Category Archives: IPO

Avoiding the Ten-Year Stock Option Trap (and Other Stock-Option Considerations)

I’ve increasingly spoken to startup employees who find themselves in a difficult trap.  Let’s demonstrate it via an example:

Say you joined a startup in September 2009 as an early employee and immediately received a stock-option grant of 400,000 shares with a strike price of $0.10 when you joined.  The company, while having experienced some ups and downs over the years, has done very well.  At its last 409a valuation, the common stock was valued at $10/share [1].  You feel great; after all, you’re a paper millionaire, with an option worth about $4M [2].

What could possibly be the problem in this seemingly great situation?  Well, sometime in the next 45 days that stock-option is going to vaporize and become worthless.  

More scarily, what needs to happen for that option to become worthless?  Absolutely nothing.  Nobody has to say or do anything.  No notices need to be sent.  Sometime in the next 45 days that option will silently cease to exist [3].  If the company gets acquired two years later at $20/share and you’re expecting an $8M payout you’re going to be rudely surprised to find you get nothing.

The Silent Killer
What happened?  What is this silent killer of stock option value?  Expiration.  The option expired ten years after its grant date.

The vast majority of Silicon Valley stock option plans feature options that expire after ten years.   In this example, your option was granted in September 2009 which means that by October 1, 2019 that option will be expired.  And the really scary part is that nobody needs to tell you it’s about to happen.

While some companies are undoubtedly more proactive than others in both helping employees avoid getting into this situation and warning them as it approaches, in the end, it’s up to you to make sure you don’t get caught in this trap.  Technically, the company doesn’t need to say or do anything.  And – to be clear — because it’s a relatively new phenomenon in Silicon Valley the company may not even have noticed it’s happening and, even if it does, it may remain silent because it doesn’t really have any good remediation options.  It’s a tough situation on both sides because there are no easy wands that anyone can wave to fix this.

If you think you should stop reading here because you’re only at year two of your vesting, don’t.  If you resign (and/or get fired) from your job your stock options will typically expire in just 90 days, so you’ll be facing these same issues — just on a greatly shortened timeframe.

Who Is The Evil Genius Who Set This Up?
None.  There is no evil genius.  It’s simply an unwelcome artifact of Silicon Valley history.  In olden days it took about 4 years for a startup to hit a liquidity event [4] [5].  That’s why stock options vest over 4 years.  It’s also why they expire after 10 years.  All options need to have an expiration date and back in the day, 10 years approximated infinity [6].

As employees, we benefit from the artifact of 4-year-vesting.  However, if we’re not paying attention, we can get crushed by the artifact of 10-year expiration.

What Can I Do About It?
First, this is a tough situation and you may have few or no good options.

Second, I’m not a financial advisor [7]; you’ll need to see your financial and/or tax advisors to figure this out.  In this post, I’ll walk through what I see as some of your options – which will itself demonstrate the problem.

Third, short timeframes are not your friend.  If you see this problem coming I recommend you start thinking hard about it at least 12 months in advance; when you’re down to 30 days left your available choices may be extremely limited.

Here are some of your available options for handling this situation.

1. Exercise the stock-option before it expires. You’ll need to find $40K to pay the company for the exercise, but that’s not the hard part.  Because the fair market value (FMV) of the stock is $10/share you’re going to face a tax bill of somewhere between $1.1M and $1.9M on the exercise, even if you hold the stock (i.e., you don’t sell it) [8].  This is, in fact, the problem statement.

2. Exercise the option before it expires and sell enough to a third-party to pay the tax bill. This means, if you’re selling in the private market (e.g., EquityZen, Sharespost) at the FMV of $10, that you exercise 400K shares and then sell about 150K of them to cover your tax bill [9] [10A].  That leaves you holding 250K shares of stock.  This, however, requires (a) the existence of such a market and/or your ability to independently find a buyer, (b) the stock to be not restricted from you selling it without company approval (or the company granting such approval), and (c) you paying I’d guess $10K or more in legal and/or other transaction fees to make it happen [10].

3. Exercise the option with the support of a specialist fund (e.g,. ESOfund) that cuts rather exotic deals to solve this and related problems [10A]. For example, one of these (typically very boutique) funds might say:  “I’ll give you the cash both for the exercise and to pay your tax bill, if you give me the shares.  When we eventually sell them, I’ll keep 100% of proceeds until I get my money back, 50% until I get 3x my money back, and 25% after that [11].”  These funds are hard to find and the deals can be very hard to understand.  Legal bills can rack up quickly.  And you’ll need to be a major shareholder; no one wants to do a lot of complex work for 2K shares. 

4. Use a company liquidity program, if offered, to avoid getting into the situation.  Some companies periodically offer employees the right to sell shares in order to demonstrate to everyone that liquidity is possible.  Don’t be so busy doing your job that you forget to consider these programs.  While you may think the valuations offered are too low, if there is no secondary market for the stock and/or the company restricts selling the stock after its purchase, you may have no choice but to use such a program.  It’s a far better deal than letting the options expire worthless.

5. Live in Belgium. I believe Belgium has a great law whereby you pay a modest tax at the time you receive a stock option grant and then no tax on either exercise or sale [12].  I’m telling you this not to encourage you to start learning to enjoy moules frites and making immediate plans to move to Brussels (it’s probably too late) — but to remind my international readers that I’m writing from a US point of view and that stock option taxation, in particular, varies a lot from country to country.  If you happen to live in Belgium and the law hasn’t changed, it’s a particularly good place to get stock-options in early-stage startups.   But the main point is to be sure you understand the law of your country before making any plans or decisions when it comes to stock options (or any other tax matter).

