Why Can’t PR People Do Math?

I think in today’s world that we need to ask PR people to be not just literate, but numerate.  What does that mean?

  • They need to do basic math correctly.  Most PR people think that going from size $100K to size $700K is 700% growth.  It’s 600%.  I cannot tell you the number of times I have caught this error.  Growth % = ((year N+1 / year N) -1).  2.4x is 140% growth.  1.3x is 30% growth.
  • They need to understand the law of small numbers as well understanding the scale of large ones.  It’s not hard to grow 1000% off a tiny base.  And the typical reader response to mega-growth claims is not “wow, look how big you are this year,” it’s “oh, I didn’t know how small you were last year.”  In addition, PR needs to understand the law of large numbers — i.e., that 10% growth off $1B is $100M.  Technically speaking whenever company A is growing faster than company B, company B is losing relative market share.  However, remember that if you compare a $10M startup that doubled to a $1B that grew 10%, the latter company still had 10x the new sales of the former.  So you need to be careful making claims in that light.
  • They need to understand how people will react to the numbers.  There is tendency in PR to throw out any numbers you can because, sadly, much of the Silicon Valley trade press will consume them wholesale.  But PR needs to be careful.  Some analysts (e.g., the 451 group) are famous for detailed note-taking and cross-checking and will challenge you if your own figures are inconsistent over time.  In addition, there are fairly normal ratios for, e.g., sales/salesperson or revenue/employee so saying one thing definitely implies another.  Savvy readers will try to triangulate things like revenue, bookings, or cashflow based on the tidbits you hand out.  And if the triangulation produces inconsistent results, it’s going to be a headache for your company and drive credibility questions about the figures and your claims.
  • They need to understand what metrics mean.  One favorite PR trick is talk about undefined metrics like sales (e.g., “company reported that sales grew 57% last year”).  It sounds good.  But wait a minute — what’s “sales”?  Do you mean revenue (and if so, why not say it) or bookings (and if so, how you define it).  Another is to discuss poorly defined product-line growth rates, where companies try to classify anything they can as related to the BNI (big new initiative — e.g., cloud at most mega-vendors).  What do those numbers actually mean?  If a purchase order has products 1, 2, and 3 on it and has $100K at the bottom, how does the company allocate the sales across product lines and does it do so consistently over time.  Product line sales figures might sound meaningful but they are often not.  Another favorite is three-division company growing 10% where each division says they’re growing 30%.  Hey, wait a minute — that’s not possible.

If you net all this out, the best advice is that PR needs to become more like IR (investor relations).  IR people know their numbers.  They’re consistent about what they release over time.  They understand how people will triangulate and the implications of so doing.  And they ensure consistency of the message as told by both the English and the math.

[Rewritten and decomposed from a prior interim version, focusing the content to better align with the title.  I removed the “beware of SaaS Companies talking bookings” meme as, while it remains a great topic that raises interesting yellow/red flags, it’s not one you can reasonably expect a PR person to understand or control.]

Summary of the 4Q14 Fenwick & West VC Survey

Because I was reading it and had a minute, I thought I’d do a quick post summarizing the 4Q14 Fenwick & West Silicon Valley Venture Capital Survey (PDF).  As the name indicates, this is an ongoing quarterly survey  on the state of venture capital that pulls from many sources, integrating lots of data into a single picture.

Some highlights (glossary here):

  • Up rounds exceeded down rounds 79% to 6%, with 15% of rounds flat.
  • Average price up 115% in 4Q14, compared to 79% in 3Q14, and the highest value they’ve recorded since they started measuring this in 2005.  (Yes Virginia, prices are good.)
  • 50% of deals were in software companies
  • $14 B was invested in US VC-backed companies in 4Q14, the highest post-bubble amount yet.  (However, remember that during Bubble 1.0, the peak ran around $25B+/quarter.)
  • $49B was invested on the year.  (And you wonder why traffic so bad on 101.)
  • There were 21 VC-backed IPOs in 4Q14 which raised $3B, and 105 on the year.
  • There were 102 acquisitions of VC-backed companies for a total price of $32B in 4Q14 and 531 such deals on the year.
  • $33B was raised by VC funds in 2014, hitting 2005-2007 levels, but not coming close to the $106B raised in 2000.
  • China passed Europe in terms of VC funding raised, tripling from less than $5B in 2013 to more than $15B in 2014.  India more than doubled going from $2B to $5B.
  • Corporate venture capitalists invested $5B in 2014, the highest amount since 2000 (where it was $15B).
  • There are currently 225 accelerators worldwide which have assisted 4264 companies.  AngelList reported over $100M was raised in 2014 across 243 startups.  (This all contributes to a system imbalance where it’s relatively too easy to get angel money, resulting in a fairly large die-off rate between angel round and series A.)
  • When classifying VC deals by the university the CEO attended and then grouping by athletic conferences, the rankings go:  Pac 12, Ivy League, Big Ten, ACC, Big Tweleve, and SEC.  (I did my part for the Pac 12 in 4Q14 — Go Bears!)
  • The Silicon Valley Venture Capitalist Confidence Index published by USF reported confidence of 3.93 in 4Q14, up from 3.89 in 3Q14, and above the (eleven-year) average of 3.72.  Full report here.
  • 19% of rounds had a senior liquidation preference (to existing preferred, not just the common).  Reminder:  glossary here.
  • Only 5% of rounds had senior multiple liquidation preference.
  • 20% of rounds had participation in liquidation, down from a recent high of 34% in 2Q13.  53% of those that had participation, had it uncapped.
  • 5% of rounds had pay-to-play provisions.
  • 13% had redemption rights.

