When Governance Slows Decisions: Rethinking Control, Materiality, and Trust
•February 6, 2026
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Companies Mentioned
Why It Matters
When governance hampers agility, firms lose competitive advantage and incur unnecessary costs, making a clear distinction between control objectives essential for sustainable performance.
Key Takeaways
- •Excessive controls delay decisions and increase costs.
- •Materiality should guide effort, not blanket precision.
- •Separate decision governance from financial reporting governance.
- •Risk avoidance replaces risk management, stifling agility.
- •Align control effort with decision relevance and uncertainty.
Pulse Analysis
In today’s volatile business environment, the traditional view of governance as an unqualified good is being challenged. Companies that pile on review layers to achieve absolute certainty often create a paradox: the very controls meant to protect the organization end up throttling its ability to act. This phenomenon, described as the "control reflex," leads to redundant validation work that consumes resources without delivering proportional value. Understanding that not every decision requires the same level of rigor is the first step toward reclaiming speed and efficiency.
A critical insight from the article is the distinction between financial‑statement integrity governance and decision governance. The former demands high‑precision, retrospective assurance for external reporting, while the latter focuses on forward‑looking, judgment‑based choices under uncertainty. When firms mistakenly apply reporting‑grade precision to internal decisions, they fall into materiality blindness—treating every minor variance as material. By redefining materiality thresholds for decision contexts, organizations can prioritize effort where it truly matters, reducing unnecessary reconciliation and freeing teams to focus on strategic analysis.
Implementing a decision‑calibrated governance model does not require new technology, but it does require cultural and process shifts. Leaders must explicitly ask what level of accuracy is sufficient for each decision, who owns the remaining uncertainty, and how risk should be managed rather than avoided. Separating decision‑grade analytics from ledger‑driven reporting, often through semantic layers, enables faster, more informed choices without compromising compliance. Companies that adopt this dual‑governance approach can maintain rigorous external controls while accelerating internal decision cycles, turning governance from a bottleneck into a strategic enabler.
When Governance Slows Decisions: Rethinking Control, Materiality, and Trust
1. The paradox of “good governance”
In most large organizations, governance is treated as an unqualified good. It signals discipline, reinforces accountability, and reassures stakeholders that risks are being managed. As uncertainty increases, whether driven by market volatility, regulatory scrutiny, or organizational change, the instinctive response is to strengthen governance rather than question it.
Yet many leadership teams experience a growing tension. Decisions take longer. Management discussions shift away from trade‑offs and toward validation. Action is delayed while information is refined, reconciled, and reviewed repeatedly. The organization appears well controlled, but increasingly slow, with tangible implications for cost to serve and, in some cases, profitability.
This reflects a broader paradox in modern governance. Frameworks designed to reduce risk often end up constraining decision‑making, not because they are overly conservative, but because they quietly redefine what control means. Control becomes associated with certainty. Protection of the status quo becomes mistaken for value creation.
I have observed this dynamic firsthand in a large, globally distributed energy company. A strong cultural emphasis on flawless execution in financial reporting gradually evolved into an environment where even immaterial risk of error was treated as unacceptable. Over time, multiple layers of review were added to ensure absolute accuracy in externally reported results, with each layer performing essentially the same level of detailed validation.
What began as a prudent response to regulatory expectations slowly expanded beyond its original purpose. Reviews multiplied not because decision quality required them, but because the organization had learned to equate more control with better governance. Errors of negligible financial significance were corrected late in reporting cycles, even when the cost of doing so far exceeded any decision or stakeholder value created.
As part of a subsequent transformation of how the organization worked, including my role leading business analysis and reporting activities across Europe, Africa and the Middle East, we deliberately reduced low‑value validation work and removed redundant layers of review. The objective was not to weaken control, but to realign effort with material risk and decision relevance.
Research on organizational decision‑making has long shown that as processes and oversight mechanisms accumulate, managerial attention shifts toward defensibility rather than choice, particularly in complex and highly regulated environments (Harvard Business Review, 2006; Bain & Company, 2016). Decisions become gated not by what leaders need to act responsibly, but by what the organization can prove with confidence.
