Scaling Anti-Patterns

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Updated August 22, 2022

Youโ€™re reading an excerpt of Founding Sales: The Early-Stage Go-To-Market Handbook, a book by Pete Kazanjy. The most in-depth, tactical handbook ever written for early-stage B2B sales, it distills early sales first principles and teaches the skills required, from being a founder selling to being an early salesperson and a sales leader. Purchase the book to support the author and the ad-free Holloway reading experience. You get instant digital access, commentary and future updates, and a high-quality PDF download.

There are a couple anti-patterns related to scaling that Iโ€™d like to discuss before we talk about sales management basics, namely premature scaling and lagged scaling. Both are problematic in different ways.

Premature Scaling

Premature scaling involves adding sales staff (or adding many more sales staff) before you have proven that the sales motion actually works. This approach typically results in an inefficient or aborted go-to-market effort that destroys cash and enterprise value, and often leads to layoffs of those sales staff, and maybe others, and an injured fundraising position. This can happen a few different ways.

โ€‹cautionโ€‹The most common way is for a founder to try to avoid having to figure out the sales and success motion himself, and instead try to โ€œsprinkle some sales on itโ€ by hiring a sales leader or a bunch of sales reps to figure it out. Usually what happens in this scenario is a sales leader who follows the playbooks that heโ€™s previously seen to work at organizations where the sales motion has already been cemented, typically by throwing bodies at the problem. The result will frequently be very inefficient reps and often customer success problems, leading to low customer satisfaction, churn, and eventually the laying off of that sales staff. I would give some examples of companies where this has happened, but you likely wonโ€™t recognize them because typically it kills the companyโ€”theyโ€™re not around anymore, so you wonโ€™t recognize the names.

โ€‹exampleโ€‹Imagine a scenario where a founder thinks that heโ€™s figured it all out, even though he hasnโ€™t sold the requisite few dozen deals on his own to prove that the product solves the problem that it seeks to solve, that the customer does indeed get value out of it, and that the customer is willing to pay for that value, and do so on an ongoing basis. Instead, in this scenario the founder hires a VP of Sales at ~$250K total compensation, with a six-month draw (the leader gets his whole target salary, ~$125K, for at least six months while the team ramps up), and that sales leader in turns hires three SDRs at ~$80K each, and three AEs, each of who target a ~$150K total compensation, each of whom are on a three-month draw. In this scenario the founder just added around ~$70K of month burn. Now, this can be totally fine, at scale, if each of those AE and SDR combos that costs ~$20K a month can deliver something like ~$80K+ of bookings (ideally paid up front) per month.

But thatโ€™s the sort of sales efficiency you would typically see only after the sales and success motion has been honed by a founder who engaged in founder-led selling for dozens and dozens of opportunities, resulting in a couple dozen deals, and then proved that this could be repeated with some reps that the founder herself hired. Rather, in this case, what you would typically end up seeing is a bunch of AEs who donโ€™t cover their own costsโ€”because they canโ€™t close enough business to cover their own salaries plus that of their SDR partners and their share of the sales leaderโ€™s salary they need to cover. And then things get even worse from there.

Because the AEs are being relied on to define the Ideal Customer Profile, and simultaneously are expected to close business, theyโ€™ll start selling to anything with a pulse, regardless of whether or not that prospect will actually get value out of the solution. And sometimes those reps will have successโ€”which of course is good in the short term, because that AE will at least defray some of his own cost, but in the long term is terrible, as that โ€œbadโ€ customer becomes a drain on customer success resources. Moreover, when that customer comes up for renewal, and churns out, it will hurt your metrics, and your ability to raise further capital, because itโ€™s clear that customers arenโ€™t getting value out of your solution. Itโ€™s no good.

โ€‹cautionโ€‹Some good recent examples of premature scaling can be seen in the cautionary tale of Zenefits, who sold epic amounts of deals without fully considering the costs associated with servicing the customers they brought onboardโ€”creating a situation where as reps sold more and more deals, they had more and more negative unit-economic customers on the books bleeding the company dry of resources. Eventually this led to massive layoffs of these inefficient reps who loaded the company with upside down customers.

