The quiet signs your operating model is under strain

What are the signs your operating model is under strain?

The signs of operating model strain are often visible in the ordinary moments of work: a report that takes longer than it used to, a key deadline that depends on one person, a system that requires a spreadsheet to make it usable or a leadership question that takes days to answer.

An operating model defines how an organization gets work done across people, processes, technology, governance and data. It includes who performs the work, how decisions are made, what systems support execution, how information moves throughout the organization and how accountability is maintained.

Operating model strain occurs when the business begins demanding more than the structure can reliably support without extraordinary effort. As organizations grow or face increasing complexity, that gap may become more evident.

That strain does not always look like failure. In many organizations, the work still gets done. Reports are produced, and compliance deadlines are met. Employees answer urgent requests while leaders eventually receive the information they need.

The issue is not whether outcomes are being delivered, but instead what it now takes to deliver them.

Operating model strain functions much like financial or technical debt. The organization can continue performing for an extended period because employees compensate for underlying weaknesses through additional effort, workarounds and informal coordination. However, as complexity increases, the effort required to sustain performance grows faster than leadership can see. By the time financial results deteriorate, remediation typically becomes more expensive, more disruptive and more urgent than it would have been when the early signs first appeared.

People: Too much work depends on too few individuals

When too much work depends on too few individuals, the organization may be relying on personal effort instead of repeatable capability. For example:

These situations can feel normal because the people involved are often highly capable and experienced. They know where the risks are, which reports need extra attention and which informal steps keep work moving. Their knowledge protects the organization, but it can also conceal the fragility of the model around them.

The risk grows when institutional knowledge remains in people’s heads instead of in documented processes, controls and systems. A vacation, resignation, illness or promotion can suddenly expose how much of the operating model a handful of employees carry.

This challenge is not only a staffing issue. It is also a visibility issue. Leaders may see a strong performer while also overlooking a concentrated operational dependency. The very people who appear to make the organization resilient may be compensating for weaknesses elsewhere in the operating model.

Over time, key-person dependency can create hidden constraints on growth. Leadership may believe capacity exists because work continues to get done, while critical employees quietly become bottlenecks to expansion efforts, transformation initiatives and succession planning.

The RSM US Middle Market Business Index Special Report: Workforce 2026 shows that 52% of executives anticipated moderate to significant hiring needs in the next 12 months, while 79% expected turnover to be at least somewhat challenging. In that environment, concentrated institutional knowledge becomes more than an inconvenience. It becomes a capacity and continuity risk.

For organizations pursuing acquisitions, artificial intelligence initiatives, geographic expansion or rapid growth, dependence on institutional knowledge can become one of the greatest barriers to scaling effectively.

Process: Routine requests take longer than they should

When routine requests begin taking longer than expected, the process may still be functioning, but only through increasing effort, coordination and follow-up.

The signs are familiar. The close takes eight days instead of five. A routine diligence request takes two weeks to answer. A customer, lender or board question triggers a scramble across departments. Teams spend more time asking who owns the next step than completing the work itself.

At first, these delays are easy to explain. The quarter was unusually busy, or a key person was out. The request was more complex than expected, or the system had a timing issue. Each explanation may be valid, but the warning sign is when exceptions start becoming routine.

A strained process often produces the right answer too slowly. It depends on manual reviews, informal routing, undocumented approvals or follow-up from people who already have more work than they can absorb. The process may have been appropriate when the organization was smaller, but growth, acquisitions, regulatory requirements and increasing stakeholder expectations can outpace how the work was originally designed.

The quiet signal is not that a process breaks. It is that everyone knows which workarounds are needed to keep it from breaking.

Process strain rarely appears on a dashboard. It shows up in longer cycle times, increased coordination costs, repeated escalations and leadership attention being diverted away from strategic priorities to operational issues.

What begins as a manageable workaround can eventually create margin pressure, operational risk and a declining ability to respond quickly to customers, regulators and stakeholders.