In environments where uncertainty is unavoidable, that shift matters. It changes not only how decisions are made, but when they are made. Delay, in many cases, becomes the most significant risk of all.
This article contributes to ongoing discussions on finance governance and enterprise performance management in three ways. First, it distinguishes financial statement integrity governance from decision governance as separate control objectives with fundamentally different standards of precision and rigor. Second, it explains how the accumulation of controls can produce false precision and materiality blindness as predictable governance failure modes. Third, it outlines a decision‑calibrated design logic for aligning control effort with materiality, trust, and decision cadence in complex organizations.
2. The control reflex
Controls are rarely added because they are ineffective. They are added because they feel safe.
When organizations face uncertainty, responses tend to be procedural. Additional review layers are introduced to validate assumptions. Reconciliations deepen to ensure consistency. Approval steps multiply to demonstrate oversight. Reporting variants expand to meet the expectations of different stakeholders. Each measure is defensible in isolation. Over time, their cumulative effect reshapes how the organization operates.
In large transformation programs I have led, this pattern typically emerged incrementally. Controls introduced years earlier to address specific audit findings, integration risks, or one‑off issues were rarely removed once the original concern had passed. Instead, they became embedded in legacy systems and inherited processes. Teams spent increasing effort reconciling and validating information that no longer influenced the underlying decision, while decision windows remained fixed.
During a major enterprise transformation, we examined financial variance analysis processes in detail. Rather than starting with existing rules and reports, we began by defining what a fit‑for‑purpose, industry‑standard process should look like. Only then did we make deliberate choices about where additional rigor created genuine strategic advantage.
This led to a fundamental shift. We explicitly distinguished between external financial reporting, which requires a high degree of precision, and internal stewardship, where numbers need to be materially correct rather than perfectly reconciled. Non‑material differences were accepted rather than chased. As a result, one core variance analysis process was redesigned from involving more than a hundred contributors globally into a small, focused team performing higher‑level analysis aligned to risk and decision relevance.
Over time, governance systems begin to prioritize the protection of existing value. The emphasis shifts toward vigilance, accuracy, and defensibility. This orientation is understandable. Protecting what already exists feels responsible and measurable. Creating new value, by contrast, involves judgment, experimentation, and acceptance of uncertainty.
Frameworks such as the COSO Internal Control Framework, reinforced through Sarbanes‑Oxley requirements, play a critical role in establishing minimum standards for reliability and integrity in financial reporting and internal control environments (COSO, 2013; U.S. Congress, 2002). These frameworks were designed to reduce the risk of material misstatement and control failure. They were never intended to define how every management decision should be governed, nor to require certainty before action is taken.
Problems arise when standards designed to prevent failure are extended beyond their original purpose and treated as proxies for decision readiness. In practice, this produces governance processes that are technically robust, yet poorly aligned to the speed and nature of the decisions they are meant to support.
3. Risk avoidance versus risk management
This drift toward heavier control is often justified in the language of risk management. In practice, many organizations move closer to risk avoidance.
The distinction is important. Risk avoidance seeks to eliminate uncertainty before action is taken. Risk management accepts uncertainty and manages exposure explicitly. The former delays decisions until information feels complete. The latter recognizes that completeness is rarely achievable and focuses instead on materiality, thresholds, and ownership.
The distinction is not semantic. It fundamentally shapes how organizations respond to uncertainty.
In many organizations, residual uncertainty is treated as a reason to delay rather than as an input to decision‑making, even when that uncertainty is well bounded and unlikely to alter the directional choice.
Contemporary risk frameworks emphasize that effective risk management does not remove uncertainty, but makes it visible and actionable, particularly in strategic decision contexts (COSO, 2017). When governance systems tilt toward avoidance, uncertainty is treated as a flaw rather than a condition to be managed. Forecasts are refined well past the point where additional accuracy changes direction, and leaders are asked to commit only once outcomes feel defensible from every angle.
