Category Archives: Sales

The SaaS Rule of 40

After the SaaSacre of early 2016, investors generally backed off a growth-at-all-costs mindset and started to value SaaS companies using an “appropriate” balance of growth and profitability.  The question then became, what’s appropriate?  The answer was:  the rule of 40 [1].

What’s the rule of 40?  Growth rate + profit should be greater than or equal to 40%.

There are a number of options for deciding what to use to represent growth (e.g., ARR) and profit (e.g., EBITDA, operating margin). For public companies it usually translates to revenue growth rate and free cash flow margin.

It’s important to understand that such “rules” are not black and white.  As we’ll see in a minute, lots of companies deviate from the rule of 40.  The right way to think about these rules of thumb is as predictors.  Back in the day, what best predicted the value of a SaaS company?  Revenue growth — without regard for margin.  (In fact, often inversely correlated to margin.)  When that started to break down, people started looking for a better independent variable.  The answer to that search was the rule of 40 score.

Let’s examine a few charts courtesy of the folks at Pacific Crest and as presented at the recent, stellar Zuora CFO Forum, an CFO gathering run alongside their Subscribed conference.


This scatter chart plots the two drivers of the rule of 40 score against each other, colors each dot with the company’s rule of 40 score, and adds a line that indicates the rule of 40 boundary.  42% of public SaaS companies, and 77% of public SaaS market cap, is above the rule of 40 line.

As a quick demonstration of the exception to every rule principle, Tintri recently went public off 45% growth with -81% operating margins, [2] reflecting a rule of 40 score of -36, and a placement that would be off the chart, in the underneath sense, even if corrected for non-cash expenses.

But for those interested in company valuations, the more interesting chart is this one.

rule of 40 valuation.PNG

This chart plots rule of 40 score on the X axis, valuation multiple on the Y axis, and produces a pretty good regression line the shows the relationship between the two.  In short, the rule of 40 alone explains nearly 50% of SaaS company valuation.  I’d guess that outliers fall into one of two categories:

  • Companies in a strategic situation that explains the premium or discount relative to the model — e.g., the premium for Cloudera’s strong market position in the Hadoop space.
  • Companies whose valuations go non-linear at the high end due to scarcity — e.g., Veeva.

Executives and employees at startups should understand [3] the rule of 40 as it explains the general tendency of SaaS companies to focus on a balance of growth and profitability as opposed to a growth at all costs strategy that was more popular several years back.  Ignore the rule of 40 at your peril.


[1] While the Rule of 40 concept preceded the SaaSacre, I do believe that the SaaSacre was the wake-up call that made more investors and companies pay attention to.

[2] Using operating margin here somewhat lazily as I don’t want to go find unlevered free cash flow margin, but I don’t think it materially changes the point.

[3] Other good rule of 40 posts are available from:  Tomasz Tungaz, Sundeep Peechu, Jeff Epstein and Josh Harder.

Detecting and Eliminating the Rolling Hairballs in your Sales Pipeline

Quick:  what’s the biggest deal in this quarter’s sales pipeline?  Was that the biggest deal in last quarter’s pipeline?  How about the quarter before?  Do you have deals in your pipeline older than your children?

If you’re answering yes to these questions, then you’re probably dealing with “rolling hairballs” in your pipeline.  Rolling hairballs are bad:

  • They exaggerate the size of the pipeline.
  • They distort coverage and conversion ratios.
  • They mess up expected-value forecasts, like a forecast-category or stage-weighted sales forecast.

Maybe they’re real deals; maybe they’re figments of a rep’s imagination.  But, if you’re not careful, they pollute your pipeline and your metrics.

Let’s define a rolling hairball

A rolling hairball is a typically large opportunity that sits in your current-quarter pipeline every quarter, with a close date that slips every quarter.  At 2 quarters it’s a suspected rolling hairball; at 3 or more quarter’s it’s a confirmed one.

Rolling Hairball Detection

The first thing you need to do is find rolling hairballs.  They’re tricky because salesreps always swear they’re real deals that are supposed to finally close this quarter.  What makes rolling hairballs obvious is their ever-sliding close dates.  What makes them dangerous is their size (including an accumulation of them that aggregate to a material fraction of the pipeline).