Technology: Systems are surrounded by shadow spreadsheets

When employees create workarounds for core systems, the technology environment may no longer support the business as intended.

One of the most common signs is the spreadsheet that was supposed to disappear. Multiple people maintain separate files that duplicate system information. A report is exported, adjusted and reloaded before leaders can use it. Data moves from one platform to another through manual entry, and teams trust the offline version more than the system of record.

The presence of shadow spreadsheets and manual workarounds does not necessarily mean the technology investment was wrong. Often, the issue is not the technology itself. The system was implemented, but the related processes were not redesigned, governance responsibilities were not clarified and data was not standardized. The result is a tool that performs part of the work while employees fill the gaps around it.

The business implications extend beyond inefficiency. Shadow processes can create version control problems, increase the risk of errors and make it harder for leaders to know which information is current. They can also make scaling harder because the organization is not scaling one process. Instead, it is scaling the official process and the hidden process beside it.

AI can accelerate work and reduce manual effort, but it depends on reliable data, clear processes, consistent governance and defined ownership. When those foundations are weak, automation often scales inefficiency rather than eliminating it, potentially exposing operating model weaknesses that employees previously compensated for manually.

Technology strain often appears as a confidence problem. Employees may use the system because they have to, but they rely on manual checks because they do not fully trust the output. When trust in core systems declines, organizations often create parallel processes to compensate, increasing effort, complexity and risk over time.

Governance: Decisions keep circling back

When decisions keep circling back, governance structures may not be clear enough for the organization’s current level of complexity.

A leadership team approves a change, but the same issue returns in the next meeting. Two functions interpret the same policy differently. Approval chains lengthen because no one is sure who has final authority. A routine exception requires input from finance, legal, compliance, IT and operations, but no single owner can resolve it.

Governance strain often grows quietly because it looks like diligence. More reviews may feel safer. More meetings may feel collaborative and more approvals may feel controlled. But when decision making slows, the organization may confuse activity with accountability.

In a smaller company, informal governance can work because leaders know the context, recognize risks and each other’s decision-making rights. As the organization expands, that informal model may lose effectiveness. More locations, functions, systems and stakeholders create more intersections where ownership must be clearly defined. As decision making slows, strategic initiatives can stall, customer issues may take longer to resolve and leaders may spend more time revisiting decisions than executing them.

The warning sign is not debate itself. Healthy organizations welcome and benefit from debate. Instead, the warning sign is repeated debate over the same categories of decisions because roles, escalation paths or standards are not clear enough to move work forward.

Governance strain creates a hidden tax on the organization. Decisions take longer, accountability becomes less clear, and leadership capacity is consumed with resolving issues that should already have clearly defined ownership.

Data: Leaders spend meetings debating the numbers

When leaders spend more time reconciling the numbers than acting on them, data strain likely affects decision making.

The signs can show up in subtle ways: Finance and operations bring different versions of the same metric. A dashboard answers the first question but not the follow-up. A board request requires manual validation across multiple sources. A performance discussion begins with, “Which number are we using?”

Data issues rarely stay contained within reporting teams. When leaders do not trust the information in front of them, decision making slows. When employees expect every report to be challenged, they add additional reviews, validations and reconciliations before sharing the information. When definitions vary across functions, teams may appear misaligned even when they are working toward the same goal.

Reliable data requires more than reporting tools. It requires common definitions, clear ownership, disciplined input, documented controls and governance over how information is created, maintained and used. Without those elements, the organization may have more data than ever and less confidence in what it means.

Data-related issues are among the clearest signs of operating model strain because they may affect the speed and quality of leadership judgment. A business can live with imperfect information, but it struggles when it cannot tell which information is reliable enough to act on.

Data strain affects more than reporting. It can influence forecasting, capital allocation, customer decisions, risk management and executive confidence. When decision making slows because leaders lack confidence in information, operational friction can become a strategic growth constraint.

Why operating model strain is easy to miss

The signs of operating model strain can be easy to miss because committed employees absorb the impact before leaders see it.

