I was talking to a founder friend of mine the other day, and she made a comment about her startup’s search for its first non-founder (aka, “professional”) CEO. She said the following about the nearly one-year recruiting process:
“Because every person in the search process had veto power, the process was inadvertently designed to go slowly and not produce the best candidate. We passed on plenty of candidates superior to the person we eventually hired because someone had a problem with them and we assumed we’d find someone better in the future. Eventually, the combination of search fatigue with dwindling cash compelled us to act so we locked in to the best person we had in-process at the time. In effect, the process wasn’t designed to hire the most qualified candidate, but the least objectionable one.”
In this case the failed process was catastrophic. The candidate they selected took the company in a different direction and my friend the founder was pushed out a few months later.
Here are some thoughts on how to create a CEO search process that produces the best, as opposed to the least objectionable, candidate:
Set up a search committee that does not include the whole board, so you are not creating a process with a large number of people who have veto power.
Write down what you want in a candidate in the form of a must-have, nice-to-have list. Don’t delegate writing the core of the job spec for your new CEO to an associate at your search firm, cutting and pasting from the last spec.
Be mindful about the sequencing and timing of candidates. Ask to see calibration candidates first to get people warmed up. Try to cluster candidates. Try to have sure candidates see the search committee in a different orders. Slow down highly-qualified early candidates and speed up highly-qualified late entrants. Like it or not, timing matters enormously.
Check some references before passing candidates beyond the committee. Do some blind reference checking before moving candidates to the next step in the process. There’s no point in having the group falling in love with a candidate only to discover they have poor reputation or dubious claims on their resume.
Let candidates ask for additional interviews beyond a relatively small core team instead of defining a process where every candidate automatically sees every board member and executive staffer. You can learn a ton about candidates by who they ask, and don’t ask, to see.
Ask candidates to present their plans for the company. While all of them should include 90 days of learning and assessment (think: “seek first to understand”) before taking action, virtually any qualified and engaged candidate has an 80% developed plan in their mind, so ask them to share it with you.
One of the hardest things about running a startup is you’re never sure who to listen to.
Your board members own big stakes in the company, but that doesn’t automatically align them with you. Your late-stage investors want low multiples on big numbers. Your early-stage investors want big multiples on small numbers. And they have their own specific needs driven by their funds and their partnerships. Your rank-and-file employees own relatively small stakes which, ceteris paribus, should make them want you to swing for the fences — but, in these days of decade-to-liquidity, you may have employees so jaded on equity compensation that they’d just like to keep their well-paying jobs.
Your executive team wants to hit their targets, earn their bonuses, and maybe some of them are deeply motivated by winning in the market, but maybe not. With a 0.5% to 1% share, a $500M exit can mean a $2.5M to $5.0M pop. Maybe some would prefer to take the early exit, upgrade the house in Menlo Park, and go do it again somewhere else, as opposed to riding it out for the long term.
In all such cases, you’ll be taking advice from business people who have gone before you, have had anywhere from some to considerable success, and interested in sharing their learnings with others. You know, people like me .
Look, I’m not going to argue that getting advice from successful people is a bad idea — it certainly seems preferable to the alternative — but I am going to point out a few caveats, most of which aren’t obvious in my estimation:
Successful people don’t actually know what made them successful. They know what they did. They know it worked. They have hunches and beliefs. Causality, not so much. Some of them can be quick to forget that, so you shouldn’t be . There was no control group. If Marc Benioff carried a rabbit’s foot, would you?
Too many successful people are rinse/repeat . I’m frankly surprised by how many successful people are chomping at the bit to do exactly what worked for them at their last company with total disregard for whether it applies to yours. Beware these folks. Interview question: so could you tell me about a situation where you wouldn’t do that? It’s not foolproof because most will catch the hint, so this is really something you need to listen for before asking. Do they diagnose-then-prescribe or prescribe without diagnosing?
Their situation was likely different from yours. In fact, in the land of disruption, as Kelly Wright points out in this podcast, it almost certainly was. Are you creating a new category without competition? Are you in an over-funded next-big-thing category? Are you competing against a big company transitioning product lines? Are you trying to get people to buy something they don’t believe they need or pick among alternatives when they know they do? Are you disrupting technology, business model, or both? Are you filling a need that is in the midst of being created the rise of another category?
Should you listen to these people? I think yes . But try to find ones who have seen both success and failure, seen success in many situations (not just one), and who are thoughtful about a company’s specific situation, and approach the advisory process and their own prior success with humility.
# # #
 While I’d characterize my own success as towards the left of that spectrum, I am advising and/or have advised over 20 startups, some of them stunningly successful.
 One of my favorite quotes of this ilk is from former Harvard marketing professor, Theodore Levitt: Nothing in business is so remarkable as the conflicting variety of success formulas offered by its numerous practitioners and professors. And if, in the case of practitioners they’re not exactly “formulas,” they are explanations of “how we did it” implying with firm control over any fleeting tendencies toward modesty that “that’s how you ought to do it.” Practitioners filled with pride and money turn themselves into prescriptive philosophers, filled mostly with hot air.
 By the way, “I made $1B doing it this way” is one of the more difficult arguments you’re probably wise not to take on.
