How to Present an Operating Plan to your Board

I’ve been CEO of two startups and on the board of about ten.  That means I’ve presented a lot of operating plans to boards.  It also means I’ve had a lot of operating plans presented to me.  Frankly, most of the time, I don’t love how they’re presented.  Common problems include:

  • Lack of strategic context: management shows up with a budget more than a plan, and without explaining the strategic thinking (one wonders, if any) behind it.  For a primer, see here.
  • Lack of organizational design: management fails to show the proposed high-level organizational structure and how it supports the strategy.  They fail to show the alternative designs considered and why they settled on the one they’re proposing.
  • A laundry list of goals. OKRs are great.  But you should have a fairly small set – no more than 5 to 7 – and, again, management needs to show how they’re linked to the strategy.

Finance types on the board might view these as simple canapes served before the meal.  I view them as critical strategic context.  But, either way, the one thing on which everyone can agree is that the numbers are always the main course. Thus, in this post, I’m going to focus on how to best present the numbers in an annual operating plan.

Context is King
Strategic context isn’t the only context that’s typically missing.  A good operating plan should present financial context as well.  Your typical VC board member might sit on 8-10 boards, a typical independent on 2 (if they’re still in an operating role), and a professional independent might sit on 3-5.  While these people are generally pretty quantitative, that’s nevertheless a lot of numbers to memorize.  So, present context.  Specifically:

  • One year of history. This year that’s 2021.
  • One year of forecast. This year that’s your 2022 forecast, which is your first through third quarter actuals combined with your fourth-quarter forecast.
  • The proposed operating plan (2023).
  • The trajectory on which the proposed operating plan puts you for the next two years after that (i.e., 2024 and 2025).

The last point is critical for several reasons:

  • The oldest trick in the book is to hit 2023 financial goals (e.g., burn) by failing to invest in the second half of 2023 for growth in 2024.
  • The best way to prevent that is to show the 2024 model teed up by the proposed 2023 plan. That model doesn’t need to be made at the same granularity (e.g., months vs. quarters) or detail (e.g., mapping to GL accounts) as the proposed plan – but it can’t be pure fiction either.  Building this basically requires dovetailing a driver-based model to your proposed operating plan.
  • Showing the model for the out years helps generate board consensus on trajectory. While technically the board is only approving the proposed 2023 operating plan, that plan has a 2024 and 2025 model attached to it.  Thus, it’s pretty hard for the board to say they’re shocked when you begin the 2024 planning discussion using the 2024 model (that’s been shown for two years) as the starting point.

Presenting the Plan in Two Slides
To steal a line from Name That Tune, I think I can present an operating plan in two slides.  Well, as they say on the show:  “Dave, then present that plan!”

  • The first slide is focused on the ARR leaky bucket, metrics derived from ARR, and ARR-related product.ivity measures
  • The second slide is focused on the P&L and related measures.

There are subjective distinctions in play here.  For example, CAC ratio (the S&M cost of a dollar of new ARR) is certainly ARR-related, but it’s also P&L-driven because the S&M cost comes from the P&L.  I did my best to split things in a way that I think is logical and, more importantly, between the two slides I include all of the major things I want to see in an operating plan presentation and, even more importantly, none of the things that I don’t.

Slide 1: The Leaky Bucket of ARR and Related Metrics

Let’s review the lines, starting with the first block, the leaky bucket itself:

  • Starting ARR is the ARR level at the start of a period. The starting water level of the bucket.
  • New ARR is the sum of new logo (aka, new customer) ARR and expansion ARR (i.e., new ARR from existing customers). That amount of “water” the company poured into the bucket.
  • Churn ARR is the sum of ARR lost due to shrinking customers (aka, downsell) and lost customers. The amount of water that leaked out of the bucket.
  • Ending ARR is starting ARR + new ARR – churn ARR. (It’s + churn ARR if you assign a negative sign to churn, which I usually do.)  The ending water level of the bucket.
  • YoY growth % is the year-over-year growth of ending ARR. How fast the water level is changing in the bucket.  If I had to value a SaaS company with only two numbers, they would be ARR and YoY ARR growth rate.  Monthly SaaS companies often have a strong focus on sequential (QoQ) growth, so you can add a row for that too, if desired.