6. Avoid the problem in the first place via an early-exercise with section 83b election. Some companies will allow you to exercise your options before they vest by effectively reversing the stock option – you pay the exercise price, the company gives you the shares, and the company retains a right to buy back the shares from you (at the exercise price) which declines by 1/48th per month over four years.  In addition, if you file a section 83b election within 30 days (and the grant was not in-the-money) then you pay no tax at exercise time and incur tax liability only when you eventually sell the shares, which if it’s more than a year away, results in long-term capital gains tax treatment [13].  Wow, this sounds awesome – and it is.

What’s the downside?  (a) Ideally, you need to do this up-front so it’s not necessarily a good solution if you’re in year three, (b) you need enough money to pay the exercise price which typically works well at early-stage startups (400K shares at $0.01/share = $4K) and a lot less well at later stage ones (100K shares at $5/share = $500K), (c) if the company gets in trouble [14] your common stock could well end up worthless and you won’t get your money back – you are effectively destroying the option-value of your option by exercising it, (d) if you don’t file your section 83b in a timely manner and/or lose your records of having filed it you could end up in a very bad position tax-wise [15].

7. Mitigate the problem via regular exercises along the way (laddered). While I don’t think this is a great strategy, it’s simple to understand, and mixes preserving option value while periodically exercising (and incurring taxes) along the way – so it’s going to be expensive to execute; but nevertheless way less expensive than a forced exercise in year 10.  The two nice things about this strategy are (a) you shouldn’t need company approval to execute it and (b) you can stop along the way and still own some of your options — it only gets very expensive in years 3 and 4.  Here’s a spreadsheet to show it (including some comments not in the image below) which you can download here.

ladder vs. panic

Of course, you may find other strategies, proactive companies may offer programs with other strategies, you might be able to execute a derivative of one of these strategies (e.g., number 3 with a rich uncle), and you can combine the above strategies (e.g., laddering plus early-exercise) as you see and your financial and tax advisors see fit.

I should note that later-stage startups may offer restricted stock units (RSUs) instead of options.  Though some of the same principles can apply (e.g., section 83b elections also relate to RSUs), RSUs work differently than stock options and bring different complexity which is beyond our current scope.

In this post, I’ve alerted you to the ten-year stock option expiration trap and given you a few ideas on how to avoid it.  Moreover, remember that if you resign (or get terminated) that this distant ten-year expiration problem becomes a 90-day problem.  Finally, I’ll point you to my favorite book on this subject (which covers both stock-options and RSUs), Consider Your Options 2019, and which has a nice website as well.

Remember to always talk to your financial and tax advisors before making key decisions about equity-based compensation.

# # #

Notes

[1]  Most private startups get an annual 409a valuation once a year to establish the fair market value (FMV) of their common stock so they can appropriately set the strike price on newly granted stock options, without being accused of granting in-the-money options (as some companies were accused of doing during the dot-com bubble).  409a valuations are always lower than “headline valuations” that companies often announce as part of financing rounds, because headline valuations take the price of a newly issued preferred share and multiply it by the entire share pool (common and preferred).  409a valuations first value the business overall, then subtract any debt, and then subtract the value of “preference stack” in arriving at a value for common stock in aggregate, and then per-share.  Because (a) of how they are calculated, (b) various valuation methodologies produce ranges, and (c) there is a general desire to preserve a low common stock price for as long as possible, 409a valuations not only differ from headline valuations (which are arguably calculated incorrectly) but they tend to produce a low-side estimate for the value of the common.

[2] And maybe a lot more than that because many private, hot-company stocks sometimes trade well above the 409a value in secondary markets.  In fact, in many cases it trades a little or no discount to the price of the last preferred round, and in some cases above it which, unless a lot of time has passed since the last round, strikes me as kind of crazy.

[3] That is, in the 45 days after August 15, 2019 – the day I wrote the post.

[4] For example, Business Objects was founded in 1990 and went public in 1994.

[5] If Silicon Valley were reinvented today, options would probably vest over 12 years, because that’s about how long it takes to get to an IPO.  However, that’s unlikely to happen as the ten years is the maximum duration under law for an ISO option.  This isn’t a VC-change kind of thing; it’s a write your Congressional Representative sort of thing.

[6] The definition of a (call) stock option is the right to buy N shares at price P by date D.  Expiration dates are inherent to options.

[7] See disclaimers in my FAQ and terms of use.

[8] Math is approximate.  On the low side, I’m assuming it’s an ISO option and the tax is all AMT at 28% and you’re in a tax-free state.  On the high side, I’m assuming it’s an NQ option, and a combined marginal rate of 49%.  See your tax professional for your situation.  The main point here:  it can be a huge number.

[9] Bear in mind, per earlier comments, the FMV tends to run on the low side and particularly for red-hot companies, prices in the secondary market can be well above the FMV, e.g., in this case, let’s say $20.  While this will help you on the sale side (you’ll need to sell half as many shares), it could bite you on the tax calculation because you’ll simultaneously be arguing that the stock is worth $10 for tax calculation purposes while actually selling it for $20.  See your tax professional.  Good luck.

[10] I’ve seen and/or heard of cases where companies charge a $5K administrative fee for people selling shares in this manner.  Some companies like it and make it easy.  Some don’t and make it anywhere from hard to impossible.

[10A] There is zero endorsement of any vendor or fund mentioned here.  I provide examples simply to make things concrete in terms of classification.

[11] This is a somewhat flawed representation of such deals, but you get the idea.  The fund effectively becomes your partner in owning the stock.  These can be expensive deals, but for the stock-optionee some value is better than none, which is what they will have once the option expires.

[12] This works particularly well for early-stage startups because I believe you pay a tax of either 9% or 18% of the aggregate value (shares x strike price) of the option at grant time, and the shares are worth next to nothing.  (It works less well if you get a grant of 100K shares valued at $100/share.)

