Many firms struggle with fragmented processes, duplicative efforts, and stalled transformation initiatives. What may seem like agility at the team level often creates hidden risks, rising costs, and significant barriers to scale. Enterprise solutions such as Total Portfolio View (TPV), Investment Book of Record (IBOR), and centralized analytics platforms are designed to unify organizations through standardized data flows, consistent logic, and shared governance, yet routinely fall short because autonomy has gone unchecked. Despite significant investment, adoption stalls when teams cling to their own ways of working.

This challenge was underscored in my recent piece, “Escaping Excel Anarchy,” which explored how unchecked spreadsheet use leads to fragmentary operations and blocks scalability. Yet, the underlying issue runs deeper: a culture that overvalues autonomy, especially at the team level, ultimately undermines the ability to build scalable, enterprise-wide solutions. Autonomy is crucial when inputs shift; strategies evolve, or outcomes are unpredictable, but it must be used strategically -not as the default. Without clear governance, autonomy rapidly turns into chaos, threatening organizational success and agility.

Importantly, when autonomy is overvalued, it often becomes inversely related to automation. Teams build bespoke processes that resist standardization, making it challenging to automate even routine tasks. The result is a landscape where manual work persists not because it’s necessary, but because no one has aligned the process across teams.

Excel Anarchy is a Symptom, Autonomy Trap Is the Root Cause

Excel Anarchy arises when spreadsheets become systems of record -built and maintained in isolation, without oversight or governance. While this behavior is common and highly visible, it reflects a deeper cultural issue: the unchecked autonomy that allows teams to create their own tools independently, often at the expense of alignment and scalability.

This is the real problem: the Autonomy Trap, a cultural norm that goes too far in decentralization. Teams solve problems in silos, even when shared solutions or standardization would better serve the business. The result is fragmentation, duplicated effort, misaligned priorities, and systemic risk that quietly erodes enterprise performance.

A significant consequence of this fragmentation is the inability to automate. When every team builds its own version of a process, whether it’s data mastering, reconciliation, or reporting, automation becomes nearly impossible. Bottlenecks form around manual reviews, handoffs, and exceptions that persist simply because no shared framework exists. These systemic blockers are not technical limitations; they are cultural ones, rooted in unchecked autonomy.

Source: Meradia

In this illustration, Excel Anarchy sits entirely within the Autonomy Trap, fully contained, but not representative of its full extent. Addressing spreadsheet misuse may relieve pain points, but lasting progress requires confronting the culture itself: rebalancing autonomy with governance, shared infrastructure, and strategic alignment.

Smarter Autonomy: Scaling Without Losing Control

Let’s bring automation into the conversation. Autonomy and automation aren’t opposites; they’re complementary when balanced well. The challenge comes when autonomy extends too deeply into core workflows, creating fragmentation that quietly undermines scale and consistency. This is the essence of the Autonomy Trap: teams optimize locally at the expense of collective efficiency.

An analysis, “How AI could reshape the economics of the asset management industry”, by McKinsey, finds that, despite rising tech investments, there’s little correlation between spending and productivity in asset management. On average, roughly 60-80% of asset manager budgets still go to maintaining legacy systems, 15-30% toward isolated use cases, and only 5-10% supports firmwide digital transformation. This spending pattern embodies the Autonomy Trap and compounds the problem: fragmented investments not only fail to scale but also lock firms into future legacy costs.

When a firm falls into the Autonomy Trap, it can be seen in many places. One simple example would be manual review steps that linger long past their usefulness, slowing processes without adding value. Data masters are often siloed, with individual desks maintaining their own versions; the security master is a prime example, resulting in inconsistent, duplicated, and mismatched records across the organization. Reconciliation workflows are also frequently reinvented by separate teams, causing delays, varying interpretations, and confusion. Automation stalls not because the technology is lacking, but because the platforms and underlying processes are too fragmented to automate at scale.