The next block has two rows focused on change in the ARR bucket:

  • Net new ARR = new ARR – churn ARR. The change in water level of the bucket.  Note that some people use “net new” to mean “net new customer” (i.e., new logo) which I find confusing.
  • Burn ratio = cashflow from operations / net new ARR. How much cash you consume to increase the water level of the bucket by $1.  Not to be confused with cash conversion score which is defined as an inception-to-date metric, not a period metric.  This ratio is similar to the CAC ratio, but done on a net-new ARR basis and for all cash consumption, not just S&M expense.

The next block looks at new vs. churn ARR growth as well as the mix within new ARR:

  • YoY growth in new ARR. The rate of growth in water added to the bucket.
  • YoY growth in churn ARR. The rate of growth in water leaking from the bucket.  I like putting them next to each other to see if one is growing faster than the other.
  • Expansion ARR as % of new ARR. Percent of new ARR that comes from existing customers.  The simplest metric to determine if you’re putting correct focus on the existing customer base.  Too low (e.g., 10%) and you’re likely ignoring them.  Too high (e.g., 40%) and people start to wonder why you’re not acquiring more new customers. (In a small-initial-land and big-expand model, this may run much higher than 30-40%, but that also depends on the definition of land – i.e., is the “land” just the first order or the total value of subscriptions acquired in the first 6 or 12 months.)

The next block focuses on retention rates:

  • Net dollar retention = current ARR from year-ago cohort / year-ago ARR from year-ago cohort. As I predicted a few years back, NRR has largely replaced LTV/CAC, because of the flaws with lifetime value (LTV) discussed in my SaaStr 2020 talk, Churn is Dead, Long Live Net Dollar Retention.
  • Gross dollar retention = current ARR from year-ago cohort excluding expansion / year-ago ARR from year-ago cohort. Excluding the offsetting effects of expansion, how much do customer cohorts shrink over a year?
  • Churn rate (ATR-based) = churn ARR/available-to-renew ARR. Percent of ARR that churns measured against only that eligible for renewal and not the entire ARR base.  An important metric for companies that do multi-year deals as putting effectively auto-renewing customers in the denominator damps out

The next block focuses on headcount:

  • Total employees, at end of period.
  • Quota-carrying reps (QCRs) = number of quota-carrying sellers at end of period. Includes those ramping, though I’ve argued that enterprise SaaS could also use a same-store sales metric.  In deeper presentations, you should also look at QCR density.
  • Customer success managers (CSMs) = the number of account managers in customer success. These organizations can explode so I’m always watching ARR/CSM and looking out for stealth CSM-like resources (e.g., customer success architects, technical account managers) that should arguably be included here or tracked in an additional row in deeper reports.
  • Code-committing developers (CCDs) = the number of developers in the company who, as Elon Musk might say, “actually write software.” Like sales, you should watch developer density to ensure organizations don’t get an imbalanced helper/doer ratio.

The final block looks at ARR-based productivity measures:

  • New ARR/ramped rep = new ARR from ramped reps / number of ramped reps. This is roughly “same-store sales [link].”  Almost no one tracks this, but it is one of several sales productivity metrics that I like which circle terminal productivity.  The rep ramp chart’s 4Q+ productivity is another way of getting at it.
  • ARR/CSM = starting ARR/number of CSMs, which measures how much ARR each CSM is managing.  Potentially include stealth CSMs in the form of support roles like technical account manager (TAM) or customer success architects (CSAs).
  • ARR/employee = ending ARR/ending employees, a gross overall measure of employee productivity.

Slide 2: The P&L and Related Metrics

This is a pretty standard, abbreviated SaaS P&L.

The first block is revenue, optionally split by subscription vs. services.

The second block is cost of goods sold.

The third block is gross margin.  It’s important to see both subscription and overall (aka, blended) gross margin for benchmarking purposes.  Subscription gross is margin, by the way, is probably the most overlooked-yet-important SaaS metric.  Bad subscription margins can kill an investment deal faster than a high churn rate.

