Category Archives: Silicon Valley

The SaaS Rule of 40

After the SaaSacre of early 2016, investors generally backed off a growth-at-all-costs mindset and started to value SaaS companies using an “appropriate” balance of growth and profitability.  The question then became, what’s appropriate?  The answer was:  the rule of 40 [1].

What’s the rule of 40?  Growth rate + profit should be greater than or equal to 40%.

There are a number of options for deciding what to use to represent growth (e.g., ARR) and profit (e.g., EBITDA, operating margin). For public companies it usually translates to revenue growth rate and free cash flow margin.

It’s important to understand that such “rules” are not black and white.  As we’ll see in a minute, lots of companies deviate from the rule of 40.  The right way to think about these rules of thumb is as predictors.  Back in the day, what best predicted the value of a SaaS company?  Revenue growth — without regard for margin.  (In fact, often inversely correlated to margin.)  When that started to break down, people started looking for a better independent variable.  The answer to that search was the rule of 40 score.

Let’s examine a few charts courtesy of the folks at Pacific Crest and as presented at the recent, stellar Zuora CFO Forum, a CFO gathering run alongside their Subscribed conference.

rule-of-40

This scatter chart plots the two drivers of the rule of 40 score against each other, colors each dot with the company’s rule of 40 score, and adds a line that indicates the rule of 40 boundary.  42% of public SaaS companies, and 77% of public SaaS market cap, is above the rule of 40 line.

As a quick demonstration of the exception-to-every-rule principle, Tintri recently went public off 45% growth with -81% operating margins, [2] reflecting a rule of 40 score of -36%, and a placement that would be off the chart (in the underneath sense) even if corrected for non-cash expenses.

For those interested in company valuations, the more interesting chart is this one.

rule of 40 valuation.PNG

This chart plots rule of 40 score on the X axis, valuation multiple on the Y axis, and produces a pretty good regression line the shows the relationship between the two.  In short, the rule of 40 alone explains nearly 50% of SaaS company valuation.  I believe that outliers fall into one of two categories:

  • Companies in a strategic situation that explains the premium or discount relative to the model — e.g., the premium for Cloudera’s strong market position in the Hadoop space.
  • Companies whose valuations go non-linear at the high end due to scarcity — e.g., Veeva.

Executives and employees at startups should understand [3] the rule of 40 as it explains the general tendency of SaaS companies to focus on a balance of growth and profitability as opposed to a growth at all costs strategy that was more popular several years back.  Ignore the rule of 40 at your peril.

Notes

[1] While the Rule of 40 concept preceded the SaaSacre, I do believe that the SaaSacre was the wake-up call that made more investors and companies pay attention to.

[2] Using operating margin here somewhat lazily as I don’t want to go find unlevered free cash flow margin, but I don’t think it materially changes the point.

[3] Other good rule of 40 posts are available from:  Tomasz Tungaz, Sundeep Peechu, and Jeff Epstein and Josh Harder.

Detecting and Eliminating the Rolling Hairballs in your Sales Pipeline

Quick:  what’s the biggest deal in this quarter’s sales pipeline?  Was that the biggest deal in last quarter’s pipeline?  How about the quarter before?  Do you have deals in your pipeline older than your children?

If you’re answering yes to these questions, then you’re probably dealing with “rolling hairballs” in your pipeline.  Rolling hairballs are bad:

  • They exaggerate the size of the pipeline.
  • They distort coverage and conversion ratios.
  • They mess up expected-value forecasts, like a forecast-category or stage-weighted sales forecast.

Maybe they’re real deals; maybe they’re figments of a rep’s imagination.  But, if you’re not careful, they pollute your pipeline and your metrics.

Let’s define a rolling hairball

A rolling hairball is a typically large opportunity that sits in your current-quarter pipeline every quarter, with a close date that slips every quarter.  At 2 quarters it’s a suspected rolling hairball; at 3 or more quarters it’s a confirmed one.

Rolling Hairball Detection

The first thing you need to do is find rolling hairballs.  They’re tricky because salesreps always swear they’re real deals that are supposed to finally close this quarter.  What makes rolling hairballs obvious is their ever-sliding close dates.  What makes them dangerous is their size (including an accumulation of them that aggregate to a material fraction of the pipeline).

If you want to find rolling hairballs, look for opportunities in the current-quarter pipeline that were also in last-quarter’s pipeline.  That will find numerous bona fide slipped deals, but it will also light-up potential rolling hairballs.  To determine if an opportunity is  a rolling hairball, for sure, you can do one of two things:

  • See if it also appeared in the current-quarter pipeline in any quarters prior to the previous one.
  • Look at its stage or forecast category.  If either of those suggest it won’t be closing this quarter, it’s another big hairball indicator.