If you want to find rolling hairballs, look for opportunities in the current-quarter pipeline that were also in last-quarter’s pipeline.  That will find numerous bona fide slipped deals, but it will also light-up potential rolling hairballs.  To determine if an opportunity is  a rolling hairball, for sure, you can do one of two things:

  • See if it also appeared in the current-quarter pipeline in any quarters prior to the previous one.
  • Look at its stage or forecast category.  If either of those suggest it won’t be closing this quarter, it’s another big hairball indicator.

The more sophisticated way to find them is to examine “stuck opportunity” reports that light-up deals that are moving through pipeline stages too slowly compared to your norms.

But typically, the hairball is a big opportunity hiding in plain sight.  You know it was in last quarter’s pipeline and the quarter before that.  You’ve just been deluded into believing it’s not a hairball.

Fixing Rolling Hairballs

There are two ways to fix rolling hairballs:

  • Fix the close date.  Reps are subtly incented to put deals in the current quarter (e.g., to show they’re working on something, to show they might bring in some big sales this quarter). The manager needs to get on the phone with the customer and, after having verified it’s a real opportunity, get the real timeframe in which it might close.  Assigning a realistic close date to the opportunity makes your pipeline more real and reminds the rep that they need to be working on other shorter-term opportunities as well.  (There is no mid-term if you fail enough in the short term.)  The deal will still remain in the all-quarters pipeline, but it won’t always be in the current-quarter pipeline, ever-sliding, and distorting metrics and ratios.


  • Fix the size. While a realistic close date is the best solution, what makes rolling hairballs dangerous is their size.  So, if the salesrep really believes it’s a current-quarter opportunity, you can either reduce its size or split it into two opportunities (particularly if that’s a possible outcome), a small one in the current quarter along with an upsell in the future.  Note that this approach can be dangerous, with lots of little hairball-lets flying below radar, so you should only try if it you’re sure your salesops team can produce the reports to find them and if you believe it reflects real customer buying patterns.

Don’t let rolling hairballs pollute your pipeline metrics and ratios.  Admit they exist, find them, and fix them.  Your sales and sales forecasting will be more consistent as a result.

How to Train Your VP of Sales to Think About the Forecast

Imagine a board meeting.

Director:  What’s the forecast for new ARR this quarter?

Sales VP:  $4.3M, with a best case of $5.0M.

Director:  So what’s the most likely outcome?

Sales VP:  $4.3M.

Director:  What are you really going to do?  (The classic noob trap question.)

Sales VP:  I think we can come in North of that.

Director:  What’s the worst case?

Sales VP:  $3.5M.

Director:  What are the odds of coming in at or above the forecast? 

Sales VP:  I always make my forecast.

Director:   What do you mean by worst case?

Sales VP:  You know, well, if the stars align in a bad way – a lot of stuff would have to go wrong – but if that happened, then we could end up at $3.5M.

Director:  So, let’s say a 10% chance of being at/below the worst case?

Sales VP:  I’d say more like 5%.

Director:  What do you mean by best case?

Sales VP:  Well, if we really struck it rich and everything lined up just the way I wanted, that would be best case.

Director:  You mean if all the deals came in — so best case basically equals pipeline?

Sales VP:  No, that never happens, I’ve made about 10 scenarios of different deal closing combinations and in 2 of them I can get to the best case.

You see the problem?  Does it sound familiar?  Do you realize how much time we spend talking in board meetings about “forecast,” “best case,” and “worst case” without every discussing what we mean by those terms?

Do you see how this is compounded by the sales VP’s natural, intuitive view of the outcomes?  Do you see the obvious mathematical contradictions?  “I always make my forecast” says it’s a 100% number, but then the VP says it’s the “most likely” number which implies 50%.  Then the VP says there’s a 5% chance of coming in at/less than worst case (which is much lower) and then kind of implies that there’s a 20% chance of beating best case – but the 2 out of 10 is meaningless because it’s not a probability, it’s just a count of scenarios.  Nothing adds up.

The result is, if you’re not careful, the board ends up counting angels on pinheads.  What can we do to fix this?  It’s simple:  teach (and if need be, force) your sales VP to think probabilistically.  Ask him/her how often:

  • It is reasonable to miss the forecast.  A typical answer might be 10%.
  • It is likely to come in at/below the worst case? Typical answer, 5%.
  • It is likely to meet/beat the best case? Typical answer, 20%.