The fourth block is operating expense (opex) by major category, which is useful for benchmarking.  It’s also useful for what I call glideslope planning, which you can use to agree with the board on a longer-term financial model and the path to get there.

The penultimate block shows a few more SaaS metrics.

  • CAC ratio = S&M cost of a $1 in new ARR
  • CAC payback period  = months of subscription gross profit to repay customer acquisition cost
  • Rule of 40 score = revenue growth rate + free cashflow margin

The last block is just one row:  ending cash.  The oxygen level for any business.  You should let this go negative (in your financial models only!) to indicate the need for future fundraising.

Scenario Comparisons
Finally, part of the planning process is discussing multiple options, often called scenarios.

While scenarios in the strategy sense are usually driven by strategic planning assumptions (e.g., “cheap oil”), in software they are often just different version of a plan optimized for different things:

  • Baseline: the default proposal that management usually thinks best meets all of the various goals and constraints.
  • Growth: an option that optimizes growth typically at the expense or hitting cash, CAC, or S&M expense goals.
  • Profit: an option that optimizes for cash runway, often at the expense of growth, innovation, or customer satisfaction.

Whatever scenarios you pick, and your reasons for picking them, are up to you.  But I want to help you present them in a way that is easy to grasp and compare.

Here’s one way to do that:

I like this hybrid format because it’s pulling only a handful of the most important rows, but laying them out with some historical context and, for each of the three proposed scenarios, showing not only the proposed 2023 plan also the 2024 model associated with it.  This is the kind of slide I want to look at while having a discussion about the relative merits of each scenario.

What’s Missing Here?
You can’t put everything on two slides.  The most important things I’m worried about missing in this format are:

  • Segment analysis: sometimes your business is a blended average of multiple different businesses (e.g., self-serve motion, enterprise motion) and thus it’s less meaningful to analyze the average than to look at its underlying components.  You’ll need to add probably one section per segment in order to address this.
  • Strategic challenges. For example, suppose that you’ve always struggled with enterprise customer CAC.  You may need to add one section focused solely on that.  “Yes, that’s the overall plan, but it’s contingent on getting cost/oppty to $X and the win rate to Y% and here’s the plan to do that.”
  • Zero-based budgeting. In tough times, this is a valuable approach to help CEOs and CFOs squeeze cost out of the business.  It takes more time, but it properly puts focus on overall spend and not simply on year-over-year increments.  In a perfect world, the board wouldn’t need to see any artifacts from the process, but only know that the expense models are tight because every expense was scrutinized using a zero-based budgeting process.

Conclusion
Hopefully this post has given you some ideas on how to better present your next operating plan to your board.  If you have questions or feedback let me know.  And I wish everyone a happy and successful completion of planning season.

You can download the spreadsheet used in this post, here.

The Balderton Founder’s Guide to B2B Sales

Working in my capacity at as an EIR at Balderton Capital, I have recently written a new publication, The Balderton Founder’s Guide to B2B Sales, with the able support of Balderton Principal Michael Lavner and the entire Balderton Capital team.  This guide is effectively a new edition, and a new take, on the prior, excellent B2B Sales Playbook.

The guide, which is now published as a microsite, will soon be available in PDF format for downloading.

I’ll put the opening quote here that the editors omitted because it’s nearly unparseable:

“I have learned everything I need to know about sales.  Sales is saying ‘yes’ in response to every question.  So, now, when a customer asks if the product has a capability that it currently lacks, I say, ‘yes, the product can’t do that.'”

— Anonymous CS PhD founder who didn’t quite learn everything they needed to know about sales.

In short, this guide’s written for you, i.e., the product-oriented founder who thought they founded a technology business only to discover that SaaS companies, on average, spend twice as much on S&M as they do on R&D, and ergo are actually running a distribution business.

The guide has seven parts:

  • Selling: what founders need to know about sales
  • Building: how to build a sales organization
  • Managing: how to manage a sales organization
  • Renewing/expanding: teaming sales and customer success
  • Marketing: using marketing to build sales pipeline
  • Partnering: how to use partners to improve reach and win rate
  • Planning: planning and the role of key metrics and benchmarks

While there are numerous good SaaS benchmarking resources out there, the guide includes some benchmark figures from the Balderton universe (i.e., European, top-tier startups) and — hint, hint — we expect to release those benchmarks more fully and in a more interactive tool in the not-too-distant future.