The more sophisticated way to find them is to examine “stuck opportunity” reports that light-up deals that are moving through pipeline stages too slowly compared to your norms.

But typically, the hairball is a big opportunity hiding in plain sight.  You know it was in last quarter’s pipeline and the quarter before that.  You’ve just been deluded into believing it’s not a hairball.

Fixing Rolling Hairballs

There are two ways to fix rolling hairballs:

  • Fix the close date.  Reps are subtly incented to put deals in the current quarter (e.g., to show they’re working on something, to show they might bring in some big sales this quarter). The manager needs to get on the phone with the customer and, after having verified it’s a real opportunity, get the real timeframe in which it might close.  Assigning a realistic close date to the opportunity makes your pipeline more real and reminds the rep that they need to be working on other shorter-term opportunities as well.  (There is no mid-term if you fail enough in the short term.)  The deal will still remain in the all-quarters pipeline, but it won’t always be in the current-quarter pipeline, ever-sliding, and distorting metrics and ratios.

 

  • Fix the size. While a realistic close date is the best solution, what makes rolling hairballs dangerous is their size.  So, if the salesrep really believes it’s a current-quarter opportunity, you can either reduce its size or split it into two opportunities (particularly if that’s a possible outcome), a small one in the current quarter along with an upsell in the future.  Note that this approach can be dangerous, with lots of little hairball-lets flying below radar, so you should only try if it you’re sure your salesops team can produce the reports to find them and if you believe it reflects real customer buying patterns.

Don’t let rolling hairballs pollute your pipeline metrics and ratios.  Admit they exist, find them, and fix them.  Your sales and sales forecasting will be more consistent as a result.

The Strategy Compiler: How To Avoid the “Great” Strategy You Couldn’t Execute

Few phrases bother me more than this one:

“I know it didn’t work, but it was a great strategy.  We just didn’t have the resources to execute it.”

Huh.  Wait minute.  If you didn’t have the resources to execute it, then it wasn’t a great strategy.  Maybe it was a great strategy for some other company that could have applied the appropriate resources.  But it wasn’t a great strategy for you.  Ergo, it wasn’t a great strategy.  QED.

I learned my favorite definition of strategy at a Stanford executive program I attended a few years back.  Per Professor Robert Burgelman, author of Strategy is Destiny, strategy is simply “the plan to win.”  Which begets an important conversation about the definition of winning.  In my experience, defining winning is more important than making the plan, because if everyone is focused on taking different hills, any resultant strategy will be a mishmash of plans to support different objectives.

But, regardless of your company’s definition of winning, I can say that any strategy you can’t execute definitionally won’t succeed and is ergo a bad strategy.

It sounds obvious, but nevertheless a lot of companies fall into this trap.  Why?

  • A lack of focus.
  • A failure to “compile” strategy before executing it.

Focus:  Think Small to Grow Big

Big companies that compete in lots of broad markets almost invariably didn’t start out that way.

BusinessObjects started out focused on the Oracle financials installed base.  Facebook started out on Harvard students, then Ivy league students.  Amazon, it’s almost hard to remember at this point, started out in books.  Salesforce started out in SMB salesforce automation.  ServiceNow on IT ticket management.  This list goes on and on.

Despite the evidence and despite the fame Geoffrey Moore earned with Crossing the Chasm, focus just doesn’t come naturally to people.  The “if I could get 1% share of a $10B market, I’d be a $100M company” thought pattern is just far too common. (And investors often accidentally reinforce this.)

The fact is you will be more dominant, harder to dislodge, and probably more profitable if, as a $100M company, you control 30% of a $300M target as opposed to 1% of a $10B target.

So the first reason startups make strategies they can’t execute is because they forget to focus.  They aim too broadly. They sign up for too much.  The forget that strategy should be sequence of actions over time.  Let’s start with Harvard. Then go Ivy League.  Then go Universities in general.  Then go everyone.

Former big company executives often compound the problem.  They’re not used to working with scarce resources and are more accustomed to making “laundry list” strategies that check all the boxes than making focused strategies that achieve victory step by step.

A Failure to Compile Strategy Before Execution

The second reason companies make strategies they can’t execute is that they forget a critical step in the planning process that I call the strategy compiler.  Here’s what I think a good strategic planning process looks like.

  • Strategy offsite. The executive team spends a week offsite focused on situation assessment and strategy.  The output of this meeting should be (1) a list of strategic goals for the company for the following year and (2) a high-level financial model that concretizes what the team is trying to accomplish over the next three years.  (With an eye, at a startup, towards cash.)

 

  • First round budgeting. Finance issues top-down financial targets.  Executives who own the various objectives make strategic plans for how to attain them.  The output of this phase is (1) first-draft consolidated financials, (2) a set of written strategies along with proposed organizational structures and budgets for attaining each of the company’s ten strategic objectives.