Managing the Fundamental Tension in Marketing

Say you’ve got a new product release.  You’re super excited about your app’s new Feature X.  It’s very innovative.  Product marketing sees it as long-needed differentiator.   Sales sees it as a silver bullet:  “with Feature X, our competition is screwed.”  Everyone’s excited.

Then it happens.  A regional sales VP says, “Hey, marketing, we’ve got a do a webinar on Feature X.”  Part of you is tempted to do it because “sales is the customer,” but deep down you also know that no one will come.  While highly differentiating, Feature X drives real benefits only indirectly and is fairly complex to understand.

Herein lies what I call the fundamental tension in marketing:

What we want to say vs. what they want to hear

I love to make physical analogies for marketing problems because I think it makes them visceral.  Most of marketing, in my opinion, can be modeled off a tradeshow booth.  “Hey, should we gate this white paper on the web?”  Well, what would you do if you were in a tradeshow booth and a student doing a research paper walked up and asked for a copy?  Would you say no (generating ill will and not spreading the message), would you say yes but not run his card (sharing the information, but not generating a fake lead), or would you say yes and run his card (strictly following procedure, but generating a “lead” that will might get $100 worth of processing before your organization figures out it’s worthless.)

The right answer:  give him the white paper – but don’t run the card.

At the risk of over-extending my metaphor, let’s say we’re working with a big tradeshow booth this time; one big enough that it has a little theater inside where we run shows (i.e., movies) every hour.  We have control over two things:  the poster we put up to advertise the shows and the content of the movie that we run.  (If you prefer, you can just use a real movie theater as the metaphor and still stick with the poster vs. the movie concept, which is the real point.)

So when thinking about the fundamental tension:

  • The poster represents what they want to hear. After all, if we want to get people to come into the theater we’re going to need to make a poster that is compelling to them.
  • The move represents what we want to say. This might be our overall story, our view of the market, or why our new features belong on the industry agenda.

Now some marketers might say put “Free Beer Here” on the poster and if we did, we would most certainly pack the theater.  The problem is most people would leave during the movie, few prospective actual buyers would hear our message, and we’d have spent a lot of money on free beer.

A bad CMO declares victory in this scenario, “We packed the house!”  A good one declares failure, “We generated no real opportunities for sales.”  Take a moment to think ponder which type of marketer you really are?  Deep down, are you more excited about leads than opportunities?  If so, you’re going to need to rewire your brain in order to be successful.

No CEO wants a bunch of deadbeats drinking his/her beer if they have no choice of buying his/her technology.

The magic in resolving the fundamental tension is two-fold:

  1. First, recognize that it exists.  The topics we want to talk about are not typically those about which the world wants to hear about.  If you fail to recognize this, you condemn yourself to running company-centric, product-oriented marketing that attracts fewer leads.  If there’s one thing to remember from this post, it’s this:  simplify and clarify the discussion with sales by talking about the poster and the movie.  Typically sales blurs them all up.
  1. Second, learn how to build bridges. This is the art – it’s not easy to figure out which poster attracts the maximum number of potentially qualified buyers who will stay and watch the movie so that you get your chance to “set the agenda” and talk about what you want say.

.When it comes to building bridges, there are three things to consider:

  • Start with the customer. Find or execute surveys of hot topics or key priorities among your target buyers.  These will help you determine “what’s on their mind” and thus “what they want to hear.”
  • Find your angle. Find a few pre- or post-sales consultants knowledgeable in the space to help you determine if your company has a story, or angle, in addressing those top priorities.  In a perfect world, there’s a straight line between the priority and your product.  Sometimes you need to connect a few dots.  Beware, however, building “a bridge too far” where the linkage is too subtle or indirect.
  • A/B test. The great thing about today’s environment is that, with a little creativity and some discipline, you can run 3-5 different posters for the same movie.  This will enable you to see which posters (e.g., PPC ads, web banners) in which locations (sites, networks, audience slices) most cost-effectively attract not only movie-goers, but more importantly people who watch the movie, take the next-step, and eventually become sales opportunities.  helps you determine the top priorities in the mind of your audience.

Kellblog Ten Predictions for 2015

As we move into the third week of January, I figured it was “now or never” in terms of getting a set of predictions out for 2015.  Before jumping into that, let’s take a quick review of how I did with my 2014 predictions and do some self-grading.

  1. 2014 to be a good year in Silicon Valley.  Correct.
  2. Cloud computing will continue to explode.  Correct.
  3. Big data hype will peak. Gartner seems to agree, placing it in August midway past peak on the way to trough of disillusionment. Correct.
  4. The market will be unable to supply enough data science talent. Mashable is now calling data scientist 2015’s hottest professionPer McKinsey, this is a problem that’s going to continue for the next several years. Correct.
  5. Privacy will remain center stage.  Correct.
  6. Mobile will continue to drive both consumer and (select) enterprise. I got the spirit correct on this one, but I think the core problem is probably better thought of as multi-device access to cloud data than mobile per se.  That is, it’s not about using Evernote on my phone, but instead about uniform access to my cloud-based notes from all my mobile (and non-mobile) devices. Basically, correct.
  7. Social becomes a feature, not an app. Correct again.  The struggles of companies like Jive only validate that (enterprise) social should be a feature of virtually all apps, and not a category unto itself.
  8. SAP’s HANA strategy actually works. Well SAP didn’t seem to agree with this one, when Hasso Plattner wrote a post blasting customers for not understanding its business benefits.  But my angle was more – the merits of the strategy aside – when a company the size of SAP shows total commitment to a strategy it’s going to get results.  And it has.  And SAP continues to drive it.  Mostly correct.
  9. Good Data goes public. While this didn’t happen, I continue to believe that Good Data has a smart strategy and a solid product.  They raised $25M in September.  Maybe this year they will make me an honest man.
  10. Adaptive Planning (now, Adaptive Insights) gets acquired by NetSuite. This didn’t happen, either.  The prediction was based on the fairly well known play of OEM-ing something before acquiring it.  Time may well prove me right on this one, but a swing-and-a-miss for 2014.

