Please note that I am switching the Kellblog RSS feed to http://feeds.feedburner.com/Kellblog.
While I will leave the old feed turned on for some long time (so as to not abandon subscribers), I would greatly prefer if all readers could quickly subscribe to the new feed address http://feeds.feedburner.com/Kellblog.
Thank you!
Posted in Uncategorized
During my time at Business Objects, we did some work with Forbes Magazine and its publisher, Rich Karlgaard. As it turns out, we live in the same town and about once a year I have pleasure of bumping into him in the local grocery store.
Because of this and because he never lacks, shall we say, “point of view,” I always keep a special eye out for his column/blog, Innovation Rules, when reading Forbes. In a recent issue, Rich offers his (judging by the reader comments, controversial) 12-Step Program for fixing America. While I don’t want to jump into the fray on his other 11 points, I must say that I largely agree with point 9.
Dump Sarbanes-Oxley. Enacted in 2002 to prevent the next Enron scandal, Sarbox has thrown sand into the gears of entrepreneurship. It has severely slowed the U.S. market for IPOs, since companies earning less than $200 million in revenue can’t afford the legal and accounting costs of being a public company today. Deprived of capital, young companies not named Facebook or Twitter prematurely stagnate or sell out. Investors are deprived of opportunity, and the nation is deprived of independent companies that surpass the $1-billion-in-revenue mark.
My estimate is that Sarbanes Oxley (Sox) compliance costs a startup about $3M to $5M/year and, more importantly, is a huge distraction for a growth company that should be focused on market share capture. I’ve worked in and around Silicon Valley for about 25 years. Before Sox, every company I worked at went public and did so in the $30M to $50M revenue range. Today, that IPO bar is closer to $100M to $200M. The average time to take a company public pre-Sox was about 5 years. Today, it’s about 10 years.
The result:
So before Sox, if you wanted to be stupid you could buy shares in Beyond.com with full knowledge that they had no business and lots of disclosures to prove that. After Sox you can buy Facebook — but only if you’re already rich/accredited — and without any information or disclosures whatsoever.
This is progress?
Posted in Uncategorized
I stumbled into this press release during my morning reading (ParAccel Triples Revenue, Doubles Customers and Appoints New Executive Team in 2010) and felt an overwhelming and immediate need to use it as an educational example in public relations (PR).
CAMPBELL, Calif.–(BUSINESS WIRE)–ParAccel, Inc., provider of the world’s fastest analytic database, today announced that it achieved record financial performance in 2010 with 300 percent revenue growth over 2009. The company doubled its customer base with key enterprise wins, launched ParAccel Analytic Database (PADB) 3.0, and continued to expand partnerships with leading platform, storage and analytics vendors. To keep pace with its growth, the company hired key new executives and moved its corporate headquarters to a larger facility located in Campbell – the heart of Silicon Valley.
Here are my comments on this release:
Make supportable claims. The “world’s fastest analytic database” claim strikes me as both unsupported and unsupportable. Different databases are good at different things and there are many analytic database competitors in the market. It is not credible that any one DBMS could be fastest at all of them. But this is supposed to be a PR , not a product marketing, post so I won’t drill further.
If you’re going to talk growth, then provide real numbers. Tripling revenue sounds very nice, but from what to what? Many private companies now make these number-free growth claims, but they’re hard to take seriously. Either release real numbers or avoid talking about growth.
If you’re going to talk about growth, do the math correctly. Tripling revenue does not equal 300% growth. Think about it: 100% growth = doubling revenue, 200% growth = tripling revenue, so 300% growth = quadrupling revenue. This is a serious credibility blunder and sadly it’s not uncommon. Get a finance person to review press releases with numbers in them.
If you’re doubling customers and tripling revenues, then you’ve got me asking questions. People will cross-check your numbers, particularly when you’re providing only pieces of the puzzle and have already made one math blunder. I think they mean to say that they tripled annual revenues and doubled the cumulative size of the installed base (i.e., number of customers). Since I’m not sure what to make of that, I made a little model in Excel. I think what the model tells me is that, ceteris paribus, when you are on a strong growth trajectory doubling the installed base is not enough to triple revenues. I’m sure there are better ways to analyze this, but that’s not my point. My point is, as a marketer, when you are providing only pieces of the puzzle you are hanging yourself out to dry if those pieces are inconsistent or provide a clue to a less rosy bigger picture.
