Less Is No Longer More: FactSet’s Performance Solution Rewrites Historical Performance Data Migrations

Less history, less risk. For more than a decade, Meradia approached investment performance implementations with this mantra. Two key assumptions underpinned the “less is more” philosophy:

Assumption 1 – Performance implementations become more difficult with longer histories and more granular data.

Assumption 2 – The exponential increase in project risk from migrating longer and more granular historical performance data does not yield an outsized return on investment.

FactSet’s Performance Solution (FPS) fundamentally challenges both assumptions. With multiple successful implementations, we’ve revisited the notion of ”less is always more.”

What is FPS and Why Does It Challenge Our Assumptions?

FactSet’s Performance Solution (FPS) empowers investment performance teams with next-generation analytic flexibility to meet the evolving needs of performance consumers. Within FPS, the difference maker is Portfolio Vault (Vault for short). Vault provides a layer of data persistence and governance for calculated performance and attribution data, enabling its use across connected analytics and distribution workflows. Vault manages performance history in different “configurations,” and the careful crafting of these “configurations” enables FPS to dynamically reconstruct aggregated performance and attribution as though that data had lived in FactSet from day 1.

To explore how FPS challenges Meradia’s assumptions of performance history migrations, level-setting of terms is required.

Configuration 0 (Config 0) is the format which a client’s performance history is loaded into Vault. With Config 0 in Vault, FactSet’s analytics engine (PA3) can run bottom-up calculations using Config 0 to recreate aggregated performance and attribution results.

These results are stored in a new “configuration” (Config ‘n’) that, in its simplest form, is a combination of a portfolio, a benchmark, a grouping structure, and a column set. Every unique combination of a portfolio, benchmark, grouping structure, and column set gets its own “configuration.”

When building these “configurations,” the four scenarios illustrated below are critical.

It’s also important to note that if daily position-level data is only available back to a certain point, and monthly aggregated data beyond that point is available, FactSet will dynamically stitch this together in a single configuration. So, you can still deliver the coveted “inception to date” return that usually takes days to produce in 5 minutes.

Challenging the 1st Assumption

Assumption 1 – Performance History Migrations become more difficult with longer histories and more granular data.

Before we declare victory, let’s be clear: performance conversions are still complex, and always will be. Vault doesn’t magically eliminate the inherent challenges of performance data. What changes is how you tackle complexity. FactSet’s architecture lets you handle data issues centrally in the Vault, once, rather than repeatedly fixing them across siloed tools or manual processes. For example, since FactSet doesn’t require transaction-level detail to rebuild performance history (unless you choose to include it for specific reasons), you can focus on curating and importing higher-level performance results and essential reference data only. That removes a huge burden. Instead of wading through every historical trade and cash flow, you target the must-have pieces (market values, P&L, weights, returns, net flows, and critical reference data) and let the system recalculate from that foundation.

Challenging the 2nd Assumption

Assumption 2 – The exponential increase in project risk from migrating longer and more granular historical performance data does not yield an outsized return on investment.

Beyond simplifying history migrations, FactSet offers tooling to accelerate history reconciliation. Within FPS, you can load top-down gold source NAV returns, and PA3 will compare top-down and bottom-up results and output the differences in an “Accounting Residual,” which serves as the discrete list of data requiring investigation. Beyond this discrete list FactSet can produce, Meradia’s iterative testing strategy accelerates the UAT process by shortening the feedback loop between test execution and reporting. This approach slashes testing timelines in half (quite literally, cutting one project timeline from 6 months to 3 and another from 24 months to 12).

While project risk decreases related to UAT testing, it’s not enough when there is no benefit to migrating history. This is the paradigm shift. With FPS, clients are rewarded with data acting as if it lived in FactSet since day 1. Clients gain the ability to perform long-horizon analysis and respond to ad-hoc questions from portfolio managers or clients without days of manual work. They can rapidly deliver new calculations (like dynamically applying different groupings or methodologies on the fly) providing a boost in confidence that the performance record is comprehensive and readily accessible. These tangible benefits flow directly to client satisfaction and accelerated decision making. With FPS, a complete historical performance can indeed pay dividends.

How to Move Forward in this Brave New World

For years, “less is more” was the responsible call. It minimized risk knowing performance history is fragile, hard to reconcile, and difficult to reuse. FPS changes the economics of performance history. Vault, configurations, and a single calculation engine turn history from a liability into an asset. Complexity still exists, but it is contained, governed, and reused instead of rediscovered. Risk shifts from exponential to manageable. Return shifts from theoretical to visible. If Meradia’s long-standing view on performance history migration changed, it is worth pressure-testing your own. Full history, done correctly, no longer compounds risk. It compounds capability.

At Meradia, we help clients translate capabilities like FPS into accelerated, lower-risk implementations. Time to market matters. The longer a performance transformation takes, the greater the exposure to shifting priorities, resource constraints, and execution risk.

Our implementation playbook is built around well-defined priorities, phased delivery, and practical early wins. This approach not only shortens timelines, but also strengthens adoption by delivering value incrementally rather than deferring it to the end of a multi-year effort.

As FPS reshapes what is possible with performance history, success depends on more than the platform itself. It requires a disciplined approach to execution that ensures speed, control, and long-term scalability.

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Clay Corcimiglia

Clay Corcimiglia supports clients by integrating enterprise data architecture, big data analysis, and investment performance operations. He effectively collaborates with both business and technology teams to implement practical solutions for complex challenges. Clay has contributed to projects involving performance implementations and operating model transformations for investment managers and vendors. Clay assists with operational dashboard initiatives, utilizing often-overlooked datasets to improve processes and enhance efficiency. With a hands-on approach, he participates in user acceptance testing for multi-asset class datasets, addressing data issues and ensuring smooth client implementations. Whether involved in strategic planning or detailed analysis, Clay consistently demonstrates his adaptability and client-focused approach.