Our “bonus” prediction last year was that my company, Host Analytics, would have a great year and indeed we did.  We grew new subscriptions well in excess of 100%, making us, I believe, the fastest growing company in the category.  We launched a new sales planning solution as part of our vision to unite financial and operational planning.  We hired scores of great new people to join us on our mission to create a great EPM company, one that transforms how enterprises manage their financial performance.  And we raised $25M in venture capital to boot.

So, all in all, for the 2014 predictions, let’s call it 8.5 out of 11.

Here are my predictions for 2015.

  1. The good times continue to roll in Silicon Valley. If you feel “bubble,” remember that unlike in the dot-com days that most companies experiencing great success today have real, often recurring, revenue and real customers.   From a cycle perspective, to the extent there is a bubble coming, I’d say we’re in 1999 not 2001.
  1. The IPO as a down-round trend continues. One of the odder things about this time period is that I’m repeatedly hearing that successful IPO companies are pricing at down-rounds relative to their last private financings.  This doesn’t spell danger in general – because the public market valuations are both healthy and supportable – it just suggests a highly competitive later-stage private financing market is overbidding prices.  I suspect that will calm down in 2015 but down-round IPOs will continue in 2015.
  1. The curse of the megaround will strike many companies and CEOs. As part of the prior bullet companies are now often able to raise unprecedented amounts of capital at high valuations.  While those companies today may celebrate their $100M, $150M or $200M+ financing rounds, tomorrow they will wake up with a hangover that looks like:  huge pressure to invest that money for growth, even in dubious growth opportunities; anxious board members who need a 3x return in three years atop already stratospheric valuations; companies missing plan when the dubious growth opportunities don’t deliver; and CEOs who get replaced for missing plans that were unrealistic in the first place.  Before you take a megaround, be careful what you wish for — you sometimes get it.
  1. Cloud disruption continues. Megavendors will continue to wrestle cloud disruption and their cloud strategies.    They will continue to talk about success and high growth in the 10% or less of their business that is cloud, while asking investors to ignore the lack of health in the 90% that is non-cloud.  As part of a general Innovator’s Dilemma problem, they will be forced to explain and defend cloud strategies that will hopefully help them long term but depress results in the short term (as SAP had to do last week.)
  1. Privacy becomes a huge issue. People who were once too busy to care when Facebook changed their security setting are now asking who can access what and how.  The Internet of Things will only exacerbate this focus as more data than ever will be available.  In the past, you could see my pictures and status updates.  Now you can know where I am, when, how many hours I sleep at night, when I exercised, what temperature I set my thermostat to, and when I’m home.  The more data that becomes available, and the more readily you can be de-anonymized, the more you will start monitoring your privacy settings and previously unread site terms and conditions.
  1. Next-generation apps continue to explode. Apps like Slack and Zenefits will continue to redefine enterprise software.  While Slack is a technology, design, and integration play in the collaboration space, Zenefits is more of a business-model disruption play (i.e., give us the rather large commissions you rather invisibly paid your health insurance broker and we’ll give you free, high-quality HR software).  Either way, consumerization, design, and the search for new business models / revenue opportunities will continue.
  1. IBM software rebounds. IBM used to be a stronger player in software than it is today (e.g., recall that they invented the relational database). Watson aside, things have been pretty quiet on the IBM software front. Cloud-wise, while they claim to have a $7B business, it’s pretty invisible to me, and it does seem that Amazon has beaten them in low-level categories like IaaS.  While I’m not sure what happened – I don’t track them that closely – they do seem to have just faded away.  Once thing’s for sure – it can’t continue.  While there are contradicting stories in recent press, IBM does appear to be in the midst of a large re-organization, and I’m going to bet that, as a result, they come to market with a stronger software and cloud story.
  1. Angel investing slows. Much has been written about the financing chokepoint where tens of thousands of angels are funding companies that then need to get in line to get funded by the approximately 100 or so VCs who do A rounds.  The first-order result is that many companies think “wow this is easy” on raising a angel round only to die 12-18 month later when they fail to raise VC.  The second-order result, which I think will start kicking in this year, is that angel money will be harder to come by as the system corrects back to a balanced state.
  1. The data scientist shortage continues. With more “big data” and a huge supply of analytic tools and computing power, the limiting factor on analysis-driven business is neither data nor technology.  It’s our ability to find people who can correctly leverage it.  Tell every college kid you know to take lots of stats, analytics, and computing classes.  Or better yet, to go get a degree in data science.
  1. The unification of planning becomes the top meme in enterprise performance management (EPM). EPM has a long history of helping finance departments prepare annual operating budgets and financial reports, but increasingly—in recent years – planning has quietly decentralized to the various departments and divisions within the enterprise.  For example, sales ops increasingly builds the sales plan, marketing ops the marketing plan, and services ops the consulting and professional services plan.   (This is why I sometimes call this trend the “rise of the ops person” as they are increasingly acting as stealth FP&A.)  What’s needed is to unite all these plans and put them on a common planning framework so the CFO and CEO can do what-if analysis and scenario planning holistically across the organization.

Some High-Tech Career Counseling Tips

I get a fair number of emails and calls from former colleagues and friends asking for career advice.  I’m always happy to provide it and the process of doing so is both thought-provoking and fun.  I have a learned a lot from having these conversations and have noticed a few patterns and principles in that process.

I’ll share them in this post.

