The Opportunity Cost of Debating Facts

Posted on December 18, 2016 | 1 comment

I read this New York Times editorial this morning, How the Truth Got Hacked, and it reminded me of a situation at work, back when I first joined Host Analytics some four years ago.  This line, in particular, caught my attention:

Imagine the conversation we’d be having if we weren’t debating facts.

Back when I joined Host Analytics, we had an unfortunate but not terribly unusual dysfunction between product management (PM) and Engineering (ENG).  By the time the conflict got to my office, it went something like this:

PM:  “ENG said they’d deliver X, Y, and Z in the next release and now they’re only delivering X and half of Y.  I can’t believe this and what am I going to the customers and analysts who I told that we were delivering …”

ENG:  “PM is always asking us to deliver too much and we never actually committed to deliver all of Y and we certainly didn’t commit to deliver Z.”

(For extra fun, compound this somewhat normal level of dysfunction with American vs. Indian communication style differences –including a quite subtle way of saying “no” – and you’ll see the real picture.)

I quickly found myself in a series of “he said, she said” meetings that were completely unproductive.  “We don’t write down commitments because we’re agile,” was one refrain.  In fact, while I agree that the words “commitment” and “agile” generally don’t belong in the same sentence, we were anything but agile at the time, so I viewed the statement more as a convenient excuse than an expression of true ideological conflict.

But the thing that bugged me the most was that we had endless meetings where we couldn’t even agree on basic facts.  After all, we either had a planning problem, a delivery problem, or both and unless we could establish what we’d actually agreed to deliver, we couldn’t determine where to focus our efforts.  The meetings were a waste of time.  I had no way knowing who said what to whom, we didn’t have great tracking systems, and I had no interest in email forensics to try and figure it out.  Worse yet, it seemed that two people could leave the same meeting not even agreeing on what was decided.

Imagine the conversation we’d be having if we weren’t debating facts.

In the end, it was clear that we needed to overhaul the whole process, but that would take time.  The question was, in the short term, could we do something that would end the unproductive meetings so we take basic facts in evidence and then have a productive debate at the next level?  You know, to try and make some progress on solving our problems?

I created a document called the Release Scorecard and Commitments document that contained two tables, each structured like this.

release-scorecard

At the start of each release, we’d list the major stories that we were trying to include and we’d have Engineering score their confidence in delivering each one of them.  Then, at the end of every release, PM would score how the delivery went, and the team could provide a comment.  Thus, at every post-release roadmap review, we could review how we did on the prior release and agree on priorities for the next one.  Most importantly, when it came to reviewing the prior release, we had a baseline off which we could have productive discussions about what did or did not happen during the cycle.

Suddenly, by taking the basic facts out of question, the meetings changed overnight.  First, they became productive.  Then, after we fully transitioned to agile, they became unnecessary.  In fact, I’ve since repeatedly said that I don’t need the document anymore because it was a band-aid artifact of our pre-agile world.  Nevertheless, the team still likes producing it for the simple clarity it provides in assessing how we do at laying out priorities and then delivering against them.

So, if you find yourself in a series of unproductive, “he said, she said” meetings, learn this lesson:  do something to get basic facts into evidence so you can have a meaningful conversation at the next level.

Because there is a massive opportunity cost when all you do is debate what should be facts.

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Posted in Leadership, Management, Uncategorized

How to Manage Your First Sales VP at a Startup

Posted on October 27, 2016 | 2 comments

One of the hardest hires — and one of the hardest jobs — is to be the first VP of sales at a startup.  Why?

  • There is no history / experience
  • Nobody knows what works and what doesn’t work
  • The company may not have a well defined strategy so it’s hard to make a go-to-market strategy that maps to it
  • Any strategy you choose is somewhat complex because it needs to leave room for experimentation
  • If things don’t work the strong default tendency is to blame the VP of sales and sales execution, and not strategy or product.  (Your second VP of sales gets to blame product or strategy — but never your first.)

It’s a tough job, no doubt.  But it’s also tough for a founder or new CEO to manage the first sales VP.

  • The people who sign up for this high-risk duty are often cocksure and difficult to manage
  • They tend to dismiss questions with experienced-based answers (i.e., well we did thing X at company Y and it worked) that make everything sound easy.
  • They tend to smokescreen issues with such dismissals in order to give themselves maximum flexibility.
  • Most founders know little about sales; they’ve typically never worked in sales and it’s not taught in (business) school.

I think the best thing a founder can do to manage this is to conceptually separate two things:

  • How well the sales VP implements the sales model agreed to with the CEO and the board.
  • Whether that model works.