So, with those three questions, we’ve now established that we want the sales VP to give us:

  • A 90% number on being at/above the forecast
  • A 20% number on being at/above the best case
  • A 5% number on being at/below the worst case

Put differently, when the sales VP decides what number to forecast that they should be thinking:

  • I should come in under my forecast once every 2.5 years (10 quarters).
  • I should hit/beat the best case about once every 5 quarters (a bit less than once a year).
  • I should come in/under the worst case once every 20 quarters (once every 5 years, or for most minds, basically never).

The beauty here is that when you work at a company a long time you can get enough quarters under your belt, to start really seeing how you’re doing relative to these frequencies.  What’s more, by converting the probabilities into frequencies (e.g., once every 10 quarters) you make it more intuitive for the sales VP and the organization to think this way.

In addition, you have a basis for conversations like this one which, among other things, is about overconfidence:

CEO:  You need to work on your forecasting.

Sales VP:  You know it’s hard out there, very competitive, and we don’t have much deal flow.  Back when I was at { Salesforce | Oracle | SAP }, I was much better at forecasting because we had more volume.

CEO:  But we agreed your forecast should be a 90% number and you’ve missed it 2 out of the past 4 quarters.

Sales VP:  Yes, but as I’ve said it’s tough to forecast in this market.

CEO:  Then forecast a lower number so you can beat it 90% of the time.  I’m asking you for a 90% number and empirically you’re giving me a 50% number. 

Sales VP:  OK.

CEO:  Plus, when those two big deals slipped last quarter you didn’t drop your forecast, why?

Sales VP:  Because where I grew up, you don’t cut the forecast.  You try like crazy to hold it.  Do you know the morale problems it causes when I cut the forecast – especially if it’s below plan? So, yes, when those two deals slipped it added more risk to the forecast – and I told you and the board that — but I didn’t cut forecast, no. 

CEO:  But “adding risk” here is meaningless.  In reality, “adding risk” means it’s not a 90% number anymore.  You’ve taken what was a 90% number and it’s now more like a 60% or 70% number.  So I want you to forget what they taught you growing up in sales and always – every week – give me a number that based on all available information you are 90% sure you can beat.  If that means dropping the forecast so be it.

sales forecast

This also helps with the board and the inevitable sandbagger issue.  In my experience (and with a bit of exaggeration) you always seem to be in one of two situations:  (1) intermittently missing plan and in trouble or (2) consistently making plan and a “sandbagger” – it feels like there’s nothing in between.

Well, if you establish with the board that your company forecast is a 90% number it means you are supposed to beat it 9 times out of 10 so you can only really be labelled a sandbagger when you’re 15 for 15 or 20 for 20.  It also reminds them that you’re supposed to arrive at the forecast so that you miss once every 10 quarters so they shouldn’t freak out if once every 2.5 years if that happens — it’s supposed to happen in this system.  (Just don’t let a once-in-ten-quarter event happen twice in a row.)

I like this quantitative basis for sales forecasting and I carry it down to the salesrep and pipeline level.  I believe that each “forecast category” should have a probability associated with it.  For example, at the opportunity level, you should link probabilities to categories, such as:

  • Commit = 90%
  • Forecast = 70%
  • Upside = 30%

This, in turn, means that over time, a given salesrep should close 90% of their committed deals, 70% of their forecast deals, and 30% of their upside.  Deviations from this over time indicate that the rep is mis-categorizing the deals because the probability should be the basis for the forecast category assignment [1].

Finally, I do believe that salesreps should give quarterly forecasts [2] that reflect their sense for how things will come in given all the odd things that can happen to deals (e.g., size changes, acceleration, slippage).  I believe those forecasts should be a 70% number because the sales manager will be managing across a  portfolio of them and while there is little room for a company to miss at the VP of Sales level, there is more room for and more variance in performance across salesreps.

While I know this will not necessarily come naturally to all sales VPs — and some may push-back hard — this is a simple, practical, and rigorous way to think about the forecast.

# # #

[1] Some people do this through an independent (orthogonal) field in the CRM system called probability.  I think that’s unnecessary because in my mind forecast category should effectively equal probability and your options for picking a probability should be bucketed.  No one can say a deal is 43% vs. 52% and forecast category doesn’t indicate some probability of closing, then … what use is it and on what basis should you classify something as forecast vs. upside?

