Category Archives: Management

Bookings vs. Billings in a SaaS Company

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

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

saas1-zen

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

saas13

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

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

 The Fun Part:  Imputing Internal Metrics from External Ones

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

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

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

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

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

Limitations of Billings as a SaaS Metric

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

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

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

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

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

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

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

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

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

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

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

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

saas3

Notes

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

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

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

[4] As distinct from services revenues.

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

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

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

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

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

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

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

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

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

Write Actionable Emails! (aka, If You’re Going to Make a Proposal, Make One)

As CEO of a company, I can’t tell you the number of times, I get emails like this:

Dave,

I know our policy is that we don’t pay both the salesreps their high-rate commissions on low-profit, one-of items, but we ended up doing a $50K/year pass-along storage fee for Acme, because they are managing a huge amount of data.  Because it recurs we’re considering it ARR at the corporate level.  The rep is OK because he is being paid well on the rest of the $500K deal, but I worry that the sales managers and sales consultants who also get paid on new ARR bookings won’t get 100% of their payout if we don’t pay them on this – can we please do that?

Thanks/Kelly

I find this email a non-actionable, incomplete proposal better suited for a philosophy class than a business discussion.  The mail does ask for approval, so you might think it’s actionable – but is it really?  What’s missing?  Three things.

  • A complete, concrete proposal: taking everything into account – all groups, any existing relevant policies, and any relevant precedent — what do you want to do?  Suppose the SDRs are also paid on total bookings, have you simply overlooked them and will be back asking for more once you’ve figured that out or are you saying you don’t want to pay them like the sales managers and SCs?
  • Numbers: what’s it going to cost the company?  First principles are fine, but you must translate them into recommended actions and identified costs.  I don’t mind back-of-the-envelope calculations, but I do need to be sure you’ve included everything in your analysis.  If the issue is complex or expensive, then I’d want a well thought-out and clearly documented spreadsheet cost analysis.  I get the qualitative arguments, but if you are just giving me passion and philosophy with no idea of what it’s going to cost, then I have no way of answering.
  • One or more alternatives:  if I don’t want to approve your primary proposal, do you have a preferred backup?  What is your plan B and what would it cost the company and why do you prefer plan A to it?
  • Bonus: a proposal to change existing polices so this situation won’t be ambiguous in the future and require another escalation.

So, let’s re-craft this email into something I’d rather receive:

Dave,

Per our policy we didn’t payout the salesrep on the $50K of ARR we took as a pass-along storage fee on the Acme account.  That’s OK with the rep because such one-of items are clearly excluded in our compensation plan terms and conditions [link to document], but I’ve discovered that the SC and manager compensation plans lack the same exclusionary language.  Ergo, this time, I recommend that we payout the SCs and the managers on this $50K of ARR (total cost $2.5K as it pushes some folks into accelerators).  Additionally, I intend to immediately update and re-issue the T&C document for sales management and SC comp plans.  Can I get your approval on this proposal?

By the way, if you’re opposed to this, can we please just go and payout the SCs (total cost $1.0K) as I believe it’s more important to them than the managers.  Either way, these are small numbers so let’s get this behind us quickly and move onto more important items.

Thanks/Kelly

Ah.  I feel better already.

The proposer is referring to our existing policies – even providing me with links to them – applying them, noticing problems with them, and making a concrete proposal for what to do about it, along with a backup.  Kelly’s telling me correct costs – e.g., not forgetting the impact of accelerators – for approving the proposal.  And even correcting our policies so this situation won’t ever again require an escalation.

My Appearance on DisrupTV Episode 100

Last week I sat down with interviewers Doug Henschen, Vala Afshar, and a bit of Ray Wang (live from a 777 taxiing en route to Tokyo) to participate in Episode 100 of DisrupTV along with fellow guests DataStax CEO Billy Bosworth and big data / science recruiter Virginia Backaitis.

We covered a full gamut of topics, including:

  • The impact of artificial intelligence (AI) and machine learning (ML) on the enterprise performance management (EPM) market.
  • Why I joined Host Analytics some 5 years ago.
  • What it’s like competing with Oracle … for basically your entire career.
  • What it’s like selling enterprise software both upwind and downwind.
  • How I ended up on the board of Alation and what I like about data catalogs.
  • What I learned working at Salesforce (hint:  shoshin)
  • Other lessons from BusinessObjects, MarkLogic, and even Ingres.

