Category Archives: EPM

The Board View: Slides From My Presentation at Host Perform 2019

The folks at Host Analytics kindly asked me to speak at their annual conference, Host Perform 2019, today in Las Vegas and I had a wonderful time speaking about one of my favorite topics:  the board view of enterprise performance management (EPM) and, to some extent, companies and management teams in general.

Embedded below are the slides from the presentation.

Highlights from Host Perform 2019 General Session

I’m here in Vegas at the amazing Aria Hotel at Host Perform 2019, having been asked to come out and speak about one of my favorite topics – how boards see the work of finance and EPM.  That speech is tomorrow at 9:00 AM and I look forward to seeing you there.

Today started with a music video, a great re-interpretation of Joan Jett’s I Love Rock N Roll.  Here is my favorite lyric from the song:

I love EBITDA,

Who cares about stock-based compensation?

I love EBITDA,

So come and take the time and plan with me.

 

Ron Baden was subtly wearing a Life is Good cap (presumably as a tip of the proverbial hat to last year’s keynote, Burt Jacobs) as he did an introduction that covered his background – now 10 years with the company in almost as many different jobs, an introduction of the executive staff (along with 1980s photos of them), a history of EPM, and some discussion of Vector Capital’s acquisition of Host Analytics in December of last year.

He also discussed this year’s keynote speaker, Doc Hendley, founder of Wine to Water.

Ron discussed highlights of the go-forward plan, including:

  • International, goal to get 25% of sales from international
  • Channel development, goal to 33% of sales from channels
  • Vertical market solutions and specialist sales teams
  • Accelerated new product introduction
  • Office-of-CFO tuck-in acquisitions

He also discussed key trends that Host is seeing in EPM:

  • Digital capabilities (e.g., robotic process automation)
  • Next-wave EPM professionals
  • Mobile workforce support
  • Connected planning, getting models talking to each other
  • Integration of best-of-breed solutions
  • Hybrid cloud

IMG_0171

Ron had some fun demonstrating the granularity and context problems via a Netflix example (“who’s watching”) and a quick demonstration of Alexa’s non-fluency in finance. On the former point, the key idea is that AI/ML, for example in sales forecasting, will benefit greatly by knowing “who’s watching” (i.e., who’s selling) because much as different people like different genres of films, different sales reps have different patterns of forecasting (e.g., Sammy sandbag, Ollie optimist).

Ron also discussed the notion of the chief performance officer, as opposed to the chief financial officer – to focus the mission on improving performance, not on finance per se.  In my humble opinion most of the time when people talk about creating a new “O” it’s about trying to get a seat at the table (e.g., chief information officer back in the day, the chief information security officer in recent times, and the chief data officer today).

Since the CFO already has a seat at the table, I think Ron’s more talking about reframing the role and the vision of the CFO.  I agree – particularly when it comes to being able to answer questions that help improve business performance.  And, I believe, that if the CFO can’t migrate to being the CAO (chief answers officer) then the chief data officer (CDO) might well do it instead via data science and operations teams.  To be a bit paranoid, it’s a threat — not an existential threat, but a threat nevertheless — to the power of the office of the CFO.

Ron then showed a presumably future version of MyPlan which shows how to build task- and action-oriented EPM and how that can easily fit into a mobile device.  Ron’s a big believer that while spreadsheets and grid interfaces are great, that end-users fundamentally want to accomplish tasks that are best done not via a grid, but via an end-user-optimized, task-oriented interface like MyPlan.

They then performed the usual, multi-player, slice-of-life skit-demonstration (aka, “skidemo”) which is always fun, and always a challenge to execute with so many moving parts (i.e., people, real software, prototype software, videos, scene changes, characters, and costumes).  Despite a brief early wardrobe failure, the six-person team pulled it off just fine, taking the crowd “back to the future” of finance – with easy rolling forecasts that take just a minute to run and prescriptive analytics to help drive the planning process.  My favorite line:

“Where we’re going, we don’t need spreadsheets!”

The keynote speaker (coincidentally named “Doc” given the skit), founder of Wine to Water, Doc Hendley then took the stage to tell his story.  I won’t summarize it here, but it was genuine, moving, at times funny, and deeply compelling.