[2] Some people believe that only managers should make forecasts, but I believe both reps and managers should forecast for two reasons:  (1) provided it’s left independent and not “managed” by the managers, the aggregated salesrep-level forecast provides another, Wisdom of Crowds-y, view into the sales forecast and (2) it’s never too early to teach salesreps how to forecast which is best learned through the experience of trial and error over many quarters.

Aligned to Achieve: A B2B Marketing Classic

Tracy Eiler and Andrea Austin’s Aligned to Achieve came out today and it’s a great book on an important and all too often overlooked topic:  how to align sales and marketing.

I’m adding it to my modern SaaS executive must-read book list, which is now:

So, what do I like about Aligned to Achieve?

The book puts a dead moose issue squarely on the table:  sales and marketing are not aligned in too many organizations.  The book does a great job of showing some examples of what misalignment looks like.  My favorites were the one where the sales VP wouldn’t shake the new CMO’s hand (“you’ll be gone soon, no need to get to know you”) and the one where sales waived off marketing from touching any opportunities once they got in the pipeline.  Ouch.  #TrustFail.

Aligned to Achieve makes great statements like this one:  “We believe that pipeline is absolutely the most important metric for sales and marketing alignment, and that’s a major cultural shift for most companies.”  Boom, nothing more to say about that.

The book includes fun charts like the one below.  I’ve always loved tension-surveys where you ask two sides for a view on the same issue and show the gap – and this gap’s a doozy.

sm gap

Aligned to Achieve includes the word “transparency” twenty times.  Transparency is required in the culture, in collaboration, in definitions, in planning, in the reasons for plans, in process and metrics, in data, in assessing results, in engaging customers, and in objectives and performance against them.  Communication is the lubricant in the sales/marketing relationship and transparency the key ingredient.

The book includes a nice chapter on the leadership traits required to work in the aligned environment:  collaborative, transparent, analytical, tech savvy, customer focused, and inspirational.  Having been a CMO fifteen years ago, I’d say that transparent, analytical, and tech savvy and now more important than ever before.

Aligned to Achieve includes a derivative of my favorite mantra (marketing exists to make sales easier) in the form of:

Sales can’t do it alone and marketing exists to make sales easier

The back half of that mantra (which I borrowed from CTP co-founder Chris Greendale) served me well in my combined 12 years as a CMO.  I love the insertion of the front half, which is now more true than ever:  sales has never been more codependent with marketing.

The book includes a fun, practical suggestion to have a bi-monthly “smarketing” meeting which brings sales and marketing together to discuss:

  • The rolling six-week marketing campaign calendar
  • Detailed review of the most recently completed campaigns
  • Update on immediately pending campaigns
  • Bigger picture items (e.g., upcoming events that impact sales and/or marketing)
  • Open discussion and brainstorming to cover challenges and process hiccups

Such meetings are a great idea.

Back in the day when Tracy and I worked together at Business Objects, I always loved Tracy’s habit of “crashing” meetings.  She was so committed to sales and marketing alignment – even back then – that if sales were having an important meeting, invited or not, she’d just show up.  (It always reminded me of the Woody Allen quote, 80% of success is showing up.)  In her aligned organization today, the CEO makes sure she doesn’t have to do that, but by hook or by crook the sales/marketing discussion must happen.

Aligned to Achieve has a nice discussion of the good old sales velocity model which, like my Four Levers of SaaS, is a good way to think about and simplify a business and the levers that drive it.

Unsurprisingly, for a book co-authored by the CMO of a company that sells market data and insights, Aligned to Achieve includes a healthy chapter on the importance of data, including a marketing-adapted version of the DIKW pyramid featuring data, insights, and connections as the three layers.  The nice part is that the chapter remains objective and factual – it doesn’t devolve into an infomercial by any means.

The book moves on to discuss the CIO’s role in a sales/marketing-aligned organization and provides a chapter reviewing the results of a survey of 1000 sales and marketing professionals on alignment, uncovering common sources of misalignment and some of the practices used by sales/marketing alignment leaders.

Aligned to Achieve ends with a series of 7 alignment-related predictions which I won’t scoop here.  I will say that #4 (“academia catches up”) and #6 (“account-based everything is a top priority”) are my two favorites.

Congratulations to my long-time friend and colleague Tracy Eiler on co-authoring the book and to her colleague Andrea Austin.

The Four Levers of SaaS

There are a lot of SaaS posts out there with some pretty fancy math in them.  I’m a math guy, so I like to geek on SaaS metrics myself.  But, in the heat of battle running a SaaS company, sometimes you just need to keep it simple.

