Asset owners managing $147 trillion globally are at an inflection point.¹ The shift from strategic asset allocation (SAA) to total portfolio approach (TPA) has exposed a fundamental gap: the data infrastructure that served siloed asset class management cannot support holistic, dynamic portfolio decisions.

The raw numbers supporting the strategic shift are compelling. TPA adopters have delivered roughly 1.3% higher annual returns than their SAA peers over the past decade, according to analysis of sovereign wealth fund data.² Australia’s Future Fund demonstrated their commitment to total portfolio outcomes during 2020-21,³ making nimble allocation shifts while traditional SAA peers stayed locked to fixed weights. CalPERS became the first major U.S. allocator to approve TPA implementation in December 2025, targeting July 2026 deployment.⁴

But here’s what the performance numbers don’t reveal: TPA can be difficult and costly to implement. The core challenge? No single provider has fully solved the TPA technology challenge. Organizations must integrate separate systems for accounting, private markets and total portfolio analytics. Most aren’t there yet.

The Dashboard Illusion

Asset owners are drowning in dashboards. Every platform promises visibility. Every vendor offers interactive charts and KPIs. Yet BNY research reveals a stark reality: 75% of asset owners still rely on heavily manual or bespoke processes to oversee holdings, and 67% cite challenges extracting and normalizing fund and asset data for alternatives.⁵

This is the dashboard paradox: proliferating metrics without enabling the decisions TPA requires.

Traditional dashboards provide static or semi-interactive views of historical data. A dashboard might show your private equity allocation has drifted from target. It won’t tell you whether that drift represents risk concentration or opportunity, how it correlates with factor exposures across your entire portfolio or what liquidity implications exist if you need to rebalance.

TPA is fundamentally chief investment officer (CIO)-centric rather than board of directors-centric. It requires timely, accurate data across all asset classes in a comparable format to support rapid decisions. Investment teams must work collaboratively with visibility across portfolios. As one industry analyst put it, CIOs need more than backward-looking metrics — they need “why” and “what next.”

The dashboard-heavy approach creates another problem: data teams become expensive help desks, responding to ad-hoc requests and building one-off reports that age quickly. Studies consistently show traditional dashboards see only about 20% user engagement.⁶ In an industry where talent management is one of the most significant challenge asset owners face, burning analytical capacity on dashboard maintenance is a strategic failure.

The Private Markets Data Problem

The challenge intensifies as allocations to alternatives expand. Private markets data is fundamentally different from public markets: no standardization, reliance on unstructured data from general partners, separate systems from public market holdings.

More than two-thirds of asset owners report significant opportunity cost from problematic private markets data.⁷ Asset owners have grown accustomed to the transparency that public markets are legally required to provide such as real-time pricing, standardized identifiers and comparable benchmarks. Private markets offer none of this by default.

The result? Data remains siloed and unstandardized, requiring manual intervention. A unified view of private market portfolios is difficult; a unified public-private portfolio view remains aspirational for most organizations. Different sources, time periods, formats and entity identifiers prevent establishing a single source of truth.

This matters because TPA treats all assets as one portfolio, where each decision is judged by its contribution to total outcomes. It would be an understatement to say that managing a unified risk budget when public and private markets operate on separate stacks — separate data, systems, people, and third-party providers — is a challenge.

The Technology Requirements for TPA

A data system provides the holistic infrastructure to manage data from end to end: data lakes or warehouses for storage, pipelines for ingestion and transformation, governance frameworks for quality and security, and increasingly “data as a product” models where datasets are treated as reusable assets.

Think of it as building a factory rather than a showroom. Dashboards are the user-facing layer. Data systems ensure that the products like a total portfolio risk view or liquidity forecasting model are standardized, reliable and scalable.

The shift enables what dashboards alone cannot: actionable intelligence embedded in workflows. A dashboard displays churn in manager performance. A data product within a robust system identifies factor exposure drift, explains drivers across the portfolio and enables the investment team to model rebalancing scenarios before execution.

Yet, nearly one-third of participants at BNY’s 2025 Asset Owner Innovation Summit identified data unification as their top operational priority. Almost 60% emphasized that establishing a data management and governance model to foster growth and generate alpha is their foremost strategic imperative.⁸ Where many fall short: achieving a well-articulated vision and blueprint for implementation.

TPA implementation requires specific capabilities that most legacy architectures lack:

The Build vs. Buy Decision

Here’s the practical reality: the most effective data solutions are likely to come from industry collaboration and outsourcing due to the required scale of investment. Individual asset owners building bespoke systems face cost structures that don’t scale.

At the 2025 Innovation Summit, asset owners overwhelmingly agreed they would rent or buy solutions rather than build bespoke systems. Off-the-shelf platforms deliver rapid deployment, proven security and ongoing vendor support. All are critical in a fast-moving market.

The remaining challenge: available solutions are still in early development stages, not yet as industrialized or repeatable as other securities services processes. This represents an opportunity for asset owners choosing partners now.

Implementation: From Dashboard Culture to Data Strategy

Making this shift requires more than technology procurement. It demands cultural change.

• Start with the operating model: 79% of respondents surveyed in a 2025 BNY survey are planning or in the process of enhancing their investment operating model.⁹ The shift from siloed asset-class structures to integrated frameworks requires collaboration across functions and asset classes under a unified strategic vision.
• Audit your current state: Identify dashboard sprawl and assess data quality. Where are you maintaining parallel systems for public and private markets? What manual processes persist because data doesn’t flow cleanly?
• Address the talent gap: Acquiring skills in data, digital and values-based investing can be a significant challenge for asset owners. The growing importance of technology requires adapting recruitment strategy to find talent with native technology and innovation mindsets.
• Measure outcomes, not outputs: Success isn’t dashboard count or report volume. It’s decision speed, risk-adjusted returns and operational efficiency. TPA adopters make more significant allocation shifts because they aren’t constrained by data limitations — measure whether your data infrastructure enables that agility.
• Collaborate strategically: The process most asset owners apply to technology discovery is inefficient — they don’t systematically document problem statements or route them to innovators who can solve them. Close to two-thirds (62%) of respondents in the 2024 BNY survey rated their organization’s operating efficiency as “efficient” or “very efficient.” Yet, 70% acknowledged they have no leading KPIs to assess operational efficiency.¹⁰ 

The Stakes

The case for TPA continues to strengthen. Analysis shows TPA funds achieved higher risk-adjusted returns over time — roughly 1% per annum or more — in part because they were more active and regime-aware in asset allocation.¹¹ They make more frequent and larger allocation adjustments because they aren’t locked to static policy weights.

But TPA without data infrastructure is aspiration without execution. You cannot manage a unified risk budget for the entire fund without unified data. You cannot make dynamic allocation decisions without real-time visibility across portfolios. You cannot integrate alternative and sustainability data into portfolio construction without the systems to ingest, normalize and analyze that data.

Dashboards aren’t obsolete. They’re just evolving. But in 2026, focusing solely on visualization while neglecting the underlying data factory is like polishing a car’s exterior while ignoring the engine. The winners will be asset owners who invest in data infrastructure as the foundation for TPA execution.

The question isn’t whether to make this shift. It’s whether asset owners can make it fast enough to capture the performance advantages that TPA promises or watch those returns accrue to competitors with better data foundations.

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