[13] You must, must, must see your tax advisor on this.  You have only 30 days to file an election and if you don’t, you lose the benefits of this approach and can put yourself in a very bad situation.

[14] And trouble doesn’t have to mean bankruptcy.  It simply means any situation where the sale price of the company is less than the sum of debt to be repaid plus the preference stack.  In these situations, the common stock becomes worthless.  Note to the wise:  while it’s often the case, you cannot assume the preference stack is simply the amount VCs have invested in preferred stock.  In some cases, you have multiple liquidation preferences where VCs (or PEs) get 1.5x to 2.0x their investment back before the common gets anything.

[15] See [13].   I won’t go into the details of what happens because it’s complicated, but if you are going to go the section 83b route, you need to file within 30 days and keep very good records that you did.  You remember when people went bankrupt on AMT taxes due to buying-and-holding ISO options in Bubble 1.0?  You could end up rekt in a similar way if you get this wrong.

Is Another SaaSacre In The Offing?

I’m not a financial analyst and I don’t make stock recommendations [1], but as a participant and observer in the software investing ecosystem, I do keep an eye on macro market parameters and I read a fair bit of financial analyst research.  Once in an while, I comment on what I’m seeing.

In February 2016, I wrote two posts (SaaS Stocks:  How Much Punishment is in Store and The SaaSacre Part II:  Time for the Rebound?).  To remind you how depressed SaaS stocks were back then:

  • Workday was $49/share, now at $192
  • Zendesk was $15/share, now at $85
  • ServiceNow was $47/share, now at $247
  • Salesforce was $56/share, now at $160

Those four stocks are up 342% over the past 3 years and two months.  More broadly, the Bessemer Emerging Cloud Index is up 385% over the same period.  Given the increase, a seemingly frothy market for stocks (P/E of the S&P 500 at ~21), and plenty of global geopolitical and economic uncertainty, the question is whether there is another SaaSacre (rhymes with massacre) in the not-too-distant future?

Based just on gut feel, I would say yes.  (Hence my Kellblog prediction that markets would be choppy in 2019.)  But this morning, I saw a chart in a Cowen report that helped bring some data to the question:

cowen

I wish we had a longer time period to look at, but the data is still interesting.  The chart plots enterprise value (EV) divided by next twelve month (NTM) sales.  As a forward multiple, it’s already more aggressive than a trailing twelve month (TTM) multiple because revenue is growing (let’s guess 25% to 30% across the coverage universe), thus the multiple gets deflated when looking forward as opposed to back.

That said, let’s look at the shape of the curve.  When I draw a line through 7x, it appears to me that about half the chart is above the line and half below, so let’s guesstimate that median multiple during the period is 7x.  If you believe in regression to the mean, you should theoretically be a bearish when stocks are trading above the median and bullish when they’re below.

Because the average multiple line is pretty thick, it’s hard to see where exactly it ends, but it looks like 8.25x to me.  That means today’s multiples are “only” 18% above the median [2].  That’s good news, in one sense, as my gut was that it would be higher.  The bad news is:  (1) when things correct they often don’t simply drop to the line but well through it and (2) if anything happens to hurt the anticipated sales growth, the EV/NTM-sales multiple goes up at constant EV because  NTM-sales goes down.  Thus there’s kind of a double whammy effect because lower future anticipated growth increases multiples at a time when the multiples themselves want to be decreasing.

This is a long way of saying, in my opinion, as a chartist [3] using this chart, I would conclude that multiples are somewhat frothy, about 20% above the median, with a lot predicated on future growth.

This exercise shows that looking only at price appreciation presents a more dangerous-looking picture than looking at prices as related to revenues:  looking across the whole chart, prices are up a lot since April 2014 but so are forward-looking revenues, and the multiple is roughly the same at the start as at the end:  8x. [4]  Looking at things differently, of the ~350% gain since April 2016, half is due to multiple expansion (from a way-below-median ~4x to an above-median ~8x), and half is to stock revenue growth.

For me, when I look at overall markets (e.g., PE of the S&P), geopolitical uncertainty, price appreciation, and SaaS multiples, I still feel like taking a conservative position.  But somewhat less than so than before I saw this chart.  While it’s totally subjective:  SaaS is less frothy than I thought when looking only at price appreciation.

Switching gears, the same Cowen report had a nice rule of 40 chart that I thought I’d share as well:

r40 cowen

Since the R^2 is only 0.32, I continue to wonder if you’d get a higher R^2 using only revenue growth as opposed to rule of 40 score on the X axis.  For more on this topic, see my other Rule of 40 posts here.

# # #

Notes
[1] See disclaimers in my FAQ and terms of use in the blog license agreement.

[2] Nevertheless, 18% is a lot to lose if multiples instantly reset to the median.  (And they often don’t just drop to the median, but break well through it — e.g., in Jan 2016, they were as low as 4x.)

[3] And chartism doesn’t work.

[4] If you ignore most of the first month where it appeared to be falling from 10x to 8x.

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.

r40-1

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.”

r40-2

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.

r40-3

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.

# # #

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.

The Domo S-1: Does the Emperor Have Clothes?

I preferred Silicon Valley [1] back in the day when companies raised modest amounts of capital (e.g., $30M) prior to an IPO that took 4-6 years from inception, where burn rates of $10M/year looked high, and where $100M raise was the IPO, not one or more rounds prior to it.  When cap tables had 1x, non-participating preferred and that all converted to a single class of common stock in the IPO. [2]

How quaint!