Here’s the picture I keep on my wall to help me do that.

It reminds me that new ARR in any given period is the product of four levers.

  • The MQL to stage 2 opportunity conversion rate (MTS2CR), the rate at which MQLs convert to stage 2, or sales-accepted, opportunities.  Typically they pass through a stage 1 phase first when a sales development rep (SDR) believes there is a real opportunity, but a salesperson has not yet agreed.
  • The stage 2 to close rate (S2TCR), the rate at which stage 2 opportunities close into deals, and avoid being lost to a competitor or derailed (e.g., having the evaluation project cancelled).
  • The annual recurring revenue average sales price (ARR ASP), the average deal size, expressed in ARR.

That’s it.  Those four levers will predict your quarterly new ARR every time.

Aside:  before diving into each of the four levers, let me note that sales velocity is omitted from this model.  That keeps it simple, but it does overlook a potentially important lever.  So if you think you have a sales velocity (i.e., sales cycle length) problem, go look at a different model that includes this lever and suggests ways to decrease it.

So now that we have identified the four levers, let’s focus on what we can do about them in order to increase our quarterly new ARR.

Marketing Qualified Leads (MQLs)

Getting MQLs is the domain of marketing, which should be constantly measuring the cost effectiveness of various marketing programs in terms of generating MQLs (cost/MQL).  This isn’t easy because most leads will require numerous touches over time in order to graduate to MQL status, but marketing needs to stay atop that complexity (e.g., by assigning credits to various programs as MQL-threshold points accumulate).

The best marketers understand the demand is variable and have designed their programs mix so they can scale spending quickly in response to increased needs.  Nothing is worse than an MQL shortage and a marketing department that’s not ready to spend incremental money to address it.

The general rule is to constantly A/B test your programs and nurture streams and do more of what’s working and less of what isn’t.

MQL to Stage 2 Opportunity Conversion Rate

Increasing the MQL to stage 2 opportunity conversion rate (MTS2CR) requires either generating better MQLs or doing a better job handling them so that they convert into stage 2 opportunities.

Generating better MQLs can be accomplished by analyzing past programs to determine which generated the best-converting MQLs and increasing them, putting a higher gate on what you pass over to sales (using predictive or behavioral scoring), or using buyer personas to optimize what you say to buyers, when, and through which channels.

Do a better job handling your existing MQLs comes down ensuring your operational processes work and you don’t let leads fall between the cracks.  Basic activity and aging reports are a start.  Establishing a formal service-level agreement between sales and marketing is a common next step.

Moving up a level and checking that your whole process fits well with the customer’s buying journey is also key.  While each step of your process might individually make sense, when assembled the process may not — e.g., are you irritating customers by triple-qualifying them with an SDR, a salesrep, and a solution consultant each doing basic discovery?

The Stage 2 to Close Rate

Once created, one of three things can happen to a stage 2 opportunity:  you can win it, you can lose it, or it can derail (i.e., anything else, such as project cancellation or “slips” to the distant future).

Increasing your win rate can be accomplished through better product positioning, sales tools, and sales training, improved competitive intelligence, improved buzz/aura, improved case studies and customer references, and better pricing and discounting strategy.  That’s not to mention more strategic approaches via improved sales methodology and process or product improvements, in terms of functionality, non-functional requirements, and product design.

Decreasing your loss rate can be accomplished through better up-front sales qualification, better sales tools and training, improved competitive strategy and tactics, and better pricing and discounting.  Improved sales management can also play a key role in catching in-trouble deals early and escalating to get the necessary resources deployed to win.

Reducing your derail rate is hard because project slips or cancellations seem mostly out of your control.  What’s the best way to reduce your derail rate?  Focus on velocity — take deals off the table before the company has a chance to prioritize another project, do a reorganization, or hire a new executive that kills it.  The longer a deal hangs around, the more likely something bad happens to it.  As the adage goes, time kills all deals.


The easiest way to increase ARR ASP is to not shrink it through last-minute discounting.  Adopt a formal discount policy with approvals so that, in the words of one famous sales leader, “your rep is more afraid of his/her sales manager than the customer” when it comes to speaking about discounts.

Selling value and product differentiation are two other discount reduction strategies.  The more customers see real value and a concrete return for their business the less they will focus on price.  Additionally, the more they see your offering as unique, the less price pressure you will face from the competition.  Conversely, the more they see your product as a cost and your company as one of several suppliers from whom they can buy the same capabilities, the more discount pressure you will face.