 

  • Strategy compilation, resources. The team meets for a day to review the consolidated plans and financials. Invariably there are too many objectives, too much operating expense, and too many new hires. The right answer here is to start cutting strategic goals.  The wrong answer is to keep the original set of goals and slash the budget 20% across the board.  It’s better to do 100% of 8 strategic initiatives than do 80% of 10.

 

  • Strategy compilation, skills. The more subtle assessment that must happen is a sanity check on skills and talent.  Do your organization have the competencies and do your people have the skills to execute the strategic plans?  If a new engineering project requires the skills of 5 founder-level, Stanford computer science PHDs who each would want 5% of a company, you are simply not going to be able to hire that kind of talent as regular employees. (This is one reason companies do “acquihires”).  The output of this phase is a presumably-reduced set of strategic goals.

 

  • Second round budgeting. Executives to build new or revised plans to support the now-reduced set of strategic goals.

 

  • Strategy compilation. You run the strategy compiler again on the revised plan — and iterate until the strategic goals match the resources and the skills of the proposed organization.

 

  • Board socialization. As you start converging via the strategy compiler you need to start working with the board to socialize and eventually sell the proposed operating plan.  (This process could easily be the subject of another post.)

 

If you view strategy as the plan to win, then successful strategies include only those strategies that your organization can realistically execute from both a resources and skills perspective.  Instead of doing a single-pass process that moves from strategic objectives to budgets, use an iterative approach with a strategy compiler to ensure your strategic code compiles before you try to execute it.

If you do this, you’ll increase your odds of success and decrease the odds ending up in the crowded section of the corporate graveyard where the epitaphs all read:

Here Lies a Company that Had a “Great” Strategy  It Had No Chance of Executing

How To Get Your Startup a Halo

How would you like your startup to win deals not only when you win a customer evaluation, but when you tie — and even sometimes when you lose?

That sounds great.  But is it even possible?  Amazingly, yes — but you need have a halo effect working to your advantage.  What is a halo effect?  Per Wikipedia,

The halo effect is a cognitive bias in which an observer’s overall impression of a person, company, brand, or product influences the observer’s feelings and thoughts about that entity’s character or properties

There’s a great, must-read book (The Halo Effect) on the how this and eight other related effects apply in business.  The book is primarily about how the business community makes incorrect attributions about “best practices” in culture, leadership, values, and process that are subsequent to — but were not necessarily drivers of — past performance.

I know two great soundbites that summarize the phenomenon of pseudo-science in business:

  • All great companies have buildings.” Which comes from the (partly discredited) Good To Great that begins with the observation that in their study cohort of top-performing companies that all of them had buildings — and thus that simply looking for commonalities among top-performing companies was not enough; you’d have to look for distinguishing factors between top and average performers.
  • “If Marc Benioff carried a rabbit’s foot, would you?”  Which comes from a this Kellblog post where I make the point that blindly copying the habits of successful people will not replicate their outcome and, with a little help from Theodore Levitt, that while successful practitioners are intimately familiar with their own beliefs and behaviors, that they are almost definitionally ignorant of which ones helped, hindered, or were irrelevant to their own success.

Now that’s all good stuff and if you stop reading right here, you’ll hopefully avoid falling for pseudo-science in business.  That’s important.  But it misses an even bigger point.

Has your company ever won (or lost) a deal because of:

  • Perceived momentum?
  • Analyst placement on a quadrant or other market map?
  • Perceived market leadership?
  • Word of mouth as the “everyone’s using it” or “next thing” choice?
  • Perceived hotness?
  • Vibe at your events or online?
  • A certain feeling or je ne sais quoi that you were more (or less) preferred?
  • Perceived vision?

If yes, you’re seeing halo effects at work.

Halo effects are real.  Halo effects are human nature.  Halo effects are cognitive biases that tip the scales in your favor.  So the smart entrepreneur should be thinking:  how do I get one for my company?  (And the smart customer, how can I avoid being over-influenced by them?  See bottom of post.)

In Silicon Valley, a number of factors drive the creation of halo effects around a company.  Some of these are more controllable than others.  But overall, you should be thinking about how you can best combine these factors into an advantage.