IMG_0174

Wine to Water focuses on providing clean water and sanitation to people around the world – while awareness of this is not as high as it should be, water-borne illness is the leading cause of death for children in many countries in the undeveloped world and directly and indirectly kills over 2M children a year and incapacitates another 10M people atop that. Preventing water-borne illness not only saves lives, but it also helps increase family income, reduces school absences, and generally strengthens the local developing economy.  Per the WHO, every one dollar invested yields $8 in benefits — a great cause and a great ROI.

If you’re interested in donating to Doc’s organization, Wine to Water, please go here.  If you’re at the conference, remember to stop by the Wine to Water booth and build some water filters.

It’s great to be here, I look forward to seeing everyone, and hope to see you at my speech bright and early tomorrow.

Speaking at Host Perform 2019

hostperform

Just a quick post to plug the fact that the kind folks at Host Analytics have invited me to speak at Host Perform 2019 in Las Vegas on May 20-22nd, and I’ll be looking forward to seeing many old friends, colleagues, customers, and partners on my trip out.

I’ll be speaking on the “mega-track” on Wednesday, May 22nd at 9:00 AM on one of my favorite topics:  how EPM, planning, and metrics all look from the board and C-level perspectives.  My official session description follows:

session

The Perform 2019 conference website is here and the overall conference agenda is here.  If you’re interested in coming and you’ve not yet registered yet, it’s not too late!  You can do so here.

I look forward to another great Perform conference this year and should be both tweeting (hashtag #HostPerform) and blogging from the conference.  I look forward to seeing everyone there.  And attend my session if you want to get more insight into how boards and C-level executives view reporting, planning, EPM, KPIs, benchmarks, and metrics.

The Next Chapter

This morning we announced that Vector Capital has closed the acquisition of Host Analytics.  As part of that transaction I have stepped down from my position of CEO at Host Analytics.  To borrow a line from The Lone Ranger, “my work is done here.”  I’ll consult a bit to help with the transition and will remain a friend of and investor in the company.

A Word of Thanks
Before talking about what’s next, let me again thank the folks who made it possible for us to quintuple Host during my tenure all while cutting customer acquisition costs in half, driving a significant increase in dollar retention rates, and making a dramatic increase in net promoter score (NPS).  Thanks to:

  • Our employees, who drove major productivity improvements in virtually all areas and were always committed to our core values of customer success, trust, and teamwork.
  • Our customers, who placed their faith in us, who entrusted us with their overall success and the secure handling of their enormously important data and who, in many cases, helped us develop the business through references and testimonials.
  • Our partners, who worked alongside us to develop the market and make customers successful – and often the most challenging ones at that.
  • Our board of directors, who consistently worked positively and constructively with the team, regardless of whether we were sailing in fair or foul weather.

We Laid the Groundwork for a Bright Future
When Vector’s very talented PR guy did his edits on the closing press release, he decided to conclude it with the following quote:

Mr. Kellogg added, “Host Analytics is a terrific company and it has been an honor lead this dynamic organization.  I firmly believe the company’s best days are ahead.”

When I first read it I thought, “what an odd thing for a departing CEO to say!”  But before jumping to change it, I thought for a bit.  In reality, I do believe it’s true.  Why do Host’s best days lie ahead?  Two reasons.

First, we did an enormous amount of groundwork during my tenure at Host.  The biggest slug of that was on product and specifically on non-functional requirements.  As a fan of Greek mythology, the technical debt I inherited felt like the fifth labor of Hercules, cleaning the Augean stables.  But, like Hercules, we got it done, and in so doing shored up the internals of a functionally excellent product and transformed our Hyderabad operation into a world-class product development center.  The rest of the groundwork was in areas like focusing the organization on the right metrics, building an amazing demand generation machine, creating our Customers for Life organization, running a world-class analyst relations program, creating a culture based on learning and development, and building a team of strong players, all curious about and focused on solving problems for customers.

Second, the market has moved in Host’s direction.  Since I have an affinity for numbers, I’ll explain the market with one single number:  three.  Anaplan’s average sales price is three times Host’s.  Host’s is three times Adaptive’s.  Despite considerable vendor marketing, posturing, positioning, haze, and confusion to the contrary, there are three clear segments in today’s EPM market.

