Custom Software Development: Build vs Buy

Most mid-market companies should buy software for commodity work and reserve custom software development for the few workflows that make them different, or that no product handles without a pile of workarounds. Decide on total cost of ownership over the system's life, not the first-year price, and insist on seeing a working prototype before you fund a build.

Is it cheaper to build or buy software?

Usually it's cheaper to buy, at least for the first year, than to pay for custom software development. A mature product spreads its development cost across thousands of customers, and it has already fixed a decade of other people's mistakes. Configuration costs less than construction.

The first-year price is the wrong number, though. Estimates of how much of software's lifetime cost goes to maintenance range from 60% to 90%, depending on the study (Schach put it at 67%, Pigoski at over 80%), according to a summary by Galorath. That cuts both ways. A custom system you build is a system you maintain for its whole life. A product you buy is one you pay for every year, at whatever price the vendor sets at renewal.

So the honest comparison is five or more years of cost on each side: licenses, renewals, integration, workarounds and staff time for the product; build, hosting, maintenance and change requests for the custom system.

What does buying really cost once you own it?

SaaS looks cheap per seat and adds up quickly. Zylo's 2026 SaaS Management Index puts average annual SaaS spend at $55.7 million (the median is $20.6 million) across an average of 305 applications. Those are large-company averages, but the pattern shows up at every size: the portfolio grows one reasonable purchase at a time.

The same report found:

79% of IT leaders saw price increases at renewal.
78% were hit by surprise charges from consumption-based or AI features.
Spending on AI-native apps rose 108% year on year.

Then there's integration. MuleSoft's 2025 Connectivity Benchmark found enterprises running 897 applications on average, with only 29% of them integrated. Every product you buy is another place your data lives, and another export someone has to reconcile at month end.

None of this means buying is a mistake. It means the subscription price is only the first line of the bill.

When does custom software development make sense?

A long-standing way to sort this out is Gartner's Pace-Layered model. It splits your applications into systems of record, systems of differentiation and systems of innovation. The short version: buy the commodity, build what differentiates.

Layer	Examples	Usual answer
System of record	Payroll, general ledger, email	Buy. Your payroll isn't why customers choose you.
System of differentiation	The workflow that makes you money, the reporting that runs the business	Often build, or buy and extend.
System of innovation	A new service or process you're testing	Prototype small, then decide.

Custom tends to pay when one or more of these is true:

The workflow exists in no vendor's catalog. Your team spends its week bending a rigid product to fit the way work actually moves.
Reporting is a manual assembly line. Executives need numbers that take people days a month to pull from several systems.
Your data is scattered. Several systems hold versions of the same truth, and nobody trusts any one of them.
The "temporary" spreadsheet is years old and quietly runs a critical process.

And it rarely pays when the need is generic, when a product already does 90% of the job, or when you don't have someone inside the business who owns the system after launch.

Two examples from insurance and manufacturing

The clearest numbers come from a construction contractor founded in 1942. Job-site and safety reports were on paper, and the office re-keyed them into payroll and invoicing. Decypher built a tablet-based reporting system that feeds time straight into payroll and generates invoicing from the job data. The published result: more than 35 hours saved across the business every week, including about 5 hours of admin per foreman and 30 hours of back-office data entry.

For a global automotive OEM, fragmented operational data was spread across legacy systems in the supply chain. Decypher Corp built a custom ERP that consolidated that supply-chain data into one platform and standardized the workflows around it. The company's own logic was the point, which is exactly where a one-size-fits-all package struggles.

For a leading U.S. insurer, the out-of-the-box reporting that came with a vendor's product couldn't serve its internal stakeholders. Decypher replaced it with custom reporting built around the metrics those people actually used. The core systems stayed bought; only the part that didn't fit was built. Both cases are summarized on our results page.

Why do custom software projects go over budget?

Because big projects are hard to predict, and the risk grows with the size of the commitment. A McKinsey and University of Oxford study of more than 5,400 large IT projects (budgets over $15 million) found they ran 45% over budget and 7% over time on average, and delivered 56% less value than predicted. About 17% went so badly they could threaten the company itself. The study dates from 2012, but it's still the standard reference.

In our view, a big part of that risk comes from committing large sums against a specification nobody has seen working. The fix isn't to avoid building. It's to shrink the bet, so custom software development is paid for in small, visible steps:

Prototype first. Ask for a working prototype against your real workflow before serious money changes hands. Decypher works this way: an initial call, a deep-dive discovery and a rapid prototype, all at its own cost, and you invest only once you have seen it handle your work.
Short timelines. Decypher aims to solve the core problem in two to four weeks, so you see progress in working software rather than in status reports, and can stop early if the value isn't there.
Build the differentiating slice, not everything. The insurer above didn't replace its core systems. It replaced the reporting that didn't work.
Plan for maintenance from day one. If maintenance is most of the lifetime cost, budget for it and decide who owns it before the first line of code.

Does AI change the build vs buy decision?

Somewhat, and not always in the direction you'd expect. AI-assisted development makes building faster, which lowers one side of the equation. But for generative AI tools specifically, MIT NANDA's 2025 report found that external partnerships reached deployment about 67% of the time, against about 33% for internal builds: roughly twice as often. The figures are self-reported, but the gap is large.

The practical reading: faster coding doesn't remove the need for people who've built this kind of system before. If you build, build with someone experienced, not just with new tools.

How to decide: a practical checklist

Before you sign another subscription or approve a build, answer these in writing:

Is this a system of record or a system of differentiation? If customers would never notice the difference, buy.
What does the product cost over five years, including likely renewal increases, integration and the staff hours spent on workarounds?
What would a build cost over the same period, including maintenance at 60% or more of lifetime cost?
Can you buy the core and build only the gap? Custom reporting on top of a bought system is often the cheapest answer.
Will the builder show you a working prototype first? If not, you're carrying the risk they should be carrying.
Who owns the system after launch? Name the person.

If you can't tell which side of the line you're on, that's a reasonable thing to get a second opinion on. Our custom software page explains how we scope it: we tell you whether to buy or build, and if a build makes sense, the work goes to Decypher, a Michigan shop that has been building since 1999 with a fully U.S.-based team. Decypher pays Salter Growth when an engagement goes ahead; you pay Salter Growth nothing. If you'd like to talk it through, book a call.

Contractors on Procore: the free Procore and QuickBooks sync check shows what the standard connector covers and what's still typed twice.

Sources

Decypher Corp, "Streamlining the Job Site Reporting Process" case study (decyphercorp.com, accessed September 2026)
Galorath, "Software Maintenance Cost" (accessed September 2026)
Zylo, "2026 SaaS Management Index" (2026)
Salesforce, "Integration Key as 93% of IT Leaders Turn to AI Agents Amid Soaring Resource Demands – New Research" (2025)
Gartner, build-vs-buy decision framework and Pace-Layered model (research document, paywalled)
McKinsey & Company and University of Oxford, "Delivering large-scale IT projects on time, on budget, and on value" (2012)
MIT NANDA, "The GenAI Divide: State of AI in Business 2025" (July 2025)

Build or buy? When custom software development pays