Framework

Scaling Laws Diagnostic Framework

TL;DR

Helps predict whether growth challenges stem from scale limits or execution failures.

A diagnostic framework for identifying which organizational properties scale favorably versus unfavorably, diagnosing scaling inflection points, and designing structures that accommodate scale transitions. Helps predict whether growth challenges stem from scale limits or execution failures.

When to Use Scaling Laws Diagnostic Framework

Use when experiencing growth challenges (declining productivity, slow decisions, coordination overhead), planning significant scaling, or diagnosing whether problems are structural versus executional.

How to Apply

1

Identify Your Scaling Exponents

Map key organizational properties and calculate how they scale with size (employees, revenue, customers).

Questions to Ask

  • How does revenue per employee change as headcount grows?
  • How do coordination costs (meetings, decision time) scale with headcount?
  • How does innovation rate per employee change with growth?
  • How does decision speed change as layers are added?

Outputs

  • Scaling exponents for key properties
  • Comparison to industry benchmarks
2

Calculate Approximate Exponents

Use the formula b = log(Y2/Y1) / log(X2/X1) to find scaling exponents by comparing values at two different sizes.

Questions to Ask

  • What was revenue/employee at 100 employees vs. 500 employees?
  • How did meeting hours/employee change between those sizes?
  • Did innovation rate per person increase or decrease?

Outputs

  • Numerical exponents for each property
  • Classification as sublinear (<1), linear (=1), or superlinear (>1)
3

Benchmark Against Biology

Compare your exponents to biological analogs to interpret their meaning.

Questions to Ask

  • Is revenue/employee >1.0 (superlinear, rare - network effects)?
  • Is revenue/employee 0.7-1.0 (healthy, like metabolic efficiency)?
  • Are coordination costs >1.5 (superlinear burden, like bone scaling)?
  • Is innovation rate <0.5 (very sublinear, stifling growth)?

Outputs

  • Interpretation guide
  • Action recommendations
4

Diagnose Scaling Inflection Points

Identify which threshold your organization is approaching or has passed.

Questions to Ask

  • Have you passed Dunbar's Number (~150)? Is informal coordination breaking down?
  • Are you in product-market fit scaling (100-500)? Is process replacing flexibility?
  • Are you hitting multi-product complexity (1,000-5,000)? Are decision bottlenecks at executive level?
  • Are you facing bureaucratic drag (10,000+)? Is innovation per employee declining?

Outputs

  • Current inflection point diagnosis
  • Symptoms checklist
5

Design for Favorable Scaling

Apply structural principles to improve scaling trajectories.

Questions to Ask

  • Can you modularize to keep effective size small (teams 5-10, divisions <1,000)?
  • Can you automate to achieve superlinear revenue scaling?
  • Can you reduce coordination surface area through vertical integration or APIs?
  • Which properties must you accept will scale unfavorably?

Outputs

  • Structural recommendations
  • Trade-off decisions

Scaling Laws Diagnostic Framework Appears in 1 Chapters

Framework introduced in this chapter

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