The guide is also chock full of links which I will attempt to maintain as sources change over time.  But I’ve written it with both in-line links (often to Kellblog) and end-of-section links that generally point to third-party resources.

I’ve packed 30 years of enterprise software experience into this.  I come at sales from an analytical viewpoint which I think should be relatable for most product-oriented founders who, like me, get turned off by claims that sales has to be artisanal magic instead of industrial process.

I hope you enjoy the guide.  Feel free to leave comments here, DM me on Twitter, or reach me at the contact information in my FAQ.

How to Fix a Broken Go-To-Market Motion Using a Steady-State Funnel

In my consulting and advising work, I’ve worked with a number of enterprise SaaS companies that get stuck with a broken go-to-market (GTM) motion.  What do I mean by broken?

  • Chronic plan misses, and not by 5-10%, but by 30-50% [1]
  • Weak sales productivity, measured either relative to the company’s model or industry averages (median $675K) [2]
  • Scarce quota attainment, measured by percentage of reps hitting quota. Instead of 80% at 80%, they’re more like 80% at 40% [3]
  • High sales turnover. Good sellers quit when they’re not making money and they perceive themselves in a no-win situation.
  • Poor pipeline conversion, closing perhaps 10-20% of early-period pipeline instead of 30% to 40% [4]
  • Poor close rates, eventually winning only 5-10% of your deals as opposed to 20-30% [5]

In such situations, it’s easy to conclude “that dog don’t hunt” when examining the company’s go-to-market.  It’s harder to know what to do about it.  Typical reactions include:

  • Fire everyone, a popular response which is sometimes correct, but risks wasting an additional year due to chaos if the people were, in fact, not the problem.
  • Pivot the company, making a major change in strategy or sales model. Let’s go product-led growth (PLG).  Let’s sell our platform instead of our application.  Let’s do only enterprise accounts and account-based marketing (ABM).  While these pivots may make sense, many companies should get called for strategic “traveling” because they pivot too often [6].
  • Hope it will get better. If I only had a dollar for every time that I heard a CRO say,” all the changes are on track, the only thing I need is time for them to work.”  Maybe they will, maybe they won’t.  But what are the tell-tales will let us know before we miss three more quarters and execute plan-A, above?

It’s an utterly soul-sucking exercise to watch sales, marketing, and finance talk about these issues when the players are not all quantitative by nature, using the same metrics definitions, using the same models, all aware of the differences between averages and distributions, and all having a good understanding of ramping and phase lags [7].  That is, well, the vast majority of the time.

So, if you’re in this situation, what should you do about it?  Three things:

  • Agree on the problem, which is often shockingly more difficult than it appears
  • Build a steady-state funnel, which among other things focuses everyone on the present
  • Ensure your leadership team is part of the solution, not part of the problem

Agree on the Problem
You can’t make a coherent plan to fix something unless you have a clear, shared, data-driven understanding of what’s causing it.  To get that, you need to block a series of meetings with a single topic:  why are we missing plan?

You want a series of meetings because you will likely need to iterate on data collection and analysis.  Someone will assert something (e.g., saying that pipeline coverage is weak) and – unless your metrics are already in perfect shape — you’ll want to look at the data you have, clean it up, get historical data for trend analysis, and then reconvene.  It’s more effective to have a series of meetings like this than it is to have one mega-meeting where you’re committed to leaving the room with a plan, but you’re simply debating opinions.  As Jim Barksdale used to say, “if we have data, let’s look at the data; if all we have is opinions, let’s go with mine.”  So, get the data.

There will invariably be some blame games in this process.  Focus on the assertions, not who made them, and focus on the data you’d need to see to back them up.

