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Build Vs Buy Calculator

Compare in-house development vs vendor software costs over any time horizon, with state-adjusted labor rates, annual maintenance, and compounding SaaS price escalation.

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Savings from Buying vs Building (positive = Buy is cheaper)

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Savings from Buying vs Building (positive = Buy is cheaper)—

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Understanding the Build vs Buy Calculator Formula

The build or buy calculator quantifies the total cost of ownership (TCO) for two strategic paths: developing software in-house versus purchasing a vendor solution. The core formula computes Savings as the difference between total build cost and total buy cost over a defined analysis period:

Savings = [H · R · Ms + Cm · Y] − [I + Σ(t=0 to Y−1) S(1+g)t]

A positive result indicates building in-house is the less expensive path over the chosen horizon. A negative result means purchasing from a vendor delivers lower total expenditure. Understanding each variable is essential to generating a reliable estimate.

Build Cost Variables

  • H — Development Hours: Total engineering hours required to design, build, test, and deploy the solution, including project management overhead, QA cycles, and internal documentation effort.
  • R — Blended Hourly Rate: The fully-loaded hourly cost of developers, encompassing base salary, benefits, payroll taxes, and allocated overhead such as office space and tooling licenses. Using fully-loaded rates rather than base salary alone prevents systematic underestimation of build cost.
  • Ms — State Labor Multiplier: A geographic adjustment factor derived from Bureau of Labor Statistics Occupational Employment and Wage Statistics for Software Developers. California developers carry a multiplier materially above the national median, while states such as Mississippi or Arkansas reflect multipliers near 0.75. This adjustment prevents geographic blind spots from distorting the comparative analysis by up to 30–40%.
  • Cm — Annual Maintenance Cost: The recurring annual expense to sustain the in-house build, typically estimated at 15–25% of initial development cost per year, covering security patches, bug remediation, compliance updates, and iterative feature enhancements.
  • Y — Analysis Years: The time horizon over which all costs accumulate. Most organizations use a 3- to 5-year window to balance forecast reliability with strategic planning relevance.

Buy Cost Variables

  • I — Implementation Cost: The one-time vendor onboarding expense covering integration engineering, data migration, staff training, and system configuration. The U.S. Small Business Administration guidance on startup costs highlights the importance of accounting for these often-underestimated one-time expenses when evaluating vendor solutions, as they commonly represent 20–50% of the first year’s subscription fee.
  • S — Annual Subscription: The baseline recurring annual fee for the SaaS license or vendor product in year one, before escalation is applied.
  • g — Annual Price Escalation: The expected yearly percentage increase in vendor pricing, expressed as a decimal. Enterprise SaaS vendors historically increase renewal prices 3–8% annually, compounding substantially over a multi-year horizon.

The Buy-Side Cumulative Cost Series

The summation Σ(t=0 to Y−1) S(1+g)t is a geometric series representing cumulative subscription expenditure with compounding annual price growth. For a non-zero escalation rate g, this simplifies to S · [(1+g)Y − 1] / g. A $60,000 annual subscription at 6% escalation over 5 years reaches $337,459 cumulatively versus $300,000 at a flat rate — a $37,459 difference that can materially shift the build vs buy outcome.

Worked Example

A mid-market company evaluates a custom order-management system against a SaaS alternative:

  • Build path: 2,500 engineering hours at a $115/hr blended rate with a Texas BLS multiplier of 0.95 yields $273,125 in initial development cost. Annual maintenance at 20% adds $54,625 per year. Total over 5 years: $273,125 + ($54,625 × 5) = $546,250.
  • Buy path: $20,000 implementation plus a $70,000/yr base subscription at 5% annual escalation over 5 years = $20,000 + $386,786 = $406,786.
  • Result: Savings = $546,250 − $406,786 = −$139,464. The vendor solution saves approximately $139,000 over five years, making buying the financially superior choice in this scenario.

Qualitative Factors Beyond the Formula

The calculator captures direct monetary costs with precision but does not quantify vendor lock-in risk, data sovereignty requirements, customization ceiling, competitive differentiation potential, or time-to-market speed advantages of pre-built solutions. Use the numerical output as a quantitative anchor within a broader strategic evaluation framework that weighs both financial and operational dimensions.

Reference

Frequently asked questions

What is a build vs buy calculator and how does it work?
A build vs buy calculator computes the total cost of ownership for two strategic paths: building software in-house versus purchasing a vendor solution. It sums all build costs, including state-adjusted engineering labor and multi-year maintenance, then compares them against all buy costs, including one-time implementation fees and compounding annual subscription costs, returning the net difference as savings or deficit over a user-defined horizon such as 3 or 5 years.
When does building software in-house cost less than buying a SaaS product?
Building in-house typically costs less when the vendor subscription is high relative to available internal engineering capacity, when vendor price escalation compounds significantly over a long analysis horizon of 5 or more years, or when deep customization would generate large vendor professional-services fees. For example, a $120,000 per year SaaS contract at 7% annual escalation over 7 years accumulates to roughly $1.07 million, an amount that can exceed the full cost of a comparable custom build plus ongoing maintenance.
How does the state labor cost multiplier affect the build vs buy analysis?
The state labor multiplier uses Bureau of Labor Statistics Occupational Employment and Wage Statistics data for software developers to scale the blended hourly rate to local market conditions. California carries a multiplier exceeding 1.20 relative to the national median, while states such as Mississippi reflect multipliers near 0.75. This geographic adjustment can shift the build cost estimate by 30 to 40 percent, which is large enough to reverse the build vs buy recommendation in borderline cases.
What annual maintenance cost percentage should be used for in-house software?
Industry practice places annual software maintenance cost at 15 to 25 percent of the initial development investment per year. Simple internal tools with stable feature sets typically fall near the 15 percent floor, covering security patches and minor bug fixes. Customer-facing applications requiring regulatory compliance updates, third-party API integrations, and ongoing feature development typically reach 20 to 25 percent. For a $300,000 initial build, annual maintenance costs range from $45,000 to $75,000, compounding substantially across a 5-year analysis window.
How does vendor price escalation affect the total cost of buying software?
Vendor price escalation applies a geometric growth series that models compounding annual subscription increases over the full analysis period. At 5% annual escalation, a $50,000 Year 1 subscription accumulates to approximately $276,281 over 5 years versus $250,000 at flat pricing. At 8% escalation, the same contract totals nearly $293,330 over 5 years. Because the effect compounds exponentially, accurately estimating the escalation rate is one of the highest-leverage inputs in any build or buy calculator analysis.
What time horizon should be used for a build vs buy analysis?
A 3- to 5-year time horizon is the industry standard for most build vs buy analyses, balancing forecast accuracy with strategic planning relevance. Shorter horizons of 1 to 2 years almost always favor buying because upfront development costs dominate before subscription fees accumulate. Horizons beyond 5 years tend to favor building when vendor price escalation is material, but forecast reliability declines sharply past 5 years due to technology evolution, vendor acquisition risk, and business model changes. Most finance and product teams default to exactly 5 years.