As firms scale their assets under management and transition into more institutional structures, internal pressure inevitably intensifies: more reporting requests, more data questions, more oversight. The natural instinct is to add headcount to cover these new demands. Yet hiring is costly and carries risk, particularly if future needs shift. The pressing question on everyone's mind is: how to extend existing resources while still maintaining high quality?
Recruiting analytics talent is competitive and costly. Even when successful, small internal teams often end up spread too thin: juggling investor requests, compliance tasks, portfolio analysis, and sometimes ad hoc data fire drills. Over time, this leads to knowledge silos, uneven quality, and vulnerability when a key person departs. What initially feels like added capacity can quickly morph into a fragile patchwork that struggles under sustained pressure.
Some industry research, including a recent McKinsey report, shows that asset managers struggle to turn technology spend into productivity gains. Bigger tech budgets don't automatically lead to efficiency: firms investing heavily in new systems often failed to improve cost-to-AUM ratios or revenue efficiency. One reason is allocation, with 60 to 80 percent of budgets going to maintaining legacy systems, leaving little for forward-looking projects. Of that remainder, only a fraction supports firmwide transformation, with much tied up in fragmented initiatives that rarely scale. This imbalance shows why simply spending more is not enough and highlights the need for a different approach.
Technology, on its own, struggles to deliver ROI. The real gains come when it is paired with human judgment and leads to redesigned processes. In practice, this means technology should be seen as an amplifier of expertise, not a substitute for it.
Purpose-built infrastructure can serve as an extension of internal staff. Standardized reporting, attribution, and diagnostics run like an embedded support team, without the overhead. Unlike the generic, so-called "plug-and-play" systems, targeted infrastructure is designed to integrate into human workflows. It gives analysts and portfolio managers leverage at the exact pressure points, freeing them from reconciliation tasks and enabling them to focus on decision-making.
Here’s how this plays out in day-to-day operations:
- Efficiency: recurring workflows operate automatically and consistently (including attribution, exposure breakdowns, stress tests).
- Resilience: standardized frameworks protect against staff turnover and institutionalize knowledge.
- Clarity: a single source of truth reduces rework, conflicting metrics, and internal debate over numbers.
- Leverage: finally, properly integrated technology multiplies human capacity, enabling a two-person team to function with the scale of a five-person team.
Instead of constructing an in-house quant or reporting department from scratch, managers can lean on infrastructure already designed for institutional-grade analytics. The key differentiator to pay attention to is intentional design: tools that allow professionals to apply judgment, not battle inefficiencies. Choose infrastructure that transforms technology spend from a cost center into a true productivity driver.
Expanding capacity isn’t always about expanding payroll, nor is it about inflating technology budgets indiscriminately. The crucial step is pinpointing how to align infrastructure with people and process. When technology is a) deliberately integrated into workflows, and b) matched with clear objectives, managers achieve sustainable scale, and more time to focus on what drives outcomes.
