Illusions of scale: does 1 x 3 = 2, 3 or 4?

Proving scalability is the final step in achieving product market fit, and a stage in startup growth where massive valuation gains can come with spend. But what does scalability really mean? Scalability is often misused and mis-understood among startup investors and founders. My conversations with startups usually go like this:

Them: “We’re at $50K in MRR and are producing $100K a month in new ARR with 5 sales development reps (appointment setters) and 5 account executives (closers).”

Me: “Nice! What is your ACV (annual contract value)?”

Them: “$10K. Each person is closing two deals a month. We’re going to add another pod and double our growth.

This is a good spot to be in, but there is spectacular nuance around whether a startup is “scalable” so that adding a second sales pod actually doubles growth. For a B2B business, I think about scalability in three modes, answering the question “what happens when I add more sales pods?”


1 x 3 = 2: In this mode, there are diminishing marginal returns to adding sales pods. Your second has less impact than the first and your third less impact than the second. This usually looks like an asymptoting revenue curve but could also disguise itself as a straight line where you need to add more and more sales people just to keep up the same linear revenue growth. (Why? churn… more on that later)

1 x 3 = 3: Sales pods scale the business “piecewise” linearly. Marginal returns to increased sales and marketing spend remain constant.

1 x 3 = 4: Adding sales pods has an exponential impact on growth. Marginal returns increase.


Three modes

Clearly the third mode is “scalability”; the second mode too though not as excitingly so. The first mode – and where we see most startups who *think* they are ready to scale – is an illusion of scalability.

The factors that qualitatively contribute to scalability and that we look for when we invest are diverse across categories of people, customer and market:

Scale final.png

*Cash efficiency is increase in MRR per month divided by net cash burned per month. **These are estimates and relevant ranges depend on exact business model and whether inside sales is single or double layer. For ACV ranges in self-service or enterprise (outside) sales models, look here

Cash efficiency can be a self-fulfilling prophecy

Cash efficiency is a key startup output metric that we look at to determine if a business is scaling well, but the relationship is circular. Cash efficiency is an input to a startup in that it helps dictate the capital barriers to growth that the company will face. Even if a cash inefficient startup could scale with access to enough capital, it’s not likely to get it. Insiders will get tired, and new investors won’t want to invest for marginal gains in valuation.

People make revenue

The talent factor is often overlooked in scaling. While people factors across an entire organization come to bear in scaling (senior team up-leveling, management tiering, training, etc), sales talent development is immediately critical to scaling. Once founder sales and early expansion of the sales team are proven, a strong sales leader is needed. Then do you have the talent pipeline to hire your second set of five sales people? How about 10, 15, 20? Do you have the training to ramp them to quota? We see almost every startup stumble here, impacting marginal gains to sales team investment. Piecewise linear growth is literally impossible without getting sales talent right.

Customer: Revenue yields growth, churn kills it

So how do you edge into exponential growth? We look for high annual contract values (ACVs) that are growing. This means ~$500+ for self-service (online) sales, $5K+ for inside sales, $100K+ for enterprise… and increasing. ACV growth is the key leading indicator of exponential growth potential in a startup. If you double the sales team effectively, you get 1 x 2 = 2. If you double ACV too, you get 1 x 2 x 2 = 4. A sales person may be able to do the same number of deals but sell twice as much. Sweet!

Why else do we like high ACVs? Churn is inversely correlated with ACV. Higher ACVs lead to lower churn, easing the path to scalability. Churn is the enemy of scalability because the $ magnitude (not %) of churn grows with revenue while revenue magnitude scales with sales people. That means holding everything else constant, you have to add sales people just to keep up with churn, or the leaky bucket will overwhelm your growth! Below is a chart showing how long it takes churn (gross, or net without upsells) to destroy 50% of the productivity of a 10K MRR/month pod. At 4% monthly churn, you start measuring in months. Yikes.


Over the past few years, we’ve seen an obsessive focus on net churn (net of upsells) in the market. There are two reasons for this – one nefarious and one practical. The nefarious reason is that gross $ churn (before upsells) is usually awful in early stage startups, so it’s not fun to talk about. Fortunately, a startup that initially uses “penetration” pricing can offsets this with rapid upselling, sometimes leading to negative net churns of -5 to -15%, a good thing. We love negative net churn, but it should never mask gross churn. Low gross churn is a high fidelity sign of product market fit and matters increasingly as markets and products mature and you can’t upsell as rapidly to offset a leaky bucket.

Calling all expanding and viral markets

Scalability (and churn) are also tied to market maturity. In a new, fast growing market (left side below), competitors are like free radicals meandering inside an ever-expanding market. Lines of competitive battle are fuzzy or non-existent, and customers can be acquired and retained with little competitive tension. Often at this stage, your biggest competitor is “do nothing”. Mature markets (right side below) instead have fixed market sizes and established competitors. This competitive pressure creates clear lines of competition littered with churned customers!