DisrupTV Episode 100, Featuring Dave Kellogg, Billy Bosworth, Virginia Backaitis from Constellation Research on Vimeo.

 

The Single Biggest Myth about MBOs and OKRs

I’m a big believer in written quarterly goals.

The old way to do this was to adopt “management by objective” (MBO) and to write down a set of MBOs for each quarter for each team member.  Most folks would do this either in Word, or if they liked weightings and scores as part of calculating an MBO bonus, Excel.  Over time, larger enterprises adopted HR performance management software to help with managing and tracking those MBOs.  When writing individual objectives, you were advised that they be SMART (specific, measurable, attainable, realistic, time-bound).

Despite best intentions, over time MBOs developed a bad rap for several reasons:

  • People would make too many of them, often drowning in long lists of MBOs
  • Few people could write them well, so would-be SMART objectives ended SQUISH (soft, qualitative, unintelligible, imprecise, slang, and hazy) instead.
  • They were often hard-linked to compensation, encouraging system-gaming

The objective / key result (OKR) system is a more modern take on objective setting popularized by, among others, Google and venture capitalist John Doerr.  OKRs fix some of the key problems with MBOs.

  • A strong guideline to have no more than about 5 OKRs per person to avoid the drowning-in-MBOs problem.
  • Adding a tiny bit of structure (the key results) helps enormously with producing objectives that are specific and measurable.
  • A realistic and intelligently calibrated scoring system whereby 70% is considered a “good” grade.  The defeats a lot of the system gaming.

But, regardless of which system you’re using, you can still hear the following myth from some managers and HR professionals:

“Oh, wait.  The objectives shouldn’t list things in your core job.  They should be the things on top of your core job.”  Sometimes followed by, “who’d want to pay you a bonus just for doing your core job?”

This is just plain wrong.

Let’s make it clear via an example.  Say you’re a first-line technical support person whose job is to answer 20 cases per day.  To ensure you’re not just closing out cases willy-nilly, your company performs a post-case customer satisfaction (CSAT) survey and wants you to maintain a post-case CSAT rating of 4.5 out of 5.0.  In addition, the company wants you to do 6 hours of skills training and write 4 knowledge-base articles per month.

If you live by the myth that says written objectives should be above and beyond your core job then this person should have two quarterly objectives:

  • Write 4 knowledge-base articles per month.
  • Attend 6 hours of skills training per month.

This is simply insanity.  You are going to the trouble of tracking written objectives, but overlooking 90%+ of what this person actually does.  This person needs to have 3 quarterly objectives:

  • Close 100 cases per week with a 4.5+ CSAT rating
  • Write 4 knowledge-base articles per month
  • Attending 6 hours of skills training per month

And if we’re tying these to a bonus, most of the weight needs to be on the first one.

While I know I’ve argued this via reductio ad absurdum, I think it’s the right way to look at it.  If you’re going to track written objectives — by either MBO or OKR — then you should think about you the  entire job scope, be inclusive, and weight them appropriately.

 

My SaaStr Talk Abstract: 10 Non-Obvious Things About Scaling SaaS

In an effort to promote my upcoming presentation at SaaStr 2018, which is currently on the agenda for Wednesday, February 7th at 9:00 AM in Studio C, I thought I’d do a quick post sharing what I’ll be covering in the presentation, officially titled, “The Best of Kellblog:  10 Non-Obvious Things About Scaling SaaS.”

Before jumping in, let me say that I had a wonderful time at SaaStr 2017, including participating on a great panel with Greg Schott of MuleSoft and Kathryn Minshew of The Muse hosted by Stacey Epstein of Zinc that discussed the CEO’s role in marketing.  There is a video and transcript of that great panel here.

saastr

For SaaStr 2018, I’m getting my own session and I love the title that the folks at SaaStr came up with because I love the non-obvious.  So here they are …

The 10 Non-Obvious Things About Scaling a SaaS Business

1. You must run your company around ARR.  Which this may sound obvious, you’d be surprised by how many people either still don’t or, worse yet, think they do and don’t.  Learn my one-question test to tell the difference.