By the way, my guess, based on playing with the model below, is that the company had a weak trajectory in 2006-2009 and then had a nice 2010.
“The data warehouse market, and specifically the market for high-performance analytic databases, is growing and evolving at an exponential rate;
Don’t say “exponential growth” if you don’t know what it means. I love the data warehousing market. It is large, growing, and healthy — but it is not growing exponentially. Exponential growth has a precise meaning. The data warehouse market is growing at a 12% (linear) rate and will $13.2B by 2013. That’s huge and wonderful already. Saying the growth is exponential just damages credibility and undermines an otherwise very strong message.
Say “Appoints New Executives,” not “Appoints New Executive Team.” The new CEO joined in August, so that’s not news. The company has appointed a new COO, CMO, and VP of International. Those are important roles and should be announced. But the headline makes it sound like the board blew out the entire executive staff and replaced them in one shot. This is not only a non sequitur (i.e., “we’re doing so well we fired everyone”), it’s also inaccurate.
“With this new, energized executive team in place, strategic partnerships with NetApp, … and leading business intelligence vendors, combined with … ParAccel is poised for an even more impressive 2011.”
Be careful in expectations management. While I just love the “energized” comment (i.e., were the old guys tired?) my real issue is that the company is saying that 2011 will be better than 2010. They shouldn’t say this unless they plan to more than triple revenues in 2011 and more than double the installed base. Logically, anything less would then be a disappointment.
To keep pace with its growth, the company hired key new executives and moved its corporate headquarters to a larger facility located in Campbell – the heart of Silicon Valley.
Be credible. Unless I somehow misplaced Bill and Dave’s Garage, Palo Alto is the heart of Silicon Valley. In 25 years in and around Silicon Valley, never before have I heard Campbell referred to as its heart. C’mon.
Reminder: see my FAQ for relevant disclaimers.
Posted in Marketing, Uncategorized
I had breakfast the other day with a software entrepreneur. When I asked if his company was on a subscription or perpetual model he said: “we should kill the guy who invented the perpetual license — I’m on the perpetual money model, subscription all the way.”
Having worked largely in perpetual license firms, I admit there are many downsides to the perpetual model. Companies on perpetual models typically:
That said, there are many ways to mitigate each of the above points and all of the world’s largest software companies, such as Oracle and SAP, still do most of their business on a perpetual license model.
Over the past decade companies like Salesforce, NetSuite, and SuccessFactors have pushed the software as a service (SaaS) model where the vendor both runs the software and bills on an annual subscription basis to use it. While the SaaS model cut its teeth in applications like sales force automation, vendors are increasingly selling platform as a service (PaaS) offerings as well, such as Amazon Web Services, Google AppEngine, or Force.com.
Clearly SaaS interest and hype remain strong. Salesforce is trading at 100x FY11 earnings. Bankers have told me that the IPO bar for SaaS companies is $75 to $100M in revenue, while for perpetual companies it might be 1.5 times higher than that. A recent Software Equity Group report pegs the median enterprise value (EV) of of SaaS companies at 4.9x revenues, almost double the 2.7x revenues for perpetual companies. On an EV/EBITDA basis, it’s even more dramatic with SaaS companies at 44x and perpetual ones at 13.6x.
Given all this, I thought it would be fun to make an Excel model that concretely demonstrates some of the differences between perpetual and SaaS software companies. To do so, I’ll first model a fictitious, red-hot software startup on a perpetual basis. Then I’ll remodel the same company on a SaaS basis. Then we’ll play around with the models and see what we find. (For Excel geeks, my model is here; you’ll need to download it.)
To make my model, I started with bookings for the perpetual company and hard coded $5M in the first year on a reasonable ramp. Then I made a set of reasonable assumptions (for a hot startup) that drove the rest of the model: 100% license bookings growth, a 20% maintenance rate, a 90% maintenance renewal rate, a 50% rate of professional services organization (PSO) services bookings relative to license, and a bookings-to-revenue conversion rate of 85% for PSO in the subsequent quarter. To keep things simple, I didn’t model months, I didn’t model cash, I assume all bookings happen on the last day of the quarter, and I assume all license revenue is immediately recognizable.
