Alessandro L. Piana Bianco
Strategic Innovation & Design — EU / MENA
← Glossary

Common core + local layers

Common core + local layers is how you scale across markets, channels, and partners without creating a Frankenstein product. You design what must stay consistent—and you explicitly design what can vary.

Definition

  • The common core is the shared foundation: system primitives, patterns, language, and key flows that must remain coherent.
  • Local layers are controlled variations: market rules, regulatory constraints, content, payment rails, operational realities.
  • The model only works when “local” is designed, not improvised.
  • This is not just architecture; it’s a governance contract: what teams can change, how they change it, and how divergence is controlled.

Why it matters

  • Global programs fail when teams either over-standardise (ignoring local reality) or over-localise (fragmenting the product).
  • Ecosystems amplify divergence: vendors, APIs, and regulations change per market.
  • A clear core/local model accelerates delivery: teams reuse what works and adapt with guardrails.
  • In practice, this is where many digital programs fail: the concept is understood, but the operating discipline is missing.

Common failure modes

  • False universality: assuming a single flow can satisfy all markets.
  • Local exceptions with no rules: every market becomes a bespoke fork.
  • Design system without governance: components are shared, but meaning and behavior diverge.
  • No versioning: changes to core break local implementations unpredictably.
  • “Local” as politics: stakeholders demand customisation without cost accountability.

How I design it

  • Define core primitives: identity, payments, state models, error handling, auditability patterns.
  • Define the variation surface: what can change (copy, content, compliance steps, integrations) and how.
  • Create pattern evolution rules: required vs optional patterns, exception process, deprecation.
  • Use state models to manage differences: states stay consistent even if steps vary per market.
  • Measure fragmentation: exception rate, divergent pattern variants, support debt by market.
  • Represent core vs local explicitly in artifacts: maps, patterns, and naming conventions that prevent accidental forks.
  • Treat it as a repeatable pattern: define it, test it in production, measure it, and evolve it with evidence.

Related work

Proof map claims

Case studies

See also

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