Many moons ago when I was young product marketing manager, I heard a new VP of Marketing speak at a marketing all-hands meeting. He spoke with a kiwi accent and his name was Chris Greendale. What he said were six words that changed my career:
Marketing exists to make sales easier
While this has clearly been a theme in Kellblog posts over the years, I realized that I’ve actually never done a dedicated post on it, despite having written reductionist mission statement posts for both professional services (“maximize ARR without losing money”) and human resources (“help managers manage”).
Being a math type, I love deriving things from first principles and this seemed the perfect first principle from which to derive marketing. First, you hire a team to build your product. Then, you hire a team to sell it. The only reason you need marketing is to help the second team do its job better.
At my next job, I remember bumping into Larry, our fresh from the used-car lot VP of Business Development, who in frustration (as he often was), one day came to work with a bunch of t-shirts that looked something like this
Enterprise software is a two-engine plane and those two engines are quota-carrying salesreps (QCRs) who sell the software and storypoint-burning developers (DEVs) who write it .
Everyone else is “the help” — including marketing, finance, sales supporting roles (e.g., SCs, SDRs), engineering-supporting roles (e.g., QA, PM, TPM), customer service, and yes, the CEO. The faster you understand this, in my humble opinion, the better.
But back to the mantra, make sales easier. Why did I like it so much?
First, it put marketing in its proper place. At the time, there was something of a power struggle between sales and marketing, and CPG/brand management types were trying to argue that product marketing mangers should be the generals and that sales were just the foot-soldiers. Looking both around me and at the P&L that just seemed wrong. Maybe it worked in consumer products  but this was enterprise software. Sales had all the budget and all the power to go with it. We should help them and, ego aside, there’s nothing wrong with being a helper.
In fact, if you define your mission statement as “help” and remember that “help is defined in the mind of the recipient,” you’ve already gone a long way to aligning your sales and marketing.
Second, there was nothing written in stone that limited the scope of that help. Narrow thinking might limit marketing to a servile role. That’s not my intent. Help could take many forms, and while the primary form of requested help has evolved over time, help can include both the tactical and the strategic:
Giving sales qualified leads to work on.
Building training and tools that helps sales sell more.
Providing competitive information that helps win more deals.
Creating an ideal customer profile (ICP) that helps sales focus on the most winnable deals.
Building industry-specific messaging that helps sell in given verticals
Working with PM  to build product that is inherently more salable .
Corporate strategy development to put the company in the right markets with the right offerings.
When I say help, I don’t mean lowercase-h tactical help. I mean help in all its forms, which can and should include the “tough love” form of help: “I know you think you want that, but let me demonstrate that I’ve heard your request and now explain why I think it’s not a good idea.”
Being helpful doesn’t mean saying yes to everything. I hearken back to Miracle on 34th Street whenever I’m drawn into this problem (quote adapted):
Kris Kringle: No, but don’t you see, dear? Some <salespeople> wish for things they couldn’t possibly use like real locomotives or B-29s.
If sales is asking you for a real locomotive or a B-29 you need to tell them.
For the rest of my marketing career, I took Greendale’s mantra and made it my own. If sales were my customer and I were helping them, then:
We’d run sales satisfaction surveys to see how happy sales was with marketing and where they wanted us to invest and improve .
We’d bring data to the party. We’d leverage syndicated and custom research to try and made data-driven as opposed to opinion-driven decisions.
We’d stop back-seat drivers. I’d remind anyone that got too uppity that “quotas are available” and they should go take one .
We wouldn’t be the marketing police, scolding people for using out-of-date materials. If sales were using a deck we’d decommissioned quarters ago, our first response wouldn’t be “stop!” but “why?”
We’d market marketing. We’d devote some time to internal marketing to let the sales organization know what we were doing and why.
We’d even do something that tested the limits of HR (particularly when I was in France). I’d use the sales satisfaction survey to rank every customer-facing marketer on a matrix.
This gave me hard data on who sales knew in the department and what they thought of them. If we’re going to make messaging for sales to present to customers, we’d better prepared to — and be good at — presenting it ourselves .
Overall, the mantra served me well, taking me from product marketing director to VP of product marketing to VP of corporate marketing to overall VP of marketing and a great run at Business Objects. I’ve had plenty of people challenge me on it over the years — usually it’s because they understand it as purely tactical. But it’s served me well and I encourage you to use it as your North Star in leading your marketing team.
After all, who doesn’t like help?
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 You’d be wise to add those two figures to your one-page key metrics. Somehow it’s always easier to hire the supporting staff than the “engine” staff, so keep an eye on the raw numbers of QCRs and DEVs and, for more fun, track their density in their respective organizations (QCRs/sales and DEVs/eng).
 Shout out to my daughter Stephanie who works in brand management on a consumer product and who can now inform me directly of how things work in that world — and it is different.
 PM = product management.
 Either in the sense of better solves the problem or in the tactical sense of wipes out competitive differentiation.
 One of my favorite results was the sales and SCs often wanted exactly the same thing, but that sales wanted it more (i.e., roughly the same priority curve but sales would rank everything even more important than the SCs).
 Most didn’t, but a few did, and some did remarkably well.