Then I remodeled the company on a SaaS basis. The most important assumption to make here is labeled “subscript as % of license” – i.e., if someone was ready to pay 100 units for a perpetual license to use something, presumably they want to pay some fraction of that for a one-year subscription to use it. (I’ll call this F for fraction.) For the initial model, I assumed F=50% which is arguably aggressive. I kept the renewal rate at 90%. I assumed that configuring a SaaS system requires less PSO than customizing a perpetual one, so I assumed a 50% PSO bookings rate relative to the subscription (or 25% of the total PSO required from the perpetual vendor). I assumed subscriptions were one year and revenue was recognized ratably over the year and that all orders were received the last day of the quarter.
When you make these two models, here is what you find:
In year 4,
Valuation and The Fallacy of Equivalence
Using the standard multiples above, let’s see what each of our companies is worth:
Simply put: the stock market works. With only a 20% difference in valuation between what ostensibly seem like two very different companies you can see that higher EV/R multiple for SaaS companies is almost completely offset by the increased difficulty of building a SaaS revenue stream. Wall Street “sees through” the differences in the models and values the companies roughly equivalently. Put differently, SaaS companies fetch 1.8x the revenue multiple of perpetual companies because they are worth 1.8x the revenue multiple of perpetual companies.
During the past few years I have spoken with several CEOs who transitioned their companies from perpetual to SaaS. The standard word is that it takes 3 years to make the transition and the transition must be a top-three company goal for that entire period. While there are many good reasons for perpetual companies to consider moving to SaaS models, valuation isn’t one of them. Yes, you get roughly twice the EV/R multiple, but building the R (revenue) stream is just about twice as hard.
Max Schireson calls this the fallacy of equivalence. If gold is worth twice silver and assume we have an equal amount of gold as we had silver then we are worth twice as much. The fallacy is that gold is twice as hard to come by as silver so you can’t assume equal amounts — see the huge revenue delta which is largely driven by the SaaS company’s need to spread revenue over 4 quarters.
Taking a Bad Quarter
Let’s look at how each company takes a bad quarter by assuming that we hit 70% of our bookings target in 3Q13 — doing only $4M in perpetual license bookings (cell P8) and only $2.25M in new subscriptions (cell P27).
Hitting The Flat Part of the Market
Now let’s examine both companies assuming that the market goes flat in 2014 (i.e., that 2014 license bookings / new subscriptions do not grow over 2013, cells S8-V8 and S27-V27).
What going on here is simple: volatility is being damped — for better and for worse — by the SaaS company’s need to spread revenue over the four quarters following the booking. That makes it harder to grow the revenue stream quickly. It also makes it harder to change once established.
Sales Compensation
One tricky issue in the SaaS model is sales compensation. In a typical perpetual company total sales commissions (at all levels) add up to around 10%. So, for 100 units of revenue, you pay 10 units in commissions. Sales reps are usually not paid on the 20 unit annuity stream of maintenance renewals.
In SaaS model, we have a conflict. If you assume the annual subscription fetches 50 units (i.e., if F=50%):
So what do you pay: 5, 15, or 30 units? I believe that most SaaS companies end up splitting the difference in the some way, perhaps paying on a declining scale over the first 3 years. If you have good examples here, please share them in the comments.
Cash
While I didn’t model cash in the spreadsheets, one huge issue is the timing of commission payments. For example, if a company were to adopt the 3-year 15-unit commission argument and foolishly pay those three years up front, it would have a big cash consumption issue because effective year 1 commission rates would be 15/50 = 30%, three times the industry norm of 10%.
I think the best answer is to pay commissions on an declining scale and timed close to the receipt of cash from the customer (e.g., on booking the annual renewal).
What if F>=1?
Recall earlier that we talked about the fraction, which I called F, that represented the fraction you would be willing to pay to use something for a year as opposed to license it forever. Because of the big difference between “forever” and “1 year,” I led you easily to the assumption that F should be less than 1.
But should it be? When you look at total cost of ownership, it’s not obvious. In the perpetual model you need to license the software, pay annual maintenance, pay typically 4x the license payment in total deployment costs, and buy the hardware on which the system will run.