These days, companies increasingly raise $200M to $300M prior to an IPO that takes 10-12 years from inception, the burn might look more like $10M/quarter than $10M/year, the cap table loaded up with “structure” (e.g., ratcheting, multiple liquidation preferences).  And at IPO time you might end up with two classes common stock, one for the founder with super-voting rights, and one for everybody else.

I think these changes are in general bad:

  • Employees get more diluted, can end up alternative minimum tax (AMT) prisoners unable to leave jobs they may be unhappy doing, have options they are restricted from selling entirely or are sold into opaque secondary markets with high legal and transaction fees, and/or even face option expiration at 10 years. (I paid a $2,500 “administrative fee” plus thousands in legal fees to sell shares in one startup in a private transaction.)
  • John Q. Public is unable to buy technology companies at $30M in revenue and with a commission of $20/trade. Instead they either have to wait until $100 to $200M in revenue or buy in opaque secondary markets with limited information and high fees.
  • Governance can be weak, particularly in cases where a founder exercises directly (or via a nuclear option) total control over a company.

Moreover, the Silicon Valley game changes from “who’s smartest and does the best job serving customers” on relatively equivalent funding to “who can raise the most capital, generate the most hype, and buy the most customers.”  In the old game, the customers decide the winners; in the new one, Sand Hill Road tries to, picking them in a somewhat self-fulfilling prophecy.

The Hype Factor
In terms of hype, one metric I use is what I call the hype ratio = VC / ARR.  On the theory that SaaS startups input venture capital (VC) and output two things — annual recurring revenue (ARR) and hype — by analogy, heat and light, this is a good way to measure how efficiently they generate ARR.

The higher the ratio, the more light and the less heat.  For example, Adaptive Insights raised $175M and did $106M in revenue [3] in the most recent fiscal year, for a ratio of 1.6.  Zuora raised $250M to get $138M in ARR, for a ratio of 1.8.  Avalara raised $340M to $213M in revenue, for a ratio of 1.6.

By comparison, Domo’s hype ratio is 6.4.  Put the other way, Domo converts VC into ARR at a 15% rate.  The other 85% is, per my theory, hype.  You give them $1 and you get $0.15 of heat, and $0.85 of light.  It’s one of the most hyped companies I’ve ever seen.

As I often say, behind every “marketing genius” is a giant budget, and Domo is no exception [4].

Sometimes things go awry despite the most blue-blooded of investors and the greenest of venture money.  Even with funding from the likes of NEA and Lightspeed, Tintri ended up a down-round IPO of last resort and now appears to be singing its swan song.  In the EPM space, Tidemark was the poster child for more light than heat and was sold in what was rumored to be fire sale [5] after raising over $100M in venture capital and having turned that into what was supposedly less than $10M in ARR, an implied hype ratio of over 10.

The Top-Level View on Domo
Let’s come back and look at the company.  Roughly speaking [6], Domo:

  • Has nearly $700M in VC invested (plus nearly $100M in long-term debt).
  • Created a circa $100M business, growing at 45% (and decelerating).
  • Burns about $150M per year in operating cash flow.
  • Will have a two-class common stock system where class A shares have 40x the voting rights of class B, with class A totally controlled by the founder. That is, weak governance.

Oh, and we’ve got a highly unprofitable, venture-backed startup using a private jet for a bit less than $1M year [7].  Did I mention that it’s leased back from the founder?  Or the $300K in catering from a company owned by the founder and his brother.  (Can’t you order lunch from a non-related party?)

As one friend put it, “the Domo S-1 is everything that’s wrong with Silicon Valley in one place:  huge losses, weak governance, and now modest growth.”

Personally, I view Domo as the Kardashians of business intelligence – famous for being famous.  While the S-1 says they have 85 issued patents (and 45 applications in process), does anyone know what they actually do or what their technology advantage is?  I’ve worked in and around BI for nearly two decades – and I have no idea.

Maybe this picture will help.

domosolutionupdated

Uh, not so much.

The company itself admits the current financial situation is unsustainable.

If other equity or debt financing is not available by August 2018, management will then begin to implement plans to significantly reduce operating expenses. These plans primarily consist of significant reductions to marketing costs, including reducing the size and scope of our annual user conference, lowering hiring goals and reducing or eliminating certain discretionary spending as necessary

A Top-to-Bottom Skim of the S-1
So, with that as an introduction, let’s do a quick dig through the S-1, starting with the income statement:

domo income

Of note:

  • 45% YoY revenue growth, slow for the burn rate.
  • 58% blended gross margins, 63% subscription gross margins, low.
  • S&M expense of 121% of revenue, massive.
  • R&D expense of 72% of revenue, huge.
  • G&A expense of 29% of revenue, not even efficient there.
  • Operating margin of -162%, huge.

Other highlights:

  • $803M accumulated deficit.  Stop, read that number again and then continue.
  • Decelerating revenue growth, 45% year over year, but only 32% Q1 over Q1.
  • Cashflow from operations around -$150M/year for the past two years.  Stunning.
  • 38% of customers did multi-year contracts during FY18.  Up from prior year.
  • Don’t see any classical SaaS unit economics, though they do a 2016 cohort analysis arguing contribution margin from that cohort of -196%, 52%, 56% over the past 3 years.  Seems to imply a CAC ratio of nearly 4, twice what is normally considered on the high side.
  • Cumulative R&D investment from inception of $333.9M in the platform.
  • 82% revenues from USA in FY18.
  • 1,500 customers, with 385 having revenues of $1B+.
  • Believe they are <4% penetrated into existing customers, based on Domo users / total headcount of top 20 penetrated customers.
  • 14% of revenue from top 20 customers.
  • Three-year retention rate of 186% in enterprise customers (see below).  Very good.
  • Three-year retention rate of 59% in non-enterprise customers.  Horrific.  Pay a huge CAC to buy a melting ice cube.  (Only the 1-year cohort is more than 100%.)