  • Lineage, typically in the form of previous success at a hot company (e.g., Reid Hoffman of PayPal into LinkedIn, Dave Duffield of PeopleSoft into Workday).  The implication here (and a key part of halo effects) is that past success will lead to future success, as it sometimes does.  This one’s hard to control, but ceteris paribus, co-founding (even somewhat ex post facto) a company with an established entrepreneur will definitely help in many ways, including halo effects.
  • Investors, in one of many forms:  (1) VC’s with a strong brand name (e.g., Andreessen Horowitz), (2) specific well known venture capitalists (e.g., Doug Leone), (3) well known individual investors (e.g., Peter Thiel), and to a somewhat lesser extent (4) visible and/or famous angels (e.g., Ashton Kutcher). The implication here is obvious, that the investor’s past success is an indication of your future success.  There’s no doubt that strong investors help build halo effects indirectly through reputation; in cases they can do so directly as well via staff marketing partners designed to promote portfolio companies.
  • Investment.  In recent years, simply raising a huge amount of money has been enough to build a significant halo effect around a company, the implication being that “if they can raise that much money, then there’s got to be a pony in there somewhere.” Think Domo’s $690M or Palantir’s $2.1B.   The media loves these “go big or go home” stories and both media and customers seem to overlook the increased risk associated with staggering burn rates, the waste that having too much capital can lead to, the possibility that the investors represent “dumb money,” and the simple fact that “at scale” these businesses are supposed to be profitable.  Nevertheless, if you have the stomach, the story, and the connections to raise a dumbfounding amount of capital, it can definitely build a halo around your company.  For now, at least.
  • Valuation.  Even as the age of the unicorn starts to wane, it’s undeniable that in recent years, valuation has been a key tool to generate halos around a company.  In days of yore, valuation was a private matter, but as companies discovered they could generate hype around valuation, they started to disclose it, and thus the unicorn phenomenon was born.  As unicorn status became increasingly de rigeur, things got upside-down and companies started trading bad terms (e.g., multiple liquidation preferences, redemption rights) in order to get $1B+ (unicorn) post-money valuations.  That multiplying the price of a preferred share with superior rights by a share count that includes the number of lesser preferred and common shares is a fallacious way to arrive at a company valuation didn’t matter.  While I think valuation as a hype driver may lose some luster as many unicorns are revealed as horses in party hats (e.g., down-round IPOs), it can still be a useful tool.  Just be careful about what you trade to get it.  Don’t sell $100M worth of preferred with a ratcheted 2 moving to 3x liquidation preference — but what if someone would buy just $5M worth on those terms.  Yes, that’s a total hack, but so is the whole idea of multiplying a preferred share price times the number of common shares.  And it’s far less harmful to the company and the common stock.  Find your own middle ground / peace on this issue.
  • Growth and vision.  You’d think that industry watchers would look at a strategy and independently evaluate its merits in terms of driving future growth.  But that’s not how it works.  A key part of halo effects is misattribution of practices and performance.  So if you’ve performed poorly and have an awesome strategy, it will overlooked — and conversely.  Sadly, go-forward strategy is almost always viewed through the lens of past performance, even if that performance were driven by a different strategy or affected positively or negatively by execution issues unrelated to strategy.  A great story isn’t enough if you want to generate a vision halo effect.  You’re going to need to talk about growth numbers to prove it.  (That this leads to a pattern of private companies reporting inflated or misleading numbers is sadly no surprise.)  But don’t show up expecting to wow folks with vision. Ultimately, you’ll need to wow them with growth — which then provokes interest in vision.
  • Network.  Some companies do a nice and often quiet job of cultivating friends of the company who are thought leaders in their areas.  Many do this through inviting specific people to invest as angels.  Some do this simply through communications.  For example, one day I received an email update from Vik Singh clearly written for friends of Infer. I wasn’t sure how I got on the list, but found the company interesting and over time I got to know Vik (who is quite impressive) and ended up, well, a friend of Infer.  Some do this through advisory boards, both formal and informal.  For example, I did a little bit of advising for Tableau early on and later discovered a number of folks in my network who’d done the same thing.  The company benefitted by getting broad input on various topics and each of us felt like we were friends of Tableau.  While sort of thing doesn’t generate the same mainstream media buzz as a $1B valuation, it is a smart influencer strategy that can generate fans and buzz among the cognoscenti who, in theory at least, are opinion leaders in their chosen areas.

Before finishing the first part of this post, I need to provide a warning that halo effects are both powerful and addictive.  I seem to have a knack for competing against companies pursuing halo-driven strategies and the pattern I see typically runs like this.

  • Company starts getting some hype off good results.
  • Company starts saying increasingly aggressive things to build off the hype.
  • Analysts and press reward the hype with strong quadrant placements and great stories and blogs.
  • Company puts itself under increasing pressure to produce numbers that support the hype.

And then one of three things happens:

  1. The company continues delivering strong results and all is good, though the rhetoric and vision gets more unrelated to the business with each cycle.
  2. The company stops delivering results and is downgraded from hot-list to shit-list in the minds of the industry.
  3. The company cuts the cord with reality and starts inflating results in order to sustain the hype cycle and avoid outcome #2 above.  The vision inflates as aggressively as the numbers.

