Build or buy: when does a custom GRC tool make sense, and when does it not?
A custom GRC application makes sense when your risk taxonomy genuinely cannot be represented in any off the shelf platform's data model without a material compromise, or when your reporting can run directly on data you already hold and a separate platform would mean maintaining a second copy of it. In every other case, configuring an existing platform against your own taxonomy is faster, cheaper and lower risk than building. If you cannot name the specific taxonomy field that no platform can represent, buying has not actually been ruled out yet.
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Maximilian Bazzi, Founder and CEOWhy the decision is not really about cost
Build is usually assumed to be the expensive option and buy the safe default. In practice the more expensive outcome is buying a platform whose data model does not fit your taxonomy and then spending years running workarounds around that mismatch. The real question is not build versus buy in the abstract, it is whether any available platform can carry your taxonomy without translation, because a translation layer is where cost and risk actually accumulate over time.
Why platform independence is the actual differentiator
Most GRC platforms ship with a risk methodology already built into their data model, and the buyer is rarely shown it during a sales process. A reseller is paid to sell you a licence, so the recommendation to buy tends to arrive regardless of whether the platform's model actually fits your organisation. An adviser with no licence to sell can make the recommendation to buy, configure or build against what your risk taxonomy and reporting obligations actually require, not against a partner commission. That is also why being able to build is the proof of independence: if nothing off the shelf carries an organisation's risk language without translation, the alternative to buying anyway is building the application that does.
When buying is still the right answer
Buying and configuring is right whenever an established platform's data model can represent your taxonomy without forcing you to change how your organisation actually talks about risk. This covers most cases: the platform's flexibility is usually underused, not exhausted, and configuration against your own control library closes most of the gap that looks at first like a data model mismatch.
Where teams commonly run into difficulty
The common failure is deciding to build before confirming that buying has genuinely been ruled out, usually because the taxonomy work that would answer that question was never done first. Building without that groundwork produces a custom application that encodes whatever assumptions were convenient at the time, which is the same problem as buying the wrong platform, just with more of your own money spent on it.
How Bazzi Consulting helps
We are platform independent, not a reseller. We confirm whether your taxonomy can be carried by an existing platform before recommending a build, and we can build the application ourselves when it genuinely cannot. See technology and custom build.