 We were probably a $100M company around the time we started this, so I’m not suggesting it for a 2-PMM startup. And yes, I’d put myself on the matrix as well.
Some SaaS startups develop a form of zero-sum delusion early in their evolution, characterized by following set of beliefs. Believing that:
A customer has a fixed budget that is 100% fungible between ARR (annual revenue revenue) and services
It is in the company’s best interest to turn as much of the customer’s budget as possible into ARR
Customers never think to budget implementation services separately from annual software licensing
A $25K StartFast offering that walks through a standard checklist is everything a customer needs for a successful implementation
If the StartFast doesn’t work, it’s not a big deal because the Customer Success team’s mission is to offer free clean-up after failed implementations
Since the only thing consultants do is implementations, their job title should be “Implementation Consultant”
Any solutions practices or offerings should be built by our partners
The services team should be introduced as late as possible in the sales cycle; ideally after contract signing, in order to eliminate the chance a post-sales consultant will show up, tell the customer “the truth,” and ruin a deal
It is impossible and/or not meaningful to create and run a separate services P&L
The need for services is a reflection of failure on the part of the product (even in an enterprise setting)
Zero-sum delusion typically presents with the following metrics:
Services being less than 10% of total company revenues
Services margins running in the negative 20% to negative 60% range
High churn on one-year deals (often 25% or higher) due to failed implementations
Competitors winning bigger deals both on the ARR and services side (and associated internal confusion about that)
Loss reports indicating that prospects believed the competition “understood our problem better” and acted “more like a partner than a vendor”
Zero-sum delusion is a serious issue for an early-stage SaaS business. It is often acquired through excess contact with purely financial venture capitalists. Happily, with critical thinking and by challenging assumptions, it can be overcome.
OK, let’s switch to my normal narrative mode and discuss what’s going on here. First, some SaaS companies deliberately run with a low set-up product, little to no services, and a customer success team that takes care of implementation issues. Usually these companies sell inexpensive software (e.g., ARR < $25K), use a low-touch sales model, and focus on the small and medium business market . If delivering such an offering is your company’s strategy then you should disregard this post.
However, if your strategy is not to be a low-touch business model disruptor, if you do deals closer to $250K than $25K, if your services attach rate  is closer to 10% than 40%, if you consider yourself a somewhat classic enterprise SaaS vendor — basically, if you solve big, hard problems for enterprises and expect to get paid for it — then you should read this post.
Let’s start with a story. Back in the day at Business Objects, we did a great business grinding out a large number of relatively small (but nevertheless enterprise) deals in the $100K to $200K range. I remember we were working a deal at a major retailer — call them SeasEdge — against MicroStrategy, a self-funded competitor bootstrapped from a consulting business.
SeasEdge was doing a business intelligence (BI) evaluation and were looking to use BI to improve operational efficiency across a wide range of retail use cases, from supply chain to catalog design. We had a pretty formulaic sales cycle, from discovery to demo to proposal. We had financials that Wall Street loved (e.g., high gross margins, a small services business, good sales efficiency) so that meant we ran with a high salesrep-to-SE (sales engineer) ratio and a relatively small, largely tactical professional services team. I remember hearing our sales team’s worries that we were under-servicing the account — the salesrep had a lot of other active opportunities and the SE, who was supporting more than two salesreps, was badly overloaded. Worse yet, MicroStrategy was swarming on the account, bringing not only a salesrep and an SE but about 5 senior consultants to every meeting. Although they were a fraction of our size, they looked bigger than we did in this account.
SeasEdge taught me the important lesson that the deal you lose is not necessarily the deal your competitor wins. We lost a $200K query-and-reporting (Q&R) deal. MicroStrategy won a $4M retail transformation deal. We were in the business of banging out $200K Q&R deals so that’s what we saw when we looked at SeasEdge. MicroStrategy, born from a consultancy, looked at SeasEdge and saw a massive software and services, retail transformation opportunity instead.
I understand this is an extreme example and I’m not suggesting your company get in the business of multi-million dollar services deals . But don’t miss the key lessons either:
Make sure you’re selling what the customer is buying. We were selling Q&R tools. They were buying retail transformation.
People may have more money than you think. Particularly, when there’s a major business challenge. We saw only 5% of the eventual budget.
A strong professional services organization can help you win deals by allowing you to better understand, more heavily staff, appear more as a partner in, and better solve customer problems in sales opportunities. Internalize: a rainmaker professional services leader is pure gold in sales cycles.
While partners are awesome, they are not you. Once in a while, the customer wants “one throat to choke” and if you can’t be that throat then they will likely buy from someone who can.
I call this problem zero-sum delusion because I think the root cause is a fallacy that a zero-sum trade-off exists between ARR and professional services. The fallacy is that if a customer has only $250K to spend, we should get as much of that $250K as possible in ARR, because ARR recurs and professional services doesn’t . The reality is that most customers, particularly when you’re selling to the information technology (IT) organization, are professional buyers — this isn’t their first rodeo, they know that enterprise software requires professional services, and they budget separately for it. Moreover, they know that a three-year $250K ARR deal represents a lot of money for their company and they darn well want the project associated with that investment to be successful — and they are willing to pay to ensure that success.