In the SaaS model, you have the subscription cost each year and some modest year 1 costs to configure the application. See this simple model:
With F at 50% the SaaS TCO is $200K vs. $610K for the perpetual model. With F at 100% the SaaS TCO is $400K. Even with F at 150% the SaaS TCO is $600K — still less expensive than the perpetual TCO at $610K.
And this, by the way, isn’t theory. A friend who worked at Siebel told me that a typical Siebel sales perpetual license seat sold for about $1,500 back in the day. A friend’s company recently renewed Salesforce at roughly $100/seat/month, that is $1,200/seat/year — not quite F=1, but in the same order of magnitude.
Let’s finish the post by seeing what happens to our model when we assume that F=1, i.e., that the SaaS vendor can get an annual subscription equivalent to the license fee a perpetual vendor would have charged.
In year 4, our our SaaS company is now $55.8M or 90% of our perpetual company, but with all the added benefits of being on a SaaS model. In terms of valuation it is now worth $274M vs. $167M for the perpetual company. This is clearly SaaS panacea. The implicit assumption that an annual subscription to use a service should cost less than equivalent perpetual license is both invalid from a customer TCO viewpoint and suboptimal from a SaaS vendor viewpoint.
While this would seem to suggest that every software vendor should switch to a SaaS model, it is important to remember that many customers don’t want to buy — particularly development platforms — on a SaaS basis. Why? Some of it is about ownership and control. But much of it is because many customers think on time horizons much longer than a 3-year TCO. With F=100% in our TCO model (and ignoring TVM effects), the SaaS system becomes more expensive after year 6.
If you like playing with financial models, I encourage you to download the model spreadsheet that I built for this analysis, play with the assumptions, and share your own conclusions. My plan is to do some open source analysis by setting F=35% and the license fee to zero.
Posted in PaaS, SaaS, Uncategorized
Just a quick post to share the slides I presented last week at the London Online Information 2010 show at Olympia. I spoke on a panel on mobile moderated by Ed Keating of the SIIA, with fellow panelists Alan Pelz-Sharpe of the Real Story Group and Robin Neidorf of Freepint.
My main argument was that publishers should not consider mobile strategy and value proposition independently, but jointly — as portrayed in the strategy quadrants slide that I came up with on slide 10.
Posted in Uncategorized
One of the advantages of children is that they keep you plugged into pop music. Hence, I’ve had the lyrics of Travie McCoy’s song Billionaire drilled into my head over the past several weeks.
I wanna be a billionaire, so freaking bad
Buy all of the things I never had
I wanna be on the cover of Forbes Magazine
Smiling next to Oprah and the Queen
As it turns out, Forbes thinks there 937 billionaires in the world, so if Travie’s wish ends up granted, he’ll be in the top 0.000014% of the population. With this as context, it did come as a surprise the other day when I stumbled into an advertising supplement in the August 30, 2010 issue of Forbes Magazine entitled So You Want To Be A Billionaire, sponsored by a wealth advisor named Hannah Grove. Part of the supplement’s pitch is to buy a book written by Grove’s partner Russ Alan Price, entitled The Family Office: Advising the Financial Elite, which fetches $150/copy.
While I doubt that any of the information presented is scientific — and I’ve not spent the $150 to find out — most of the time books like these seek to identify supposed patterns that separate the ultra-rich from the regular riff-raff one encounters day-to-day. Since they’re not scientific, the patterns are typically someone’s perception as to how the ultra-rich are different, other than the obvious “they seem to have a lot more money.”
Here are seven rules presented in the Forbes supplement. I don’t believe for a second that anyone is likely to place themselves in the top 0.000014% by following them, but I think seeing the perception an advisor to the ultra-rich (who, mind you, probably isn’t in that club himself) is interesting if not useful. The table aims to differentiate working professionals and the ultra-rich along several dimensions.
Commitment
Self-Interest
Line of Money
Connections
Payouts
Failure
Centered
In some ways the list is interesting — e.g., the attitude towards failure is in my opinion healthy, though I believe that most entrepreneurial people have it. Sometimes it’s almost tautological: saying the ultra-rich focus self-interest on making money is like saying champion athletes are focused on winning. Yes, that’s true: if you meet 10 professional athletes you will find they are very competitive people; so, however, were the 10,000 they beat out over the years on their fight to the top. That is, competitiveness was an enabling, not a differentiating trait.