Up-selling to a higher edition or cross selling (“fries with your burger?”) are both ways to increase your ASP as well.  Just be careful to avoid customers feeling nickled and dimed in the process.

For SaaS businesses, remember that multi-year deals typically do not help your ARR ASP (though, if prepaid, they do help with year-one cash).  In fact, it’s usually the opposite — a small ARR discount is typically traded for the multi-year commitment.  My general rule of thumb is to offer a multi-year discount that’s less than your churn rate and everybody wins.


Hopefully this framework will make it easier for you to diagnose and act upon the problems that can impede achieving your company’s new ARR goals.  Always remember that any new ARR problem can be broken down into some combination of an MQL problem, an MQL to stage 2 conversion rate problem, a stage 2 to close rate problem, or an average sales price problem.  By focusing on these four levers, you should be able to optimize the productivity of your SaaS sales model.



Book Review:  From Impossible to Inevitable

This post reviews Aaron Ross and Jason Lemkin’s new book, From Impossible to Inevitable, which is being launched at the SaaStr Conference this week.  The book is a sequel of sorts to Ross’s first book, Predictable Revenue, published in 2011, and which was loaded with great ideas about how to build out your sales machine.

From Impossible to Inevitable is built around what they call The Seven Ingredients of Hypergrowth:

  1. Nail a niche, which is about defining your focus and ensuring you are ready to grow. (Or, as some say “nail it, then scale it.)  Far too many companies try to scale it without first nailing it, and that typically results in frustration and wasted capital.
  2. Create predictable pipeline, which about “seeds” (using existing successful customers), “nets” (classical inbound marketing programs), and “spears” (targeted outbound prospecting) campaigns to create the opportunities sales needs to drive growth.
  3. Make sales scalable, which argues convincingly that specialization is the key to scalable sales. Separate these four functions into discrete jobs:  inbound lead handing, outbound prospecting, selling (i.e., closing new business), and post-sales roles (e.g., customer success manager).  In this section they include a nice headcount analysis of a typical 100-person SaaS company.
  4. Double your deal size, which discusses your customer mix and how to build a balanced business built off a run-rate business of average deals topped up with a lumpier enterprise business of larger deals, along with specific tactics for increasing deal sizes.
  5. Do the time, which provides a nice reality check on just how long it takes to create a $100M ARR SaaS company (e.g., in a great case, 8 years, and often longer), along with the wise expectations management that somewhere along the way you’ll encounter a “Year of Hell.”
  6. Embrace employee ownership, which reminds founders and executives that employees are “renting, not owning, their jobs” and how to treat them accordingly so they can act more like owners than renters.
  7. Define your destiny, which concludes the book with thoughts for employees on how to take responsibility for managing their careers and maximizing the opportunities in front of them.

The book is chock full of practice advice and real-world stories.  What it’s not is theoretical.  If Crossing the Chasm offered a new way of thinking about product lifecycle strategy that earned it a place on the top shelf of the strategy bookcase, From Impossible to Inevitable is a cookbook that you keep in the middle of the kitchen prep table, with Post-It’s sticking out the pages and oil stains on the cover.  This is not a book that offers one big idea with a handful of chapters on how to apply it.  It’s a book full of recipes and tactics for how to improve each piece of your go-to-market machine.

This book — like Predictable Revenue, The Lean Startup, Zero to One, and SalesHood — belongs on your startup executive’s bookshelf.  Read it!  And keep up with Jason’s and Aaron’s great tweetstreams and the awesome SaaStr blog.

A Disney Parking Lot Attendant Gets More Training than Your Typical $250K Enterprise Sales Rep: Thoughts on Bootcamps

At Disney — a company that is truly focused on customer experience — every “cast member” (i.e., employee) gets six weeks of training before they see a “guest” (i.e., customer). “Face characters” (e.g., Snow White walking through the park) spend an additional 40 hours just watching and re-watching the movie to ensure they get every nuance right.

Oh, and how much training does your company give your $250K enterprise salesreps?

Anecdotally, I think the typical answer is a one-week bootcamp. Two weeks is on the long side. Once in a blue moon, you’ll hear 4 to 6 weeks, but that’s typically one to two weeks of corporate training followed by two to four weeks of deep technical training.