As of January 31, 2018, for the cohort of enterprise customers that licensed our product in the fiscal year ended January 31, 2015, the current ACV is 186% of the original license value, compared to 129% and 160% for the cohorts of enterprise customers that subscribed to our platform in the fiscal years ended January 31, 2016 and 2017, respectively. For the cohort of non-enterprise customers that licensed our product in the fiscal year ended January 31, 2015, the current ACV as of January 31, 2018 was 59% of the original license value, compared to 86% and 111% for the cohorts of non-enterprise customers that subscribed to our platform in the fiscal years ended January 31, 2016 and 2017, respectively.

  • $12.4M in churn ARR in FY18 which strikes me as quite high coming off subscription revenues of $58.6M in the prior year (21%).  See below.

Our gross subscription dollars churned is equal to the amount of subscription revenue we lost in the current period from the cohort of customers who generated subscription revenue in the prior year period. In the fiscal year ended January 31, 2018, we lost $12.4 million of subscription revenue generated by the cohort in the prior year period, $5.0 million of which was lost from our cohort of enterprise customers and $7.4 million of which was lost from our cohort of non-enterprise customers.

  • What appears to be reasonable revenue retention rates in the 105% to 110% range overall.  Doesn’t seem to foot to the churn figure about.  See below:

For our enterprise customers, our quarterly subscription net revenue retention rate was 108%, 122%, 116%, 122% and 115% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively. For our non-enterprise customers, our quarterly subscription net revenue retention rate was 95%, 95%, 99%, 102% and 98% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively. For all customers, our quarterly subscription net revenue retention rate was 101%, 107%, 107%, 111% and 105% for each of the quarters during the fiscal year ended January 31, 2018 and the three months ended April 30, 2018, respectively.

  • Another fun quote and, well, they did take about the cash it takes to build seven startups.

Historically, given building Domo was like building seven start-ups in one, we had to make significant investments in research and development to build a platform that powers a business and provides enterprises with features and functionality that they require.

  • Most customers invoiced on annual basis.
  • Quarterly income statements, below.

domo qtr

  • $72M in cash as of 4/30/18, about 6 months worth at current burn.
  • $71M in “backlog,” multi-year contractual commitments, not prepaid and ergo not in deferred revenue.  Of that $41M not expected to be invoiced in FY19.
  • Business description, below.  Everything a VC could want in one paragraph.

Domo is an operating system that powers a business, enabling all employees to access real-time data and insights and take action from their smartphone. We believe digitally connected companies will increasingly be best positioned to manage their business by leveraging artificial intelligence, machine learning, correlations, alerts and indices. We bring massive amounts of data from all departments of a business together to empower employees with real-time data insights, accessible on any device, that invite action. Accordingly, Domo enables CEOs to manage their entire company from their phone, including one Fortune 50 CEO who logs into Domo almost every day and over 10 times on some days.

  • Let’s see if a computer could read it any better than I could.  Not really.

readability

  • They even have Mr. Roboto to help with data analysis.

Through Mr. Roboto, which leverages machine learning algorithms, artificial intelligence and predictive analytics, Domo creates alerts, detects anomalies, optimizes queries, and suggests areas of interest to help people focus on what matters most. We are also developing additional artificial intelligence capabilities to enable users to develop benchmarks and indexes based on data in the Domo platform, as well as automatic write back to other systems.

  • 796 employees as of 4/30/18, of which 698 are in the USA.
  • Cash comp of $525K for CEO, $450K for CFO, and $800K for chief product officer
  • Pre-offering it looks like founder Josh James owns 48.9M shares of class A and 8.9M shares of class B, or about 30% of the shares.  With the 40x voting rights, he has 91.7% of the voting power.

Does the Emperor Have Any Clothes?
One thing is clear.  Domo is not “hot” because they have some huge business blossoming out from underneath them.  They are “hot” because they have raised and spent an enormous amount of money to get on your radar.

Will they pull off they IPO?  There’s a lot not to like:  the huge losses, the relatively slow growth, the non-enterprise retention rates, the presumably high CAC, the $12M in FY18 churn, and the 40x voting rights, just for starters.

However, on the flip side, they’ve got a proven charismatic entrepreneur / founder in Josh James, an argument about their enterprise customer success, growth, and penetration (which I’ve not had time to crunch the numbers on), and an overall story that has worked very well with investors thus far.

While the Emperor’s definitely not fully dressed, he’s not quite naked either.  I’d say the Domo Emperor’s donning a Speedo — and will somehow probably pull off the IPO parade.

###

Notes

[1] Yes, I know they’re in Utah, but this is still about Silicon Valley culture and investors.

[2] For definitions and frequency of use of various VC terms, go to the Fenwick and West VC survey.

[3] I’ll use revenue rather than trying to get implied ARR to keep the math simple.  In a more perfect world, I’d use ARR itself and/or impute it.  I’d also correct for debt and a cash, but I don’t have any MBAs working for me to do that, so we’ll keep it back of the envelope.

[4] You can argue that part of the “genius” is allocating the budget, and it probably is.  Sometimes that money is well spent cultivating a great image of a company people want to buy from and work at (e.g., Salesforce).  Sometimes, it all goes up in smoke.

[5] Always somewhat truth-challenged, Tidemark couldn’t admit they were sold.  Instead, they announced funding from a control-oriented private equity firm, Marlin Equity Partners, as a growth investment only a year later be merged into existing Marlin platform investment Longview Solutions.

[6] I am not a financial analyst, I do not give buy/sell guidance, and I do not have a staff working with me to ensure I don’t make transcription or other errors in quickly analyzing a long and complex document.  Readers are encouraged to go the S-1 directly.  Like my wife, I assume that my conclusions are not always correct; readers are encouraged to draw their own conclusions.  See my FAQ for complete disclaimer.

