Over the past several years, many hedge funds have expanded their use of Separately Managed Accounts (SMAs) to meet growing investor demand for transparency, control, and flexibility. Early on, the implementation of SMAs works well. Investors have greater transparency, and client demand accelerates.
But as the number of accounts grows, operational complexity compounds quickly. What begins as a manageable level of customization can become a growing burden across data management, reporting, and oversight, particularly for teams built around commingled fund workflows.
Compared to launching a new commingled fund, SMAs often feel easier at the outset because investors are typically allocating to the manager’s existing strategy, which means the SMA is built using largely the same underlying securities.
Once an SMA is live, complexity compounds. Each account brings its own mandates, constraints, reporting expectations, and oversight requirements. Data aggregation challenges increase as the number of data sources grows with additional fund administrators being used by investors. Customization becomes the norm. And tolerance for delays or inconsistencies drops quickly, particularly in larger, more sophisticated mandates.
This is often where operational alpha becomes visible, particularly for firms trying to scale customization without introducing friction.
Why SMAs Are Gaining Momentum and What That Can Obscure
The appeal of SMAs is straightforward. Institutional investors increasingly seek transparency, control, and flexibility, whether around risk limits, liquidity, tax considerations, tax treatment, or governance. OCIOs, pensions, and multi-manager platforms favor SMA structures as a way to meet those needs while maintaining access to differentiated strategies.
For managers, SMAs can accelerate distribution and strengthen allocator relationships. The challenge isn’t the structure itself. It’s what the structure demands operationally as it scales.
What Actually Breaks as SMAs Scale
The investment strategy often scales.
What tends to break are the operational protocols that surround it.
Data Stops Lining Up Cleanly
Different administrators with different data delivery times, inconsistent security masters, and varying reporting formats are among the challenges. Teams spend more time reconciling numbers that aren’t wrong, just inconsistent. What was once a periodic cleanup becomes a constant effort.
Reporting Quietly Consumes More Time
What was once a single monthly fund report turns into a growing set of bespoke deliverables. Exposure is grouped differently. Risk metrics are calculated differently. Attribution must align with allocator-specific frameworks. Over time, senior team members find themselves producing reports rather than generating insight.
Reconciliation Becomes Ongoing
In pooled vehicles, reconciliation has a predictable rhythm. In SMA environments, it becomes continuous. Manual processes that once felt manageable begin to get stretched. Firms often describe reconciliation work that once took hours each month becoming a significant effort as SMA complexity increases.
Headcount Becomes the Default Fix
When operations teams fall behind, the instinct is to hire. Additional analysts and specialists help keep things moving, but firms often see margin pressure increase, staff-turnover risk rise, and responsiveness fail to improve in proportion to cost.
When Operations Enter the Investment Conversation
Operational execution is no longer invisible to investors.
As SMA mandates grow larger and more complex, allocators perform deeper operational due diligence than they would for commingled funds. They ask how data flows through the organization, how reconciliation is handled, how quickly ad-hoc requests can be answered, and what happens operationally when the next SMA comes onboard.
Operational fragility tends to surface early, through delays, inconsistencies, or uncertainty, long before it appears in performance.
And when operations rely heavily on manual work or institutional knowledge, that becomes clear.
This is no longer just an efficiency conversation. As SMAs proliferate, allocators increasingly evaluate how consistently firms deliver under customization pressure. In many cases, operational confidence has become a gating factor in mandate decisions alongside performance.
What Operational Alpha Really Means
In SMA-heavy environments, operational alpha shows up in a firm’s ability to support customization at scale without incremental headcount, inconsistent reporting, or growing operational risk. In practice, that often means teams can absorb additional mandates without slowing response times or increasing operational strain, even as SMA complexity grows.
At its core, this comes down to designing operations that flex as complexity grows rather than breaking under it. By building this discipline early, firms can deliver consistent reporting across customized mandates while preserving margins as SMA complexity increases. It reduces operational noise and risk, allowing teams to respond confidently during allocator due diligence rather than scrambling to explain inconsistencies. Over time, firms with stronger operational alpha tend to feel the benefits most clearly as complexity increases, while those without it often experience growing friction instead.
The Operational Reality of Scaling SMAs
As SMAs continue to grow, we’re starting to see meaningful differences emerge in how firms absorb that complexity.
Some firms built operations for a different era, when customization was limited, reporting cycles were slower, and complexity was easier to manage. For them, SMA growth increasingly feels constraining.
Others invested earlier in data discipline, integrated workflows, and operational leverage, not because it was fashionable, but because it made long-term sense. They understood that every manual process caps scale, and every workaround eventually becomes visible to investors.
The difference between those firms isn’t strategy or performance.
It’s whether SMA growth feels like momentum or like drag.
The question for managers increasingly isn’t whether to pursue SMA growth, but whether their operating model is built to support it.
