The framing of build versus buy implies a binary choice. In practice, most technology decisions are more nuanced and the teams that make them well are asking a different set of questions from the ones that end up with expensive regrets on both sides of the ledger.
The problem with the binary
Build versus buy is shorthand for a more complicated set of trade-offs: control versus speed, customisation versus maintenance burden, capital expense versus operating expense. Framing it as a simple choice causes teams to optimise for the wrong variable.
The teams that consistently make good technology decisions are not asking 'should we build or buy?' They are asking: which parts of this problem are genuinely specific to how our business operates, and which are solved problems that someone else has already invested decades and capital into?
Three questions that resolve most cases
Is this a competitive differentiator? If the capability you are trying to build is visible to your customers or directly affects how you outperform competitors, it almost certainly warrants custom development. Your payroll processing probably does not. Your pricing model, risk engine, or customer-facing product experience probably does.
What is the five-year total cost of ownership? SaaS pricing is seductive at small scale and expensive at large scale. Model the cost at three times your current volume the number of staff using it, data processed, seats required. Compare that to an amortised build cost plus ongoing maintenance. The crossover point is usually earlier than most finance teams expect.
What is the integration tax? Off-the-shelf tools rarely fit cleanly into existing infrastructure. The cost of making them work API integrations, data migrations, custom connectors, and the ongoing engineering overhead of maintaining those connections can easily double the effective cost of a SaaS subscription over three years.
The integration tax is almost always underestimated. Every connection between a bought tool and your existing systems is an ongoing maintenance liability, not a one-time engineering cost.
When SaaS is the right answer
SaaS wins decisively in three scenarios: when the function is genuinely commodity, when you need to move faster than a build timeline allows and the cost of delay outweighs the cost of fit, and when your usage patterns are standard enough that the platform's defaults require minimal adaptation.
The mistake is treating these as permanent decisions. A SaaS tool that is right at your current scale may be the wrong choice three years from now. Build the capability to revisit these decisions on a two-year cycle as your business changes.
When custom is the right answer
Custom development wins when the process being digitised is genuinely unique to your business model, when the data or logic at the core of the process is a competitive asset, or when the available SaaS alternatives require you to significantly change how you operate to fit their model.
It also wins when your integration landscape is already complex. A purpose-built system designed around your data model and your existing tools will always integrate more cleanly and remain easier to maintain than a third-party platform retrofitted into a stack it was not designed for.
- Competitive differentiation test: if a direct competitor buying the same SaaS product would reach feature parity, that is a signal to build
- Scale sensitivity: model costs at 3× current volume before committing to per-seat or usage-based pricing
- Integration count: more than two integrations with existing systems tilts the decision toward custom
- Process uniqueness: if your team would spend more than 20% of their time working around the platform's defaults, build
- 01Apply the competitive differentiator test before evaluating cost capability matters more than price
- 02Model total cost of ownership over five years at three times current scale before committing to SaaS
- 03Integration overhead is a permanent maintenance cost, not a one-time implementation project
- 04Technology decisions should be formally reviewed on a two-year cycle as business scale changes