[7] $900K, $700K, and $800K run-rate for FY17, FY18, and 1Q19 respectively.

Bookings vs. Billings in a SaaS Company

Financial analysts speak a lot about “billings” in a public SaaS companies, but in private VC-backed SaaS companies, you rarely hear discussion of this metric.  In this post, we’ll use a model of a private SaaS company (where we know all the internal metrics), to show how financial analysts use rules of thumb to estimate and/or impute internal SaaS metrics using external ones – and to see what can go wrong in that process.

For reference, here’s an example of sell-side financial analyst research on a public SaaS company that talks about billings [1].

saas1-zen

Let’s start with a quick model that builds up a SaaS company from scratch [1].  To simplify the model we assume all deals (both new and renewal) are for one year only and are booked on the last day of the quarter (so zero revenue is ever recognized in-quarter from a deal).  This also means next-quarter’s revenue is this-quarter’s ending annual recurring revenue (ARR) divided by 4.

saas13

Available to renew (ATR) is total subscription bookings (new and renewal) from four quarters prior.  Renew bookings are ATR * (1 – churn rate).  The trickiest part of this model is the deferred revenue (DR) waterfall where we need to remember that the total deferred revenue balance is the sum of DR leftover from the current and the prior three quarters.

If you’re not convinced the model is working and/or want to play with it, you can download it, then see how things work by setting some drivers to boundary conditions (e.g., churn to 0%, QoQ sales growth to 0, or setting starting ARR to some fixed number [2]).

 The Fun Part:  Imputing Internal Metrics from External Ones

Now that we know what’s going on the inside, let’s look in from the outside [3]:

  • All public SaaS companies release subscription revenues [4]
  • All public SaaS companies release deferred revenues (i.e., on the balance sheet)
  • Few SaaS companies directly release ARR
  • Few SaaS companies release ATR churn rates, favoring cohort retention rates where upsell both masks and typically exceeds churn [5]

It wasn’t that long ago when a key reason for moving towards the SaaS business model was that SaaS smoothed revenues relative to the all-up-front, lumpy on-premises model.  If we could smooth out some of that volatility then we could present better software companies to Wall Street.  So the industry did [6], and the result?  Wall Street immediately sought a way to look through the smoothing and see what’s really going on in the inherently lumpy, backloaded world of enterprise software sales.

Enter billings, the best answer they could find to do this.  Billings is defined as revenue plus change in deferred revenue for a period.  Conceptually, when a SaaS order with a one-year prepayment term is signed, 100% of it goes to deferred revenue and is burned down 1/12th every month after that.  To make it simple, imagine a SaaS company sells nothing in a quarter:  revenue will burn down by 1/4th of starting deferred revenue [7] and the change in deferred revenue will equal revenue – thus revenue plus change in deferred revenue equals zero.  Now imagine the company took an order for $50K on the last day of the quarter.  Revenue from that order will be $0, change in deferred will be +$50K, implying new sales of $50K [8].

Eureka!  We can see inside the SaaS machine.  But we can’t.

Limitations of Billings as a SaaS Metric

If you want to know what investors really care about when it comes to SaaS metrics, ask the VC and PE folks who get to see everything and don’t have to impute outside-in.  They care about

Of those, public company investors only get a clear look at subscription gross margins and the customer acquisition cost (CAC) ratio.  So, looking outside-in, you can figure out how efficiency a company runs its SaaS service and how efficiently it acquires customers [9].

But you typically can’t get a handle on churn, so you can’t calculate LTV/CAC or CAC Payback Period.  Published cohort growth, however, can give you comfort around potential churn issues.

But you can’t get a precise handle on sales growth – and that’s a huge issue as sales growth is the number one driver of SaaS company valuation [10].  That’s where billings comes into play.  Billings isn’t perfect because it shows what I call “total subscription bookings” (new ARR bookings plus renewal bookings) [11], so we can’t tell the difference between a good sales and weak renewals quarter and a bad sales and a good renewals quarter.

Moreover, billings has two other key weaknesses as a metric:

  • Billings is dependent on prepaid contract duration
  • Companies can defer processing orders (e.g., during crunch time at quarter’s end, particularly if they are already at plan) thus making them invisible even from a billings perspective [12]

Let’s examine how billings depends on contract duration.  Imagine it’s the last day of new SaaS company’s first quarter.  The customer offers to pay the company:

  • 100 units for a prepaid one-year subscription
  • 200 units for a prepaid two-year subscription
  • 300 units for a prepaid three-year subscription

From an ARR perspective, each of the three possible structures represents 100 units of ARR [13].  However, from a deferred revenue perspective, they look like 100, 200, 300 units, respectively.  Worse yet, looking solely at deferred revenue at the end of the quarter, you can’t know if 300 units represents three 100-unit one-year prepay customers or a single 100-unit ARR customer who’s done a three-year prepay.

In fact, when I was at Salesforce we had the opposite thing happen.  Small and medium businesses were having a tough time in 2012 and many customers who’d historically renewed on one-year payment cycles started asking for bi-annual payments.  Lacking enough controls around a rarely-used payment option, a small wave of customers asked for and got these terms.  They were happy customers.  They were renewing their contracts, but from a deferred revenue perspective, suddenly someone who looked like 100 units of deferred revenue for an end-of-quarter renewal suddenly looked 50.  When Wall St. saw the resultant less-than-expected deferred revenue (and ergo less-than-expected billings), they assumed it meant slower new sales.  In fact, it meant easier payment terms on renewals – a misread on the business situation made possible by the limitations of the metric.