  • You are responsible for your career development.   Some folks, particularly at larger companies, seems to think the onus is on the company to provide career development for you.  While I’d say it is indeed smart for larger companies to do this as a retention incentive, it does not change the simple fact that you and you alone are responsible for your career development.  You can use company-provided mentors, coaches, courses, rotations as help, but in the end — at the risk of sounding existentialist — you and you alone will have to live the results and ergo you and you alone are responsible for your career development.  Don’t confuse assistance with responsibility.
  • Brands matter.  People are going to look first at where you worked and then second at what you did.  So if you have an MIT MBA, then worked at Salesforce for 5 years, and then did 3 two-year stints at failed startups, it’s time to go to NewRelic or Zendesk or some other hot brand to polish up the resume.  You need to actively manage the brands on your resume.  It’s fine to take risks and if they work out well, then great.   A failed startup or two is a red badge of courage in Silicon Valley.  Just don’t get too many of them in a row.
  • Patterns matter.  To the prior point, everyone is looking for a pattern of success.  Success ideally meaning you had a growing and successful career at a growing and successful company.  Rising up a shrinking organization at a dying startup doesn’t do much for your CV.  Growing through an organization as a company goes from $10M to $100M does a lot.  Why?   Because companies want to hire people on upward trajectories who have experienced growth.  (Why?  Because invariably they are planning to grow and want you to help them do so.)
  • Do new things at your current employer.  Beware any employer willing to hire you to do something you haven’t done before, because in theory they shouldn’t be willing to.  If you look at the matrix below, companies will periodically give new opportunities to known performers in order to help develop and retain them.  But why would you ever hire a total stranger and pay them to learn on-the-job in doing something they haven’t done before.  When you move across companies you should plan on doing things you know how to do, and thus when you are at a company and performing well, you should be pushing to learn new things.

  • Don’t take job B and hope to switch into job A.  Because brands matter, people are sometimes tempted to join a great organization in a bad job.  “I’m really a product marketing director, but the only job they had open was competitive analyst, so I’ll take that and switch.”  There are two problems with this logic:  (1) the second you join the company as competitive analyst you are a competitive analyst (you’ll be the only person thinking you’re a slumming product marketing director), and (2) if you are not great at job B then you probably won’t be offered job A.  Sometimes people do this strategy and pull it off.  But at least understand the risk:  it’s a Hail Mary play if there ever was one.
  • Categories matter.  In addition, you need to manage the categories in which you work.  You might see yourself as a general software marketer, but if you’ve worked at BEA, Oracle, VMware, and Cloudera, the world is going to see you as a middleware / database / infrastructure person and you will have trouble finding, for example, jobs at SaaS applications companies.  Be mindful of the positioning you are creating by virtue of the categories you work in.  The world does not see you as a generalist.
  • Boxes matter.  Like it or not and for better and for worse, Silicon Valley — the valley of innovation — is incredibly “in the box” when it comes to hiring.  Companies want to hire experienced people in known roles.  This means you need to be careful in managing your career because sometimes companies create unusual roles (e.g., chief of staff, certain CTO roles, certain VP individual contributor roles, various special project roles) that might leverage your strengths and meet your interests but end up damaging your resume.  While it can be fun to spend some time out of the box, be careful that you end up on no headhunters to-call list.  Put in reverse, how many people are going to to call a headhunter and say “get me a senior product manager out of Salesforce” vs. “get me a interdepartmental facilitator at Unicornia.”  Some new roles (e.g., sales productivity) get institutionalized and become “normal” over time.  Most don’t.
  • Take the time to network, but with the intent to do your job better (e.g., best practice sharing), not with the intent to find your next job.  If there’s no obvious “club” at which to do so, then make your own.  One of my CMOs called our board members for referrals and created a portfolio-company CMO club that met once/month to share best practices.   You’ll get both better connected and, more importantly, better at your job.
  • Don’t be too busy to learn.  Read books, attend webinars, and ask to attend executive executive programs.  (If you can get your company to pony up, the executive education programs offered by the Stanford Graduate School of Business are excellent.)
  • Make VCs money or go to Stanford.  To the extent you want work at and/or found startups, remember my (only half-joking) view of how VCs view people, below.  The moral is that one of the best opportunity-creators you can have is a VC for whom you’ve made money.  So get to know the VCs on your board if you can — and yes, don’t forget to make them money (and yourself some in the process).  Either that or go to Stanford.  Ideally, both.  :-)

vc people view

A Review of SalesHood by Elay Cohen

I recently completed SalesHood by my former Salesforce colleague Elay Cohen and wanted to do a quick book review in this post.

Net/net:  I think SalesHood, along with Predictable Revenue (by another former Salesforce leader Aaron Ross) are two of the best books out there on contemporary business-to-business high-technology sales. Between these two books, you can capture decades of valuable experience in building and leading sales teams (SalesHood) as well as in building “the machine” that drives opportunity creation for them (Predictable Revenue).

Over the past decade enterprise technology sales has changed radically – in fact, the only discipline that has changed more is marketing which has (happily) transformed from largely unaccountable black art to highly-accountable demand generation science.

At Salesforce Elay ran, among other things, arguably the best sales productivity programs in the business. As such, SalesHood contains not only a lot of great Salesforce best practices, but also a healthy dose of Salesforce culture. For example, Elay says to “start with values” – which is very aligned with the Salesforce culture and the V2MOM (vision, values, methods, obstacles, metrics) planning framework.

Overall, I would describe SalesHood as less ground-breaking and more best-practice-sharing. If you’ve somehow missed the changes in sales over the past decade (e.g., say you’re a rep at IBM or SAP), then the book is a must-read to catch you up with the state of the art. On the flip side, if you’ve been working at a leading startup, I’d still recommend SalesHood not so much as to introduce you to a slew of new ideas but so as to help you structure and organize them.