At some point, governance stops being about making better decisions and becomes about avoiding blame.
The result is an organization that becomes highly effective at demonstrating care, while becoming less effective at acting in time. Value protection quietly replaces value creation as the dominant objective, even in contexts where speed and judgment are critical to performance.
A mature governance system does not pretend uncertainty can be removed. It makes uncertainty explicit, bounded, and owned. To do that, it must be grounded in a clear understanding of what accuracy actually means in practice, and what level of precision decisions truly require. That is where many governance designs begin to break down.
4. Seeking assurance in false precision: when governance demands certainty that accounting cannot deliver
The shift from risk management to risk avoidance does not remain abstract for long. In most organizations, it becomes visible in a very specific place: how financial information is treated inside governance processes.
Many governance frameworks carry an implicit assumption that numbers must be fully correct before decisions can be made. As business environments become more volatile, uncertain, and complex, tolerance for estimation narrows. Decision forums increasingly seek comfort in numbers that appear more precise, in the belief that greater numerical certainty reduces the risk of error or adverse outcomes. Finance teams respond by reconciling more deeply, validating more extensively, and refining forecasts well beyond the point where additional precision leads to materially improved insight.
This dynamic is rarely described as false precision. It is framed as rigor, discipline, or prudence. Yet it rests on a quiet fiction: that financial numbers can, and should, reach a level of accuracy that the underlying accounting model was never designed to provide.
Accrual‑based accounting is inherently estimate‑driven. Many of the figures that underpin enterprise decision‑making are not precise measurements, but informed judgments made under uncertainty. Provisions reflect probability‑based expectations rather than certainties. Impairments depend on assumptions about future cash flows and discount rates. Depreciation allocates cost over time based on estimated useful lives. Reserves represent assessments of likelihood, not known outcomes.
This is not a weakness of accounting. It is a necessary design feature. Accrual accounting exists precisely because organizations must act before outcomes are fully known. It enables comparability, stewardship, and decision‑making in environments where cash flows unfold over time and uncertainty cannot be eliminated.
Problems arise when governance processes implicitly deny this reality. When decision readiness becomes tied to ever finer reconciliation of estimated numbers, organizations begin to chase a level of precision that does not exist. Additional effort produces diminishing returns. Time is consumed validating assumptions that remain assumptions, regardless of how many times they are reviewed or reconciled.
The cost of this behavior is not limited to efficiency. Decisions stall. Opportunities narrow. In competitive environments, waiting for certainty is not a neutral choice. It is a decision to delay, and delay shifts advantage to those willing to act with bounded uncertainty.
In this environment, precision becomes performative. Numbers appear increasingly exact, while the underlying uncertainty remains unchanged. Governance processes signal control, but decision quality does not improve proportionally. In many cases, it deteriorates, as attention shifts from understanding ranges, drivers, and trade‑offs to explaining small variances that carry little relevance for the decision at hand.
False precision is therefore not an accounting failure. It is a governance failure. It reflects a mismatch between what decisions require and what governance systems implicitly demand. Decisions that call for directional confidence and understanding of risk exposure are held to standards appropriate for external financial reporting, where accuracy and consistency are essential.
The consequence is predictable. Decision forums wait for convergence that accounting cannot deliver. Finance organizations devote scarce capacity to reconciliation rather than deep business understanding and insight generation. Leaders receive information that is increasingly detailed, yet no more timely or actionable.
Understanding this distinction is critical. The issue is not whether numbers are accurate. The issue is whether governance frameworks are aligned with the nature of the decisions being made. Until organizations explicitly confront the limits of precision inherent in accrual accounting, governance will continue to optimize for certainty at the expense of speed and value creation.
That misalignment becomes most visible when organizations fail to define materiality in decision‑making contexts. This is where false precision does the greatest damage.
5. Materiality blindness: when governance forgets why accuracy exists
False precision becomes most damaging when organizations lose sight of why accuracy exists in the first place.