This issue only gets more complex when a company is enabling some varying mix of one through five year deals combined with partial up-front payments (e.g., a five-year contract with years 1-3 paid up front, but years 4 and 5 paid annually).  This starts to make it really hard to know what’s in deferred revenue and to try and use billings as a metric.

Let’s close with an excerpt from the Zuora S-1 on billings that echoes many of the points I’ve made above.

saas3

Notes

[1] Source:  William Blair, Inc., Zendesk Strong Start to 2018 by Bhavan Suri.

[2] Even though it’s not labelled as a driver and will break the renewals calculations, implicitly assuming all of it renews one year later (and is not spread over quarters in anyway).

[3] I’m not a financial analyst so I’m not the best person to declare which metrics are most typically released by public companies, so my data is somewhat anecdotal.  Since I do try to read interesting S-1s as they go by, I’m probably biased towards companies that have recently filed to go public.

[4] As distinct from services revenues.

[5] Sometimes, however, those rates are survivor biased.

[6] And it worked to the extent that from a valuation perspective, a dollar of SaaS revenue is equivalent to $2 to $4 of on-premises revenue.  Because it’s less volatile, SaaS revenue is more valuable than on-premises revenue.

[7] Provided no customers expire before the last day of the quarter

[8] Now imagine that order happens on some day other than the last day of the quarter.  Some piece, X, will be taken as revenue during the quarter and 50 – X will show up in deferred revenue.  So revenue plus change in deferred revenue = it’s baseline + X + 50 – X = baseline + 50.

[9] Though not with the same clarity VCs can see it — VCs can see composition of new ARR (upsell vs. new business) and sales customers (new customer acquisition vs. customer success) and thus can create more precise metrics.  For example, a company that has a solid overall CAC ratio may be revealed to have expensive new business acquisition costs offset by high, low-cost upsell.

[10] You can see subscription revenue growth, but that is smoothed/damped, and we want a faster way to get the equivalent of New ARR growth – what has sales done for us lately?

[11] It is useful from a cash forecasting perspective because all those subscription billings should be collectible within 30-60 days.

[12] Moving the deferred revenue impact of one or more orders from Q(n) to Q(n+1) in what we might have called “backlogging” back in the day.  While revenue is unaffected in the SaaS case, the DR picture looks different as a backlogged order won’t appear in DR until the end of Q(n+1) and then at 75, not 100, units.

[13] Normally, in real life, they would ask a small discount in return for the prepay, e.g., offer 190 for two years or 270 for three years.  I’ll ignore that for now to keep it simple.

Kellblog Predictions for 2018

In continuing my tradition of offering predictions every year, let’s start with a review of my hits and misses on my 2017 predictions.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s.  HIT.
  2. Social media companies finally step up and do something about fake news. MISS, but ethical issues are starting to catch up with them.
  3. Gut feel makes a comeback. HIT, while I didn’t articulate it as such, I see this as the war on facts and expertise (e.g., it’s cold today ergo global warming isn’t real despite what “experts” say).
  4. Under a volatile leader, we can expect sharp reactions and knee-jerk decisions that rattle markets, drive a high rate of staff turnover in the Executive branch, and fuel an ongoing war with the media.  HIT.
  5. With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. MISS, turns out this program was never classical government investment in infrastructure, but a massive privatization plan that never happened.
  6. Huge emphasis on security and privacy. PARTIAL HIT, security remained a hot topic and despite numerous major breaches it’s still not really hit center stage.
  7. In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media).  HIT.
  8. Artificial intelligence hits the peak of inflated expectations. HIT.
  9. The IPO market comes back. MISS, though according to some it “sucked less.”
  10. Megavendors mix up EPM and ERP or BI. PARTIAL HIT.  This prediction was really about Workday and was correct to the extent that they’ve seemingly not made much progress in EPM.

Kellblog’s Predictions for 2018

1.  We will again continue to see a level of divisiveness and social discord not seen since the 1960s. We have evolved from a state of having different opinions about policies based on common facts to a dangerous state based on different facts, even on easily disprovable claims, e.g., the White House nativity scene.  The media is advancing, not reducing, this divide.

2.  The war on facts and expertise will continue to escalate. Read The Death of Expertise for more.   This will extend to a war on college. While an attempted opening salvo on graduate student tuition waivers didn’t fire, in an environment where the President’s son says, “we’ll take $200,000 of your money; in exchange we’ll train your children to hate our country,” you can expect ongoing attacks on post-secondary education.  This spells trouble for Silicon Valley, where a large number of founders and entrepreneurs are former grad students as well as immigrants (which is a whole different area of potential trouble).

3.  Leading technology and social media companies finally step up to face ethical challenges. This means paying more attention to their own culture (e.g., sexual harassment, brogrammers).  This means taking responsibility for policing trolls, spreading fake news, building addictive content, and enabling foreign intelligence operations.  Thus far, they have tended to argue they are simply keepers of the town square, and not responsible for the content shared there.  This abdication of responsibility should start to stop in 2018, if only because people start to tune-out the services.  This leads to one of my favorite tweets of the year:

Capture

4.  AI will move from hype to action, meaning bigger budgets, more projects, and some high visibility failures. It will also mean more emphasis on voice and more conversational chatbots.  For finance departments, this means more of what Ventana’s Rob Kugel calls the age of robotic finance, which unites AI and machine learning, robotic process automation (RPA), natural language bots, and blockchain-based distributed ledgers.

5. AI will continue to generate lots of controversy about job displacement. While some remain optimistic, the consensus viewpoint seems to be that AI will suppress employment, most likely widening the wealth inequality gap.  A collapsing educational system combined with AI-driven pressure on low-skilled work seems a recipe for trouble.

