GCC 운영 모델: 캡티브·BOT·매니지드 중 선택

Frequently asked executive questions

Captive vs BOT vs managed GCC: which model is best?

There is no universally best model — the right one follows from how strategic the work is, how quickly you must start, and how much operating risk you can hold. Captive suits work that is core, long-lived and worth owning outright; build-operate-transfer suits organizations that want eventual ownership without absorbing early setup risk; managed suits scoped, non-core capacity where speed matters more than control. Hybrids are common and legitimate: own the differentiated work, contract the rest.

Is a captive GCC always cheaper at scale?

Often, but not automatically. Marginal cost per role is usually lower once a captive is at scale, and that advantage can be erased by low utilization, slow ramp, high attrition or governance overhead that was never costed. The comparison should be run on your own volumes and ramp, over the same horizon for every model.

How long does a BOT transfer typically take?

Commonly two to four years from build start to transfer, though the operative constraint is contractual rather than technical. The transfer window, trigger conditions and pricing formula should be defined in the original agreement; negotiating them later is where most value is lost.

Can we start managed and convert to captive later?

Yes, and many organizations do — but only if the contract anticipates it. Rights over people, processes, tooling and data at conversion need to be explicit from the outset. Without them, conversion means rebuilding capability rather than transferring it.

What governance does a hybrid model require?

A single accountable owner for the whole capability, one performance framework covering both modes, clear boundaries on which decisions sit inside the captive core, and a shared architecture and security standard. Running two governance systems side by side is the most common reason hybrids underperform.

How does an AI-native design change the operating model choice?

It usually strengthens the case for owning the core. When AI capability, proprietary data and evaluation are central to how the work is done, that layer belongs under direct control even if surrounding delivery is partnered. It also changes role mix and seniority, which should be reflected in the business case for each model.