  • Anaplan is expensive, up-market, and focused primarily on operational planning.
  • Adaptive is cheap, down-market, and focused primarily on financial planning.
  • Host is reasonably priced, mid-market, focused primarily on financial planning, with some operational modeling capabilities.

Host serves the vast middle where people don’t want (1) to pay $250K/year in subscription and build a $500K/year center of excellence to support the system or (2) to pay $25K/year only to be nickeled and dimed on downstream services and end up with a tool they outgrow in a few years.

Now, some people don’t like mid-layer strategies and would argue that Host risks getting caught in a squeeze between the other two competitors.  That never bothered me – I can name a dozen other successful SaaS vendors who grew off a mid-market base, including within the finance department where NetSuite created a hugely successful business that eventually sold for $9.3B.

But all that’s about the past.  What’s making things even better going forward?  Two things.

  • Host has significantly improved access to capital under Vector, including the ability to better fund both organic and inorganic growth. Funding?  Check.
  • If Workday is to succeed with its goals in acquiring Adaptive, all rhetoric notwithstanding, Adaptive will have to become a vendor able to deliver high-end, financial-focused EPM for Workday customers.  I believe Workday will succeed at that.  But you can’t be all things to all people; or, to paraphrase SNL, you can’t be a dessert topping and a floor wax.  Similarly, Adaptive can’t be what it will become and what it once was at the same time – the gap is too wide.  As Adaptive undergoes its Workday transformation, the market will switch from three to two layers, leaving both a fertile opening for Host in mid-market and a dramatically reduced risk of any squeeze play.  Relatively uncontested market space?  Check.

Don’t underestimate these developments.  Both these changes are huge.  I have a lot of respect for Vector in seeing them.  They say that Michelangelo could see the statue within the block of marble and unleash it.  I think Vector has clearly seen the potential within Host and will unleash it in the years to come.

What’s Next?
I don’t have any specific plans at this time.  I’m happily working on two fantastic boards already – data catalog pioneer Alation and next-generation content services platform Nuxeo.   I’ll finally have time to write literally scores of blog posts currently stalled on my to-do list.  Over the next few quarters I expect to meet a lot of interesting people, do some consulting, do some angel investing, and perhaps join another board or two.  I’ll surely do another CEO gig at some point.  But I’m not in a rush.

So, if you want to have a coffee at Coupa, a beer at the Old Pro, or – dare I date myself – breakfast at Buck’s, let me know.

Host Analytics + Vector Capital = Growth

I’m delighted to say that Host Analytics has signed a definitive agreement to be acquired by Vector Capital, a San Francisco private equity (PE) firm with over $4B in capital under management.  Before diving into some brief analysis of the deal, I want to thank Host Analytics customers, employees, partners, investors, and board of directors for everything they’ve done to help make this happen.

Going forward, I expect the company’s top three priorities to be growth, growth, and growth.  Why?  Given a large market opportunity and a company that’s executing well, it’s the right time to add fuel to the tanks.

Large Market Opportunity
To wit:

  • The total available market (TAM) for Host’s enterprise performance management (EPM) products is $12B.
  • The market, somewhat amazingly, remains less than 10% penetrated by cloud solutions, which means there is an enormous on-premises replacement opportunity.
  • The market, equally amazingly, still over-relies on Microsoft Excel for planning, budgeting, reporting – even sometimes stunningly consolidation – which represents an enormous greenfield opportunity.
  • Recent consolidation in the market (e.g., Workday’s acquisition and, in my opinion, up-market hijacking of Adaptive Insights) creates new space in various market segments

Executing Well
Host is wrapping up an excellent 2018 with strong sales growth (e.g., new subscriptions up 50%+ this quarter), record ending annual recurring revenue (ARR), historically high customer satisfaction (i.e., net promoter score), above-benchmark employee satisfaction — and we’ve been doing all that while transitioning to positive cashflow.  On the product front, we’ve been pumping out innovations (e.g., Host MyPlan, Host Dashboards) and have an exciting product roadmap.

