Category Archives: Management

How To Sales Manage Upside and Unlikely Deals

If your sales organization is like most, you classify sales opportunities in about four categories, such as:

  • Commit, which are 90% likely to close
  • Forecast, which are 70% likely to close
  • Upside, which are 33% likely to close
  • Unlikely, which are 5% likely to close

And then, provided you have sufficient pipeline, your sales management team basically puts all of its effort into and attention on the commit and forecast deals.  They’re the ones that get deal reviews.  They’re the ones where the team does multiple dry runs before big demos and presentations.  They’re the deals that get discussed every week on the forecast call.

The others ones?  No such much.  Sure, the salesreps who own them will continue to toil away.  But they won’t get much, if any, management attention.  You’ll probably lose 75% of them and it won’t actually matter much, provided you have enough high-probability deals to make your forecast and plan.

But, what a waste.  Those opportunities probably each cost the company $2500 to $5000 to generate and many multiples of that to pursue.  But they’re basically ignored by most sales management teams.

The classical solution to this problem is to tell the sales managers to focus on everything.  But it doesn’t work.   A smart sales manager knows the only thing that really matters is making his/her number and doing that typically involves closing almost all the committed and most of the forecast deals.  So that is where their energy goes.

jumpballThe better way to handle these deals is to recognize they’re more likely to be lost than won (e.g., calling them jump-balls, 50/50 balls, or face-offs, depending on your favorite sport), find the most creative non-quota-carrying manager in the sales organization (e.g., VP of salesops) and have him/her manage these low-probability, high-risk deals in the last month of the quarter using non-traditional (i.e., Crazy Ivan) tactics.

This only works if you have happen to have a VP of salesops, enablement, alliances, etc., who has the experience, passion, and creativity to pull it off, but if you do it’s a simply fantastic way to allow core sales management to focus on the core deals that will make or break the quarter while still applying attention and creativity to the lower probability deals that can drive you well over your targets.

This is not as crazy as it might sound, because those in sales ops or productivity positions typically do have prior sales management experience.  Thus, this becomes a great way to keep their saw sharp and keep them close/relevant to the reality of the field in performing their regular job.  What could be better than a VP of sales productivity who works on closing deals 4 months/year?

If your VP of sales ops or sales enablement doesn’t have the background or interest to do this, maybe they should.  If not, and/or you are operating at bigger scale, why not promote a salesperson with management potential into jump-ball, overlay deal management as their first move into sales management?

The Two Engines of SaaS: QCRs and DEVs

I remember one day, years ago, when I was a VP at $10M startup and Larry, the head of sales, came in one day handing out t-shirts that said:

“Code, sell, or get out of the way.”

Neither I, nor the rest of marketing team, took this particularly well because the shirt obviously devalued the contributions of F&A, HR, and marketing.  But, ever seeking objectivity, I did concede that the shirt had a certain commonsense appeal.  If you could only hire one person at a startup, it would be someone to write the product.  And if you could only hire one more, it would be someone to sell it.

This became yet another event that reconfirmed my belief in my “marketing exists to make sales easier” mantra.  After all, if you’re not coding or selling, at least you can help someone who is.

Over time, Larry’s t-shirt morphed in my mind into a new mantra:

“A SaaS company is a two-engine plane.  The left engine is DEVs.  The right is QCRs.”

QCR meaning quota-carrying (sales) representative and DEV meaning developer (or, for symmetry and emphasis, storypoint-burning developer).  People who sell with truly incremental quota, and people who write code and burndown storypoints in the process.

It’s a much nicer way of saying “code, sell, or get out of the way,” but it’s basically the same idea.  And it’s true.  While Larry was coming from a largely incorrect “protest overhead and process” viewpoint, I’m coming from a different one:  hiring.

The two hardest lines in a company headcount plan to keep at-plan are guess which two?  QCRs and DEVs.  Forget other departments for a minute — I’m saying is the the hardest line for the VP of Engineering to stay fully staffed on is DEVs, and the hardest line for the VP of Sales to stay fully staffed on is QCRs.

Why is this?

  • They are two, critical highly in-demand positions, so the market is inherently tight.
  • Given their importance, the hiring VPs can be gun-shy about making mistakes and lose candidates due to hesitation or indecision.
  • Both come with a short-term tax and mid-term payoff because on-boarding new hires slows down the rest of the team, a possible source of passive resistance.
  • Sales managers dislike splitting territories because it makes them unpopular, which could drive more foot-dragging.
  • It’s just plain easier to find the associated support functions — (e.g,. program managers, QA engineers, techops, salesops, sales productivity, overlays, CSMs, managers in general) than it is find the QCRs and DEVs.

Let me be clear:  this is not to say that all the supporting functions within sales and engineering do not add value, nor is this to say that supporting corporate functions beyond sales and engineering do not add value — it is to say, however, that far too often companies take their eye off the ball and staff the support functions before, not after, those they are supporting.  That’s a mistake.

What happens if you manage this poorly?  On the sales side, for example, you end up with an organization that has 1 SVP of Sales, 1 VP of sales consulting, 4 sales consultants, 1 director of sales ops, 1 director of sales productivity, 1 manager of sales development reps (SDRs), 4 SDRs, an executive assistant, and 4 quota-carrying salespeople.  So only 22% of the people in your sales organization actually carry a quota.

“Uh, other than QCRs, we’re doing great on sales hiring,”  says the sales VP.  “Other than that, Mrs. Lincoln, how did you find the play?” thinks the board.

Because I’ve seen this happen so often, and because I’ve seen companies accused of it both rightfully and unjustly, I’d decided to create two new metrics:

  • QCR density = number of QCRs / total sales headcount
  • DEV density = numbers of DEVs / total engineering headcount

The bad news is I don’t have a lot of benchmark data to share here.  In my experience, both numbers want to run in the 40% range.

The good news is that if you run a ratio-driven staffing model (which you should do for both sales and engineering), you should be able to calculate what these densities should be when you are fully staffed.

Let’s conclude with a simple model that does just that on the sales side, producing a result in the 38% to 46% range.

qcr dens

Finally, let me add that having such a model helps you understand whether, for example, your QCR density is low due to slow QCR hiring (and/or bad retention) against a good model, or on-pace hiring against a “fat” model.  The former is an execution problem, the latter is a problem with your model.

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 perspective, they look like 100, 200, 300 units, respectively.  Worse yet, looking solely at deferred revenue 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 deferred revenue for an end-of-quarter renewal suddenly looked 50.  When Wall St. saw the resultant less-than-expected deferred revenue (and ergo less-than-expected billings), 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.