If you combine the zero-sum fallacy with purely financial investors applying pressure to maximize blended gross margins  and the fantasy that you can somehow run a low-touch services model when that isn’t actually your company and product strategy, you end up with a full-blown case of zero-sum delusion.
Curing the Zero-Sum Delusion
If your organization has this problem, here are some steps you can take to fix it.
Convince yourself it’s not zero sum. Interview customers. Look at competitors. Look at you budget in your own company. Talk to consultants who help customers buy and implement software. When you do, you will realize that customers know that enterprise software requires services and they budget accordingly. You’ll also understand that customers will happily pay to increase the odds of project success; buying quality services is, in effect, an insurance policy on the customer’s job .
Change your negotiation approach. If you think it’s zero sum, you’ll create a self-fulfilling prophecy in negotiation. Don’t frame the problem as zero sum. Negotiate ARR first, then treat that as fixed. Add the required services on top, negotiating services not as a zero-sum budget trade-off against ARR, but as a function of the amount of work they want done. I’ve won deals precisely because we proposed twice the services as our competition because the customer saw we actually wanted to solve their problem, and not just low-ball them on services to sell subscription.
Change sales’ mental math. If you pay salesreps 12% on ARR and 2% on services, if your reps have zero-sum delusion they will see a $250K ARR, $100K services deal as $5K to $10K in lost commission . Per the prior point we want them to see this as a $30K ARR commission opportunity with some services commissions on top — and the higher the services commissions the higher the chance for downstream upsell. Moreover, once they really get it, they see a 50% chance of winning a 250/25 deal, but a 80% chance of winning a 250/100 deal. An increase in expected value by over $10K.
Put a partner-level, rainmaker leader in charge of your services organization and each region of it. The lawyer who makes partner isn’t the one with the best legal knowledge; it’s the one with the biggest book of business. Adopt that mentality and run your services business like, well, a services business.
Create a services P&L and let your VP of Services fully manage it. They will know to get more bookings when the forecast is light. They will increase hiring into a heavy forecast and cut weak performers into a light forecast. They know how to do this. Let them.
Set your professional services gross margin target at 5-10%. As an independent business it can easily run in the 30-40% range. As a SaaS adjunct you want services to have time to help sales, time to help broken customers (helping renewals), time to enable partners, and the ability to be agile. All that costs you some margin. The mission should be to maximize ARR while not losing money.
Constrain services to no more than 20% of revenue. This limits the blended gross margin impact, is usually fine with the board, keeps you well away from the line where people say “it’s really a services firm,” usually leaves plenty of room for a services partner ecosystem, and most importantly, creates artificial scarcity that will force you to be mindful about where to put your services team versus where to put a partner’s.
Force sales to engage with services earlier in the sales cycle. This is hard and requires trust. It also requires that the services folks are ready for it. So wait until the rainmakers in charge have trained, retrained, or cleared people and then begin. It doesn’t take but a few screw-ups to break the whole process so make sure services understand that they are not on the sales prevention team, but on the solving customer problems team. When this is working, the customer buys because both the VP of Sales, and more importantly, the VP of Services looked them in the eye and said, “we will make you successful” .
Outplace any consultant who thinks their mission is “tell the truth” and not help sales. Nobody’s saying that people should lie, but there is a breed of curmudgeon who loves to “half empty” everything and does so in the name of “telling the truth.” In reality, they’re telling the truth in the most negative way possible and, if they want to do that, and if they think that helps their credibility, they should go work at independent services firm . You can help them do that.
Under no circumstances create a separate services sales team — i.e., hire separate salespeople just to sell services . The margins don’t support it and it’s unnecessary. If you have strong overall and regional leadership, if those leaders are rainmakers as they should be, then there is absolutely zero reason to hire separate staff to sell services.
# # #
 Yes, they can eventually be enterprise disruptors by bringing this low-touch, cheap-and-cheerful approach to the enterprise (e.g., Zendesk), but that’s not the purpose of this post.
 Services attach rate is the ratio of professional services to ARR in a new booking. For example, if you sell $50K of services as part of a $500K ARR deal, then your attach rate is 10%.
 We had neither that staffing levels nor the right kind of consultants to even propose, let alone take on, such an engagement. The better strategy for us would have been to run behind a Big 4 systems integrator bidding who included our software in their proposal.
 Sales compensation plans typically reinforce this as well. Remediating that is hard and beyond the scope of this post, but at least be aware of the problem.
 At the potential expense of maximizing ARR — which should be the point.
 If you think from the customer’s perspective. Their job is to make sure projects succeed. Bad things sometimes happen when they don’t.
 On the theory that the perfect deal, compensation wide, is 100% ARR. Math wise, 0.12*250+0.02*100 = $32K whereas 0.12*350+0.02*0 = $42K. More realistically, if they could have held services to $50K, you’d get 0.12*300+0.02*50 = $37K. Note that this way of thinking is zero-sum and ignores the chance you can expand services while holding ARR constant.
 And, no offense, they believed the latter more than the former. And they know the latter is the person on the hook to make it happen.