Some of Elay’s advice is sales motherhood and apple pie (e.g., always be hiring, compete with intensity, win as a team, it’s all about first-line sales management). Good sales people and sales managers can never get enough repetition of these basics and a book like SalesHood can be used to drive them into your culture and get everyone on the same page.

In other areas, Elay offers fresh takes on old problems. I particularly liked:

  • The sales huddle concept, frequent small team meetings to focus on key topics that arise during the quarter.
  • The general concept of more social/peer-led sales training. Death to death by corporate PowerPoint!
  • The chapter on story-telling, where the only twist I’d add is to challenge the customer during the exercise – the relevancy of a story is defined in the mind of the customer, not the salesrep.
  • Elay’s (and Barry Rhein’s) thoughts on curiosity and why it matters so much in sales.  Genuinely curious salespeople sell more – and get blind-sided less — than their non-inquisitive counterparts.

To wrap it up, even though I was familiar with many SalesHood concepts, I found the book a great synthesis of them, along with some great new concepts thrown in.

Short Video on the Host Analytics Mission

This is just a quick post to highlight a short video we made that answers three questions about Host Analytics:

  • What is our core mission at Host Analytics?
  • How is Host Analytics transforming the EPM market?
  • What’s in store for Host Analytics?

Here it is:

Host Analytics Raises $25M to Fuel Aggressive Growth

Last week we announced that we had successfully closed a $25M round of financing and received some pretty good coverage in the media, including this story in TechCrunch, this story in Talking Cloud, and this one in the Silicon Valley Business Journal.

In this post, I thought I’d offer a few thank-you’s and share a little perspective on the round.

First, the thank-you’s:

  • Thanks to our amazing customers who entrust us with helping them solve their financial planning, budgeting, forecasting, consolidation, and reporting challenges.  Without you, nothing else happens.
  • Thanks to our fantastic partners who help us deploy within customers, co-market with us, and refer us into new opportunities.
  • Thanks to the wonderful employees who constitute the Host Analytics team.  We have done amazing things in the past two years and will do even more amazing ones in the two years to come.
  • Thanks to our superb investors for having faith in the company, the market opportunity, and the team.  And a special thanks to our new investor Centerview Capital, who led the round and with whom we very excited to work to build a market-defining company.

In terms of perspective, here are some thoughts:

  • We believe that Host Analytics is the fastest-growing company in the cloud EPM space.  This year we will grow new subscriptions at over 120%.  This validates that the strategic and operational decisions we have made over the past two years have been correct, if not always obvious.
  • I am proud that we have driven this success by focusing on the customer.  While at least one competitor competes heavily on the basis of chest-thumping and corporate FUD, we have competed based on customer focus and on a consultative approach to solving business problems.  This isn’t easy to do — it requires both deep category knowledge and a strong constitution.  And  while we routinely get broad-sided, we do not let that distract us from our focus on solving the customer’s problem.  I often tell the team to forget the competition and follow the advice from the secret advocate in Disclosure:  “solve the problem.”
  • We have a huge opportunity before us to unite financial and operational planning.  Over the past decade, a lot of work that was traditionally done by the financial planning and analysis (FP&A) department, has silently moved outside finance and into the operations.  Salesops does sales forecasting, commission forecasting, territory management, and quota-setting.  Marketingops does marketing budgeting, lead forecasting, and pipeline coverage analysis.  Servciesops does services planning, forecasting, and margin analysis.  The good news is that businesses are more data-driven than ever.  The bad news is that all these teams are disconnected from finance and the financial planning system.  There is a big opportunity to bring this all back together and put the E (enterprise) back in EPM.  We are going to lead the market in pursuing that opportunity.

Thanks to everyone who has helped make our progress thus far possible.  I believe the next two years are going to be even better than the past two.

CFOs: More Strategic Than Ever

I was digging through my reading pile and found this about nine-month-old report by Accenture and Oracle entitled The CFO as Corporate Strategist by Donniel Schulman and David Axson of Accenture.  Those who follow Host Analytics might remember David Axson as he’s spoken at several of our user conferences.  (Note:  the 2015 conference is May 18-21 — save the date!)

The overall theme of the paper is that the traditional “bean counter” positioning of CFOs is as outdated as the hula hoop, with CFOs becoming more strategic over time, and partnering with the CEO to run the company.

Here’s one chart from the report that shows just that:

cfo influence

We definitely seeing this trend with our customers at Host Analytics.

As I’ve always said, “CEOs live in the future,” so if CFOs want to partner with them, they are going to de-emphasize a lot of their backwards-looking role and join their CEOs in the future.  This means automating and delegating backwards-looking functions like consolidations and reporting.  And it means getting more involved with both financial planning & analysis (FP&A) and their cousins in the various “ops” teams springing up around the organization — e.g., salesops — who also do lot of planning, modeling, and scenario building.

It Ain’t Easy Making Money in Open Source:  Thoughts on the Hortonworks S-1

It took me a week or so to get to it, but in this post I’ll take a dive into the Hortonworks S-1 filing in support of a proposed initial public offering (IPO) of their stock.

While Hadoop and big data are unarguably huge trends driving the industry and while the future of Hadoop looks very bright indeed, on reading the Hortonworks S-1, the reader is drawn to the inexorable conclusion that  it’s hard to make money in open source, or more crassly, it’s hard to make money when you give the shit away.

This is a company that,  in the past three quarters, lost $54M on $33M of support/services revenue and threw in $26M in non-recoverable (i.e., donated) R&D atop that for good measure.