In financial reporting, materiality has a clear and well‑established meaning. Information is considered material if there is a substantial likelihood that its omission or misstatement would alter the total mix of information available to a reasonable user. Regulatory and legal guidance reinforces that materiality is not a purely quantitative threshold, but a contextual judgment that considers both magnitude and nature. This definition is deliberately pragmatic. It recognizes that not all inaccuracies matter equally, and that precision only has value to the extent that it influences judgment and action (TSC Industries v. Northway, 1976; Basic Inc. v. Levinson, 1988; SEC Staff Accounting Bulletin No. 99).
Inside many organizations, however, this logic erodes as numbers move from external reporting into internal governance. Materiality thresholds are rarely defined for decision‑making contexts. As a result, the standards appropriate for statutory reporting are implicitly applied to management decisions, even when the decisions themselves do not require that level of precision.
When materiality is undefined, everything becomes critical. Small differences trigger reconciliation. Minor variances demand explanation. Residual uncertainty is treated as a failure rather than a feature of informed judgment. Governance processes lose their ability to distinguish signal from noise.
This is not a theoretical concern. Longstanding regulatory guidance cautions against mechanical approaches to accuracy that obscure qualitative significance and distort behavior. Materiality is explicitly intended to be assessed in context, rather than reduced to numerical thresholds or pursued through repeated correction of immaterial differences. Yet internal governance frequently does the opposite. Finance organizations expend significant effort reconciling non‑material differences between plans, forecasts, and actuals, even when those differences have no bearing on the decision at hand (SEC Staff Accounting Bulletin No. 99; SEC Staff Accounting Bulletin No. 108).
The consequences are predictable. Decision cycles lengthen. Management attention shifts from choice to explanation. Leaders become conditioned to wait for cleaner numbers rather than engage with ranges, sensitivities, and trade‑offs.
More subtly, materiality blindness reinforces risk avoidance. When every number is treated as critical, uncertainty becomes unacceptable. Decisions are deferred until apparent clarity emerges, even when that clarity is illusory. Governance signals responsibility, while the organization steadily loses responsiveness.
Materiality, properly applied, does the opposite. It restores proportionality. It focuses effort where it matters most. It aligns analytical rigor with decision value rather than reporting convention.
The failure, therefore, is not one of compliance. The standards are clear. The failure lies in governance design. When organizations import reporting‑grade precision into decision contexts without redefining materiality, they mistake accuracy for insight and control for effectiveness.
6. Decision governance versus financial statement integrity governance
Many governance debates stall because they assume a single governance objective. In reality, large organizations operate under at least two distinct and equally legitimate forms of governance, which are often conflated.
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Financial statement integrity governance – protects external stakeholders by ensuring that reported results are accurate, consistent, and compliant with applicable standards. It is necessarily conservative, retrospective, and intolerant of error.
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Decision governance – enables timely, well‑informed management decisions under uncertainty in complex and volatile environments. It is forward‑looking, surfaces uncertainty, bounds it, and makes it actionable.
Problems arise when these two objectives are implicitly treated as interchangeable. Standards designed to safeguard external reporting are applied to internal decision‑making. Rigor appropriate for financial statements is imposed on analyses intended to guide action. The result is slower decisions and diminished value creation.
In a large, multi‑year finance and analytics transformation I led, this distinction was made explicit. Financial statement integrity governance remained unchanged, with full rigor applied to external reporting. At the same time, decision governance was redesigned so that planning, forecasting, and performance discussions were anchored in material thresholds aligned to executive decision forums rather than reporting tolerances. This separation allowed decisions to move faster without increasing risk, because uncertainty was surfaced and owned rather than eliminated through reconciliation.
Decision governance asks different questions:
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What decision is being made?
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What level of accuracy is sufficient to make that decision responsibly?
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What uncertainty remains, and who owns it?
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What range of outcomes is acceptable given the risk and opportunity profile?
