Prashanthi Kolluru is the founder of KloudPortal. Helping global capability centers (GCCs) hire product-ready engineering teams.

At KloudPortal, we partner with global capability centers (GCCs) and technology enterprises to own and deliver their data engineering projects. In our experience working with our client partners, we have observed this common trend across the IT services and consulting industry: When data delivery slows down, many organizations often resort to a familiar solution: hiring more data engineers. The assumption is simple: More people will accelerate the output.

In today's environment, that assumption is increasingly misguided. As data platforms evolve to support real-time decision-making, AI-driven applications and operational analytics, delivery challenges are rarely caused by a lack of talent. More often, they arise from fragmented systems, unclear ownership and inefficient operating models. Adding more engineers in such an environment does not solve the problem; it often amplifies it. ​

The Misdiagnosis Of A Capacity Problem

Backlogs, delayed dashboards and unreliable pipelines are often interpreted as signs of insufficient capacity. Leadership sees growing demand from business intelligence to AI workloads and assumes the team cannot keep up. But what appears to be a capacity issue is often a coordination problem.