They work late to finish the financial close or rebuild a report because the source data was inconsistent. They remind colleagues which approval is required or keep a personal checklist to manage exceptions. They know which spreadsheet is correct.

From a distance, the operating model appears to work. The deadline was met, or the report went out. The issue was resolved. But the organization may be measuring completion rather than effort required, and effort is often where strain hides.

For that reason, leaders should pay attention not only to whether work gets done, but how it gets done. How many steps did it take? How many people had to be consulted? How much manual review was required? Which person made the process work because they knew the history?

The answers may reveal a gap between the operating model documented on paper and the one employees rely on every day to keep the business running.

Operating model strain rarely remains static. What begins as a handful of manual workarounds or key-person dependencies can gradually evolve into broader operational constraints as complexity increases. Additional growth, acquisitions, technology investments and stakeholder expectations place more demands on the same underlying structures. Over time, organizations often experience slower execution, higher coordination costs, greater operational risk and reduced scalability before those issues become visible through financial performance.

How should leaders read these warning signs?

Leaders should read these warning signs as patterns, not isolated complaints.

A delayed report may be ordinary. However, a delayed report combined with a manual reconciliation, unclear ownership and reliance on one person may indicate something more structural. The value is not in treating every friction point as a crisis. The value is in seeing where friction clusters.

While any individual signal can occur occasionally, leaders should pay particular attention when multiple warning signs appear simultaneously. The strongest indicators often include key-person dependency, repeated manual reconciliations, recurring decision delays, lack of trust in core data and widespread reliance on spreadsheets outside systems of record. When these conditions appear across multiple functions, they often signal structural limitations rather than isolated inefficiencies.

Leaders should resist evaluating these signals in isolation. A delayed report alone may not be concerning. But a delayed report combined with manual reconciliations, unclear ownership, key-person dependency and inconsistent metrics may indicate an operating model issue requiring attention. 

This lens helps leaders move beyond a general sense that teams are busy. It also helps distinguish normal growing pains from structural weaknesses that can ultimately affect scalability, profitability, resilience and enterprise value.

The goal is not to assign blame. In many cases, operating model strain appears because the organization has grown, expectations have changed or complexity has increased. The teams doing the work may be the reason the model continues to function at all.

The question is whether that model can continue to support the business without relying on extraordinary effort as a normal operating condition and whether it can support the organization's next stage of growth.

Operating model strain ultimately creates financial consequences. Organizations often experience rising coordination costs, increasing selling, general and administrative expenses, slower cycle times, delayed integration efforts and reduced productivity gains from technology investments.

These effects may not appear immediately on financial statements, but over time they can affect margins, growth capacity and the organization's ability to generate sustainable earnings. Investors, lenders and acquirers increasingly evaluate whether operational foundations can support future growth, making operating model maturity an important contributor to enterprise value.

The takeaway: Quiet signs deserve early attention

The quiet signs of operating model strain often emerge long before financial performance deteriorates. They appear as additional reconciliations, increasing coordination effort, duplicated work, unclear ownership, repeated escalations and growing reliance on individual heroics.

Individually, these signs may look manageable. Together, they can reveal a gap between what the organization needs from its operating functions and what the current model can reliably provide. Leaders who recognize those patterns early are better positioned to strengthen visibility, reduce dependency and build the operational resilience needed to support growth, transformation and increasing business complexity.

The organizations that scale most effectively are not always the ones with the fewest challenges. They are often the ones that recognize operating model strain before it becomes a performance problem.

As business complexity increases, you should periodically assess whether your people, processes, technology, governance and data still fit your organization today. A useful next step is to assess where work depends on informal fixes, manual effort or individual knowledge, then evaluate whether those patterns represent isolated inefficiencies or signs that the operating model needs to evolve.

Once patterns are identified, you should prioritize areas where strain creates the greatest business risk, scalability limitations or transformation barriers. Addressing operating model strain does not always require large-scale redesign. In many cases, documenting critical knowledge, clarifying ownership, standardizing key processes and improving data governance can significantly improve operational resilience.