 Oh, but they want the stock-options upside of working at a vendor! If that’s true, then they need to get on board and help maximize ARR while, yes, still telling the truth but in a positive way.
 Wanting to do so is actually a symptom of advanced zero-sum delusion.
I earned my spending money in high school and partially paid for college by working as a lifeguard and water safety instructor. Working at a lovely suburban country club you don’t make a lot of saves. One day, working from the deep-end chair, I noticed two little kids hanging on a lane line. That was against the rules. I blew my whistle and shouted, “off!”
Still young enough to be obedient (i.e., under 11), the two kids let go of the line. The trouble was they couldn’t swim. Each grabbed the other and they sank to the bottom. “Oh my God,” I thought as I dove off the chair to make the save, “I just provoked a double drowning.”
While that was happily the last actual (and yes, averted) double drowning I have witnessed, I’ve seen a lot of metaphorical ones since. They involve adults, not kids. And it’s always the VP of Sales in a deadly embrace with the VP of Marketing. Sure, it may not be an exactly simultaneous death — sometimes they might leave a few months apart — but make no mistake, in the end they’re both gone and they drowned each other.
How To Recognize the Deadly Embrace
I believe the hardest job in software is the VP of Sales in an early-stage startup. Why? Because almost everything is unknown.
Is the product salable?
How much will people pay for it?
What’s a good lead?
Who should we call on?
What’s the ideal customer profile?
What should we say / message?
Who else is being evaluated?
What are their strengths/weaknesses?
What profile of rep should I hire?
How much can they be expected to sell?
What tools do they need?
Which use-cases should we sell to?
What “plays” should we run?
You might argue every startup less then $50M in ARR is still figuring out some of this. Yes, you get product-market fit in the single-digit millions (or not at all). But to get a truly repeatable, debugged sales model takes a lot longer.
This painful period presents a great opportunity for sales and marketing to blow each other up. It all begins with sales signing up for (or being coerced into) an unrealistic number. Then, there aren’t enough leads. Or, if there are, the leads are weak. Or the leads don’t become pipeline. Or pipeline doesn’t close.
At each step one side can easily blame the other.
There aren’t enough leads
There are, but they’re all stuck with your “generation Z” SDRs
The SDRs are great, I hired them
The SQL acceptance rate says they are passing garbage to sales.
The SQLs aren’t bad, there just aren’t enough of them
Your reps are greasing the SDRs by accepting bad SQLs
We’re not getting 80% of pipeline from marketing
We’re delivering our target of 70% and then some
But the pipeline is low quality, look at the poor close rate
The close rate is poor because of your knuckleheaded sellers
Those knuckleheads all crushed it at my last company
Your derail rate’s insane
Lots of deals in this space end up no-decision
Maybe they derail because we don’t follow-up fast enough
Our message isn’t crisp or consistent
Our messaging is fine, the analysts love it
We’re the greatest thing nobody’s ever heard of
We’ve got a superior product that your team can’t sell
We’re being out-marketed!
We’re being out-sold!
Once this ping-pong match starts, it’s hard to stop. People feel blamed. People get defensive. Anecdotal bloody shirts are waived in front of the organization — e.g., “marketing counted five grad students who visited the booth as MQLs!” or “we lost an opportunity at BigCo because our seller was late for the big meeting!”
With each claim and counter-claim sales and marketing tighten the deadly embrace. Often the struggling CRO is fired for missing too many quarters, guns still blazing as he/she dies. (Or even beyond the grave if they continue to trash the CMO post departure.) Sometimes the besieged CMO quits in anticipation of termination. Heck, I even had one quit after I explicitly told them “I know you’re under attack, but it’s unfair and I’ve got your back.”
Either way, in whatever order, they go down together. Each one mortally wounds the spirit, the confidence, or the pleasure-in-work of the other.
How to Break Out of It
Like real double drownings, it’s hard for one of the participants to do an escape maneuver. The good news is that it’s not hard to know there’s a problem because the mess is clearly visible to the entire organization. Everyone sees the double downing. Heck, employees’ spouses probably even know about it. However, only the CEO can stop it and — trust me — everyone’s waiting for them to do so.
The CEO has four basic options:
Take some pressure off. If the primary reason you’re missing plan is because the plan is too aggressive, go to the board and reduce the targets. (Yes, even if it means reducing some expense budget as well.) As Mike Moritz said to me when I started at MarkLogic: “make a plan that you can beat.” Tell them both that you’re taking off the pressure, them them why (because they’re not collaborating), and tell them that you’ve done your part and now it’s time for them to do theirs: collaborate non-defensively to solve problems.
Force them to work together. This the old “this shit needs to stop and I’m going to fire one of the two of you, maybe both, if you can’t work together” meeting. A derivation is to put both in a room and tell them not to leave until either they agree to work together or come out with a piece of paper with one name on it (i.e., the one who’s leaving). The key here for them to understand that you are sufficiently committed to ending the bullshit that you are willing to fire one or both of them to end it. In my experience this option tends not to work, I think because each secretly believes they will be the winner if you are forced to choose.