Example:

CMO: “I think conversion rates are the problem.”
CEO: “Based on what data are you arriving at conclusion?”
CMO: “Overall pipeline is up, but the results are flat.”
CEO: “Please put up the slides from the last QBR on pipeline conversion.”
CEO:  “OK, this only shows one quarter so we can’t analyze historical trends, and it’s looking at rolling four-quarter pipeline so we can’t tell if actual current-quarter pipeline is sufficient.  Salesops, how can you help?”
Salesops: “I can make a trailing-five-quarter count- and dollar-based, week 3 pipeline conversion chart and make a pipeline progression chart that shows a better view of how the pipeline is evolving.” [8]
CEO: “Great, do that, and let’s reconvene on Friday to see what it says.”

Finally, ensure that you keep the conversion moving by forcing people to answer questions.  Call out people who “Swiss village” their answers [9].  Ask people who are being defensive to focus on the go-forward.  Interrupt people when they’re waxing poetic.  Time is of the essence and you can’t waste it.

Build and Focus on a Steady-state Funnel
To make things simple, concrete, and focused on the immediate future, I think the best thing you can do is build a steady-state funnel model.

If you’re missing plan consistently and significantly, there’s no need to have in-depth future hiring, ramping, and capacity conversations, phase-lagging lead generation to opportunity creation and then opportunities to deals.  That’s all besides the point.  The point is your model isn’t working and you need to get back on track.

Here are the magic words that change the conversation: “what if we just wanted to add $1M in ARR per quarter?”  No ramps, no phase lags, no ramp resets, none of that planning for future scaling that actually doesn’t matter when you’re presently, chronically missing plan [10].  None of the complexity that turns conversations into rabbit holes, all for invalid analytical reasons.

Think:  how about before we start planning for sequential quarterly growth, we start to consistently add ARR that closely resembles the plan number from two quarters ago that we never came close to hitting?  Got it?

Here’s what that steady-state funnel model looks like:

Let’s be clear, you can build much more complex funnel models, and I’ve written about how.  But now is not the time to use them.  The purpose here is simple.  Think: “team, if we want to add $1M in ARR per quarter …”

  • Can we get (usually down) to 7 sellers?
  • Can we get the deal size to $50K
  • Can each seller close 4 deals per quarter?
  • Can we generate 112 oppties per quarter?
  • Can we close 25% of early-period oppties?
  • Can we generate oppties for $3.5K?

For each assumption, you need to look at historical actuals, have a debate, and decide if the proposed steady-state model is realistic.  Not, “does finance think the math works,” but “can the GTM team sign up to execute it?” If you’re trying to move the needle on a metric (e.g., taking deal size from $30K to $50K) there has to a clear and credible reason why.

If you can’t convince yourself that you can deliver against the model, then maybe it’s time to let the company find someone who does.  It’s far better to part ways with integrity than to “fake commit” to a model you don’t believe in and then unsurprisingly fail to execute.  Or, if the whole team can’t commit to the model, or you can’t find a model to which they would commit that produces an investable CAC ratio, then maybe it is time to pivot the company.  These are hard questions.  There are few easy answers.

Ensure Leadership is Part of the Solution   
As you move forward, you need to ensure that your leadership team is part of the solution and not part of the problem.  This is always a difficult question, not only for relationship reasons, but for more practical ones as well.

  • If you replace an exec, what are the odds their successor will be better? If you have a solid, competent person in place, odds are the next person (who will be knowingly joining a company that’s off-rails) will be no better.  But who’s to decide if someone’s solid and competent?  Board members, your peer network, and advisors can certainly help (but beware halo effects in their assessments).  So-called “calibration meetings” can help you make your own assessment, by simply meeting – not in a recruiting context – other CXOs at similar and next-level companies.
  • If you replace an exec, how long will the resultant turmoil last? Four quarters is not uncommon because the new person will frequently rebuild the organization over their first two quarters and then you’ll need at least two additional quarters to see if it worked.  A failed replacement hire can easily cost you (another) year.  It’s criminal to incur that cost only to replace reasonably-good person X with reasonably-good person Y.

