What "Analysis-Ready" Data Actually Means for a Pension Fund
“The data can be entirely correct and still be the wrong shape for the analytical question being asked.”
Public pension plans often run on a stack of specialized systems: a custodian for cash and settlement, an accounting platform for book of record and valuation and separate risk and performance tools layered on top. Each system does its job well. The friction shows up at the seams, when data built for one purpose (accounting) has to power a different one (risk and performance analysis).
"Analysis-ready" data is data that is structured, tagged and complete enough to answer the question being asked of it, not just accurate enough to close the books. A plan can have pristine, audited accounting data and still lack analysis-ready data for risk and performance.
Position-level granularity: Aggregated NAVs and fund-level valuations are sufficient for accounting, but risk decomposition and factor attribution require the underlying security- and instrument-level positions, including reference data on those positions.
Look-through to underlying holdings: For funds-of-funds, private funds and commingled vehicles, the plan needs visibility into what those vehicles hold (not just their reported value) to see true asset allocation, concentration and factor exposure across the total plan.
Consistent security identification and classification: Risk models and performance attribution depend on every position mapping cleanly to a security master, sector/industry taxonomy and currency consistently across managers and asset classes.
Timeliness aligned to the use case: Month-end accounting cycles are fine for financial reporting; performance, risk monitoring and allocation decisions need data on a cadence that matches how often the plan wants to look, often daily.
A common data model across public and private assets: Total plan risk and performance depend on public equity, fixed income and private-market positions being represented in a consistent structure that allows risk models and attribution engines to analyze them side by side.
Platforms that are purpose-built for investment accounting are very good at that job. But accounting platforms are generally optimized for producing accurate net-asset value (NAV), not for exposing the position-level detail, look-through structure or factor linkages that risk and performance analytics need. The data can be entirely correct and still be the wrong shape for the analytical question being asked.
This is a common pattern for plans running a factor-based risk model alongside an accounting-driven system: the risk model is only as good as the positions it can see, and if commingled fund exposure only arrives as a single NAV line with no look-through, the plan's true total-fund risk picture has a blind spot exactly where private-market allocations have grown.
A total portfolio view sits between the accounting system and the risk/performance layer, taking in data from custodians, administrators and accounting platforms and reshaping it into a single, position-level, look-through data model spanning public and private assets. That reshaped data is what then feeds performance measurement, liquidity modeling, exposure analysis and risk.
The takeaway: analysis-ready is not a better data feed; it's the same data restructured for a different question. Risk and performance analytics depend on that restructuring being a deliberate step, rather than an assumption that accounting-grade data will simply carry over.
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