Anyway, if you like this kind of information, a free teaser download is here and the full $150 book is here.
Posted in Uncategorized
This is a post on marketing as much as sports. Here’s my logic:
The real problem here is FIFA which stubbornly refuses to use technology to solve this problem. Video replays and ball-sensors are obvious solutions to the problem. (I’d also argue that soccer should add a fifth referee simply to manage the pushing and shoving in the box on set pieces, much as years ago hockey added a fourth one just to look after nastiness off the play.) Yet FIFA somehow insists that such things are not in the culture of soccer, which is frankly an idiotic excuse for not fixing the problem. As a friend once said about presentations — why is the presenter the only person in the room who can’t see the tweetstream? — why is the center referee the only person on the planet who can’t see the video replay?
Back to marketing, if FIFA won’t fix the problem, then over time I think Adam Smith will. People will gradually lose interest in a sport that every day becomes more and more out of touch with both technology and consumer expectations. Yes soccer has a huge worldwide audience today, but if such injustices continue, worldwide interest will erode over time, and in America, soccer — from an audience size perspective — will continue to be a C-tier sport.
Posted in Uncategorized
MarkLogic and its customer and partner the Warrior Gateway were profiled yesterday on this NBC news story (video below and brief write-up here).
We’re proud to work with the team on Warrior Gateway to help build a site that I view as Kayak plus Yelp all rolled into one, aimed at the specific needs of veterans and their families. Here are some statistics that might surprise you:
For more information on the Warrior Gateway, visit the about page here, the site here, their blog here, or the page about the project from its sponsoring organization, Business Executives for National Security, here.
I’ve embedded the video of the news segment below.
The Associated Press published a story about the Warrior Gateway here.
The other day I noticed a taxonomy used on one of the NoSQL Database blogs that went like this:
Types of NoSQL systems
- Core NoSQL Systems
- Wide column stores
- Document stores
- Key-value / tuple stores
- Eventually consistent key-value stores
- Graph databases
- Soft NoSQL Systems (not the original intention …)
- Object databases
- Grid database solutions
- XML databases
- Other NoSQL-related databases
I, perhaps obviously, take some umbrage at having MarkLogic (acceptably classified as an XML database) being declared “soft NoSQL.” In this post I’ll explain why.
Who decided that being open source was a requirement to be real NoSQL system? More importantly, who gets to decide? NoSQL – like the Tea Party – is a grass-roots, effectively leaderless movement towards relational database alternatives. Anyone arguing original intent of the founders is misguided because there is no small group of clearly identified founders to ask. In reality, all you can correctly argue is what you think was the intent of the initial NoSQL developers and early adopters, or — perhaps more customarily — why you were drawn to them yourself, disguised or confused as original founder intent.
As mentioned here, movements often appear homogeneous when they are indeed heterogeneous. What looks like a long line of demonstrators protesting a single cause is in fact a rugby scrum of different groups pushing in only generally aligned directions. For example, for each of the following potential motivations, I am certain that I can find some set of NoSQL advocates that are motivated by it:
(Since this was a source of confusion in prior posts, note that this is not to claim the inverse: that all NoSQL advocates are motivated by all of the possible motivations.)
I’d like to advocate a simple idea: that NoSQL means NoSQL. That a NoSQL system is defined as:
A structured storage system that is not based on relational database technology and does not use SQL as its primary query language
In short, my proposed definition means that NoSQL (broadly) = NoSQL (literally) + NoRelational. In short: relational database alternatives. It does not mean:
Recently, I’ve heard a piece of backpeddling that I’ve found rather irritating: that NoSQL was never intended to mean “no SQL,” it was actually intended to mean “not only SQL.” Frankly, this strikes me as hogwash: uh oh, I’m afraid that people are seeing us as disruptors and it’s probably easier to penetrate the enterprise as complementary, not competitive, so let’s turn what was a direct assault into a flanking attack.
To me, it’s simple: NoSQL means NoSQL. No SQL query language and no relational database management system. Yes, it’s disruptive and — by some measures — “crazy talk” but no, we shouldn’t hide because there are lots of perfectly valid (and now socially acceptable) reasons to want to differ from the relational status quo.