Other questions you should consider in assessing if you want to weather the storm with your current team:

  • Do they really believe in the plan? Execs can’t just be going through the motions.  You need leaders on your team who can enlist their teams in the effort.
  • Are they truly collaborating?  Some execs don’t internalize the Three Musketeers attitude that’s required in these situations.  You need leaders on your team who want to see their peers succeed.  One for all and all for one.
  • Are they still in the fight? Sometimes execs decide the situation is hopeless, but lack the nerve to quit.  They’ll pay lip service to the plan, but not give their best effort.  You need leaders on the team who are still in the fight and giving their best each day.

If you’re going through a rough situation, my advice is stay strong, stay data-driven, leverage the resources around you, and demand the best of your team.  Focus on first diagnosing the problem and then on building and attaining a steady-state funnel model to get things back on track.

It may feel like you’re going through hell, but remember, as Winston Churchill famously said, “if you’re going through hell, keep going.”

# # #

Notes

[1] Plan meaning New ARR bookings and not Ending ARR balance.  The latter can mask problems with the former.  If we’re trying to measure sales performance, we should look the amount of ARR sales pours into the SaaS leaky bucket and not what happens to its overall level.

[2] New ARR per seller per year.  Remember this is a median across all SaaS companies and my guess is enterprise is more $800K to $1200K and SMB is more $400-500K.  Introducing ramping to this discussion is always a superb way to burn a few hours of your life.  The pragmatic will just look at ramped rep productivity, excluding momentarily the effects of ramping reps.  Pros will use ramped req equivalents and then look at ARR/RRE.

[3] See prior point.  The pragmatic will look only at ramped rep attainment.  Pros will look at attainment relative to ramped quota.

[4] For companies on quarterly cadence:  new ARR booked / week 3 new ARR pipeline.

[5] Don’t confuse early-period pipeline conversion with opportunity close rate.  The former looks within one period.  The latter measures what closes in the fullness of time.   Example:  you can have a week 3 pipeline conversion rate of 33% (which suggests the need for 3x starting pipeline coverage) and an opportunity win rate of 20%.  See my post on time-based close rates for more.

[6] In the basketball sense that a player is called for a traveling violation when they pivot off more than one foot.

[7] Phase lags here meaning the time between generating a lead and it becoming an opportunity or generating an opportunity and it becoming a deal.

[8] This begs the question why those charts aren’t in the QBR template.  Hopefully, going forward, they’ll ensure they are.  Odds are, however, that they don’t exist so hopefully a good debate and a Google search on Kellblog pipeline will help people find the analytical tools they need.

[9] The expression is based on this quip: “When you ask them the time, some people tell you how to build a watch.  Some tell you how to build a Swiss village.”

[10] To state the obvious, for your company that magic number might be $2M, $5M or $10M – but the same principle applies. Let’s pick a steady-state, per-quarter, net-new ARR number and keep focusing on it until we start to achieve it.

Key Takeaways from the 2022 KeyBanc SaaS Metrics Survey

KeyBanc Capital Markets (KBCM) recently published their 13th annual private SaaS company survey.  This post has three purposes:  to let you know it’s out, to provide you with a link so you can get it, and to offer some quick takeaways on skimming through the results.

The first thing to remember about this survey is that it’s private SaaS companies.  Unlike Meritech Public Comps, where you can see metrics for the best [1], public SaaS companies, this private company data is somewhat harder to come by (the only other source that springs to mind is RevOps Squared) and, for most of us, it provides much more realistic comparables than Meritech [2].

The second thing to remember is that there are a lot of smaller companies in the sample:  about 20% of respondents are less than $5M in ARR and about 40% are less than $10M.   (The overall median is $13MM.)  Depending on who you want to compare to, this may be a good or a bad thing.  In addition, for most of the metrics they exclude companies <$5M in ARR from the calculations, which brings up the overall median for that set to $17.6M.

Net:  this is not VC-backed SaaS companies (62% are), this is not IPO-track SaaS companies (presumably some small subset of that 62%).  This is all private SaaS companies, including 22% PE-backed and 13% boostrapped.

One of my new benchmarking themes is that people need to pay more attention to matching their benchmarks with their aspirations. If your aspirations are to raise money from top VCs at a good valuation, my guess is you should be thinking 75th precentile of this data set; if they’re to IPO, you should be thinking 90th.