The payments company Square had a similar situation when trying to take their Square Stand product to market into higher-end retail outlets beyond basic coffee shops in 2014. Instead of de-risking their go-to-market and first validating at a smaller scale that this new product fit the new market they were going after, Square hired 20 fairly senior AEsโ€”all with substantial salariesโ€”raising the burn of that business unit dramatically, under the assumption that they would be selling into higher end segments. They eventually realized that the product did not have the functionality required for those customers, which showed up in unsatisfactory win rates as compared to lower-end, coffee-shop deals that had previously been their bread and butter. They started to react to that, but unfortunately their hiring profile for AEs was far more senior than necessitated by the high velocity, transactional sale that Square Stand coffee-shop opportunities required. Ultimately most of the team left or was let go after having wasted large amounts of time and salary expense.

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The good news was Square has senior leadership whose reputation made it easy for them to raise lots of capital, and they had an existing Square Reader and Register business at the low end to help sustain them. But it put a huge cash divot into that business unit while they were figuring it outโ€”the kind of cash divot that would destroy a smaller company with less capital firepower behind it.

Lagged Scaling

The other anti-pattern you commonly see in scaling is simply not doing it. This is different from organizations that think that they donโ€™t need to do salesโ€”we already addressed that in the first section of this book. Rather, this is the situation where a founder or early salesperson has gotten good at selling the solution and can reliably and repeatedly turn new meetings into closed deals at a consistent win rate. But rather than recognizing that they need to move on from just turning the crank on more deals, they get stuck doing just that, either motivated by running up the customer count, or because theyโ€™re unaware of the need to move on, or afraid of the next set of challenges that need to be addressed.

โ€‹cautionโ€‹Whatever the cause, this failure mode, while less common than premature scaling, and also less existentially threatening, is problematic in its own way. Unlike premature scaling which threatens to burn cash reserves and shorten your runway, lagged scaling is more about eating opportunity cost. Once you have proven that a founder can reliably sell the solution, the next step in scaling the organization is packaging that ability so it can be scaled out across multiple sales repsโ€”which is the key to scaling a B2B sales organizationโ€™s revenue acquisition. The more time that is wasted before moving from doing to packaging and then proving that this de-risked sales motion can be replicated by others, the more time is lost as your runway shortens. (You likely have far more engineering salary expense than revenue at this pointโ€”so the quicker you can ramp up your revenue acquisition, the faster you can get to cash flow.) And that time is lost to competitors attacking the market.

Moreover, consider that your goal in building your org is to build enterprise value as quickly as possible. The means by which organizations are valued for either acquisition or public flotation is multiples of revenue, so time lost acting as a sales rep when you could be acting like a sales manager, and adding multiple units of revenue production (sales reps!), keeps you from building enterprise value in your org.

When Is the Right Time to Scale Sales?

So if this is indeed a Goldilocks situation where we donโ€™t want to scale too soon, and donโ€™t want to wait too long, then how do you know when youโ€™re ready to go?

First, itโ€™s less of a binary โ€œnow youโ€™re not ready, poof, now you areโ€ situation, but instead itโ€™s typically better to treat this like making your way into a hot jacuzzi, a bit at a time, validating that things are working as you go, but always making constant progress.

How do you know the time is right for you to take that first step of bringing on another sales rep, or two, to prove that someone other than you can sell the solution? Usually the answer can be found in the math of your sales metrics. A good B2B sales win rate is typically anywhere between 15% and 30%. Of all demos or first meetings you do, eventually 15โ€“30% turn into closed-won deals (while the others either closed-lost or fizzle out into nothingness). If you find yourself in this range reliably, then itโ€™s probably time to bring on other reps and prove that you can get them to close at a similar pace. If your win rate is substantially above thatโ€”well maybe consider raising your pricing, but certainly get a move on on abstracting and scaling your sales function! If your win rate is below that, then it probably makes more sense for you to figure out why only, say, 10% of your initial engagements are turning into customers before you turn to scale up customer engagements. Whether itโ€™s the result of your messaging, product feature deficit, or pricing, sort that out first before scaling up.

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