Simply put, the company is executing on eight cylinders.  Strong execution plus large opportunity usually calls for one thing:  more fuel.

Shareholder Rotation
Host was well ahead of the market with its vision of cloud-based EPM and raised its first venture capital in 2008.  As some of our early investors are thinking about how to wrap up those funds, it’s the right time for a shareholder rotation where our last-phase investors are able to get liquidity and the company can get new investors who are focused on the next phase, i.e., the next five years of growth and scale.

That’s why I think “shareholder rotation” is the right way to think about this transaction — the old shareholders rotate out and Vector rotates in.  And I should note that our largest shareholder, StarVest Partners, is not rotating entirely out — they will remain a significant shareholder in the company going forward.

In many respects, things won’t change.  Host will remain focused on:

  • Delivering a complete EPM suite
  • Providing solutions for the Office of Finance
  • World-class professional services and support, and our desire to create Customers for Life
  • Partnership, working with other leaders to provide our customers with complete solutions
  • Product innovation, finding novel ways to help finance better partner with the business
  • Core values: trust, customer success, and teamwork

Other things will change.  We’ll see some new faces as we evolve and grow the company.  We’ll get the benefit of Vector’s internal management consultancy (i.e., the value creation team) to help drive best practices.  You should expect to see us accelerate growth through both organic means (e.g., scaling up sales, launching in new geographies) and inorganic means (e.g., follow-on acquisitions).

Thanks to our founder, serial entrepreneur Jim Eberlin, for creating the company.  Thanks to everyone who helped us get here.  Thanks to our board for its foresight and support.  Thanks to Vector for taking us forward.  And thanks to StarVest for coming along for the ride.  Onward, full speed ahead!

# # #

The New Gartner 2018 Magic Quadrants for Cloud Financial Planning & Analysis and Cloud Financial Close Solutions

If all you’re looking for is the free download link, let’s cut to the chase:  here’s where you can download the new 2018 Gartner Magic Quadrant for Financial Planning and Analysis Solutions and the new 2018 Gartner Magic Quadrant for Cloud Financial Close Solutions.  These MQs are written jointly by John Van Decker and Chris Iervolino (with Chris as primary author on the first and John as primary author on the second).  Both are deep experts in the category with decades of experience.

Overall, I can say that at Host Analytics, we are honored to a leader in both MQs again this year.  We are also honored to be the only cloud pure-play vendor to be a leader in both MQs and we believe that speaks volumes about the depth and breadth of EPM functionality that we bring to the cloud.

So, if all you wanted was the links, thanks for visiting.  If, however, you’re looking for some Kellblog editorial on these MQs, then please continue on.

Whither CPM?
The first thing the astute reader will notice is that the category name, which Gartner formerly referred to as corporate performance management (CPM), and which others often referred to as enterprise performance management (EPM), is entirely missing from these MQs.  That’s no accident.  Gartner decided last fall to move away from CPM as a uber category descriptor in favor of referring more directly to the two related, but pretty different, categories beneath it.  Thus, in the future you won’t be hearing “CPM” from Gartner anymore, though I know that some vendors — including Host Analytics — will continue to use EPM/CPM until we can find a more suitable capstone name for the category.

Personally, I’m in favor of this move for two simple reasons.

  • CPM was a forced, analyst-driven category in the first place, dating back to Howard Dresner’s predictions that financial planning/budgeting would converge with business intelligence.  While Howard published the research that launched a thousand ships in terms of BI and financial planning industry consolidation (e.g., Cognos/Adaytum, BusinessObjects/SRC/Cartesis, Hyperion/Brio), the actual software itself never converged.  CPM never became like CRM — a true convergence of sales force automation (SFA) and contact center.  In each case, the two companies could be put under one roof, but they sold fundamentally different value propositions to very different buyers and thus never came together as one.
  • In accordance with the prior point, few customers actually refer to the category by CPM/EPM.  They say things much more akin to “financial planning” and “consolidation and close management.”  Since I like referring to things in the words that customers use, I am again in favor of this change.

It does, however, create one problem — Gartner has basically punted on trying to name a capstone category to include vendors who sell both financial planning and financial consolidation software.  Since we at Host Analytics think that’s important, and since we believe there are key advantages to buying both from the same vendor, we’d prefer if there were a single, standard capstone term.  If it were easy, I suppose a name would have already emerged [1].

