I preferred Silicon Valley  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. 
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  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 .
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  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 , Domo:
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 . 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.
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:
G&A expense of 29% of revenue, not even efficient there.
Operating margin of -162%, huge.
$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.
$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.
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.
 Yes, I know they’re in Utah, but this is still about Silicon Valley culture and investors.
 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.
 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.
 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.
 $900K, $700K, and $800K run-rate for FY17, FY18, and 1Q19 respectively.
I remember one day, years ago, when I was a VP at $10M startup and Larry, the head of sales, came in one day handing out t-shirts that said:
“Code, sell, or get out of the way.”
Neither I, nor the rest of marketing team, took this particularly well because the shirt obviously devalued the contributions of F&A, HR, and marketing. But, ever seeking objectivity, I did concede that the shirt had a certain commonsense appeal. If you could only hire one person at a startup, it would be someone to write the product. And if you could only hire one more, it would be someone to sell it.
This became yet another event that reconfirmed my belief in my “marketing exists to make sales easier” mantra. After all, if you’re not coding or selling, at least you can help someone who is.
Over time, Larry’s t-shirt morphed in my mind into a new mantra:
“A SaaS company is a two-engine plane. The left engine is DEVs. The right is QCRs.”
QCR meaning quota-carrying (sales) representative and DEV meaning code-committing developer. People who sell with truly incremental quota, and people who actually write code and commit it to the code repository.
It’s a much nicer way of saying “code, sell, or get out of the way,” but it’s basically the same idea. And it’s true. While Larry was coming from a largely incorrect “protest overhead and process” viewpoint, I’m coming from a different one: hiring.
The two hardest lines in a company headcount plan to keep at-plan are guess which two? QCRs and DEVs. Forget other departments for a minute — I’m saying is the the hardest line for the VP of Engineering to stay fully staffed on is DEVs, and the hardest line for the VP of Sales to stay fully staffed on is QCRs.
Why is this?
They are two, critical highly in-demand positions, so the market is inherently tight.
Given their importance, the hiring VPs can be gun-shy about making mistakes and lose candidates due to hesitation or indecision.
Both come with a short-term tax and mid-term payoff because on-boarding new hires slows down the rest of the team, a possible source of passive resistance.
Sales managers dislike splitting territories because it makes them unpopular, which could drive more foot-dragging.
It’s just plain easier to find the associated support functions — (e.g,. program managers, QA engineers, techops, salesops, sales productivity, overlays, CSMs, managers in general) than it is find the QCRs and DEVs.
Let me be clear: this is not to say that all the supporting functions within sales and engineering do not add value, nor is this to say that supporting corporate functions beyond sales and engineering do not add value — it is to say, however, that far too often companies take their eye off the ball and staff the support functions before, not after, those they are supporting. That’s a mistake.
What happens if you manage this poorly? On the sales side, for example, you end up with an organization that has 1 SVP of Sales, 1 VP of sales consulting, 4 sales consultants, 1 director of sales ops, 1 director of sales productivity, 1 manager of sales development reps (SDRs), 4 SDRs, an executive assistant, and 4 quota-carrying salespeople. So only 22% of the people in your sales organization actually carry a quota.
“Uh, other than QCRs, we’re doing great on sales hiring,” says the sales VP. “Other than that, Mrs. Lincoln, how did you find the play?” thinks the board.
Because I’ve seen this happen so often, and because I’ve seen companies accused of it both rightfully and unjustly, I’d decided to create two new metrics:
QCR density = number of QCRs / total sales headcount
DEV density = numbers of DEVs / total engineering headcount
The bad news is I don’t have a lot of benchmark data to share here. In my experience, both numbers want to run in the 40% range.
The good news is that if you run a ratio-driven staffing model (which you should do for both sales and engineering), you should be able to calculate what these densities should be when you are fully staffed.
Let’s conclude with a simple model that does just that on the sales side, producing a result in the 38% to 46% range.
Finally, let me add that having such a model helps you understand whether, for example, your QCR density is low due to slow QCR hiring (and/or bad retention) against a good model, or on-pace hiring against a “fat” model. The former is an execution problem, the latter is a problem with your model.
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.
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.
$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.
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.
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
“I know it didn’t work, but it was a great strategy. We just didn’t have the resources to execute it.”
Huh. Wait minute. If you didn’t have the resources to execute it, then it wasn’t a great strategy. Maybe it was a great strategy for some other company that could have applied the appropriate resources. But it wasn’t a great strategy for you. Ergo, it wasn’t a great strategy. QED.