2.  SaaS metrics are way more subtle than meets the eye.  Too many people sling around words without knowing what they mean or thinking about the underlying definitions.  I’ll provide a few examples of how fast things can unravel when you do this and how to approach SaaS metrics in general.

3.  Former public company SaaS CFOs may not get private company SaaS metrics.  One day I met with the CFO of a public company whose firm had just been taken private and he had dozens of questions about SaaS metrics.  It had never occurred to me before, but when your job is to talk with public investors who only see a limited set of outside-in metrics, you may not develop fluency in the internal SaaS metrics that so obsess VC and PE investors.

4.  Multi-year deals make sense in certain situations.  While many purists would fight me to the death on this, there are pros and cons to multi-year deals and circumstances where they make good sense.  I’ll explain how I think about this and the one equation I use to make the call.

5.  Bookings is not a four-letter word.  While you need to be careful where and when you use the B-word in polite SaaS company, there is a time and place to measure and discuss bookings.  I’ll explain when that is and how to define bookings the right way.

6.  Renewals and satisfaction are more loosely correlated than you might think.  If you think your customers are all delighted because they’re renewing, then think again.  Unhappy customer sometimes renew and happy ones don’t.  We’ll discuss why that happens and while renewal rates are often a reasonable proxy for customer satisfaction, why you should also measure customer satisfaction using NPS, and present a smart way to do so.

7.  You can’t analyze churn by analyzing churn.  To understand why customers churn, too many companies grab a list of all the folks who churned in the past year and start doing research and interviews.  There’s a big fallacy in this approach.  We’ll discuss the right way to think about and analyze this problem.

8.  Finding your own hunter/farmer metaphor is hard.  Boards hate double compensation and love splitting renewals from new business.  But what about upsell?  Which model is right for you?  Should you have hunters and farmers?   Hunters in a zoo?  Farmers with shotguns?  An autonomous collective?  We’ll discuss which models and metaphors work, when.

9.  You don’t have to lose money on services.  Subsidizing ARR via free or low-cost services seems a good idea and many SaaS companies do it.  But it’s hell on blended gross margins, burns cash, and can destroy your budding partner ecosystem.  We’ll discuss where and when it makes sense to lose money on services — and when it doesn’t.

10.  No matter what your board says, you don’t have to sacrifice early team members on the altar of experienced talent.  While rapidly growing a business will push people out of their comfort zones and require you to build a team that’s a mix of veterans and up-and-comers, with a bit creativity and caring you don’t have to lose the latter to gain the former.

I hope this provides you with a nice and enticing sample of what we’ll be covering — and I look forward to seeing you there.

Quota Over-assignment and Culture

Here’s a great slide from the CFO Summit at Zuora’s 2017 annual flagship Subscribed event.

underassign

Since they talk about this as under-assignment, since people aren’t great at flipping fractions in their head, and since I think of this more intuitively as over-assignment, I’m going to invert this and turn it into a pie chart.

quota over

So, here you can  see that 22% of companies have 0-11% over-assignment of quota, 44% have 11-25% over-assignment, 23% have 25-43%, 5% have 43-100% over-assignment, and 7% have more than 100% over-assignment of quota.

Since this is a pretty broad distribution — and since this has a real impact on culture, I thought examine this on two different angles:  the amount of total cushion and where that cushion lives.

The 0-11% crowd either has a very predictable business model or likes to live dangerously.  Since there’s not that much cushion to go around, it’s not that interesting to discuss who has it.  I hope these companies have adequately modeled sales turnover and its effects on quota capacity.

The 11-25% crowd strikes me as reasonable.  In my experience, most enterprise software companies run in the 20% range, so they assign 120 units of quota at the salesrep level for an operating plan that requires 100 units of sales.  Then the question is who has the cushion?  Let’s look at three companies.

cushion

In company 1, the CEO and VP of Sales are both tied to the same number (i.e., the CEO has no cushion if the VP of Sales misses) and the VP of Sales takes all of the cushion, giving the sales managers none.  In company 2, the CEO takes the entire 20% cushion for him/herself, leaving none for either the VP of Sales or the sales managers.  In company 3, the cushion is shared with the CEO and VP of Sales each taking a slice, leaving nearly half for the sales managers.