In effect, my definition of NoSQL is relational database alternative. Such options include both alternative databases (e.g., MarkLogic) and database alternatives (e.g., key/value stores). This, of course, then cuts at your definition of database management system where I (for now at least) still require the support of a query language and the option to have ACID transactions.
By the way, I understand the desire to exclude various bandwagon-jumpers from the NoSQL cause. Like most, I have no interest in including thrice-reborn object databases in the discussion, but if the cost of excluding them is excluding systems like MarkLogic then I think that cost is too high. Many people contemplating the top-of-mind NoSQL systems (e.g., Hadoop) could be better served using MarkLogic which addresses many typical NoSQL concerns, including:
All with all the pros (and cons) of being a commercial software package and without requiring reduced consistency: losing a few Tweets won’t kill Twitter, but losing a few articles, records, or individuals might well kill a patient, bank, or counter-terrorism agency. BASE is fine for some; many others still need ACID. Michael Stonebraker has some further points on this idea in this CACM post.
I’d like to suggest that we should combine the ideas in this post with the ideas in my prior one, Classifying Database Management Systems. That post says the correct way to classify DBMSs is by their native modeling element (e.g., table, class, hypercube). This post says that NoSQL is semi-orthogonal – i.e., I can imagine a table-oriented database that doesn’t use SQL as its query language, but I doubt that any exist. Applying my various rules, the combined posts say that:
Finally, I’d conclude that even with these rules I have trouble classifying MarkLogic because of multiple inheritance: MarkLogic is both a document database and an XML database, it is difficult to pick one over the other, and I there certainly are non-document-oriented XML database systems. Similar issues exist with classifying the various hybrids of document databases and key/value stores. So while I may have more work to do on building an overall taxonomy, I am absolutely sure about one thing: MarkLogic is a NoSQL system.
—
* The “Yes, Virginia” phrase comes from a 1897 story in the New York Sun. For more, see here.
As I sit here at Palantir’s Govcon 5 conference at the lavish Ritz Carlton in Tyson’s Corner (Virgina), I can’t help but think about the recent “fit or fat” startup debate that hit the blogosphere a few weeks back. The debate started with a post by VC Ben Horowitz of Andreessen Horowitz entitled The Case for the Fat Startup. Excerpts:
The [Sequoia RIP Good Times] presentation catalyzed a movement. Startups everywhere adopted a lean, low-burn, low-investment model. To this day, companies seeking funding at our venture firm, Andreessen Horowitz, proudly proclaim in their pitch decks that they are raising tiny amounts of capital so they can run lean.
Here is my central argument. There are only two priorities for a startup: (1) winning the market and (2) not running out of cash.
Running lean is not an end. For that matter, neither is running fat. Both are tactics that you use to win the market and not run out of cash before you do so. By making “running lean” an end, you may lose your opportunity to win the market, either because you fail to fund the R&D necessary to find product/market fit or you let a competitor out-execute you in taking the market. Sometimes running fat is the right thing to do.
The part of his argument with which I agree is the “sometimes.” The simple fact is that strategy must be a function of situation and there are indeed some situations (e.g., landgrabs) where the run-fat model is required. By landgrabs, I mean the early days of new, destined-to-be-large markets with sufficient switching costs so as to realistically justify losing lots of money in the quest to establish market leadership. Examples include Amazon in online retail and PayPal (which raised $194M) in online payments. Remember these strategies do not always end happily: WebVan consumed $1.2B in venture capital before it went bankrupt in 2001. Hence my two key criteria:
When you “go big or go home,” sometimes you go home. I’d argue that the media biases us by looking primarily at successes, not failures, artificially reducing the perceived risk in such strategies. It’s a bit like saying inner-city youth can escape the inner city through athletic scholarships. Yes, it does happen. And yes those athletes sometimes become rich and famous. But simply because it sometimes works, you cannot argue it’s a good strategy.
I was going to use Oracle as example because they played the landgrab game superbly in the early days of the RDBMS market. But I think they only raised $10M or so before their IPO in 1986. (Vent: I just wasted 30 minutes trying to find a precise answer). So unlike the go-big VC burners, Oracle largely self-funded its ten-year journey to $50M. My prior employer, Business Objects, raised a total of less than $5M in VC.