Fire one of the participants. This has the effect of rewarding the survivor as the victor. If done too late (before death but after the mortal wound — i.e., after the victor is far along in finding another job), it can still result in the loss of both. To the extent one person clearly picked the fight, my tendency is to want to reward the victim, not the aggressor — but that discounts the possibility the aggressor is either correct and/or more highly skilled. If they are both equally skilled and equally at fault, a rational alternative is to flip a coin and tell them: “I value you both, you are unable to work together, I think you’re equally to blame, so I’m going to flip a coin and fire one of you: heads or tails.” An alternative is to fire one and demote the other — that way it’s very clear to all involved that there was no winner. If fights have winners, you’re incenting fighting.
Fire both. I love this option. While it’s not always practical, boy does it send a strong message about collaboration to the rest of the organization: “if you fight, are asked to stop, and you don’t — you’re gone.” Put differently: “I’m not firing them for fighting, I’m firing them for insubordination because I told them not to fight.” Odds are you might lose both anyway so one could argue this is simply a proactive way of dealing with the inevitable.
One of the hardest things for executives is to maintain the balance between healthy cross-functional tension and accountability and unhealthy in-fighting and politics. It’s the CEO’s job to set the tone for collaboration in the company. While Larry Ellison and his disciplines may love “two execs enter, one exec leaves” cage fights as a form of corporate Darwinism, most CEOs prefer a tone of professional collaboration. When that breaks down, weak CEOs get frustrated and complain about their executive team. Strong ones take definitive action to define what is and what isn’t acceptable behavior in the organization and put clear actions behind their words.
This is part II in this series. Part I is here and covers the basics of management education, employee communications, and simple steps to help slow virus transmission while keeping the business moving forward.
In this part, we’ll provide:
A short list of links to what other companies are doing, largely when it comes to travel and in-office work policies.
A discussion of financial planning and scenario analysis to help you financially navigate these tricky waters.
I have broken out the list of useful information links and resources (that was formerly in this post) to a separate, part III of this series.
What Other Companies are Saying and Doing
Relatively few companies have made public statements about their response policies. Here are a few of the ones who have:
Financial Planning and Scenario Analysis: Extending the Runway
It’s also time to break out your driver-based financial model, and if you don’t have one, then it’s time to have your head of finance (or financial planning & analysis) build one.
Cash is oxygen for startups and if there are going to be some rough times before this threat clears, your job is to make absolutely sure you have the cash to get through it. Remember one of my favorite all-time startup quotes from Sequoia founder Don Valentine: “all companies go out of business for the same reason. They run out of money.”
In my opinion you should model three scenarios for three years, that look roughly like:
No impact. You execute your current 2020 operating plan. Then think about the odds of that happening. They’re probably pretty low unless you’re in a counter-cyclical business like videoconferencing (in which case you probably increase targets) or a semi-counter-cyclical one like analytics/BI (in which case maybe you hold them flat).
20% bookings impact in 2020. You miss plan bookings targets by 20%. Decide if you should apply this 20% miss to new bookings (from new customers), expansion bookings (new sales to existing customers), renewal bookings — or all three. Or model a different percent miss on each of those targets as it makes sense for your business. The point here is to take a moderately severe scenario and then determine how much shorter this makes your cash runway. Then think about steps you can take to get that lost runway back, such as holding costs flat, reducing costs, raising debt, or — if you’re lucky and/or have strong insiders — raising equity.
40% bookings impact in 2020. Do the same analysis as in the prior paragraph but with a truly major bookings miss. Again, decide whether and to what extent that miss hits new bookings, expansion bookings, and renewal bookings. Then go look at your cash runway. If you have debt make sure you have all covenant compliance tests built into your model that display green/red — you shouldn’t have to notice a broken covenant, it should light up in big letters (YES/NO) in a good model. Then, as in the prior step, think about how to get that lost runway back.
Once you have looked at and internalized these models, it’s time for you and your CFO to call your lead investors to discuss your findings. And then schedule a discussion of the scenario analysis at your next board meeting.
Please note that it’s not lost on me that accelerating out of the turn when things improve can be an excellent way to grab share in your market. But in order to so, you need to have lots of cash ready to spend in, say, 6-12 months when that happens. Coming out of the corner on fumes isn’t going to let you do that. And, as many once-prodigal, now-thrifty founders have told me: “the shitty thing is that once you’ve spent the money you can’t get it back.” Without dilution. With debt. Maybe without undesirable structure and terms.
Now is the time to think realistically about how much fuel you have in the tank, if you can get more, how long should it last, and how much you want in the tank 6-12 months out.
I’ve seen numerous startups try numerous ways to calculate their sales capacity. Most are too back-of-the-envelope and to top-down for my taste. Such models are, in my humble opinion, dangerous because the combination of relatively small errors in ramping, sales productivity, and sales turnover (with associated ramp resets) can result in a relatively big mistake in setting an operating plan. Building off quota, instead of productivity, is another mistake for many reasons .
Sales productivity, measured in ARR/rep, and at steady state (i.e., after a rep is fully ramped). This is not quota (what you ask them to sell), this is productivity (what you actually expect them to sell) and it should be based on historical reality, with perhaps incremental, well justified, annual improvement.
Rep hiring plans, measured by new hires per quarter, which should be realistic in terms of your ability to recruit and close new reps.