One of the biggest challenges for investment managers today is achieving a true Total Portfolio View (TPV) across all asset classes. Most firms still rely on manual processes, often stitching data together from multiple systems using Excel, because their infrastructure cannot deliver a unified view. In SimCorp’s recent “Investment Management 2025 Simplify, Innovate, Transform” report, 60% of executives cited “inability to manage multi-assets in one view” as their top current infrastructural challenge, underscoring the scale of the issue. This fragmentation is the long-term result of the autonomy trap: separate asset desks built their own operating and data models over decades, with little centralized governance. Now, as firms seek holistic oversight, they face incompatible architectures and complex legacy paths that make integration difficult.

These examples are not failures of skill but symptoms of ungoverned autonomy, in which groups independently solve problems in isolation, leading to fragmented, inefficient enterprise operations. The introduction of improved governance in this sense isn’t bureaucracy. It’s an embedded discipline: aligning autonomy with enterprise goals, defining shared standards, and weaving those standards into daily workflows, so they guide decisions rather than constrain them. When done right, governance becomes connective tissue, linking teams through common data and principles, not top-down control.

With improved governance, modern platforms make this possible. Rules engines, AI, and adaptive workflows can absorb bespoke processes, standardizing what should be standardized while preserving configurability or flexibility where judgment and creativity matter. The result is smarter autonomy, a state where teams innovate freely, but within a structure that scales, learns, and stays coherent over time. McKinsey estimates AI and workflow automation can reduce investment manager cost bases by 25-40% -but only if governance closes the gap first.

Strategic Governance: Enabling Autonomy Without Fragmentation

The solution isn’t to eliminate autonomy; it’s to govern it. But governing autonomy is far easier said than done. It’s not a one-time project or a static framework; it’s an ongoing discipline that requires continuous effort, cross-functional alignment, and cultural reinforcement.

In theory, decentralized decision-making fosters innovation and responsiveness. In practice, decentralized teams operate in silos, often leading to misalignment, inefficiency, and duplicated effort. Autonomy in core processes may meet team needs, but without governance, it won’t scale or align with enterprise objectives.

To support autonomy without compromising control, governance must be intentional, dynamic, and embedded into daily workflows. That means:

• Align autonomy with enterprise goals, defining key spots where flexibility adds value.
• Set shared standards and definitions, so teams speak the same language.
• Embed governance into workflows to support scalable, day-to-day decision-making.
• Use governance to connect teams, enable collaboration, and not create constraints.
• Keep governance adaptive, evolving with business needs, tools, and data.

The Way Forward: Balancing Autonomy, Automation, and Scale

Many firms are already working to balance autonomy and automation, but too often without a clear framework. Recognizing symptoms of the Autonomy Trap, such as fragmented workflows, key-person dependencies, or persistent Excel use, is the first step. The next step is diagnosing where autonomy adds value and where it creates friction.

That starts with:

• Evaluate your governance model: Is it enabling autonomy or allowing fragmentation?
• Assess your data platform(s): Are they modern and leveraged to support scale and flexibility?
• Shift your data culture: Are teams empowered to innovate within a shared framework?

These are strategic questions. Firms that modernize governance and platform design unlock agility, transparency, and enterprise-wide alignment.

Why Meradia?

Unchecked autonomy leads to duplicated efforts, inconsistent data, and stalled transformation projects. It slows decision-making, drives up costs, and erodes confidence in enterprise-wide initiatives. Recognizing the Autonomy Trap is the first step. The real challenge is in the following steps: building governance and data platforms that protect flexibility where it adds value, and enforcing consistency where scale demands it.

Meradia partners with investment managers to rebalance autonomy and automation, modernize governance frameworks, and optimize data platforms. The best platforms automate the backbone, ingestion, reconciliation, and monitoring, while enabling autonomy at the edges through rules, exceptions, and analytics.

For investment managers, the imperative is clear: Are you empowering innovation, or just avoiding modernization?

Download Thought Leadership ArticleServices: Solution Design, Strategy and RoadmapExpertises: Data and Digital TransformationClients: Asset ManagersAuthors: Jim Turner