Uncovering hidden capacity in a FinTech's operation

The client was a banking technology services provider supporting a complex book of work across multiple intake channels, teams, and commercial agreements. While leadership had a strong intuition that significant capacity was being consumed by lower-value or poorly classified activity, the organisation lacked the data visibility to validate where the friction actually sat. Multiple systems were used to track work, each with inconsistent definitions and varying levels of accuracy, which meant that even basic questions about how time was being spent could not be answered with confidence. Without that clarity, decisions about workforce allocation, pricing, and growth investment were being made on instinct rather than evidence, which was becoming increasingly difficult to sustain as the business scaled.

We designed the discovery around the full lifecycle of how work moved through the business, breaking it into six connected stages from the nature of requests through to charging and invoicing. Each stage was examined through both an operational and a data lens, drawing on available system extracts alongside stakeholder workshops to validate what the numbers were telling us. Throughout the engagement, we were deliberate about distinguishing what the data could prove from what it could only suggest, ensuring that recommendations were grounded in evidence while also flagging where data gaps themselves needed to be addressed. The result was a structured view of how work originated, how it was assessed and prioritised, how it was allocated and completed, and how it was ultimately charged.

The discovery surfaced a connected set of issues that, together, explained much of the capacity friction the leadership team had been sensing. Around 15,400 work requests were analysed across a six-month window, and while one specific category (the focus of the original brief) accounted for only around 15% of total volume, it absorbed disproportionate effort from the most critical delivery teams. Prioritisation emerged as a structural issue: the overwhelming majority of work was being classified at the same priority level, which made meaningful sequencing almost impossible and left resource allocation vulnerable to ad-hoc influence rather than commercial agreements or business value. We also found that work was entering the business through multiple channels, including informal routes that bypassed tracking altogether, and that several departments were carrying a disproportionate share of the load with no view of utilisation to manage it. Most significantly, the analysis of charging and invoicing revealed a sizeable gap between what should have been charged for work performed and what was actually invoiced.

The discovery gave leadership a clear, evidence-based blueprint for change across three connected fronts: prioritisation, workforce management, and chargeability. We recommended establishing a unified definition of work activities and a prioritisation matrix that connected directly to commercial agreements, so that resource allocation decisions could be made transparently against agreed customer expectations rather than the loudest voice in the room. We proposed consolidating intake channels into a single monitored pipeline, supported by a dashboard that gave the leadership team near real-time visibility of incoming demand for the first time. On the commercial side, we recommended formalising chargeability rules within client agreements alongside an organisation-wide education program, reducing reliance on discretionary calls at the team-leader level. Underpinning all of this was a set of foundational data recommendations, including a clear source-of-truth model and standardised time tracking, so that the disciplines could be sustained beyond the engagement.

The most tangible finding was a revenue leakage of approximately $1.5 million across the six-month analysis window, representing the gap between work that should have been charged and work that was actually invoiced. Extrapolated across a full year, this pointed to a multi-million dollar opportunity to recover value already being earned but not collected, achievable largely through clearer rules and better discipline rather than new revenue generation. Beyond the direct financial finding, the engagement gave leadership something they had previously been operating without: a clear evidence base for where capacity was being absorbed, where prioritisation was breaking down, and where data gaps themselves were preventing better decisions. This shifted the basis of workforce, commercial, and investment decisions from instinct to evidence, and laid the foundation for a more scalable operating model.