Rep ramping, typically a vector that has percentage of steady-state productivity in the rep’s first, second, third, and fourth quarters . This should be based in historical data as well.
Rep turnover, the annual rate at which sales reps leave the company for either voluntary or involuntary reasons.
Judgment, the model should have the built-in ability to let the CEO and/or sales VP manually adjust the output and provide analytical support for so doing .
Quota over-assignment, the extent to which you assign more quota at the “street” level (i.e., sum of the reps) beyond the operating plan targets
For extra credit and to help maintain organizational alignment — while you’re making a bookings model, with a little bit of extra math you can set pipeline goals for the company’s core pipeline generation sources , so I recommend doing so.
If your company is large or complex you will probably need to create an overall bookings model that aggregates models for the various pieces of your business. For example, inside sales reps tend to have lower quotas and faster ramps than their external counterparts, so you’d want to make one model for inside sales, another for field sales, and then sum them together for the company model.
In this post, I’ll do two things: I’ll walk you through what I view as a simple-yet-comprehensive productivity model and then I’ll show you two important and arguably clever ways in which to use it.
Walking Through the Model
Let’s take a quick walk through the model. Cells in Excel “input” format (orange and blue) are either data or drivers that need to be entered; uncolored cells are either working calculations or outputs of the model.
You need to enter data into the model for 1Q20 (let’s pretend we’re making the model in December 2019) by entering what we expect to start the year with in terms of sales reps by tenure (column D). The “first/hired quarter” row represents our hiring plans for the year. The rest of this block is a waterfall that ages the rep downward as we move across quarters. Next to the block ramp assumption, which expresses, as a percentage of steady-state productivity, how much we expect a rep to sell as their tenure increases with the company. I’ve modeled a pretty slow ramp that takes five quarters to get to 100% productivity.
To the right of that we have more assumptions:
Annual turnover, the annual rate at which sales reps leave the company for any reason. This drives attriting reps in row 12 which silently assumes that every departing rep was at steady state, a tacit fairly conservative assumption in the model.
Steady-state productivity, how much we expect a rep to actually sell per year once they are fully ramped.
Quota over-assignment. I believe it’s best to start with a productivity model and uplift it to generate quotas .
The next block down calculates ramped rep equivalents (RREs), a very handy concept that far too few organizations use to convert the ramp-state to a single number equivalent to the number of fully ramped reps. The steady-state row shows the number of fully ramped reps, a row that board members and investors will frequently ask about, particularly if you’re not proactively showing them RREs.
After that we calculate “productivity capacity,” which is a mouthful, but I want to disambiguate it from quota capacity, so it’s worth the extra syllables. After that, I add a critical row called judgment, which allows the Sales VP or CEO to play with the model so that they’re not potentially signing up for targets that are straight model output, but instead also informed by their knowledge of the state of the deals and the pipeline. Judgment can be negative (reducing targets), positive (increasing targets) or zero-sum where you have the same annual target but allocate it differently across quarters.
The section in italics, linearity and growth analysis, is there to help the Sales VP analyze the results of using the judgment row. After changing targets, he/she can quickly see how the target is spread out across quarters and halves, and how any modifications affect both sequential and quarterly growth rates. I have spent many hours tweaking an operating plan using this part of the sheet, before presenting it to the board.
The next row shows quota capacity, which uplifts productivity capacity by the over-assignment percentage assumption higher up in the model. This represents the minimum quota the Sales VP should assign at street level to have the assumed level of over-assignment. Ideally this figure dovetails into a quota-assignment model.
Finally, while we’re at it, we’re only a few clicks away from generating the day-one pipeline coverage / contribution goals from our major pipeline sources: marketing, alliances, and outbound SDRs. In this model, I start by assuming that sales or customer success managers (CSMs) generate the pipeline for upsell (i.e., sales to existing customers). Therefore, when we’re looking at coverage, we really mean to say coverage of the newbiz ARR target (i.e., new ARR from new customers). So, we first reduce the ARR goal by a percentage and then multiple it by the desired pipeline coverage ratio and then allocate the result across the pipeline-sources by presumably agreed-to percentages .
Building the next-level models to support pipeline generation goals is beyond the scope of this post, but I have a few relevant posts on the subject including this three-part series, here, here, and here.
Two Clever Ways to Use the Model
The sad reality is that this kind of model gets a lot attention at the end of a fiscal year (while you’re making the plan for next year) and then typically gets thrown in the closet and ignored until it’s planning season again.
That’s too bad because this model can be used both as an evaluation tool and a predictive tool throughout the year.
Let’s show that via an all-too-common example. Let’s say we start 2020 with a new VP of Sales we just hired in November 2019 with hiring and performance targets in our original model (above) but with judgment set to zero so plan is equal to the capacity model.
Our “world-class” VP immediately proceeds to drive out a large number of salespeople. While he hires 3 “all-star” reps during 1Q20, all 5 reps hired by his predecessor in the past 6 months leave the company along with, worse yet, two fully ramped reps. Thus, instead of ending the quarter with 20 reps, we end with 12. Worse yet, the VP delivers new ARR of $2,000K vs. a target of $3,125K, 64% of plan. Realizing she has a disaster on her hands, the CEO “fails fast” and fires the newly hired VP of sales after 5 months. She then appoints the RVP of Central, Joe, to acting VP of Sales on 4/2. Joe proceeds to deliver 59%, 67%, and 75% of plan in 2Q20, 3Q20, and 4Q20.