I have repeatedly had to compete against companies where claims/results were inflated to “prove” the value of bad/ordinary strategies to impress industry analysts to get strong quadrant positions to support broader claims of vision and leadership to drive more sales to inflate to even greater claimed results.  Surprisingly, I think this is usually done more in the name of ego than financial gain, but either way the story ends the same way — in terminations, lawsuits and, in one case, a jail sentence for the CEO.

Look, there are valid halo-driven strategies out there and I encourage you to try and use them to your company’s advantage — just be very careful you don’t end up addicted to halo heroin.  If you find yourself wanting to do almost anything to sustain the hype bubble, then you’ll know you’re addicted and headed for trouble.

The Customer View

Thus far, I’ve written this post entirely from the vendor viewpoint, but wanted to conclude by switching sides and offering customers some advice on how to think about halo effects in choosing vendors.   Customers should:

  • Be aware of halo effects.  The first step in dealing with any problem is understanding it exists. While supposedly technical, rational, and left-brained, technology can be as arbitrary as apparel when it comes to fashion.  If you’re evaluating vendors with halos, realize that they exist for a reason and then go understand why.  Are those drivers relevant — e.g., buying HR from Dave Duffield seems a reasonable idea.  Or are they spurious —  e.g., does it really matter that one board member invested in Facebook?  Or are they actually negative — e.g., if the company has raised $300M how crazy is their burn rate, what risk does that put on the business, and how focused will they stay on you as a customer and your problem as a market?
  •  Stay focused on your problem.  I encourage anyone buying technology to write down their business problems and high-level technology requirements before reaching out to vendors.  Hyped vendors are skilled at “changing the playing field” and trained to turn their vision into your (new) requirements.  While there certainly are cases where vendors can point out valid new requirements, you should periodically step back and do a sanity check:  are you still focused on your problem or have you been incrementally moved to a different, or greatly expanded one.  Vision is nice, but you won’t be around solve tomorrow’s problems if you can’t solve today’s.
  • Understand that industry analysts are often followers, not leaders.  If a vendor is showing you analyst support for their strategy, you need to figure out if the analyst is endorsing the strategy because of the strategy’s merits or because of the vendor’s claimed prior performance.  The latter is the definition of a halo effect and in a world full of private startups where high-quality analysts are in short supply, it’s easy to find “research” that effectively says nothing more than “this vendor is a leader because they say they’re performing really well and/or they’ve raised a lot of money.” That doesn’t tell you anything you didn’t know already and isn’t actually an independent source of information.  They are often simply amplifiers of the hype you’re already hearing.
  • Enjoy the sizzle; buy the steak.  Hype king Domo paid Alec Baldwin to make some (pretty pathetic) would-be viral videos and had Billy Beane, Flo Rida, Ludacris, and Marshawn Lynch at their user conference.  As I often say, behind any “marketing genius” is an enormous marketing budget, and that’s all you’re seeing — venture capital being directly converted into hype.  Heck, let them buy you a ticket to the show and have a great time.  Just don’t buy the software because of it — or because of the ability to invest more money in hand-grooming a handful of big-name references.  Look to meet customers like you, who have spent what you want to spend, and see if they’re happy and successful.  Don’t get handled into meeting other customers only at pre-arranged meetings.  Walk the floor and talk to regular people.  Find out how many are there for the show, or because they’re actual successful users of the software.
  • Dive into detail on the proposed solution.  Hyped vendors will often try to gloss over solutions and sell you the hype (e.g., “of course we can solve your problem, we’ve got the most logos, Gartner says we’re the leader, there’s an app for that.”)  What you need is a vendor who will listen to your problem, discuss it with you intelligently, and provide realistic estimates on what it takes to solve it.  The more willing they are to do that, the better off you are.  The more they keep talking about the founder’s escape from communism, the pedigree of their investors, their recent press coverage, or the amount of capital they’ve raised, the more likely you are to end up high and dry.  People interested in solving your problem will want to talk about your problem.
  • Beware the second-worst outcome:  the backwater.  Because hyped vendors are actually serving Sand Hill Road and/or Wall Street more than their customers, they pitch broad visions and huge markets in order to sustain the halo.  For a customer, that can be disastrous because the vendor may view the customer’s problems as simply another lily pad to jump off on the path to success.  The second-worst outcome is when you buy a solution and then vendor takes your money and invests it in solving other problems.  As a customer, you don’t want to marry your vendor’s fling.  You want to marry their core.  For startups, the pattern is typically over-expansion into too many things, getting in trouble, and then retracting hard back into the core, abandoning customers of the new, broader initiatives.  The second-worst outcome is when you get this alignment wrong and end up in a backwater or formerly-strategic area of your supplier’s strategy.
  • Avoid the worst outcome:  no there there.  Once in awhile, there is no “there there” behind some very hyped companies despite great individual investors, great VCs, strategic alliances, and a previously experienced team.  Perhaps the technology vision doesn’t pan out, or the company switches strategies (“pivots”) too often.  Perhaps the company just got too focused on its hype and not on it customers.  But the worst outcome, while somewhat rare, is when a company doesn’t solve its advertised problem. They may have a great story, a sexy demo, and some smart people — but what they lack is a core of satisfied customers solving the problem the company talks about.  In EPM, with due respect and in my humble opinion, Tidemark fell into this category, prior to what it called a “growth investment” and what sure seemed to me like a (fire) sale, to Marlin Equity Partners.  Customers need to watch out for these no-there-there situations and the best way to do that is taking strong dose of caveat emptor with a nose for “if it sounds too good to be true, then it might well possibly be.”

