buy/sell recommendations.  I own positions in a wide range of public and private technology companies.  See complete disclaimers in my FAQ.

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Notes
[1] Comps = comparables.

[2] EV/NTM Revenue = enterprise value / next twelve months revenue, a so-called “forward” multiple.

[3] Per the footer, since Salesforce’s June, 2004 IPO.

[4] As are most stock indexes. See here for more.

[5] And not everybody does.  People often believe “this time it’s different” based on irrational folly, but sometimes this time really is different (e.g., structural change).  For example, software multiples have structurally increased over the past 20 years because the underlying business model changed from one-shot to recurring, ergo increasing the value of the revenue.

[6] And that’s not to mention external risk factors such as pandemic or election uncertainty.  Presumably these are already priced into the market in some way, but changes to how they are priced in could result in swings either direction.

[7] You might argue a scarcity premium for such leaders constitutes a form of structural change. I’m sure there are other arguments as well.

[8] To the extent a stock price is determined by some metric * some multiple, the price goes up either due to increasing the multiple (aka, multiple expansion) or increasing the metric (or both).

[9] While not a scientific way to look at this, the last time I blogged on a Rule of 40 chart, the Y axis topped out at 18x, with the highest data point at nearly 16x.  Here the Y axis tops out at 60x, with the highest data point just above 50x.

[10] In English, to the extent you’re paying for EV/R multiple in order to buy growth, Zoom buys you 7x more growth per EV/R point than Coupa.

[11] As an operator, I don’t like compound operational metrics because you need to un-tangle them to figure out what to fix (e.g., is a broken LTV/CAC due to LTV or CAC?), but as investor I like compound metrics as much as the next person.

## The Rule of 40 — Down, But Not Out!

Neeraj Agrawal and Logan Bartlett of Battery Ventures recently published the 2019 version of its outstanding annual software round-up report.  I highly recommend this report — it’s 78-pages chock full of great data about topics like:

• Why Battery is long software overall
• The four eras of software evolution
• The five forces driving software’s accelerating growth
• Key trends in 2018, including setting records in three areas:  (1) public company revenue multiples, (2) IPO volume (by over 2x), and (3) M&A volume (by over 2x).
• Key trends from their 2017 report that are still alive, well, and driving software businesses.

But, most of all, it has some great charts on the Rule of 40 [1] that I want to present and discuss here.  Before doing that, I must note that I drank today’s morning coffee reading Alex Clayton’s CloudStrike IPO breakdown, a great post about a cloud security company with absolutely stunning growth at scale — 121% growth to \$312M in Ending ARR in FY19.  And, despite my headline, well in compliance with the Rule of 40.  110% revenue growth + -26% free cashflow margin = 84%, one of the highest Rule of 40 scores that I’ve ever seen [2].  Keep an eye on this company, I expect it should have a strong IPO [3].

However, finding one superstar neither proves nor disproves the rule.  Let’s turn to the Battery data to do that.

When discussing the Rule of 40, most financial analysts make one of two plots.

• They do a scatter plot with revenue growth on the X-axis and FCF margin on the Y-axis.  The Rule of 40 then becomes a line that separates the chart into two zones (compliant and non-compliant).  Note that a minority of public companies actually comply suggesting the rule of 40 is a pretty high bar [4].
• Or, more interestingly, they do a linear regression of Rule of 40 score vs. enterprise-value/revenue (EV) multiple.  This puts focus on the question:  what’s the relationship between Rule of 40 score and company value? [5]

But that thing has always bugged me is that nobody does the linear regression against both the Rule of 40 score and revenue growth.  Nobody, until Battery.  Here’s what it shows.