Let’s take it top to bottom:

  • They have solid bankers: Goldman Sachs, Credit Suisse, and RBC are leading the underwriting with specialist support from Pacific Crest, Wells Fargo, and Blackstone.
  • They have an awkward, jargon-y, and arguably imprecise marketing slogan: “Enabling the Data-First Enterprise.”  I hate to be negative, but if you’re going to lose $10M a month, the least you can do is to invest in a proper agency to make a good slogan.
  • Their mission is clear: “to establish Hadoop as the foundational technology of the modern enterprise data architecture.”
  • Here’s their solution description: “our solution is an enterprise-grade data management platform built on a unique distribution of Apache Hadoop and powered by YARN, the next generation computing and resource management framework.”
  • They were founded in 2011, making them the youngest company I’ve seen file in quite some years. Back in the day (e.g., the 1990s) you might go public at age 3-5, but these days it’s more like age 10.
  • Their strategic partners include Hewlett-Packard, Microsoft, Rackspace, Red Hat, SAP, Teradata, and Yahoo.
  • Business model:  “consistent with our open source approach, we generally make the Hortonworks Data Platform available free of charge and derive the predominant amount of our revenue from customer fees from support subscription offerings and professional services.”  (Note to self:  if you’re going to do this, perhaps you shouldn’t have -35% services margins, but we’ll get to that later.)
  • Huge market opportunity: “According to Allied Market Research, the global Hadoop market spanning hardware, software and services is expected to grow from $2.0 billion in 2013 to $50.2 billion by 2020, representing a compound annual growth rate, or CAGR, of 58%.”  This vastness of the market opportunity is unquestioned.
  • Open source purists: “We are committed to serving the Apache Software Foundation open source ecosystem and to sharing all of our product developments with the open source community.”  This one’s big because while it’s certainly strategic and it certainly earns them points within the Hadoop community, it chucks out one of the better ways to make money in open source:  proprietary versions / extensions.  So, right or wrong, it’s big.
  • Headcount:  The company has increased the number of full-time employees from 171 at December 31, 2012 to 524 at September 30, 2014

Before diving into the financials, let me give readers a chance to review open source business models (Wikipedia, Kellblog) if they so desire, before making the (generally true but probably slightly inaccurate) assertion:  the only open source company that’s ever made money (at scale) is Red Hat.

Sure, there have been a few great exits.  Who can forget MySQL selling to Sun for $1B?  Or VMware buying SpringSource for $420M?  Or RedHat buying JBoss for $350M+?  (Hortonworks CEO Rob Bearden was involved in both of the two latter deals.)   Or Citrix buying XenSource for $500M?

But after those deals, I can’t name too many others.  And I doubt any of those companies was making money.

In my mind there are a two common things that go wrong in open source:

  • The market is too small. In my estimation open source compresses the market size by 10-20x.  So if you want to compress the $30B DBMS market 10x, you can still build several nice companies.  However, if you want to compress the $1B enterprise search market by 10x, there’s not much room to build anything.  That’s why there is no Red Hat of Lucene or Solr, despite their enormous popularity in search.    For open source to work, you need to be in a huge market.
  • People don’t renew. No matter which specific open source business model you’re using, the general play is to sell a subscription to <something> that complements your offering.  It might be a hardened/certified version of the open source product.  It might be additions to it that you keep proprietary forever or, in a hardcover/paperback analogy, roll back into the core open source projects with a 24 month lag.  It might be simply technical support.  Or, it might be “admission the club” as one open source CEO friend of mine used to say:  you get to use our extensions, our support, our community, etc.  But no matter what you’re selling, the key is to get renewals.  The risk is that the value of your extensions decreases over time and/or customers become self-sufficient.    This was another problem with Lucene.  It was so good that folks just didn’t need much help and if they did, it was only for a year or so.

So Why Does Red Hat work?

Red Hat uses a professional open source business model  applied to primarily two low-level infrastructure categories:  operating systems and later middleware.   As general rules:

  • The lower-level the category the more customers want support on it.
  • The more you can commoditize the layers below you, the more the market likes it. Red Hat does this for servers.
  • The lower-level the category the more the market actually “wants” it standardized in order to minimize entropy. This is why low-level infrastructure categories become natural monopolies or oligopolies.

And Red Hat set the right price point and cost structure.  In their most recent 10-Q, you can see they have 85% gross margins and about a 10% return on sales.  Red Hat nailed it.

But, if you believe this excellent post by Andreessen Horowitz partner Peter Levine, There Will Never Be Another Red Hat.  As part of his argument Levine reminds us that while Red Hat may be a giant among open source vendors, that among general technology vendors they are relatively small.  See the chart below for the market capitalization compared to some megavendors.

rhat small fish

Now this might give pause to the Hadoop crowd with so many firms vying to be the Red Hat of Hadoop.  But that hasn’t stopped the money from flying in.  Per Crunchbase, Cloudera has raised a stunning $1.2B in venture capital, Hortonworks has raised $248M, and MapR has raised $178M.  In the related Cassandra market, DataStax has raised $190M.  MongoDB (with its own open source DBMS) has raised $231M.  That’s about $2B invested in next-generation open source database venture capital.

While I’m all for open source, disruption, and next-generation databases (recall I ran MarkLogic for six years), I do find the raw amount of capital invested pretty crazy.   Yes, it’s a huge market today.  Yes, it’s exploding as do data volumes and the new incorporation of unstructured data.  But we will be compressing it 10-20x as part of open-source-ization.  And, given all the capital these guys are raising – and presumably burning (after all, why else would you raise it), I can assure you that no one’s making money.