How Not To Use Magic Quadrants
While they are Gartner’s flagship deliverable, magic quadrants (MQs) can generate a lot of confusion.  MQs don’t tell you which vendor is “best” because there is no universal best in any category.  MQs don’t tell you which vendor to pick to solve your problem because different solutions are designed around meeting different requirements.  MQs don’t predict the future of vendors — last-year’s movement vectors rarely predict this year’s positions.  And the folks I know at Gartner generally strongly dislike vector analysis of MQs because they view vendor placement as relative to each other at any moment in time [2].

Many things that customers seem to want from Gartner MQs are actually delivered by Gartner’s Critical Capabilities reports which get less attention because they don’t produce a simple, dramatic 2×2 output, but which are far better suited for determine the suitability of different products to different use-cases.

How To Use A Gartner Magic Quadrant?
In my experience after 25+ in enterprise software, I would use MQs for their overall purpose:  to group vendors into 4 different bucketsleaders, challengers, visionaries, and niche players.  That’s it.  If you want to know who the leaders are in a category, look top right.  If you want to know who the visionaries are, look bottom right.  You want to know which big companies are putting resources into the category but who thus far are lacking strategy/vision, then look top-left at the challengers quadrant.

But should you, in my humble opinion, get particularly excited about millimeter differences on either axes?  No.  Why?  Because what drives those deltas may have little, none, or in fact a counter-correlation to your situation.  In my experience, the analysts pay a lot of attention to the quadrants in which vendors end up in [2] so quadrant-placement, I’d say, is quite closely watched by the analysts.  Dot-placement, while closely watched by vendors, save for dramatic differences, doesn’t change much in the real world.  After all, they are called the magic quadrants, not the magic dots.

All that said, let me wind up with some observations on the MQs themselves.

Quick Thoughts on the 2018 Cloud FP&A Solutions MQ
While the MQs were published at the end of July 2018, they were based on information about the vendors gathered in and largely about 2017.  While there is always some phase-lag between the end of data collection and the publication data, this year it was rather unusually long — meaning that a lot may have changed in the market in the first half of 2018 that customers should be aware of. For that reason, if you’re a Gartner customer and using either the MQs or critical capabilities reports that accompany them, you should probably setup an appointment to call the analysts to ensure you’re working off the latest data.

Here are some of my quick thoughts the Cloud FP&A Solutions magic quadrant:

  • Gartner says the FP&A market is accelerating its shift from on-premises cloud.  I agree.
  • Gartner allows three types of “cloud” vendors into this (and the other) MQ:  cloud-only vendors, on-premise vendors with new built-for-the-cloud solutions, and on-premises vendors who allow their software to be run hosted on a third-party cloud platform.  While I understand their need to be inclusive, I think this is pretty broad — the total cost of ownership, cash flows, and incentives are quite different between pure cloud vendors and hosted on-premises solutions.  Caveat emptor.
  • To qualify for the MQ vendors must support at least two of the four following components of FP&A:  planning/budgeting, integrated financial planning, forecasting/modeling, management/performance reporting.  Thus the MQ is not terribly homogeneous in terms of vendor profile and use-cases.
  • For the second year in a row, (1) Host is a leader in this MQ and (2) is the only cloud pure-play vendor who is a leader in both.  We think this says a lot about the breadth and depth of our product line.
  • Customer references for Host cited ease of use, price, and solution flexibility as top three purchasing criteria.  We think this very much represents our philosophy of complex EPM made easy.