Our question: is Joe doing a good job?
At first blush, he appears more zero than hero: 59%, 67%, and 75% of plan is no way to go through life.
But to really answer this question we cannot reasonably evaluate Joe relative to the original operating plan. He was handed a demoralized organization that was about 60% of its target size on 4/2. In order to evaluate Joe’s performance, we need to compare it not to the original operating plan, but to the capacity model re-run with the actual rep hiring and aging at the start of each quarter.
When you do this you see, for example, that while Joe is constantly underperforming plan, he is also constantly outperforming the capacity model, delivering 101%, 103%, and 109% of model capacity in 2Q through 4Q.
If you looked at Joe the way most companies look at key metrics, he’d be fired. But if you read this chart to the bottom you finally get the complete picture. Joe is running a significantly smaller sales organization at above-model efficiency. While Joe got handed an organization that was 8 heads under plan, he did more than double the organization to 26 heads and consistently outperformed the capacity model. Joe is a hero, not a zero. But you’d never know if you didn’t look at his performance relative to the actual sales capacity he was managing.
Second, I’ll say the other clever way to use a capacity model is as a forecasting tool. I have found a good capacity model, re-run at the start of the quarter with then-current sales hiring/aging is a very valuable predictive tool, often predicting the quarterly sales result better than my VP of Sales. Along with rep-level, manager-level, and VP-level forecasts and stage-weighted and forecast-category-weighted expected pipeline values, you can use the re-run sales capacity model as a great tool to triangulate on the sales forecast.
You can download the four-tab spreadsheet model I built for this post, here.
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 Starting with quota starts you in the wrong mental place — what you want people to do, as opposed to productivity (what they have historically done). Additionally, there are clear instances where quotas get assigned against which we have little to no actual productivity assumption (e.g., a second-quarter rep typically has zero productivity but will nevertheless be assigned some partial quota). Sales most certainly has a quota-allocation problem, but that should be a separate, second exercise after building a corporate sales productivity model on which to base the operating plan.
 A typically such vector might be (0%, 25%, 50%, 100%) or (0%, 33%, 66%, 100%) reflecting the percentage of steady-state productivity they are expected to achieve in their first, second, third, and fourth quarters of employment.
 Without such a row, the plan is either de-linked from the model or the plan is the pure output of the model without any human judgement attached. This row is typically used to re-balance the annual number across quarters and/or to either add or subtract cushion relative to the model.
 Back in the day at Salesforce, we called pipeline generation sources “horsemen” I think (in a rather bad joke) because there were four of them (marketing, alliances, sales, and SDRs/outbound). That term was later dropped probably both because of the apocalypse reference and its non gender-neutrality. However, I’ve never known what to call them since, other than the rather sterile, “pipeline sources.”
 Many salesops people do it the reverse way — I think because they see the problem as allocating quota whereas I see the the problem as building an achievable operating plan. Starting with quota poses several problems, from the semantic (lopping 20% off quota is not 20% over-assignment, it’s actually 25% because over-assignment is relative to the smaller number) to the mathematical (first-quarter reps get assigned quota but we can realistically expect a 0% yield) to the procedural (quotas should be custom-tailored based on known state of the territory and this cannot really be built into a productivity model).
 One advantages of having those percentages here is they are placed front-and-center in the company’s bookings model which will force discussion and agreement. Otherwise, if not documented centrally, they will end up in different models across the organization with no real idea of whether they either foot to the bookings model or even sum to 100% across sources.
I’m Dave Kellogg, consultant, independent director, advisor, and blogger focused on enterprise software startups.
I bring a unique perspective to startup challenges having 10 years’ experience at each of the CEO, CMO, and independent director levels across 10+ companies ranging in size from zero to over $1B in revenues.
From 2012 to 2018, I was CEO of cloud enterprise performance management vendor Host Analytics, where we quintupled ARR while halving customer acquisition costs in a competitive market, ultimately selling the company in a private equity transaction.
Previously, I was SVP/GM of Service Cloud at Salesforce and CEO at NoSQL database provider MarkLogic, which we grew from zero to $80M in run-rate revenues during my tenure. Before that, I was CMO at Business Objects for nearly a decade as we grew from $30M to over $1B. I started my career in technical and product marketing positions at Ingres and Versant.
I love disruption, startups, and Silicon Valley and have had the pleasure of working in varied capacities with companies including Cyral, FloQast, Fortella, GainSight, Kelda, MongoDB, Plannuh, Recorded Future, and Tableau. I currently sit on the boards of Alation (data catalogs), Nuxeo (content management) and Profisee (master data management). I previously sat on the boards of agtech leader Granular (acquired by DuPont for $300M) and big data leader Aster Data (acquired by Teradata for $325M).
I periodically speak to strategy and entrepreneurship classes at the Haas School of Business (UC Berkeley) and Hautes Études Commerciales de Paris (HEC).