Business Scaling: Capacity vs. Demand Simulator

Growth Levers

Marketing spend / mo $8,000

Hiring rate (hires/mo) 1.0

Subscription price / mo $60

Business State

Month 0 · Seed stage

Service quality100%

Customers

Team size

Capacity utilization

40%

Monthly churn

3.0%

Cash

$50,000

Runway

∞

How it works

Each employee can competently serve a limited number of customers. This is a capacity-constrained growth model — the same "scaling trap" that has sunk real startups that grew demand faster than their ability to deliver:

Capacity   C = teamSize x 20 customers/employee
Utilization U = customers / C
Quality    Q = 1 / (1 + max(0, U-1) x 2.2)   (1 = perfect, drops when overloaded)
Churn      c = c_base + (1-Q) x 0.35 + priceDrag
Acquired   a = marketingSpend / CAC(price)   (higher price -> pricier CAC)
dCustomers = a - c x customers   (per month)
Revenue    R = customers x price x Q
Costs      = teamSize x $6,000 + marketingSpend
dCash      = R - Costs   (per month)

Marketing spend — buys new customers at a fixed cost-per-acquisition; pushes demand up.
Hiring rate — adds staff over time, raising capacity C and therefore how much demand the business can serve without quality collapsing.
Price — raises revenue per customer but also raises churn slightly and the cost of acquiring each customer (harder sell).
When utilization U rises above 100% (green capacity tower is smaller than the customer swarm), quality Q falls, churn rises, and customers turn red and peel away — the visual signature of over-scaling.

Real-world relevance: this same demand/capacity feedback loop governs support-ticket backlogs, restaurant table turnover, hosting infrastructure load, and hospital bed occupancy — any service business that must add capacity ahead of demand or pay for it in quality and churn.

Month 0

Team capacity (tower) Served customers Overloaded / churning

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