How do you calculate the true cost of building in-house?

Start with direct engineering costs (salaries, benefits, infrastructure), then add opportunity cost (what else the team could build), ongoing maintenance (20-30% of initial build cost per year), and operational overhead (monitoring, on-call, documentation). Most teams underestimate maintenance by 2-3x. A feature that takes 3 months to build will likely require 1-2 engineers maintaining it indefinitely.

When should you build even if a good vendor exists?

When the capability is a core differentiator for your product. If your competitive advantage depends on doing something better than alternatives, buying a generic solution means your competitors can match you by buying the same vendor. Also build when vendor data policies conflict with your compliance requirements, or when the integration complexity exceeds the cost of building from scratch.

What about open-source alternatives?

Open-source sits between build and buy. You get pre-built functionality without vendor lock-in, but you own the hosting, maintenance, security patches, and customization. Treat open-source like building: budget for ongoing engineering time. The code is free, but running it in production is not. Evaluate the project's maintenance health (commit frequency, issue response time, contributor count) before depending on it.

How do you handle the transition when switching from buy to build?

Run both systems in parallel during the migration. Build the replacement to handle the same data formats and API contracts as the vendor tool, so the switch is transparent to other systems. Set a hard cutover date and track migration progress against it. The most common failure mode is running both systems indefinitely because the replacement never reaches parity. Define minimum viable parity upfront and stick to it.

Should PMs or engineering leads make the build vs buy decision?

Both, together. PMs bring the business context: how strategically important is the capability, what's the timeline pressure, what's the budget. Engineering leads bring the technical context: integration complexity, maintenance burden, team capacity, technical debt implications. The decision requires both perspectives. Neither should make it alone.

Build vs Buy: When to Build In-House vs Buy a Solution

TL;DR: A decision framework for the build vs buy tradeoff. Total cost of ownership, competitive differentiation, vendor lock-in, and the questions that actually matter.

Every PM Faces This Decision

At some point, every product team confronts the same question: should we build this ourselves, or buy an existing solution? The answer seems simple until you try to calculate it. Vendor pricing looks cheap until you account for integration work. Building looks expensive until you account for the vendor's yearly price increases.

The build vs buy decision, as ThoughtWorks describes it, is really a bet on where your team's time creates the most value. Build when the capability is your competitive edge. Buy when it's commodity infrastructure that your users don't care about. The tricky part is distinguishing between the two.

Quick Comparison

Factor	Build In-House	Buy (Vendor/SaaS)
Upfront cost	High (engineering time)	Low to moderate (subscription + integration)
Ongoing cost	20-30% of build cost per year	Predictable subscription + usage fees
Time to deploy	Months to quarters	Days to weeks
Customization	Unlimited	Limited to vendor's configuration options
Data control	Full ownership	Subject to vendor's data policies
Maintenance burden	Fully on your team	Handled by vendor
Vendor lock-in	None	Moderate to high (data migration, API coupling)
Competitive differentiation	High (unique to your product)	Low (competitors can buy the same thing)
Team learning	Deep domain expertise	Surface-level integration knowledge
Scaling risk	Your problem	Vendor's problem (usually)

When to Build

Build when the capability directly contributes to why customers choose your product over alternatives. This sounds obvious, but teams regularly misjudge what counts as differentiation.

Build when:

It's your core differentiator. If your product's value comes from doing X better than anyone else, you can't outsource X. A recommendation engine for a discovery platform. A real-time collaboration layer for a design tool. A pricing algorithm for a revenue management system. These are worth the engineering investment because they're why customers pay you.

Vendor integration is more work than building. Sometimes the vendor's API is so limited, their data model so different from yours, or their authentication so clunky that the integration project rivals the effort of building the feature from scratch. If the integration estimate exceeds 60% of the build estimate, strongly consider building.

Data sensitivity is paramount. Healthcare, finance, and enterprise B2B products often have compliance requirements that vendor solutions can't satisfy. If your customers' contracts prohibit sending data to third parties, the vendor option disappears.

You need to iterate fast on this capability. Vendor roadmaps don't bend to your priorities. If you need to ship changes to this capability weekly, owning the code is the only way. Waiting months for a vendor to add a feature you need is painful. Use the ROI Calculator to quantify the cost of that delay.

The market lacks a good vendor. If existing solutions are immature, poorly maintained, or aimed at a different use case, building may be the only viable path. But verify this thoroughly before concluding the market is empty.

The Build Trap

The danger of building is underestimating ongoing costs. Building a feature takes 3-6 months. Maintaining it takes forever. A team of 3 engineers building a notification system for 4 months will need at least 0.5-1 engineer maintaining it indefinitely: bug fixes, scaling, new channel support, deliverability monitoring, compliance updates.

Before committing to build, answer these:

Who maintains this after launch? Name specific people
What's the on-call burden? Who gets paged at 2 AM when it breaks?
What features won't get built because this team is maintaining internal infrastructure?
Are you comfortable with this technical debt tradeoff for the next 3 years?

When to Buy

Buy when the capability is necessary but not differentiating. Authentication, payments, email delivery, monitoring, analytics. Your users don't choose your product because of your login page.