6.  The bitcoin bubble bursts. As a reminder, at one point during the peak of tulip mania, the Dutch East India Company was worth more, on an inflated-adjusted basis, than twenty of today’s technology giants combined.

tulips

7.  The Internet of Things (IoT) will continue to build momentum.  IoT won’t hit in a massive horizontal way, instead B2B adoption will be lead by certain verticals such as healthcare, retail, and supply chain.

8.  The freelance / gig economy continues to gain momentum with freelance workers poised to pass traditional employees by 2027. While the gig economy brings advantages to high-skilled knowledge workers (e.g., freedom of location, freedom of work projects), this same trend threatens low-skilled workers via the continual decomposition of full-time jobs in a series of temp shifts.  This means someone working 60 hours a week across three 20-hour shifts wouldn’t be considered to be a full-time employee and thus not eligible for full-time benefits, further increasing wealth inequality.

freelancers

9.  M&A heats up due to repatriation of overseas cash. Apple alone, for example, has $252B in overseas cash.  With the new tax rate dropping from 35% to 15.5%, it will now be ~$50B less expensive for Apple to repatriate that cash.  Overall, US companies hold trillions of dollars overseas and making it cheaper for them to repatriate that cash suggests that they will be flush with dollars to invest in many areas, including M&A

10.  2018 will be a good year for cloud EPM vendors. The dynamic macro environment, the opportunities posed by cash repatriation, and the strong fundamentals in the economy will increase demand for EPM software that helps companies explore how to best exploit the right set of opportunities facing them.  Oracle will fail in pushing PBCS into the NetSuite base, creating a nice third-party opportunity.  SAP, Microsoft, and IBM will continue to put resources into other strategic investment areas (e.g., IBM and Watson, SAP and Hana) leaving fallow the EPM market adjacent to ERP.  And the greenfield opportunity to replace Excel for financial planning, budgeting, and even consolidations will continue drive strong growth.

Let me wish everyone, particularly the customers, partners, and employees of Host Analytics, a Happy New Year in 2018.

# # #

Disclaimer:  these predictions are offered in the spirit of fun.  See my FAQ for more on this and other usage terms.

A Look at the Tintri S-1

Every now and then I take a dive into an S-1 to see what clears the current, ever-changing bar for going public.  After a somewhat rocky IPO process, Tintri went public June 30 after cutting the IPO offering price and has traded flat thus far since then.

Let’s read an excerpt from this Business Insider story before taking a look at the numbers.

Before going public, Tintri had raised $260 million from venture investors and was valued at $800 million.

With the performance of this IPO, the company is now valued at about about $231 million, based on $7.50 a share and its roughly 31 million outstanding shares, (if the IPO’s bankers don’t buy their optional, additional roughly 1.3 million shares.)

In other words, this IPO killed a good $570 million of the company’s value.

In other words, Tintri looks like a “down-round IPO” (or an “IPO of last resort“) — something that frankly almost never happened before the recent mid/late stage private valuation bubble of the past 4 years.

Let’s look at some numbers.

tintri p+l

Of note:

  • $125M in FY2017 revenue.  (They have scale, but this is not a SaaS company so the revenue is mostly non-recurring, making it easier to get to grow quickly and making the revenue is worth less because only the support/maintenance component of it renews each year.)
  • 45% YoY total revenue growth.  (On the low side, especially given that they have a traditional license/maintenance model and recognize revenue on shipment.)
  • 65% gross margins  (Low, but they do seem to sell flash memory hardware as part of their storage solutions.)
  • 87% of revenue spent on S&M (High, again particularly for a non-SaaS company.)
  • 43% of revenue spent on R&D  (High, but usually seen as a good thing if you view the R&D money as well spent.)
  • -81% operating margins (Low, particularly for a non-SaaS company.)
  • -$70.4M in cashflow from operating activities in 2017 ($17M average quarterly cash burn from operations)
  • Incremental S&M / incremental product revenue = 73%, so they’re buying $1 worth of incremental (YoY) revenue for an incremental 73 cents in S&M.  Expensive but better than some.

Overall, my impression is of an on-premises (and to a lesser extent, hardware) company in SaaS clothing — i.e., Tintri’s metrics look like a SaaS company, but they aren’t so they should look better.  SaaS company metrics typically look worse than traditional software companies for two reasons:  (1) revenue growth is depressed by the need to amortize revenue over the course of the subscription and (2) subscriptions companies are willing to spend more on S&M to acquire a customer because of the recurring nature of a subscription.

Concretely, if you compare two 100-unit customers, the SaaS customer is worth twice the license/maintenance customer over 5 years.

saas compare

Moreover, even if Tintri were a SaaS company, it is quite out of compliance with the Rule of 40, that says growth rate + operating margin >= 40%.  In Tintri’s case, we get -35%, 45% growth plus -81% operating margin, so they’re 75 points off the rule.

Other Notes

  • 1250+ customers
  • 21 of the Fortune 100
  • 527 employees as of 1/31/17
  • CEO 2017 cash compensation $525K
  • CFO 2017 cash compensation $330K
  • Issued special retention stock grants in May 2017 that vest in the two years following an IPO
  • Did option repricing in May 2017 to $2.28/share down from weighted average exercise price of $4.05.
  • $260M in capital raised prior to IPO
  • Loans to CFO and CEO to exercise stock options at 1.6% to 1.9% interest in 2013
  • NEA 22.7% ownership prior to opening
  • Lightspeed 14.5% ownership
  • Insight Venture Partners 20.2% ownership
  • Silver Lake 20.4% ownership
  • CEO 3.8% ownership
  • CFO 0.7% ownership
  • $48.9M in long-term debt
  • $13.8M in 2017 stock-based compensation expense

Overall, and see my disclaimers, but this is one that I’ll be passing on.