For example, if your team agrees that it wants to focus on Defense as its beachhead market, but still opportunistically experiment horizontally, then you might agree with the sales VP to build a model that creates a focused team on Department of Defense (DoD) and covers the rest of the country horizontally with a enterprise/corporate split.  More specifically, you might decide to:

  • Create a team of 3 quota carrying reps (QCRs) selling to the DoD who each have 10+ years experience selling to the DoD, ideally holding top secret clearances, supported by 2 sales consultants (SCs) and 2 business development reps (BDRs) with the entire team located in a Regus office in McLean, VA and everyone living with a one-hour commute of that office.
  • Hire 2 enterprise QCRs, one for the East and one for the West, the former in McLean and the latter in SF, each calling only on $1B+ revenue companies, each supported by 1 local SC, and 2 BDRs, where the BDRs are located at corporate (in SF).  Each enterprise QCR must have 10+ years experience selling software in the company’s category.
  • Hire 2 corporate reps in SF, each sharing 1 SC, and supported by 2 BDRs calling on sub $1B revenue companies.  Each corporate rep must have 5+ years experience selling software in the category.

In addition, you would create specific hiring profiles for each role ideally expressed with perhaps 5-10 must-have and 3-5 nice-to-have criteria.

Two key questions:

  • Do we know if this is going to work?  No, of course not.  It’s a startup.  We have no customers, data, or history.  We’ve taken our best guess based on understanding the market and the customers.  But we can’t possibly know if this is going to work.
  • Can we tell if the sales VP is executing it?  Yes.  And you can hold him/her accountable for so doing.  That’s the point.

At far too many startups, the problem is not decomposed in this manner, the specifics are not spelled out, and here’s what happens instead.  The sales VP says:

The plan?  Yes, let me tell you the plan.  I’m going to put boots down in several NFL cities, real sales athletes mind you, the best.  People I’ve worked with who made $500K, $750K, or even $1M in commissions back at Siebel or Salesforce or Oracle.  The best.  We’re going to support those athletes with the best SCs we can find, and we’re going to create an inside sales and SDR team that is bar none, world-class.  We’re going to set standard quotas and ramps and knock this sonofabitch out of the park.  I’ve done this before, I’m matching the patterns, trust me, this is going to be great.

Translation:  we’re going to hire somewhere between 4 and 8 salespeople who I have worked with in the past and who were successful in other companies regardless of whether they have expertise in our space, the skills required in our space, are located where out strategy indicates they should be.  Oh, and since I know a great pharma rep, we’re going to make pharma a territory  and even though he moved to Denver after living in New Jersey, we’ll just fly him out when we need to.  Oh, and the SDRs, I know a great one in Boise and one in Austin.  Yes, and the inside reps, Joe, Joey, Joey-The-Hacksaw was a killer back in the day and even though he’s always on his bass boat and living in Michigan now, we’re going to hire him even though technically speaking our inside reps are supposed to be in SF.

This, as they say in England, is a “dog’s breakfast” of  a sales model.  And when it doesn’t work — and the question is when, not if — what has the company learned?  Precisely and absolutely zero.

If you’re a true optimist, you might say we’ve learned that a bunch of random decisions to hire old cronies scattered across the country with no regard for strategy, models, or hiring profiles, doesn’t work.  But wait a minute — you knew that already; you didn’t need to spend $10M in VC to find out.  (See my post, If We Can’t Have Repeatable Success Can We At Least Have Repeatable Failure?)

By making the model clear — and quite specific as in my example above — you can not only flush out any disagreements in advance, but you can also hold the sales VP accountable for building the model they say they are going to build.  With a squishy model, as my other example shows, you can never actually know because it’s so vague you can’t tell.

This approach actually benefits both sides

  • The CEO benefits because he/she doesn’t get pushed around into agreeing to a vague model that he/she doesn’t understand.  By focusing on specifics the CEO gets to think through the proposed model and decide whether he/she likes it.
  • The Sales VP benefits as well.  While he/she loses some flexibility because hiring can’t be totally opportunistic, on the flip side, if the Sales VP implements the agreed-to model and it doesn’t work, he/she is not totally alone and to blame.  It’s “we failed,” not “you failed.”  Which might lead to a second chance for the sales VP to implement a new model.

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Posted in Hiring, Startups, Strategy, VC

The Era of Consumer Deception:  Why Do We Tolerate Such Price Opacity?

Posted on September 15, 2016 | 6 comments

I was wondering the other day why Southwest would spend millions of dollars to remind people that Bags Fly Free.  I’d argue there are two reasons:

  • It generally supports their friendly and transparent, low fees brand strategy
  • It reminds customers that a $500 fare on United might actually cost you more than a $550 on Southwest if you’ve got a few bags

Price have become so opaque over the past few decades that not only are consumers routinely surprised when they receive a bill, but companies now feel compelled to spend millions to remind them that quoted prices are often apples/oranges comparisons.

It’s not hard to find examples of price opacity:

  • Mortgages with variable rate structures people don’t understand and which exposes them to massive increase in payments (i.e., the 2008 crisis).
  • Bank accounts that have no monthly fee, but are laden with subtle and not-inexpensive fees that seem to silently sneak back in as terms are quietly changed.
  • Numerous airline refundability tiers, change fee policies, per-seat premium economy seat fees, and baggage fees that make true price comparison next to impossible.
  • Rental car policies like Hertz’s usurious $10/gallon refueling fee or the maze of overpriced and often unneeded insurance options that can double the price of a rental
  • Teaser rates for many services, including cellular and Internet, that bear no resemblance to the actual monthly fees

Most, but not all, of the time I manage to sidestep these problems because I’m sophisticated and can figure them out (when I take the time), because I carry balances that preclude most of the sneaky banking fees, and because I fly a lot and get exempt from some of the change fees and seat fees.

