Catalog
concept#Architecture#Product#Governance

Build vs Buy Decision

Decision framework for weighing whether to develop a solution in-house or procure it externally.

The build-vs-buy decision is a structural decision model for evaluating whether software or components should be developed in-house or sourced externally.
Established
Medium

Classification

  • Medium
  • Organizational
  • Architectural
  • Intermediate

Technical context

SaaS vendors and managed servicesInternal platform and infrastructure componentsCI/CD and operations tooling

Principles & goals

Clear objectives: decide based on strategic product goals.Consider total cost of ownership, not only upfront costs.Cross-functional evaluation with product, engineering, and procurement.
Discovery
Enterprise, Domain, Team

Use cases & scenarios

Compromises

  • Vendor lock-in and reduced flexibility.
  • Underestimating integration and operational costs.
  • Lack of strategic control over critical core functions.
  • Start small: validate proofs-of-concept for both options.
  • Consider lifecycle costs over multiple years.
  • Define contractual exit clauses and SLAs clearly.

I/O & resources

  • Product vision and roadmap
  • Technical requirements and architecture overview
  • Cost and resource estimations
  • Documented decision rationale with options comparison
  • Recommended implementation plan and timeline
  • Identified risks and migration paths

Description

The build-vs-buy decision is a structural decision model for evaluating whether software or components should be developed in-house or sourced externally. It weighs costs, time-to-market, strategic advantage, and total cost of ownership. The decision requires cross-functional input from product, engineering, and procurement.

✔

  • Reduced time-to-market when using existing solutions.
  • Control and differentiation when building in-house.
  • Transparent risk and cost assessment enables informed decisions.

✖

  • Not all requirements can be covered by standard products.
  • Internal development ties up resources and extends delivery timelines.
  • External vendors can create long-term dependencies.

  • Time-to-Market

    Time until functionality is available to users.

  • Total Cost of Ownership (TCO)

    Cumulative costs over the considered lifecycle.

  • Risk score

    Combined assessment of technical, legal, and operational risks.

Using a payment service provider instead of building a payments platform

Startup reduced time-to-market by integrating a SaaS payment provider instead of building in-house.

Building an in-house core search capability

Company opted to build in-house to secure differentiating search quality and control.

Using a managed hosting provider for infrastructure

Organization shifted operations to a managed service to reduce operational effort and focus on product features.

1

Consolidate and prioritize requirements

2

Conduct market research and vendor evaluation

3

Produce cost, risk and TCO analysis

4

Cross-functional review and document final decision

⚠️ Technical debt & bottlenecks

  • Growing maintenance burden from heavily customized vendor components.
  • Legacy created by fragmented in-house developments without standards.
  • Lack of documentation following quick decisions favoring fast delivery.
Lack of internal capacityIntegration complexityLong-term contractual commitments
  • A company builds a non-differentiating infrastructure component instead of using an inexpensive SaaS solution.
  • Product team decides without involving operations and security — resulting in significant rework.
  • Procurement signs a long-term contract without technical validation.
  • Underestimating ongoing integration and operational costs.
  • Ignoring future scaling requirements when buying.
  • Missing exit strategy for vendor decisions.
Architecture and integration expertiseFinancial assessment and TCO skillsContracting and procurement knowledge
Scalability and performance requirementsSecurity and compliance constraintsTime-to-market and product strategy
  • • Budget constraints and funding cycles
  • • Regulatory requirements and data sovereignty
  • • Organizational decision-making and procurement processes