Hortonworks certainly isn’t — which serves as a good segue to dive into the financials.  Here’s the P&L, which I’ve cleaned up from the S-1 and color-annotated.

horton pl

  •  $33M in trailing three quarter (T3Q) revenues ($41.5M in TTM, though not on this chart)
  • 109% growth in T3Q revenues
  • 85% gross margins on support
  • Horrific -35% gross margins on services which given the large relative size of the services business (43% of revenues) crush overall gross margins down to 34%
  • More scarily this calls into question the veracity of the 85% subscription gross margins — I recall reading in the S-1 that they current lack VSOE for subscription support which means that they’ve not yet clearly demonstrated what is really support revenue vs. professional services revenue.  [See footnote 1]
  • $26M in T3Q R&D expense.  Per their policy all that value is going straight back to the open source project which begs the question will they ever see return on it?
  • Net loss of $86.7M in T3Q, or nearly $10M per month

Here are some other interesting tidbits from the S-1:

  • Of the 524 full-time employee as of 9/30/14, there are 56 who are non-USA-based
  • CEO makes $250K/year in base salary cash compensation with no bonus in FY13 (maybe they missed plan despite strong growth?)
  • Prior to the offering CEO owns 6.8% of the stock, a pretty nice percentage, but he was a kind-of a founder
  • Benchmark owns 18.7%
  • Yahoo owns 19.6%
  • Index owns 9.5%
  • $54.9M cash burn from operations in T3Q, $6.1M per month
  • Number of support subscription customers has grown from 54 to 233 over the year from 9/30/13 to 9/30/14
  • A single customer represented went from 47% of revenues for the T3Q ending 9/30/13 down to 22% for the T3Q ending 9/30/14.  That’s a lot of revenue concentration in one customer (who is identified as “Customer A,” but who I believe is Microsoft based on some text in the risk factors.)

Here’s a chart I made of the increase in value in the preferred stock.  A ten-bagger in 3 years.

horton pref

One interesting thing about the prospectus is they show “gross billings,” which is an interesting derived metric that financial analysts use to try and determine bookings in a subscription company.  Here’s what they present:

horton billings

While gross billings is not a bad stab at bookings, the two metrics can diverge — primarily when the duration of prepaid contracts changes.  Deferred revenue can shoot up when sales sells longer prepaid contracts to a given number of customers as opposed to the same-length contract to more of them.  Conversely, if happy customers reduce prepaid contract duration to save cash in a downturn, it can actually help the vendor’s financial performance (they will get the renewals because the customer is happy and not discount in return for multi-year), but deferred revenue will drop as will gross billings.  In some ways, unless prepaid contract duration is held equal, gross billings is more of a dangerous metric than anything else.  Nevertheless Hortonworks is showing it as an implied metric of bookings or orders and the growth is quite impressive.

Sales and Marketing Efficiency

Let’s now look at sales and marketing efficiency, not using the CAC which is too hard to calculate for public companies but using JMP’s sales and marketing efficiency metric = gross profit [current] – gross profit [prior] / S&M expense [prior].

On this metric Hortonworks scores a 41% for the T3Q ended 9/30/14 compared to the same period in 2013.  JMP considers anything above 50% efficient, so they are coming in low on this metric.  However, JMP also makes a nice chart that correlates S&M efficiency to growth and I’ve roughly hacked Hortonworks onto it here:

JMP

I’ll conclude the main body of the post by looking at their dollar-based expansion rate.  Here’s a long quote from the S-1:

Dollar-Based Net Expansion Rate.    We believe that our ability to retain our customers and expand their support subscription revenue over time will be an indicator of the stability of our revenue base and the long-term value of our customer relationships. Maintaining customer relationships allows us to sustain and increase revenue to the extent customers maintain or increase the number of nodes, data under management and/or the scope of the support subscription agreements. To date, only a small percentage of our customer agreements has reached the end of their original terms and, as a result, we have not observed a large enough sample of renewals to derive meaningful conclusions. Based on our limited experience, we observed a dollar-based net expansion rate of 125% as of September 30, 2014. We calculate dollar-based net expansion rate as of a given date as the aggregate annualized subscription contract value as of that date from those customers that were also customers as of the date 12 months prior, divided by the aggregate annualized subscription contract value from all customers as of the date 12 months prior. We calculate annualized support subscription contract value for each support subscription customer as the total subscription contract value as of the reporting date divided by the number of years for which the support subscription customer is under contract as of such date.

This is probably the most critical section of the prospectus.  We know Hortonworks can grow.  We know they have a huge market.  We know that market is huge enough to be compressed 10-20x and still have room to create a a great company.  What we don’t know is:  will people renew?   As we discussed above, we know it’s one of the great risks of open source

Hortonworks pretty clearly answers the question with “we don’t know” in the above quote.  There is simply not enough data, not enough contracts have come up for renewal to get a meaningful renewal rate.  I view the early 125% calculation as a very good sign.  And intuition suggests that — if their offering is quality — that people will renew because we are talking low-level, critical infrastructure and we know that enterprises are willing to pay to have that supported.

# # #

Appendix

In the appendix below, I’ll include a few interesting sections of the S-1 without any editorial comments.

A significant portion of our revenue has been concentrated among a relatively small number of large customers. For example, Microsoft Corporation historically accounted for 55.3% of our total revenue for the year ended April 30, 2013, 37.8% of our total revenue for the eight months ended December 31, 2013 and 22.4% of our total revenue for the nine months ended September 30, 2014. The revenue from our three largest customers as a group accounted for 71.0% of our total revenue for the year ended April 30, 2013, 50.5% of our total revenue for the eight months ended December 31, 2013 and 37.4% of our total revenue for the nine months ended September 30, 2014. While we expect that the revenue from our largest customers will decrease over time as a percentage of our total revenue as we generate more revenue from other customers, we expect that revenue from a relatively small group of customers will continue to account for a significant portion of our revenue, at least in the near term. Our customer agreements generally do not contain long-term commitments from our customers, and our customers may be able to terminate their agreements with us prior to expiration of the term. For example, the current term of our agreement with Microsoft expires in July 2015, and automatically renews thereafter for two successive twelve-month periods unless terminated earlier. The agreement may be terminated by Microsoft prior to the end of its term. Accordingly, the agreement with Microsoft may not continue for any specific period of time.