First, let’s look at the classic Rule of 40 regression.  Recall that R-squared is a statistical measure that explains the dependence of the dependent variable (in this case, EV multiple) on the independent variable (Rule of 40 score).  Here you can see that about 58% of the variation in enterprise value multiple is explained by Rule of 40 score.  You can intuit that by looking at the dots relative to the line — while there is clearly some linear correlation between the data, it’s a long way from perfect (i.e., lots of dots are pretty far from the line).  [6]

Now, the fun part.  Let’s see the same regression against revenue growth alone.  R-squared here is 51%.  So the explanatory power of the Rule of 40 is only 7% higher than revenue growth alone.  Probably still worth looking at, but it sure gets a lot of PR for explaining only an incremental 7%.  It could be worse, I suppose.  Rule of 40 could have a lower R-squared than revenue growth alone — in fact, it did back in 2008 and in 2012.

In the vein, for some real fun let’s look at how this relationship has changed over time.  The first thing you’ll notice is that pre-2012 both last twelve month (LTM) revenue growth and the Rule of 40 had far weaker explanatory power, I suspect because profitability played a more important role in the equation.  In 2012, the explanatory power of both metrics doubled.  In 2015 and 2016 the Rule of 40 explained nearly 20% more than revenue growth alone.  In 2017 and 2018, however, that’s dropped to 7 to 8%.

I still think the Rule of 40 is a nice way to think about balancing growth vs. profit and Rule of 40 compliant companies still command a disproportionate share of market value.  But remember, its explanatory power has dropped in recent years and, if you’re running an early or mid-stage startup, there is very little comparative data available on the Rule of 40 scores of today’s giants when they were at early- or mid-stage scale.  That’s why I think early- and mid-stage startups need to think about the Rule of 40 in terms of glideslope planning.

Thanks to the folks at Battery for producing and sharing this great report. [7]

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Notes
[1] Rule of 40 score = typically calculated as revenue growth + free cashflow (FCF) margin.  When FCF margin is not available, I typically use operating margin.   Using GAAP operating margin here would result in 110% + -55% = 55%, much lower, but still in rule of 40 compliance.

[2] If calculated using subscription revenue growth, it’s 137% + -26% = 111%, even more amazing.  One thing I don’t like about the fluidity of Rule of 40 calculations, as you can see here, is that depending what might seem small nuances in calculations, you can produce a very broad range of scores.   Here, from 55% to 137%.

[3] To me, this means ending day 1 with a strong valuation.  The degree to which that is up or down from the opening price is really about how the bankers priced the offer.  I am not a financial analyst and do not make buy or sell recommendations.  See my disclaimers, here.

[4] In fact, it’s actually a double bar — first you need to have been successful enough to go public, and second you need to clear the Rule of 40.  Despite a minority of public companies actually clearing this bar, financial analysts are quick to point out the minority who do command a disproportionate share of market cap.

[5] And via the resultant R-squared score, to what extent does the Rule of 40 score explain (or drive) the EV/R multiple?

[6] If R-squared were 1.0 all the dots would fall on the least-squares fit line.

[7] Which continues with further analysis, breaking the Rule of 40 into 4 zones.

## Rule of 40 Glideslope Planning

Enterprise SaaS companies need a lot of money to grow. The median company spends \$1.32 to acquire \$1.00 in annual recurring revenue (ARR) [1].  They need to make that investment for 14 years before getting to an IPO.  It all adds up to a median of \$300M in capital raised prior to an IPO.

With such vast amounts of money in play, some say “it’s a growth at all costs” game.  But others hold to the Rule of 40 which attempts to balance growth and profitability with a simple rule:  grow as fast as you want as long as your revenue growth rate + your free cashflow margin >= 40%.

The Rule of 40 gets a lot of attention, but I think that companies are not asking the right question about it.  The right question is not “when should my growing startup be Rule of 40 compliant?” [2]

For more than half of all public SaaS companies, the answer to that question, by the way, is “not yet.”  Per multiple studies I’ve read the median Rule of 40 score for public SaaS companies is ~31%, meaning that more than half of public SaaS companies are not Rule of 40 compliant [3].

So, unless you’re an absolutely amazing company like Elastic (which had a Rule of 40 score of 87% at its IPO), you probably shouldn’t be unrealistically planning to become Rule of 40 compliant three years before your IPO [4].  If you do, especially if you’re well funded and don’t need additional expense constraints, you might well compromise growth with a premature focus on the Rule of 40, which could shoot off your corporate foot in terms of your eventual valuation.