Do You Want to be Judged on Intentions or Results?

It was early in my career, maybe 8 years in, and I was director of product marketing at a startup.  One day, my peer, the directof of marketing programs hit me with this in an ops review meeting:

You want to be judged on intentions, not results.

I recall being dumbfounded at the time.  Holy cow, I thought.  Is he right?  Am I standing up arguing about mitigating factors and how things might have been when all the other people in the room were thinking only about black-and-white results?

It was one of those rare phrases that really stuck with me because, among other reasons, he was so right.  I wasn’t debating whether things happened or not.  I wasn’t making excuses or being defensive.  But I was very much judging our performance in the theoretical, hermetically sealed context of what might have been.

Kind of like sales saying a deal slipped instead of did not close.   Or marketing saying we got all the MQLs but didn’t get the requisite pipeline.  Or alliances saying that we signed up the 4 new partners, but didn’t get the new opportunities that were supposed to come with them.

Which phrase of the following sentence matters more — the first part or the second?

We did what we were supposed to, but it didn’t have the desired effect.

We would have gotten the 30 MQLS from the event if it hadn’t snowed in Boston.  But who decided to tempt fate by doing a live event in Boston in February?  People who want to be judged on intentions think about the snowstorm; people who want to be judged on results think about the MQLs.

People who want to judged on intentions build in what they see as “reasons” (which others typically see as “excuses”) for results not being achieved.

I’m six months late hiring the PR manager, but that’s because it’s hard to find great PR people right now.  (And you don’t want me to hire a bad one, do you?)

No, I don’t want you to hire a bad one.  I want you to hire a great one and I wanted you to hire them 6 months ago.  Do you think every other PR manager search in the valley took 6 months more than plan?  I don’t.

Fine lines exist here, no doubt.  Sometimes reasons are reasons and sometimes they are actually excuses.  The question isn’t about any one case.  It’s about, deep down, are you judging yourself by intentions or results?

You’d be surprised how many otherwise very solid people get this one thing wrong — and end up career-limited as a result.

Kellblog’s 2017 Predictions  

New Year’s means three things in my world:  (1) time to thank our customers and team at Host Analytics for another great year, (2) time to finish up all the 2017 planning items and approvals that we need to get done before the sales kickoff (including the one most important thing to do before kickoff), and time to make some predictions for the coming year.

Before looking at 2017, let’s see how I did with my 2016 predictions.

2016 Predictions Review

  1. The great reckoning begins. Correct/nailed.  As predicted, since most of the bubble was tied up in private companies owned by private funds, the unwind would happen in slow motion.  But it’s happening.
  2. Silicon Valley cools off a bit. Partial.  While IPOs were down, you couldn’t see the cooling in anecdotal data, like my favorite metric, traffic on highway101.
  3. Porter’s five forces analysis makes a comeback. Partial.  So-called “momentum investing” did cool off, implying more rational situation analysis, but you didn’t hear people talking about Porter per se.
  4. Cyber-cash makes a rise. CorrectBitcoin more doubled on the year (and Ethereum was up 8x) which perversely reinforced my view that these crypto-currencies are too volatile — people want the anonymity of cash without a highly variable exchange rate.  The underlying technology for Bitcoin, blockchain, took off big time.
  5. Internet of Things goes into trough of disillusionment. Partial.  I think I may have been a little early on this one.  Seems like it’s still hovering at the peak of inflated expectations.
  6. Data science rises as profession. Correct/easy.  This continues inexorably.
  7. SAP realizes they are a complex enterprise application company. Incorrect.  They’re still “running simple” and talking too much about enabling technology.  The stock was up 9% on the year in line with revenues up around 8% thus far.
  8. Oracle’s cloud strategy gets revealed – “we’ll sell you any deployment model you want as long as your annual bill goes up.”  Partial.  I should have said “we’ll sell you any deployment model you want as long as we can call it cloud to Wall St.”
  9. Accounting irregularities discovered at one or more unicorns. Correct/nailed.  During these bubbles the pattern always repeats itself – some people always start breaking the rules in order to stand out, get famous, or get rich.  Fortune just ran an amazing story that talks about the “fake it till you make it” culture of some diseased startups.
  10. Startup workers get disappointed on exits. Partial.  I’m not aware of any lawsuits here but workers at many high flyers have been disappointed and there is a new awareness that the “unicorn party” may be a good thing for founders and VCs, but maybe not such a good thing for rank-and-file employees (and executive management).
  11. The first cloud EPM S-1 gets filed. Incorrect.  Not yet, at least.  While it’s always possible someone did the private filing process with the SEC, I’m guessing that didn’t happen either.
  12. 2016 will be a great year for Host Analytics. Correct.  We had a strong finish to the year and emerged stronger than we started with over 600 great customers, great partners, and a great team.