I learned my favorite definition of strategy at a Stanford executive program I attended a few years back. Per Professor Robert Burgelman, author of Strategy is Destiny, strategy is simply “the plan to win.” Which begets an important conversation about the definition of winning. In my experience, defining winning is more important than making the plan, because if everyone is focused on taking different hills, any resultant strategy will be a mishmash of plans to support different objectives.
But, regardless of your company’s definition of winning, I can say that any strategy you can’t execute definitionally won’t succeed and is ergo a bad strategy.
It sounds obvious, but nevertheless a lot of companies fall into this trap. Why?
A lack of focus.
A failure to “compile” strategy before executing it.
Focus: Think Small to Grow Big
Big companies that compete in lots of broad markets almost invariably didn’t start out that way.
BusinessObjects started out focused on the Oracle financials installed base. Facebook started out on Harvard students, then Ivy league students. Amazon, it’s almost hard to remember at this point, started out in books. Salesforce started out in SMB salesforce automation. ServiceNow on IT ticket management. This list goes on and on.
Despite the evidence and despite the fame Geoffrey Moore earned with Crossing the Chasm, focus just doesn’t come naturally to people. The “if I could get 1% share of a $10B market, I’d be a $100M company” thought pattern is just far too common. (And investors often accidentally reinforce this.)
The fact is you will be more dominant, harder to dislodge, and probably more profitable if, as a $100M company, you control 30% of a $300M target as opposed to 1% of a $10B target.
So the first reason startups make strategies they can’t execute is because they forget to focus. They aim too broadly. They sign up for too much. The forget that strategy should be sequence of actions over time. Let’s start with Harvard. Then go Ivy League. Then go Universities in general. Then go everyone.
Former big company executives often compound the problem. They’re not used to working with scarce resources and are more accustomed to making “laundry list” strategies that check all the boxes than making focused strategies that achieve victory step by step.
A Failure to Compile Strategy Before Execution
The second reason companies make strategies they can’t execute is that they forget a critical step in the planning process that I call the strategy compiler. Here’s what I think a good strategic planning process looks like.
Strategy offsite. The executive team spends a week offsite focused on situation assessment and strategy. The output of this meeting should be (1) a list of strategic goals for the company for the following year and (2) a high-level financial model that concretizes what the team is trying to accomplish over the next three years. (With an eye, at a startup, towards cash.)
First round budgeting. Finance issues top-down financial targets. Executives who own the various objectives make strategic plans for how to attain them. The output of this phase is (1) first-draft consolidated financials, (2) a set of written strategies along with proposed organizational structures and budgets for attaining each of the company’s ten strategic objectives.
Strategy compilation, resources. The team meets for a day to review the consolidated plans and financials. Invariably there are too many objectives, too much operating expense, and too many new hires. The right answer here is to start cutting strategic goals. The wrong answer is to keep the original set of goals and slash the budget 20% across the board. It’s better to do 100% of 8 strategic initiatives than do 80% of 10.
Strategy compilation, skills. The more subtle assessment that must happen is a sanity check on skills and talent. Do your organization have the competencies and do your people have the skills to execute the strategic plans? If a new engineering project requires the skills of 5 founder-level, Stanford computer science PHDs who each would want 5% of a company, you are simply not going to be able to hire that kind of talent as regular employees. (This is one reason companies do “acquihires”). The output of this phase is a presumably-reduced set of strategic goals.
Second round budgeting. Executives to build new or revised plans to support the now-reduced set of strategic goals.
Strategy compilation. You run the strategy compiler again on the revised plan — and iterate until the strategic goals match the resources and the skills of the proposed organization.
Board socialization. As you start converging via the strategy compiler you need to start working with the board to socialize and eventually sell the proposed operating plan. (This process could easily be the subject of another post.)
If you view strategy as the plan to win, then successful strategies include only those strategies that your organization can realistically execute from both a resources and skills perspective. Instead of doing a single-pass process that moves from strategic objectives to budgets, use an iterative approach with a strategy compiler to ensure your strategic code compiles before you try to execute it.
If you do this, you’ll increase your odds of success and decrease the odds ending up in the crowded section of the corporate graveyard where the epitaphs all read:
Here Lies a Company that Had a “Great” Strategy It Had No Chance of Executing
I’m Dave Kellogg, advisor, director, consultant, angel investor, and blogger focused on enterprise software startups. I am an executive-in-residence (EIR) at Balderton Capital and principal of my own eponymous consulting business.
I bring an uncommon perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud EPM vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of the $500M Service Cloud business at Salesforce; CEO of NoSQL database provider MarkLogic, which we grew from zero to $80M over 6 years; and CMO at Business Objects for nearly a decade as we grew from $30M to over $1B in revenues. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Bluecore, Cyral, FloQast, GainSight, MongoDB, Pigment, Recorded Future, and Tableau.