> tpl_arc_007
Technology Evaluation and Build/Buy Decision Workbook
Comprehensive technology evaluation framework and financial decision workbook comparing custom in-house build, commercial off-the-shelf (COTS), open-source software (OSS), and SaaS options across 5-year Total Cost of Ownership (TCO), vendor lock-in risk, integration complexity, and strategic core differentiation.
Strategic architecture scoring workbook evaluating multi-year build vs buy economics, implementation runway, engineering opportunity cost, and strategic IP value.
Important Tech Document Template & Operational Notice
TinyCTO.tv Tech Document Template Notice: This template is a general educational and operational starting point. It is not legal, tax, accounting, investment, procurement, regulatory, security or certification advice. Requirements vary by jurisdiction, organization, contract and risk. Review and adapt it with qualified professionals before relying on it.
Problem Solved
Engineering teams succumb to "Not Invented Here" syndrome and spend millions reinventing commodity software (e.g. auth, billing, search), depleting capital needed for competitive, revenue-generating core features.
When to Use
- •Deciding whether to build bespoke internal platforms or purchase specialized commercial SaaS/COTS tools
- •Comparing multiple competing commercial technology vendors during enterprise RFP selection processes
- •Evaluating 3 to 5-year Total Cost of Ownership (TCO) including maintenance, upgrades, and hosting overheads
When NOT to Use
- •For evaluating trivial npm libraries or open-source utility dependencies with zero commercial cost
- •For individual employee hardware laptop purchasing decisions (use general IT procurement)
5 Template Sections & Structural Outline
Assessing whether the capability is a core competitive moat or commodity context that should be outsourced/bought.
Weighted scoring matrix covering feature parity, scalability, API maturity, security certifications, and extensibility.
Comparing build (dev labor, infrastructure, ongoing maintenance) vs buy (subscription, implementation fees, seat growth).
Assessing vendor financial solvency, data export capabilities, proprietary lock-in risks, and contingency transition paths.
Final weighted score ranking, executive summary, risk trade-off justification, and formal governance sign-off.
Completion Instructions
Independent Review Checklist
- All mandatory sections completed
- No secrets or passwords included
- Executive sponsor sign-off obtained
Technology Evaluation and Build/Buy Decision Workbook - Worked Case Study
Fictional Entity: Enterprise Search & Vector Discovery Engine Build vs Buy Assessment
Real-world production case study demonstrating complete operational adoption for Enterprise Search & Vector Discovery Engine Build vs Buy Assessment.
- •Evaluated 2 commercial search SaaS platforms against custom Elasticsearch / Milvus in-house architecture
- •Calculated 5-year TCO revealing in-house build cost $2.4M vs $1.1M commercial SaaS due to specialized ML engineering labor
- •Selected commercial SaaS with contractually guaranteed sub-30-day raw data export clause mitigating vendor lock-in
Frequently Asked Questions
What is "core vs context" and how does it drive the build vs buy decision?
Defined by Geoffrey Moore, "core" represents capabilities that create direct competitive advantage and customer differentiation—these should almost always be built in-house. "Context" encompasses essential supporting operations (e.g. email delivery, user authentication, payroll) that customers do not buy your product for—these should almost always be bought from specialized vendors.
Why are internal build estimates almost always lower than actual multi-year costs?
Engineering teams consistently underestimate ongoing "Day-2" operational costs, including security vulnerability patching, third-party dependency updates, architectural refactoring, documentation maintenance, and high developer turnover. A build initiative that costs $200K to code typically requires $80K to $100K every year thereafter just to keep operational.
How can an organization mitigate vendor lock-in when choosing to buy COTS/SaaS?
Mitigate lock-in by enforcing standard data interchange formats (JSON/Parquet), requiring comprehensive REST/GraphQL APIs for automated data egress, establishing contractual service level agreements (SLAs) for data extraction upon termination, and encapsulating the vendor behind an internal abstraction layer (Adapter pattern).
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Authoritative Sources
- Dealing with Darwin: How Great Companies Innovate at Every Phase of Their Evolution (Geoffrey Moore)Portfolio / Penguin • OFFICIAL REQUIREMENT
- TOGAF Standard: Architecture Development Method (Phase D: Technology Architecture)The Open Group • OFFICIAL REQUIREMENT