The debate picked up steam when fellow VC Fred Wilson of Union Square Ventures responded with a post entitled Being Fat Is Not Healthy. Excerpt:
In short, since I started investing in the web in ’93/’94, I have invested in about 100 software-based web companies. And the success rate of fat companies versus lean companies is stark. I have never, not once, been successful with an investment in a company that raised a boatload of money before it found traction and product market fit with its primary product.
Boatload is a subjective term. So is traction. So is product market fit. And so is successful. So let me try to define them in the way that I think about them. A boatload of cash is more than $20mm of invested capital. A boatload of cash is monthly burn rates of tens of millions of dollars. Traction and product market fit are customers or users buying or using your product in droves. It is the realization that you’ve found the sweet spot of the market you were going for. And successful is an investment that pays out multiples of the dollars we invested in it. Getting our money back is not successful in my book. Getting three times our money back is good. More than that is great.
Let me say it again. I have never been involved in a successful software-based web service that raised and spent boatloads of money before it found it’s sweet spot. But it has happened. The Loudcloud story that Ben lived and tells in the All Things D post is proof that it can happen.
You can also win the lottery. The odds aren’t great that you will. But millions of people play it every day. I don’t.
Basically, I agree with Fred, with the sole exception of those Amazon- and PayPal-like landgrabs that really are one-shot opportunities that someone is going to win. The problem is that entrepreneurs, being rabid and optimistic, assume they are in that 1-in-1000 situation about 95% of the time.
Back to Palantir, I think they’re pretty clearly playing the “fat” strategy. That’s logical because the founders are from PayPal and are undoubtedly applying some rewind/play logic from those days and should certainly have some survivor bias because — well — it worked last time. (Try convincing a lottery winner that buying lottery tickets is, on average, a very bad idea.) While they’ve raised $35M to-date, I suspect they’ll be raising another round soon, especially if they are to grow from 250 to 400 employees by December 31st as CEO Alex Karp said this morning.
My issue for Palantir is that I don’t see a landgrab market opportunity which they (see prior points) most certainly do. The technology looks like a set of nice data visualization and graph analysis tools; kind of a nice suite of graph-centered BI tools for tracking entities, relationships, events, and documents across collections of unstructured and structured data tapped from various repositories. While the front-ends are sexy, and most likely easier to use than what they’re replacing, if you think using traditional BI tools is tough, I think these tools are harder. Search meets BI this ain’t.
Visualization companies have had a checkered history in enterprise software, with the most successful being vertical and application specific (e.g., Spotfire), so I think Palantir’s vertical focus on government is a good one. They seem also to make an effort in finance, but my gut feel is that they’re 90% government. The company is good at PR, has some creative and interesting management philosophies (e.g., 210 of the 250 employees are supposedly “engineers”), and has a professorial and clearly very intelligent CEO.
Operationally, I think they’d be an excellent partner for Mark Logic because we specialize in back-end heavy lifting and (whether they’d freely admit it or not) everything I saw today strikes me as front-end and/or data aggregation, as opposed to data management, technology. I know we have some partners in common and I believe some customers may have integrated the systems.
Could Palantir be BusinessObjects for unstructured data? I don’t think so — the technology seems too specialized and too hard for the average user; it’s clearly made for analysts. On the other hand, could they be MicroStrategy? Maybe.
Either way, they’re one of very few enterprise software startups these days playing it fat. If I’m right, they’ll be raising another round in the next few quarters, probably at a nice valuation, and basically playing Horowitz’s playbook. On verra.
Posted in strategy, Uncategorized, Venture Capital
Dave Kellogg is Senior Vice President and General Manager of the Service Cloud at Salesforce.com. From 2004 to 2010, I was CEO at unstructured information leader MarkLogic, taking the company from zero to $80M in run-rate revenues.
Before that, I was CMO at Business Objects as we grew from 250 to over 4,500 people and $30M in revenues to over $1B. Prior to that, I was VP of Marketing at Versant, where we executed a chasm-crossing strategy that resulted in a successful IPO. I started my career in both technical and marketing positions at Ingres.In addition, I sat on the board of big data analytics provider Aster Data until its successful sale to Teradata for $325M. I also do some angel investing and advise the chief executives of several startups.
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