Category Archives: QCR

The Holy Grail of Enterprise Sales: Defining the Repeatable Sales Process

(This is the first in a three-part restructuring and build-out of the prior post.  See note [1] for details.)

The number one question go-to-market question in any enterprise software startup is:  “do you have a repeatable sales process?” or, in more contemporary Silicon Valley patois, “do you have a repeatable sales motion?”

It’s one of the key milestones in startup evolution, which proceed roughly like:

  • Do you have a concept?
  • Do you have a working product?
  • Do you have any customer traction (e.g., $1M in ARR)?
  • Have you established product-market fit?
  • Do you have a repeatable sales process?

Now, when pressed to define “repeatable sales process,” I suspect many of those asking might reply along the same lines as the US Supreme Court in defining pornography:

“I shall not today attempt further to define the kinds of material I understand to be embraced… but I know it when I see it …”

That is, in my estimation, a lot of people throw the term around without defining it, so in the Kelloggian spirit of rigor, I thought I’d offer my definition:

A repeatable sales process means you have six things:

  1. Standard hiring profile
  2. Standard onboarding program
  3. Standard support ratios
  4. Standard patch
  5. Standard kit
  6. Standard sales methodology

All of which contribute to delivering a desirable, standard result.  Let’s take a deeper look at each:

  1. You hire salesreps with a standard hiring profile, including items such as years of experience, prior target employers or spaces, requisite skills, and personality assessments (e.g., DiSC, Hogan, CCAT).
  2. You give them a standard onboarding program, typically built by a dedicated director of sales productivity, using industry best practices, one to three weeks in length, and accompanied by ongoing clinics.
  3. You have standard support ratios (e.g., each rep gets 1/2 of a sales consultant, 1/3 of an SDR, and 1/6 of a sales manager).  As you grow, your sales model should also use ratios to staff more indirect forms of support such as alliances, salesops, and sales productivity.
  4. You have a standard patch (territory), and a method for creating one, where the rep can be successful.  This is typically a quantitative exercise done by salesops and ideally is accompanied by a patch-warming program [2] such that new reps don’t inherit cold patches.
  5. You have standard kit including tools such as collateral, presentations, demos, templates.  I strongly prefer fewer, better deliverables that reps actually know how to use to the more common deep piles of tools that make marketing feel productive, but that are misunderstood by sales and ineffective.
  6. You have a standard sales methodology that includes how you define and execute the sales process.  These include programs ranging from the boutique (e.g., Selling through Curiosity) to the mainstream (e.g., Force Management) to the classic (e.g., Customer-Centric Selling) and many more.  The purpose of these programs is two-fold:  to standardize language and process across the organization and to remind sales — in a technology feature-driven world — that customers buy products as solutions to problems, i.e., they buy 1/4″ holes, not 1/4″ bits.

And, most important, you can demonstrate that all of the above is delivering some desirable standard result, which will be the topic of the next post.

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[1] I have a bad habit, which I’ve been slowly overcoming, to accidently put real meat on one topic into an aside of a post on a different one.  My favorite example:  it took me ~15 years to create a post on my marketing credo (marketing exists to make sales easier) despite mentioning it in passing in numerous posts.  After reading the prior post, I realized that I’d buried the definition of a repeatable sales model and the tests for having one into a post that was really about applying CMMI to the sales model.  Ergo, as my penance, as a service to future readers, and to help my SEO, I am decomposing that post into three parts and elaborating on it during the restructuring process.

[2] I think of patch-warming as field marketing for fallow patches.  Much as field marketing works to help existing reps in colder patches, why can’t we apply the same concepts to patches that will soon be occupied?  This is an important, yet often completely overlooked, aspect of reducing rep ramping time.

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

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.

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[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.