If “when should we be Rule of 40 compliant” is the wrong question, then what’s the right one?

What should my company’s Rule of 40 glideslope be?

That is, over the next several years what is your eventual Rule of 40 score target and how do you want to evolve to it?  The big advantage of this question is that the answer isn’t “a year” and it doesn’t assume Rule of 40 compliance.  But it does get you to start thinking about and tracking your Rule of 40 score.

I built a little model to help do some what-if analysis around this question.  You can download it here.

In our example, we’ve got a 5 year-old, \$30M ARR SaaS company planning the next five years of its evolution, hopefully with an IPO in year 8 or 9.  The driver cells (orange) define how fast you want to grow and what you want your Rule of 40 glideslope to be.  Everything else is calculated.  At the bottom we have an overall efficiency analysis:  in each year how much more are we spending than the previous year, how much more revenue do we expect to get, and what’s the ratio between the two (i.e., which works like kind of an incremental revenue CAC).  As we improve the Rule of 40 score you can see that we need to improve efficiency by spending less for each incremental dollar of revenue.  You can use this as a sanity check on your results as we’ll see in a minute.

Let me demonstrate why I predict that 9 out 10 ten CFOs will love this modeling approach.  Let’s look at every CFO’s nightmare scenario.  Think:  “we can’t really control revenues but we can control expenses so my wake up in the middle of the night sweating outcome is that we build expenses per the plan and miss the revenues.”

In the above (CFO nightmare) scenario, we hold expenses constant with the original plan and come in considerably lighter on revenue.  The drives us miles off our desired Rule of 40 glideslope (see red cells).  We end up needing to fund \$42.4M more in operating losses than the original plan, all to generate a company that’s \$30.5M smaller in revenue and generating much larger losses.  It’s no wonder why CFOs worry about this.  They should.

What would the CFO really like?  A Rule-of-40-driven autopilot.

As in, let’s agree to a Rule of 40 glideslope and then if revenues come up short, we have all pre-agreed to adjust expenses to fall in line with the new, reduced revenues and the desired Rule of 40 score.

That’s what the third block shows above.  We hold to the reduced revenues of the middle scenario but reduce expenses to hold to the planned Rule of 40 glideslope.  Here’s the bad news:  in this scenario (and probably most real-life ones resembling it) you can’t actually do it — the required revenue-gathering efficiency more than doubles (see red cells).  You were spending \$1.38 to get an incremental \$1 of revenue and, to hold to the glideslope, you need to instantly jump to spending only \$0.49.  That’s not going to happen.  While it’s probably impossible to hold to the original {-10%, 0%, 5%} glideslope, if you at least try (and, e.g., don’t build expenses fully to plan when other indicators don’t support it), then you will certainly do a lot better than the {-10%, -32%, -42%} glideslope in the second scenario.

In this post, we’ve talked about the Rule of 40 and why startups should think about it as a glideslope rather than a short- or mid-term destination.  We’ve provided you with a downloadable model where you can play with your Rule of 40 glideslope.  And we’ve shown why CFOs will inherently be drawn to the Rule of 40 as a long-term planning constraint, because in many ways it will help your company act like a self-righting ship.

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Notes

[1] The 75th percentile spends \$1.92.  And 25% spend more than that.  Per KeyBanc.

[2] Rule of 40 compliant means a company has an rule of 40 score >= 40%.  See next note.

[3] Rule of 40 score is generally defined as revenue growth rate + free cashflow (FCF) margin.  Sometimes operating margin or EBITDA margin is used instead because FCF margin can be somewhat harder to find.

[4] I’m trying to find data a good data set of Rule of 40 scores at IPO time but thus far haven’t found one.  Anecdotally, I can say that lots of successful high-growth SaaS IPOs (e.g., MongoDB, Anaplan, and Blackline) were not Rule of 40 compliant at IPO time — nor were they well after, e.g., as of Oct 2018 per JMP’s quarterly software review.  It seems that if growth is sufficiently there, that the profitability constraint can be somewhat deferred in the mind of the market.