Now, let’s move on to my predictions for 2017 which – as a sign of the times – will include more macro and political content than usual.

  1. The United States will see a level of divisiveness and social discord not seen since the 1960s. Social media echo chambers will reinforce divisions.  To combat this, I encourage everyone to sign up for two publications/blogs they agree with and two they don’t lest they never again hear both sides of an issue. (See map below, coutesy of Ninja Economics, for help in choosing.)  On an optimistic note, per UCSD professor Lane Kenworthy people aren’t getting more polarized, political parties are.

news

  1. Social media companies finally step up and do something about fake news. While per a former Facebook designer, “it turns out that bullshit is highly engaging,” these sites will need to do something to filter, rate, or classify fake news (let alone stopping to recommend it).  Otherwise they will both lose credibility and readership – as well as fail to act in a responsible way commensurate with their information dissemination power.
  1. Gut feel makes a comeback. After a decade of Google-inspired heavily data-driven and A/B-tested management, the new US administration will increasingly be less data-driven and more gut-feel-driven in making decisions.  Riding against both common sense and the big data / analytics / data science trends, people will be increasingly skeptical of purely data-driven decisions and anti-data people will publicize data-driven failures to popularize their arguments.  This “war on data” will build during the year, fueled by Trump, and some of it will spill over into business.  Morale in the Intelligence Community will plummet.
  1. Under a volatile leader, who seems to exhibit all nine of the symptoms of narcissistic personality disorder, we can expect sharp reactions and knee-jerk decisions that rattle markets, drive a high rate of staff turnover in the Executive branch, and fuel an ongoing war with the media.  Whether you like his policies or not, Trump will bring a high level of volatility the country, to business, and to the markets.
  1. With the new administration’s promises of $1T in infrastructure spending, you can expect interest rates to raise and inflation to accelerate. Providing such a stimulus to already strong economy might well overheat it.  One smart move could be buying a house to lock in historic low interest rates for the next 30 years.  (See my FAQ for disclaimers, including that I am not a financial advisor.)
  1. Huge emphasis on security and privacy. Election-related hacking, including the spearfishing attack on John Podesta’s email, will serve as a major wake-up call to both government and the private sector to get their security act together.  Leaks will fuel major concerns about privacy.  Two-factor authentication using verification codes (e.g., Google Authenticator) will continue to take off as will encrypted communications.  Fear of leaks will also change how people use email and other written electronic communications; more people will follow the sage advice in this quip:

Dance like no one’s watching; E-mail like it will be read in a deposition

  1. In 2015, if you were flirting on Ashley Madison you were more likely talking to a fembot than a person.  In 2016, the same could be said of troll bots.  Bots are now capable of passing the Turing Test.  In 2017, we will see more bots for both good uses (e.g., customer service) and bad (e.g., trolling social media).  Left unchecked by the social media powerhouses, bots could damage social media usage.
  1. Artificial intelligence hits the peak of inflated expectations. If you view Salesforce as the bellwether for hyped enterprise technology (e.g., cloud, social), then the next few years are going to be dominated by artificial intelligence.  I’ve always believed that advanced analytics is not a standalone category, but instead fodder that vendors will build into smart applications.  They key is typically not the technology, but the problem to which to apply it.  As Infer founder Vik Singh said of Jim Gray, “he was really good at finding great problems,” the key is figuring out the best problems to solve with a given technology or modeling engine.  Application by application we will see people searching for the best problems to solve using AI technology.
  1. The IPO market comes back. After a year in which we saw only 13 VC-backed technology IPOs, I believe the window will open and 2017 will be a strong year for technology IPOs.  The usual big-name suspects include firms like Snap, Uber, AirBnB, and SpotifyCB Insights has identified 369 companies as strong 2017 IPO prospects.
  1. Megavendors mix up EPM and ERP or BI. Workday, which has had a confused history when it comes to planning, acquired struggling big data analytics vendor Platfora in July 2016, and seems to have combined analytics and EPM/planning into a single unit.  This is a mistake for several reasons:  (1) EPM and BI are sold to different buyers with different value propositions, (2) EPM is an applications sale, BI is a platform sale, and (3) Platfora’s technology stack, while appropriate for big data applications is not ideal for EPM/planning (ask Tidemark).  Combining the two together puts planning at risk.  Oracle combined their EPM and ERP go-to-market organizations and lost focus on EPM as a result.  While they will argue that they now have more EPM feet on the street, those feet know much less about EPM, leaving them exposed to specialist vendors who maintain a focus on EPM.  ERP is sold to the backward-looking part of finance; EPM is sold to the forward-looking part.  EPM is about 1/10th the market size of ERP.  ERP and EPM have different buyers and use different technologies.  In combining them, expect EPM to lose out.