Buy when:

It's commodity infrastructure. Auth, payments, email, SMS, error tracking, logging. These are solved problems. Building your own auth system is almost never worth the security risk and engineering cost. The PM Tools Directory covers the best options across categories.

Speed matters more than control. If you need the capability in weeks, not months, buying is the only option. A competitor launching a similar feature next month doesn't give you time to build from scratch.

Your team lacks domain expertise. Building a search engine without search engineering experience produces a bad search engine. Building a payments system without payments expertise produces a risky payments system. Vendors have specialist teams that your generalist engineers can't match.

The vendor's scale gives you advantages. Email deliverability, fraud detection, and CDN performance all improve with scale. A vendor serving thousands of customers has better deliverability reputation, more fraud data, and more edge nodes than your single-product infrastructure ever will.

Total cost is genuinely lower. Compare 3-year total cost of ownership, not just year-one pricing. Include: vendor subscription, integration engineering, ongoing integration maintenance, and the opportunity cost of engineering time. For guidance on evaluating market fit and sizing, the TAM Calculator can help quantify the business opportunity you're enabling.

The Buy Trap

The danger of buying is vendor lock-in. Every vendor integration creates a dependency. The deeper the integration, the harder and more expensive it is to switch. Lock-in manifests in three ways:

Data lock-in. Your data sits in the vendor's system in their format. Exporting it is painful or impossible. Always verify data export capabilities before signing
API lock-in. Your codebase is coupled to the vendor's API. Switching requires rewriting every integration point. Use an abstraction layer to minimize coupling
Process lock-in. Your team's workflows depend on vendor-specific features. Switching requires retraining and process redesign

Mitigate lock-in by:

Wrapping vendor APIs in your own abstraction layer
Ensuring you can export your data in standard formats
Avoiding vendor-specific features when standard alternatives exist
Negotiating data portability terms in the contract
Reviewing the vendor's financial health. Acquisitions and shutdowns happen

The Decision Framework

Run through these questions in order. The first "yes" answer is usually your answer.

Build if:

Is this your core product differentiator? If yes, build. No exceptions
Would buying create unacceptable compliance or security risk? If yes, build
Is the integration effort >60% of the build effort? If yes, build
Do you need to iterate on this capability weekly? If yes, build

Buy if:

Is this commodity infrastructure? If yes, buy
Do you need it deployed in <4 weeks? If yes, buy
Does your team lack domain expertise to build it well? If yes, buy
Is the 3-year TCO of buying <50% of building? If yes, buy

Dig deeper if:

The build and buy costs are within 2x of each other
The capability is moderately differentiating
You're uncertain about vendor stability or roadmap fit

The product strategy framework covers how build vs buy decisions fit into broader strategic planning.

Cost Comparison Template

When you need to present this decision to leadership, structure it as a 3-year total cost comparison.

Build costs:

Initial engineering (headcount x months x fully loaded cost)
Infrastructure (hosting, monitoring, CI/CD, staging environments)
Ongoing maintenance (20-30% of initial cost per year)
Opportunity cost (what the team would have built instead)
Security and compliance (audits, penetration testing, certifications)

Buy costs:

Subscription or license fees (year 1, 2, 3 with expected increases)
Integration engineering (initial build + ongoing maintenance)
Data migration and setup
Training and change management
Switching cost (estimated cost to replace the vendor if needed)

Most teams discover that building costs 2-5x what they initially estimated. As Martin Fowler describes in his analysis of technical debt, the first estimate always underweights maintenance, on-call, and opportunity cost. The technical debt guide explains why these hidden costs accumulate.

Hybrid Approaches

Not every decision is binary. Three hybrid patterns work well:

Build on top of a platform. Use a low-level vendor (database, cloud functions, message queue) and build your differentiating logic on top. You get infrastructure reliability without the lock-in of a feature-complete SaaS tool.

Buy now, build later. Use a vendor to ship quickly, learn from real usage, then build a custom replacement once you understand the requirements. This works when speed-to-market matters more than long-term efficiency. Set a timeline for the "build later" decision so it actually happens.

Build the core, buy the edges. Build the differentiating core yourself and buy the commodity pieces around it. A product analytics company might build its own event pipeline and query engine but buy Stripe for payments and Auth0 for authentication.

Common Mistakes

Underestimating maintenance. The feature you built in Q1 needs a full-time engineer by Q4. If you wouldn't hire an engineer to maintain this indefinitely, don't build it.

Overvaluing customization. "We need full control" is often an emotional argument, not a business one. Ask what specific customization you need that the vendor can't provide. If the answer is vague, buy.

Ignoring opportunity cost. The 3 engineers building internal tooling could have been building customer-facing features. Every build decision is also a decision not to build something else.

Choosing based on current needs only. Your requirements will change. A vendor that fits today may not fit in 18 months. A system you build today may need capabilities you can't predict. Evaluate both options against your 12-18 month product roadmap, not just today's requirements.

Making the decision alone. Build vs buy requires both business judgment (PM) and technical assessment (engineering). A PM making this call without engineering input will underestimate build costs. An engineer making it without PM input will underweight strategic importance.

Bottom Line

Build what makes your product unique. Buy everything else. When in doubt, bias toward buying first and building later, because you'll learn what you actually need from real usage. The worst outcome is spending 6 months building something, launching it, and discovering you needed different capabilities than you assumed.