# # #

We do not currently have vendor-specific objective evidence of fair value for support subscription offerings, and we may offer certain contractual provisions to our customers that result in delayed recognition of revenue under GAAP, which could cause our results of operations to fluctuate significantly from period-to-period in ways that do not correlate with our underlying business performance.

In the course of our selling efforts, we typically enter into sales arrangements pursuant to which we provide support subscription offerings and professional services. We refer to each individual product or service as an “element” of the overall sales arrangement. These arrangements typically require us to deliver particular elements in a future period. We apply software revenue recognition rules under U.S. generally accepted accounting principles, or GAAP. In certain cases, when we enter into more than one contract with a single customer, the group of contracts may be so closely related that they are viewed under GAAP as one multiple-element arrangement for purposes of determining the appropriate amount and timing of revenue recognition. As we discuss further in “Management’s Discussion and Analysis of Financial Condition and Results of Operations—Critical Accounting Policies and Estimates—Revenue Recognition,” because we do not have VSOE for our support subscription offerings, and because we may offer certain contractual provisions to our customers, such as delivery of support subscription offerings and professional services, or specified functionality, or because multiple contracts signed in different periods may be viewed as giving rise to multiple elements of a single arrangement, we may be required under GAAP to defer revenue to future periods. Typically, for arrangements providing for support subscription offerings and professional services, we have recognized as revenue the entire arrangement fee ratably over the subscription period, although the appropriate timing of revenue recognition must be evaluated on an arrangement-by-arrangement basis and may differ from arrangement to arrangement. If we are unexpectedly required to defer revenue to future periods for a significant portion of our sales, our revenue for a particular period could fall below  our expectations or those of securities analysts and investors, resulting in a decline in our stock price

 # # #

We generate revenue by selling support subscription offerings and professional services. Our support subscription agreements are typically annual arrangements. We price our support subscription offerings based on the number of servers in a cluster, or nodes, data under management and/or the scope of support provided. Accordingly, our support subscription revenue varies depending on the scale of our customers’ deployments and the scope of the support agreement.

 Our early growth strategy has been aimed at acquiring customers for our support subscription offerings via a direct sales force and delivering consulting services. As we grow our business, our longer-term strategy will be to expand our partner network and leverage our partners to deliver a larger proportion of professional services to our customers on our behalf. The implementation of this strategy is expected to result in an increase in upfront costs in order to establish and further cultivate such strategic partnerships, but we expect that it will increase gross margins in the long term as the percentage of our revenue derived from professional services, which has a lower gross margin than our support subscriptions, decreases.

 # # #

Deferred Revenue and Backlog

Our deferred revenue, which consists of billed but unrecognized revenue, was $47.7 million as of September 30, 2014.

Our total backlog, which we define as including both cancellable and non-cancellable portions of our customer agreements that we have not yet billed, was $17.3 million as of September 30, 2014. The timing of our invoices to our customers is a negotiated term and thus varies among our support subscription agreements. For multiple-year agreements, it is common for us to invoice an initial amount at contract signing followed by subsequent annual invoices. At any point in the contract term, there can be amounts that we have not yet been contractually able to invoice. Until such time as these amounts are invoiced, we do not recognize them as revenue, deferred revenue or elsewhere in our consolidated financial statements. The change in backlog that results from changes in the average non-cancelable term of our support subscription arrangements may not be an indicator of the likelihood of renewal or expected future revenue, and therefore we do not utilize backlog as a key management metric internally and do not believe that it is a meaningful measurement of our future revenue.

 # # #

We employ a differentiated approach in that we are committed to serving the Apache Software Foundation open source ecosystem and to sharing all of our product developments with the open source community. We support the community for open source Hadoop, and employ a large number of core committers to the various Enterprise Grade Hadoop projects. We believe that keeping our business model free from architecture design conflicts that could limit the ultimate success of our customers in leveraging the benefits of Hadoop at scale is a significant competitive advantage.

 # # #

International Data Corporation, or IDC, estimates that data will grow exponentially in the next decade, from 2.8 zettabytes, or ZB, of data in 2012 to 40 ZBs by 2020. This increase in data volume is forcing enterprises to upgrade their data center architecture and better equip themselves both to store and to extract value from vast amounts of data. According to IDG Enterprise’s Big Data Survey, by late 2014, 31% of enterprises with annual revenues of $1 billion or more expect to manage more than one PB of data. In comparison, as of March 2014 the Library of Congress had collected only 525 TBs of web archive data, equal to approximately half a petabyte and two million times smaller than a zettabyte.

# # #

Footnotes:

[1]  Thinking more about this, while I’m not an accountant, I think the lack of VSOE has the following P&L impact:  it means that in contracts that mix professional services and support they must recognize all the revenue ratably over the contract.  That’s fine for the support revenue, but it should have the effect of pushing out services revenue, artificially depressing services gross margins.  Say, for example you did a $240K that was $120K of each.  The support should be recognized at $30K/quarter.  However, if the consulting is delivered in the first six months it should be delivered at $60K/quarter for the first and second quarters and $0 in the third and fourth.  Since, normally, accountants will take the services costs up-front this should have the effect of hurting services by taking the costs as delivered but by the revenue over a longer period.

[2] See here for generic disclaimers and please note that in the past I have served as an advisor to MongoDB