Holding everything else constant, a startup entering a maturing market will have a harder time winning and retaining customers… and therefore see greater barriers to scale.

Finally, virality and network effects are big unlocks to achieving exponential scalability in B2B startups. We know this anecdotally from stories like Dropbox and Slack – and certainly SaaS collaboration takes the cake for B2B virality and network effects. These companies didn’t rely on sales teams early on, relying instead on self-service online sales. Self-service sales makes achieving exponential growth with the aid of virality and network effects easier, but direct sales models can pull it off too. Every time our portfolio company, Geofeedia, sells its security monitoring solution to a new municipality, neighboring cities find out about it and see it in use (virality) while increasing the value to them because their neighbor already uses (network effects). This increased value ultimately translates to higher ACVs. Harmonious and …exponential.

8 thoughts on “Illusions of scale: does 1 x 3 = 2, 3 or 4?

  1. Another fantastic post. So what I love to do is take your approach and apply it to healthcare to see if the pressure of specialization crumples the general logic.

    1. White Space vs. Mature Market (healthcare):
    In healthcare I think there’s a nuance assigned to regulation, integration and professionalization. A start-up building a new market in healthcare will die like a fruit fly if they can’t withstand the disease of regulation (reimbursement, HIPAA, geographic disparities, etc.) or if they cannot find a way to integrate the solution into the eco-system. Why is this different than other markets? Take Uber for example. There’s a lot of regulation around taxis/etc., but it’s built to bolster non-professional workers (taxi-cab drivers). People talk about being the “Uber of healthcare” – but what they really mean isn’t that they are creating an entirely new market for transportation/data collection but that they are building a cool app WITHIN the healthcare ecosystem.

    In this way, it is nearly impossible to have a white-space healthcare application because there are always “system boundaries” of regulation, integration and professionalization. Otherwise it wouldn’t be healthcare!

    The real world impact is that healthcare entrepreneurs can think big, bold visions within that framework but should not expect to fundamentally change the healthcare landscape. Drilling down, this means that healthcare companies, even those with relatively new markets (like telemedicine/digital health) will always face more Mature Market forces than other markets. Plan accordingly both on the investor side and entrepreneur side.

    2. People Make Revenue:
    Love this. What I’m hyper focused on is time to revenue. A variable in that equation is time to productivity for the sales team. An interesting metric would be to measure the churn rate vs. time to productivity for new sales members. E.g. how much faster is the water flowing out than being pumped in (or alternatively, can I pump more water in via account management/existing clients than new ones?)? It could be that it’s not an addition problem (1+1=2) but an allocation problem – where talent can be better applied at reducing churn than being used to generate new revenue (for example, if I have 3 sales members and one account manager, am I better off applying an existing sales member, because she understands the market/product, to reduce churn/service extension revenue, than trying to hire and train a new sales person? Maybe if their time to productivity is instant..).


    1. Jon, thank you for these terrific thoughts. I largely agree:

      My thoughts:
      1. Uber didn’t create a new market. They just did an existing one differently. The way they did it was white space but they had a lot of regulation in their way – which they blew through. So I’m not sure the same rules don’t apply in HC… but maybe another way to think of it is that the air in the empty balloon is viscous because of regulation, reimbursement, etc

      2. You can’t grow a business fast unless you do both sales and customer success. It’s not either or. But sure with constrained resources there should be an optimal ratio. Technically I think it’s a differential equation where you solve for the ratio by setting the delta revenue as a function of change in sales person equal to delta revenue as a function of change in customer success person. Or something like that!

  2. Hi Guy – great piece! I recently read a complimentary article on scaling your company’s ‘unit of value’: I think these go hand in hand, and could link to a *Product* row in your framework (Value requires explanation, Value quantified, Value builds through utilization). We’ve found this when trying to move from penetration pricing to a higher ARR; the most seasoned reps can be agile, and problem solve in the sale. Scaling that then becomes tricky, and diminishes with each new rep, because it’s not quite inherent in the product implementation yet. The clearer that unit of value, the less friction on a new rep.

  3. Hey Guy – I’m trying to calculate how much value each closer produces per month, but have a few questions given that we operate under monthly billing (i.e., no annual contracts). i/ assuming we have a decent churn (<1.5%) and customers stay for multiple years, how would we calculate the value produced each month by closers? Would it be ARR? If so, should we simply multiply the new MRR x 12? ii/ Is there a proxy that we can use for ACV under monthly billing? If so, how should we calculate? MRR x 12? (Note: even though our customers stay for multiple years, something seems off by simply multiplying by 12 as there are instances when customers leave before they year is out).

    1. Indeed, for a specific customer in monthly SaaS, ARR = MRR*12. Average contract value is a bit of an irrelevant term for monthly SaaS, but fine to use as MRR*12 understanding the caveats.

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