Quick Thoughts on the 2018 Cloud Financial Close Solutions MQ
Here are some of my quick thoughts on the Cloud Financial Close Solutions magic quadrant:

  • Gartner says that in the past two years the financial close market has shifted from mature on-premises to cloud solutions.  I agree.
  • While Gartner again allowed all three types of cloud vendors in this MQ, I believe some of the vendors in this MQ do just-enough, just-cloud-enough business to clear the bar, but are fundamentally still offering on-premise wolves in cloud sheep’s clothing.  Customers should look to things like total cost of ownership, upgrade frequency, and upgrade phase lags in order to flesh out real vs. fake cloud offerings.
  • This MQ is more of a mixed bag than the FP&A MQ or, for that matter, most Gartner MQs.  In general, MQs plot substitutes against each other — each dot on an MQ usually represents a vendor who does basically the same thing.  This is not true for the Cloud Financial Close (CFC) MQ — e.g., Workiva is a disclosure management vendor (and a partner of Host Analytics).  However, they do not offer financial consolidation software, as does say Host Analytics or Oracle.
  • Because the scope of this MQ is broad and both general and specialist vendors are included, customers should either call the Gartner for help (if they are Gartner customers) or just be mindful of the mixing and segmentation — e.g., Floqast (in SMB and MM) and Blackline (in enterprise) both do account reconciliation, but they are naturally segmented by customer size (and both are partners of Host, which does financial consolidation but not account reconciliation).
  • Net:  while I love that the analysts are willing to put different types of close-related, office-of-the-CFO-oriented vendors on the same MQ, it does require more than the usual amount of mindfulness in interpreting it.

Conclusion
Finally, if you want to analyze the source documents yourself, you can use the following link to download both the 2018 Gartner Magic Quadrant for Financial Planning and Analysis and Consolidation and Close Management.

# # #

Notes

[1] For Gartner, this is likely more than a semantic issue.  They are pretty strong believers in a “post-modern” ERP vision which eschews the idea of a monolithic application that includes all services, in favor of using and integrating a series of cloud-based services.  Since we are also huge believers in integrating best-of-breed cloud services, it’s hard for us to take too much issue with that.  So we’ll simply have to clearly articulate the advantages of using Host Planning and Host Consolidations together — from our viewpoint, two best-of-breed cloud services that happen to come from a single vendor.

[2] And not something done against absolute scales where you can track movement over time.  See, for example, the two explicit disclaimers in the FP&A MQ:

Capture

[3] I’m also a believer in a slightly more esoteric theory which says:  given that the Gartner dot-placement algorithm seems to try very hard to layout dots in a 45-degree-tilted football shaped pattern, it is always interesting to examine who, how, and why someone ends up outside that football.

The Use of Ramped Rep Equivalents (RREs) in Sales Analytics and Modeling

[Editor’s note:  revised 7/18, 6:00 PM to fix spreadsheet error and change numbers to make example easier to follow, if less realistic in terms of hiring patterns.]

How many times have you heard this conversation?

VC:  how many sales reps do you have? 

CEO:  Uh, 25.  But not really.

VC:  What do you mean, not really?

CEO:  Well, some of them are new and not fully productive yet.

VC:  How long does it take for them to fully ramp?

CEO:  Well, to full productivity, four quarters.

VC:  So how many fully-ramped reps do you have?

CEO:  9 fully ramped, but we have 15 in various stages of ramping, and 1 who’s brand new …

There’s a better way to have this conversion, to perform your sales analytics, and to build your bookings capacity waterfall model.  That better way involves creating a new metric called ramped rep equivalents (RREs). Let’s build up to talking about RREs by first looking at a classical sales bookings waterfall model.

ramped rep equivalents, picture 1, revised

I love building these models and they’re a lot of fun to play with, doing what-if analysis, varying the drivers (which are in the orange cells) and looking at the results.  This is a simplified version of what most sales VPs look at when trying to decide next year’s hiring, next year’s quotas [1], and next year’s targets.  This model assumes one type of salesrep [2]; a distribution of existing reps by tenure as 1 first-quarter, 3 second-quarter, 5 third-quarter, 7 fourth-quarter, and 9 steady-state reps; a hiring pattern of 1, 2, 4, 6 reps across the four quarters of 2019; and a salesrep productivity ramp whereby reps are expected to sell 0% of steady-state productivity in their first quarter with the company, and then 25%, 50%, 75% in quarters 2 through 4 and then become fully productive at quarter 5, selling at the steady-state productivity level of $1,000K in new ARR per year [3].

Using this model, a typical sales VP — provided they believed the productivity assumptions [4] and that they could realistically set quotas about 20% above the target productivity — would typically sign up for around a $22M new ARR bookings target for the coming year.