In practice, effective decision governance is difficult to sustain when analytics is tightly coupled to general‑ledger structures or individual systems of record. When every change in transactional systems propagates directly into decision metrics, materiality thresholds collapse and reconciliation pressure returns. Separating decision‑grade analytics from underlying ledgers—often through stable semantic layers—allows governance to focus on decision relevance rather than mechanical accuracy.
This distinction does not weaken control; it strengthens it. Financial statement integrity governance remains essential and uncompromised. Decision governance complements it by ensuring that governance frameworks support action as well as assurance.
Organizations that make this distinction explicitly are able to move faster without being reckless. They accept bounded uncertainty where appropriate, while maintaining high standards where accuracy is truly critical. Organizations that fail to make the distinction often move slowly while believing they are being prudent.
Reframing governance in this way does not require new systems or looser discipline. It requires clarity—clarity about purpose, about materiality, and about the difference between governing results and governing decisions.
Conclusion: governance as an enabler of judgment, not a substitute for it
Governance is often discussed as a constraint on decision‑making. In practice, the greater risk for many organizations is not too little governance, but the wrong kind applied in the wrong places.
When standards designed to protect financial statement integrity are extended wholesale into decision‑making contexts, organizations drift toward false precision, materiality blindness, and risk avoidance. Accuracy becomes an end in itself. Control becomes equated with certainty. Decisions slow, not because leaders lack courage, but because governance quietly demands a level of assurance that accounting and analytics were never designed to provide.
The remedy is not weaker controls or looser discipline. It is clearer design.
Effective organizations distinguish between governing results and governing decisions. They protect the integrity of external reporting with rigor and consistency, while allowing decision governance to operate with proportionality, explicit materiality, and ownership of uncertainty. They recognize that uncertainty is not a governance failure, but a condition of operating in complex environments.
When this distinction is made explicit, governance becomes an enabler rather than an obstacle. Finance and analytics shift from reconciling immaterial differences to illuminating trade‑offs. Leaders are asked not to wait for certainty, but to decide responsibly within known bounds. Speed improves, not because standards are lowered, but because rigor is applied where it actually changes outcomes.
Ultimately, good governance is not about eliminating risk or perfecting numbers. It is about creating the conditions for sound judgment. Organizations that understand this do not sacrifice control to move faster. They move faster because their governance is designed to support judgment and decision‑making rather than delay it.
About the Author
Werner van Rossum is a senior finance and business transformation leader specializing in enterprise‑scale FP&A, performance management, and operating‑model design. He has led large, multi‑year enterprise finance and performance‑management transformations across globally distributed organizations, focusing on aligning processes, systems, and capabilities to improve decision quality at scale.
His work centers on designing decision‑oriented FP&A models that reduce complexity, strengthen governance, and enable timely, trusted insight in highly matrixed environments. He has held leadership roles spanning corporate finance, performance management, and enterprise transformation, and regularly contributes perspectives on finance transformation, decision effectiveness, and organizational design.
Werner holds an MSc in International Business and has completed executive education in global leadership and transformation. He is based in the United States.
References
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Bain & Company (2016). The Five Steps to Better Decisions.
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Committee of Sponsoring Organizations of the Treadway Commission (COSO) (2013). Internal Control Integrated Framework.
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Committee of Sponsoring Organizations of the Treadway Commission (COSO) (2017). Enterprise Risk Management: Integrating with Strategy and Performance.
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Harvard Business Review (2006). Who Has the D? How Clear Decision Roles Enhance Organizational Performance.
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U.S. Congress (2002). Sarbanes‑Oxley Act of 2002.
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U.S. Securities and Exchange Commission (1999). Staff Accounting Bulletin No. 99: Materiality.
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U.S. Securities and Exchange Commission (2006). Staff Accounting Bulletin No. 108.
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TSC Industries, Inc. v. Northway, Inc., 426 U.S. 438 (1976).
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Basic Inc. v. Levinson, 485 U.S. 224 (1988).
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