This is genuinely strange because a typical enterprise software or SaaS company freely spends between 40% and 100% of revenue on sales. Sales is typically the single biggest expense line in the firm. Sales runs 2-5x cost of goods sold.  It runs 2-5x R&D expense.  So, if we’re going to spend all this money on salespeople, then why don’t we want to train them?

I think there are a number of rationalizations:

  • “We hire experienced people so we don’t need to.” This is dangerous because your new people are experienced at someone else’s company and may have learned norms quite different from those you desire at yours.
  • “We train them on the job.” Either by throwing them in the pool and seeing if they sink or by building a conveyor-belt model where we hire folks as in-bound call-takers who we promote into outbound call-makers then into SMB reps then into mid-market reps. While there is nothing wrong with these models and they do very much help develop reps, it still doesn’t answer why we don’t give them deep training at the start.
  • “We never really developed it as a competency.” When you only have three reps you’re not going to create a six-week training program because — among other reasons — you don’t know what to teach. But as you scale your business that quickly becomes more excuse than reason.

I think the root answer is simple: most senior executives just don’t believe in training. (Think: “those who can, do; those who can’t, teach; and those who can’t teach do marketing.”)

Having competed against the output of some great internal training programs at Oracle and MicroStrategy, having created and run Business Objects University for several years, and then having gone through the outstanding on-boarding program at Salesforce, I’d like to share some perspective.

First, given my experience I would argue that by far the #1 key success criteria for these programs is a dictum from the CEO that they are important, they will be funded, and the organization will support them. Barring that, they get launched to lots of hype and then slowly erode into a self-fulfilling prophecy of mediocrity.

Here are some thoughts on how to run a great bootcamp.

  • Make it mandatory. Everybody goes. No one is too important to skip it from the new accountant to the new COO.
  • Make it long. Shoot for two weeks, minimum. Three is better. A double-dip is probably best of all (2 weeks initially followed by 3 months on the job followed by 2 weeks of reinforcement.)
  • Do it live. Some virtual pre-work and post-work is fine, but the core of your program should be live and in person. It shows commitment. It helps people build relationships. It enables better progress tracking and assessment.
  • Engage practitioners. Don’t learn how to sell from only a bootcamp trainer; hear from one of your top 5 reps on a rotating basis. (And pulling those top reps out of the field is an example of just one thing requires top-level support for the program.
  • Teach culture. Hit values. Train in how you define “The Your-Company Way.”
  • Be operational. Teach how the company wants deals entered in the pipeline, what your stage definitions are, and how to value deals. (These are critical items to maintaining a comparable set of pipeline metrics over time.)
  • Mix up the format. Have lectures, panels, individual exercises, group projects, videos, homework, reading, and team building exercises. Where applicable, do a volunteering session. (If volunteering is a key part of your culture, do some right from the get-go in the bootcamp – as Salesforce does.)
  • Keep it applied. Don’t just teach facts or theory (“Competitor A uses a proprietary, non-Excel formula language.”) Show them how to apply that fact in everyday life (e.g., suggest prospects to build some models to get a taste of what that feels like versus good-old Excel).
  • Everyone’s in sales. Teach everyone how the company sells, what problems it solves, and why customers buy from it.
  • Fire people who don’t take it seriously. The University head should be able to fire any employee during the training period. If you’re skipping sessions, not paying attention, late, disrupting, etc., then boom, you’re gone. It sends a message that won’t soon be forgotten.
  • Send home a report card. Build a culture where managers are embarrassed when their new hire gets a B- and the put people immediately on a performance plan when they get a C. List specific student strengths and development areas. Build the University program into the management process right from the start. Train managers on how work with fresh bootcamp graduates.
  • Try to use it for prediction. Give granular objective grades in different areas (e.g., delivery of corporate message, fluency in finance, consultative selling) along with an instructor success prediction and do regressions over time to see what really drives sales success as opposed to what you might think does. Try to answer the question: do people who do better in the University do better in real life?
  • Hire a consultant. My colleague Elay Cohen is a sales productivity expert, the author of Saleshood (Kellblog review here), and ran the outstanding program at Salesforce — I’m pretty sure he’d be happy to help you setup yours. You don’t have to invent this stuff anymore. Plenty of people know how to do it.

Finally, don’t stop with bootcamp. Build ongoing training programs that take care of your existing hires as much as your new ones. But that’s the subject of a different post.