But just the other day, while I was in the midst of congratulating myself for avoiding the Hertz $10/gallon refueling fee, I looked on the receipt and saw a per-mile fee that nearly doubled the cost of my rental — when was the last time a rental car didn’t have unlimited miles?

It’s a cat-and-mouse game and companies keep getting better at playing it.

Now you could argue that this opacity is a company’s way of fighting back against price competition, and particularly the price transparency and comparability that the Internet brought.  In an era of price comparison engines that scour the Internet for the best deal, why not sneak in some fees that give you an edge?

You can argue, as people often do when it comes to the airlines, that we’ve done it to ourselves – our consumer behavior has trained the companies towards these strategies.  And that may be true, but we need to accept that these strategies are often fundamentally dishonest.

I realized this as my kids got older and I had to explain how rental cars work (which I still don’t know that well apparently), how airfares work (self-insure against cancellation by throwing out a ticket every now and then as opposed to getting gouged on refundable fares – or just fly SouthWest), how credit cards work (that’s a long one), how mortgages work, and on and on.

It’s what in Texas they call a boiled frog problem. It’s happened so slowly and incrementally that we’ve just gotten accustomed to it and the people most hurt by the practices tend to be at the bottom of the socioeconomic ladder (e.g., payday loans) and have the least voice.

And this society of deception already extends well beyond consumer pricing.  Contests and prizes are another huge area, like fake $1M TV show prizes (e.g., America’s Got Talent) that are actually a 40-year annuity worth more like $300K, fake unwinnable TV contests like American Ninja Warrior (which has only been completed twice) which are made harder every year so nobody wins the fake 40-year $1M annuity, or even state lotteries (which started the annuity deception) which typically pay out over 20 years, slashing prize values by about half.

But where we’ve ended up is not acceptable.  Ironically, after the Internet brought a brief wave of price transparency, we have ended with potentially more opacity than we had before as fees and terms and packaging get ever more complex.  We’re eroding consumer trust by living in an era of manufactured confusion and price deception.

You may not think this is a big deal, but I’d argue it’s like Malcom Gladwell’s broken window theory.  If we tolerate constant small deceptions in our lives, we open the doors to the big ones.

6 Comments

Posted in Marketing

Win Them Alone, Lose Them Together

Posted on September 6, 2016 | 2 comments

It was back in the 1990s, at Versant, when my old (and dearly departed) friend Larry Pulkownik first introduced me to the phrase:

Win Them Alone, Lose Them Together

And its corollary:

Ask for Help at the First Sign of Trouble

Larry told me this rule from the sales perspective:

“Look, if you’re working on a deal and it starts to go south, you need to get everyone involved in working on it.  First, that puts maximum resources on winning the deal and if — despite that effort — you end up losing, you want people saying ‘We lost the Acme deal,’ not ‘You lost the Acme deal.'”

It’s a great rule.  Why?  Because it’s simple, it engages the team on winning, and most of all — it combats what seems to be a natural tendency to hide bad news.  Bad news, like sushi, does not age well.

Twenty years later, and now as CEO, I still love the rule — especially the part about “the first sign of trouble.”  If followed, this eliminates the tendency to go into denial about bad news.

  • Yes, they’re not calling me back when they said they would, but I’m sure it’s no problem.
  • They did say they expected to be in legal now on the original timeline, but I’m sure the process is just delayed.
  • Yes, I know our sponsor seemed to have flipped on us in the last meeting, but I’m sure she was just having a bad day.
  • Well I’m surprised to hear our competitor just met with the CIO because they told us that the CIO wasn’t involved in the decision.
  • While the RFP does appear to have been written by our competitor, that’s probably just coincidence.

These things — all of them — are bad news.  Because many people’s first reaction to bad news is denial, the great thing about the “first sign” rule is that you remove discretion from the equation. We don’t want you to wait until you are sure there is trouble — then it’s probably too late.  We want you to ask for help at the first sign.

The rule doesn’t just apply to sales.  The same principle applies to pretty much everything:

  • Strategic partnerships (e.g., “they’ve gone quiet”)
  • Analyst relations (e.g., “it feels like the agenda is set for enemy A”)
  • Product development (e.g., “I’m worried we’ve badly over-scoped this”)
  • Financing (e.g., “they’re not calling back after the partner meeting”)
  • Recruiting (e.g., “the top candidate seemed to be leaning back”)
  • HR (e.g., “our top salesperson hated the new comp plan”)

I’ll always thank Larry for sharing this nugget of wisdom (and many others) with me, and I’ll always advise every manager I know to follow it.

2 Comments

Posted in Leadership, Management, Startups

The Four Levers of SaaS

Posted on September 1, 2016 | 6 comments

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.

ARR ASP

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.

Conclusion

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.

 

 

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Posted in Metrics, SaaS, Sales, Startups, VC

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