And, as usual, I must add the bonus prediction that 2017 proves to be a strong year for Host Analytics.  We are entering the year with positive momentum, the category is strong, cloud adoption in finance continues to increase, and the megavendors generally lack sufficient focus on the category.  We continue to be the most customer-focused vendor in EPM, our new Modeling product gained strong momentum in 2016, and our strategy has worked very well for both our company and the customers who have chosen to put their faith in us.

I thank our customers, our partners, and our team and wish everyone a great 2017.

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Can the Media Please Stop Referring to Company Size by Valuation?

The following tweet is the umpteenth time I’ve seen the media size a company by valuation, not revenue, in the past few years:

mktcap

Call me old school, but I was taught to size companies by revenue, not market capitalization (aka, valuation).

Calling Palantir a $20B company suggests they are doing $20B in revenues, which is certainly not the case.  (They say they did $1B in 2015 and that’s bookings, not revenue.)  So we’re not talking a small difference here.  Depending on the hype factor surrounding a company, we might be talking 20x.

Domo is another company the media loves to size by its market cap.

domo

I’ve heard revenue estimates of $50M to $100M for Domo, so here again, we’re not talking about a small difference.  Maybe 20x.

When my friend Max Schireson stepped down from MongoDB to spend more time with his family, the media did it again (see the first line of text below the picture)

mongodb

I love Max.  I love MongoDB.  While I don’t know what their revenues were when he left (I’d guess $50M to $100M), they certainly were not a “billion-dollar database company.”  But, hey, the article got 4,000 shares.  Inflation-wise, I’m again guessing 10-20x.

So why does the media do this?  Why do they want to mislead readers by a factor of 20?

  • Because if makes the numbers bigger
  • And makes the headlines cooler
  • And increases drama

In the end, because it (metaphorically) sells more newspapers.  “Wow, some guy just quit as CEO of a billion-dollar company to actually spend more time with his family” just sounds a whole lot better than the same line with a comparatively paltry $50M instead.  Man Bites Dog beats Dog Bites Man every time.

But it’s wrong, and the media should stop doing it.  Why?

  • It’s misleading, and not just a little.  Up to 20x as the above examples demonstrate.
  • It’s not verifiable.  For private companies, you can’t really know or verify the valuation.  It’s not in any public filing.  (While private companies don’t disclose revenue either, it’s much more easily triangulated.)
  • Private company valuations are misleading because VCs buy preferred stock and employees/founders have common stock. So you take a preferred share price and multiply it by the total number of outstanding shares, both preferred and common.  (This ignores the fact that the common is definitionally worth less than the preferred and basically assumes an IPO scenario, which happens only for the fortunate few, where the preferred converts into common.)
  • In the past few years, companies are increasingly taking late-stage money that often comes with “structure” that makes it non-comparable in rights to both the regular preferred and the common.  So just compound the prior problem with a new class of essentially super-preferred stock.  The valuation gets even more misleading.
  • Finally, compound the prior problem with a hyped environment where everyone wants to be a unicorn so they might deliberately take unfavorable terms/structure in order get a higher valuation and hopefully cross into unicorn-dom.  The valuation gets even-more-misleading squared.  See the following Tweet as my favorite example of this phenom.  (OH means overheard.)

ego

When was the last time I saw the media consistently size companies by valuation instead of revenue?  1997 to 2001.  Bubble 1.0.

Maybe we’ll soon be talking about eyeballs again.  Or, if you like Stance, the company that has raised $116in VC and has “ignited a movement of art and self-expression,” in socks (yes, socks) then maybe we’ll be talking about feet.

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(And while I’m not sure about the $116M, I do love the socks.)