While these models work just fine, I have always felt like the second block (bookings capacity by tenure), while needed for intermediate calculations, is not terribly meaningful by itself.  The lost opportunity here is that we’re not creating any concept to more easily think about, discuss, and analyze the productivity we get from reps as they ramp.

Enter the Ramped Rep Equivalent (RRE)
Rather than thinking about the partial productivity of whole reps, we can think about partial reps against whole productivity — and build the model that way, instead.  This has the by-product of creating a very useful number, the RRE.  Then, to get bookings capacity just multiply the number of RREs times the steady-state productivity.  Let’s see an example below:

ramped rep equivalents, picture 2, revised

This provides a far more intuitive way of thinking about salesrep ramping.  In 1Q19, the company has 25 reps, only 9 of whom are fully ramped, and rest combine to give the productivity of 8.5 additional reps, resulting in an RRE total of 17.5.

“We have 25 reps on board, but thanks to ramping, we only have the capacity equivalent to 17.5 fully-ramped reps at this time.”

This also spits out three interesting metrics:

  • RRE/QCR ratio:  an effective vs. nominal capacity ratio — in 1Q19, nominally we have 25 reps, but we have only the effective capacity of 17.5 reps.  17.5/25 = 70%.
  • Capacity lost to ramping (dollars):  to make the prior figure more visceral, think of the sales capacity lost due to ramping (i.e., the delta between your nominal and effective capacity) expressed in dollars.  In this case, in 1Q19 we’re losing $1,875K of our bookings capacity due to ramping.
  • Capacity lost to ramping (percent):  the same concept as the prior metric, simply expressed in percentage terms.  In this case, in 1Q19 we’re losing 30% of our bookings capacity due to ramping.

Impacts and Cautions
If you want to move to an RRE mindset, here are a few tips:

  • RREs are useful for analytics, like sales productivity.  When looking at actuals you can measure sales productivity not just by starting-period or average-period reps, but by RRE.  It will provide a much more meaningful metric.
  • You can use RREs to measure sales effectiveness.  At the start of each quarter recalculate your theoretical capacity based on your actual staffing.  Then divide your actuals by that start-of-quarter theoretical capacity and you will get a measure of how well you are performing, i.e., the utilization of the quarterly starting capacity in your sales force.  When you’re missing sales targets it is typically for one of two reasons:  you don’t have enough capacity or you’re not making use of the capacity you have.  This helps you determine which.
  • Beware that if you have multiple types of reps (e.g., corporate and field), you be tempted to blend them in the same way you do whole reps today –i.e., when asked “how many reps do you have?” most people say “15” and not “9 enterprise plus 6 corporate.”  You have the same problem with RREs.  While it’s OK to present a blended RRE figure, just remember that it’s blended and if you want to calculate capacity from it, you should calculate RREs by rep type and then get capacity by multiplying the RRE for each rep type by their respective steady-state productivity.

I recommend moving to an RRE mindset for modeling and analyzing sales capacity.  If you want to play with the spreadsheet I made for this post, you can find it here.

Thanks to my friend Paul Albright for being the first person to introduce me to this idea.

# # #

Notes
[1] This is actually a productivity model, based on actual sales productivity — how much people have historically sold (and ergo should require little/no cushion before sales signs up for it).  Most people I know work with a productivity model and then uplift the desired productivity by 15 to 25% to set quotas.

[2] Most companies have two or three types (e.g., corporate vs. field), so you typically need to build a waterfall for each type of rep.

[3] To build this model, you also need to know the aging of your existing salesreps — i.e., how many second-, third-, fourth-, and steady-state-quarter reps you have at the start of the year.

[4] The glaring omission from this model is sales turnover.  In order to keep it simple, it’s not factored in here. While some people try to factor in sales turnover by using reduced sales productivity figures, I greatly prefer to model realistic sales productivity and explicitly model sales turnover in creating a sales bookings capacity model.

[5] This is one reason it’s so expensive to build an enterprise software sales force.  For several quarters you often get 100% of the cost and 50% of the sales capacity.

[6] Which should be an weighted average productivity by type of rep weighted by number of reps of each type.