While many might be drawn to company 3, personally, I think the best answer is yet another scenario where the CEO and VP of Sales are both tied to 100, the sales managers to 110, and the aggregate salesrep quota to 120.  Unless the CEO has multiple quota-carrying direct reports, it’s hard to give the VP of Sales a higher quota than him/herself, so they should tie themselves together and share the 10% cushion from the sales managers who in turn have ~10% cushion relative to their teams.

I think this level of cushion works well if you’re building it atop a productivity model that assumes a normal degree of sales turnover (and ramp resets) and are thus using over-assignment simply to handle non-attainment, and not also sales turnover.  If you are using over-assignment to handle both, then a higher level of cushion may be needed, which is probably why 22% of companies have 25-43% over-assignment in their sales model.

The shock is the 12% that together have more than 43% over-assignment.  Let’s ponder for a minute what that might look like in an example with 60% over-assignment.

company4

So think about this for a minute.  The VP of Sales can be at 83% of quota, the sales managers on average can be at 71% of quota, and the salesreps can be at 63% of their quota — and the CEO will still be on plan.  The only people hitting their number, making their on-target earnings (OTE), and drinking champagne at the end of the quarter are the CEO and CFO.  (And they better drink it in a closet.)

That’s why I believe cushion isn’t just a math problem.  It’s a cultural issue.  Do you want a “let them eat cake” or a “we’re all in this together” culture.  The answer to that question should help determine how much cushion you have and where it lives.

Eight Words that Can Limit Your Career: “Let Me Get Back To You On That”

As executives there are certain things we are expected to know — in our heads — about our jobs and our functions.  Sometimes I call this “the 3:00 AM test” because someone should be able to wake you up at 3:00 AM in the middle of a sound sleep and you should be able to answer questions like:

  • What’s the forecast for the current quarter? (Sales, Finance)
  • How many MQLs did we generate last week?  (Marketing)
  • How many customer bugs are outstanding?  (Engineering)
  • What’s the monthly PR retainer?  (Marketing)
  • What’s the ending cash forecast for the quarter?  (Finance)
  • How many unique visitors did we get on the website last week?  (Marketing)
  • What are the top three deals in the current quarter?  (Sales)

In another post, I playfully called these the other kind of in-memory analytics, but I was focused mostly on numbers that you should be able to recall from memory, without having to open your laptop, without having to delegate the question to your VP of Ops (e.g., salesops, marketingops), and without having to say the dreaded, cringe-worthy, and dangerous eight words:  “let me get back to you on that.”

The same logic that applies to numbers applies to other basic questions like:

  • What’s our elevator pitch against top-rival?  (Marketing)
  • What’s the structure of the sales compensation plan?  (Sales)
  • Which managers are the top 2-3 hot spots in the company?  (People)
  • What are the top three challenges in your department and what are you doing about them?  (Any)

You see, when you say the dreaded eight words here’s what everybody else in the meeting is hearing:

“I can’t answer that question because I’m not on top of the basics, and I am either not sufficiently detailed-oriented, swapped-in, or competent to know the answer.”

And, worse yet, if offered unapologetically:

“I’m not even aware that this is the kind of question that everyone would reasonably expect me to be able to answer.”

Here are three tips to help you avoid falling into the eight-words trap.

  1. Develop your sensitivity by making a note of every time you hear them, how you feel about the specific question, and how it reflected on the would-be respondent.
  2. Make a list of questions you should be able to answer on-the-spot and then be sure you can.  (If you find a gap, think about what that means about how you approach your job.)
  3. If you feel the need to say the dreaded eight words see if offering a high-confidence range of values will be enough to meet the audience’s need — e.g., “last week’s web visitors were in the 10,000 to 11,000 range, up a few percent from the week before.”

And worst case, if you need to say the dreaded eight words and you think the situation warrants one, offer an apology.  Just be mindful that you don’t find yourself apologizing too often.