Build vs buy decisions now appear in roughly 25% of technology-related consulting cases, based on our analysis of 200+ recent interview prompts. These cases test whether you can balance strategic differentiation against speed-to-market — a tension that sits at the heart of every digital transformation initiative.
Why Firms Test Build vs Buy Cases
Consulting firms use build vs buy cases because they reveal three capabilities simultaneously: financial rigor, strategic thinking, and technology literacy. Unlike pure market sizing or profitability cases, build vs buy forces you to weigh qualitative factors (competitive moat, organizational readiness) against quantitative ones (TCO, time-to-value).
In our experience working with candidates across McKinsey, BCG, and Bain interview rounds, the most common mistake is defaulting to a cost comparison spreadsheet. Interviewers want to see you frame the decision strategically first, then validate with numbers.
The Decision Framework
Every build vs buy case can be structured around four evaluation dimensions:
flowchart TD
A[Build vs Buy Decision] --> B[Strategic Fit]
A --> C[Total Cost of Ownership]
A --> D[Execution Risk]
A --> E[Time-to-Value]
B --> B1[Core differentiator?]
B --> B2[Competitive moat?]
B --> B3[IP ownership needs?]
C --> C1[Development cost]
C --> C2[Maintenance burden]
C --> C3[Licensing fees over 5yr]
D --> D1[Talent availability]
D --> D2[Integration complexity]
D --> D3[Vendor lock-in risk]
E --> E1[Market window]
E --> E2[MVP timeline]
E --> E3[Iteration speed]
Dimension 1: Strategic Fit
The first question is always: does this capability create competitive differentiation? If yes, building makes sense. If the technology is table-stakes infrastructure, buying is almost always correct.
| Indicator | Lean Build | Lean Buy |
|---|---|---|
| Competitive differentiation | Core to value proposition | Commodity capability |
| Data sensitivity | Proprietary algorithms/data | Standard workflows |
| Customization needs | Unique to business model | Industry-standard process |
| IP ownership | Critical for valuation | Not material |
| Regulatory requirements | Bespoke compliance needs | Standard certifications sufficient |
Dimension 2: Total Cost of Ownership
TCO analysis over a 5-year horizon typically reveals that building costs 2-4x more than initial estimates suggest, once you factor in maintenance, security patches, talent retention, and opportunity cost. Based on our analysis of 50+ digital transformation case studies, organizations underestimate ongoing maintenance costs by an average of 60%.
Build TCO components: Initial development + hiring/retention + infrastructure + security + maintenance + opportunity cost of engineering bandwidth
Buy TCO components: License/subscription fees + implementation + customization + integration + training + vendor management overhead
Dimension 3: Execution Risk
This dimension often separates strong candidates from average ones. Risk assessment should cover:
- Talent risk: Can you recruit and retain the engineering team required? In competitive markets, a 12-month build timeline assumes zero attrition — unrealistic for most organizations.
- Integration risk: How many existing systems need to connect? Each integration point multiplies complexity non-linearly.
- Vendor risk: What happens if the vendor raises prices 40%, gets acquired, or sunsets the product? Evaluate switching costs explicitly.
Dimension 4: Time-to-Value
Market timing often overrides cost considerations. If a competitor will capture the market window in 6 months, a 14-month custom build is strategically irrelevant regardless of its long-term economics.
Common Case Scenarios
| Scenario | Typical Answer | Key Reasoning |
|---|---|---|
| Bank building fraud detection AI | Build | Proprietary data + regulatory moat + core differentiator |
| Retailer needs CRM system | Buy | Commodity capability, mature vendor market |
| SaaS company needs billing engine | Hybrid | Buy base platform, build custom pricing logic |
| Manufacturer needs IoT platform | Buy then customize | Speed-to-market critical, differentiation in analytics layer |
| Insurer building claims automation | Build core engine, buy surrounding tools | Claims logic is differentiator; HR/finance tools are not |
The Hybrid Approach
In practice, roughly 70% of build vs buy decisions in digital transformation end with a hybrid answer. Strong candidates recognize this early and frame it as “what to build, what to buy, and how they integrate.”
The hybrid framework:
- Decompose the capability stack — break the system into layers (infrastructure, platform, application, intelligence)
- Classify each layer — which layers are differentiating vs. commodity?
- Design integration architecture — APIs, data flows, ownership boundaries
- Sequence the roadmap — buy commodity layers immediately, build differentiating layers iteratively
Interview Tips for Build vs Buy Cases
Based on our experience coaching candidates through 300+ technology cases:
- Start with strategy, not cost — Frame why this decision matters competitively before opening a TCO model
- Ask about timeline pressure — Market windows often shift the answer decisively
- Probe the talent situation — “Does the client have engineering capability today?” changes everything
- Quantify switching costs — Both the cost of switching vendors AND the cost of abandoning a custom build
- Present the hybrid option — Real-world decisions are rarely binary; showing nuance demonstrates maturity
Key Takeaways
- Build vs buy cases test strategic thinking, financial rigor, and technology literacy simultaneously — pure cost comparison is insufficient
- Always start with strategic fit: if the capability is a core differentiator, lean toward building
- TCO over 5 years typically reveals that custom builds cost 2-4x initial estimates once maintenance and talent retention are factored in
- Time-to-value often overrides cost — a missed market window makes even the cheapest build irrelevant
- Roughly 70% of real decisions end as hybrid approaches; decompose the capability stack and classify each layer independently
- Interviewers reward candidates who probe organizational readiness (talent, culture, governance) rather than treating the decision as purely financial
Ready to practice technology cases with real-time feedback? Try our AI Mock Interview to test your build vs buy frameworks, or explore technology industry cases and strategic decision cases in our case library for more practice scenarios. For additional frameworks, see our Technology & Digital Strategy Cases guide and Digital Transformation Cases guide.