That said, let’s meet the Joneses, who have median:

  • ARR growth of 31%, lower than I’d hope.
  • Forecast 2022 ARR growth of 36%, so they’re planning to accelerate.  Everyone’s an optimist.
  • Expansion ARR of 46%, higher than I’d hope.
  • Net dollar retention (NDR) of 109%.
  • Customer acquisition cost (CAC) ratio of 1.2 blended, 1.8 new, and 0.6 expansion, in line with my expectations.
  • Gross churn of 14%, in line, perhaps a tad high, relative to my guess.
  • Available to renew (ATR) gross churn of 10%, but it’s hard to understand how ATR rate can be lower than gross churn rate [3].
  • Margin profile of 77% subscription, 73% blended.  In line.
  • Sales and marketing (S&M) expense of 40% of revenues.  They’re frugal, but they’re not growing that fast, either.
  • Free cashflow (FCF) margin of -5%.
  • New ARR per seller of $673K, which I if I understand, is what I’d call sales productivity.
  • Contract length and billing frequency of one year.
  • ARR/FTE of $143K, lower than I’d guess (for public companies it’s nearly double that).
  • Valuation of 6.1x ARR at their most recent round (in 2021 or later).

Since I don’t want to lift too many of their slides, I’ll extract just two.  The first shows S&M spend as a function of growth rate.

If there’s one area where you really need to look at metrics as a function of growth rate, it’s customer acquistion cost and, by extension S&M spend, on the theory that in enterprise SaaS you need to invest up front to grow.  Therefore a high-growth company is theoretically carrying the cost of as-yet-unproductive capacity where as a steady-state one is not.  You can see this pretty clearly here where the sub-20% growth companies spend 27% on S&M, which surprisingly drops to 17% at the 30-40% bucket, but then begins a steady upward march to 59% for those growing faster than 80%.

The second discusses a concept I’ve called The Rule of 56789

Here, KeyBanc is saying roughly what I say, which is [4]:

  • 5 years to $10M (5.6 years, per KCBM)
  • 6 years to $20M (7.1 years, but to $25M)
  • 7 years to $50M (7.6 years)
  • 8 years to $75M (they have no threshold here)
  • 9 years to $100M (9.3 years)

I’m glad they’re now tracking this, along with net burn rate (aka, cash conversion score) though I’d say their implied cash conversion scores are more efficient than I’d guess based on my experience and Bessemer’s data.

Overall, this is a seminal report for SaaS companies.  Every private SaaS company should read it.  Grab yours here.

Notes

[1]  In the sense that even a “bad” public SaaS company (dare I suggest Domo or C3 as two of my favorites to scrutinize) was still good enough to get public in the first place and ergo creme de la creme when viewed more broadly.

[2]  As I said in a recent speech, it’s the difference between benchmark off all SAT test takers and Ivy League applicants.  See slide 13 of this presentation.

[3]  KBCM calls this non-renewal rate, but I think it’s 1 – ATR churn.  The reason it’s hard to believe it’s lower is that it should be the same numerator over a smaller denominator.

[4]  I was looking at European 75th percentiles and they are looking at worldwide (but US-weighted) medians

Slides from a CFO Summit on Leading and Lagging Indicators

Just a quick post to share the slides of a presentation on leading, lagging, and predictive indicators that I gave at the recent Foundry CFO Summit.

  • It starts with a discussion of the importance of leading indicators, particularly as we head into an uncertain business environment.
  • It discusses go-to-market funnel and how leading indicators are basically up and lagging ones are down.
  • I observe that we’ve spent 30 years trying to get marketers to focus down-funnel, so we should care before suddently saying, go worry about names or responses.
  • We discuss whether you want to use a metric for prediction or management.  You can’t really pick both.
  • It concludes by suggesting an ICP re-evaluation that’s both qualitative (which use-cases should be more compelling in the new environment) and quantitative (which prospective customers look most like our existing successful ones).
  • The last point begs an interesting riff on what we mean by successful, which is far more of a greased-pig question than most realize.

The slides are here on slideshare, and here on Google Drive.  Thanks to Brian Weisberg for inviting me.