The Hidden Cost of Operational Debt: Why Operations Matter More Than You Think

tl;dr

• Operations as competitive advantage: While companies chase revenue growth, operational efficiency often delivers faster ROI with lower risk
• The visibility problem: Most businesses don't realize where inefficiencies exist because they're not looking at operations systematically
• Information flow logic: Operations work best when viewed as logical information pathways rather than disconnected tasks
• Automation opportunities beyond the obvious: CRMs and ERPs are just the beginning. Significant opportunities exist when automating processes that aren't the obvious targets
• The scaling inflection point: The sweet spot for operational investment is in support of scaling – from startup to established business, from $1M to $10M, $10M to $100M, and so on - before growth exposes system weaknesses
• Prevention vs. crisis: Building operational infrastructure before growth prevents the crash that come from trying to scale without foundation
   

A three-person company runs smoothly on a simple system: when a new order comes in, it lands in a single shared inbox. Whoever's free replies, updates the customer, and moves on. Everyone sits in the same room and coordinating takes seconds. It works perfectly. Until it doesn't.

Scale that same company to ten employees, and suddenly people are tripping over each other in that inbox. Messages get double-answered or ignored. Scale to 100 employees with 100-person-company demand, and the system breaks completely. Threads are buried. Orders are missed. Your communication and processes fail. You’re not just slower; you crash and burn because you don’t have the systems to support your scale.

This scenario plays out constantly across growing businesses. The operations that got you here, won't get you there. Yet companies consistently prioritize revenue-generating activities over the operational foundation that makes everything else possible. It's understandable because sales and marketing are the visible face of the business. But then what is operations? Well, that's the heart pumping blood through the entire system.¹

The Logical Flow of Information

Sales and marketing are built on experimentation, iteration, repetition and volume -- testing messages, channels, and offers in an ever-changing landscape. Operations, by contrast, represents the logical black-and-white. At its core, operational work is about clear information flow with binary outcomes. Did this person receive the information they need? Does this calculation equal the expected result? Do we have sufficient inventory to meet demand? These are questions with definitive answers.

And it's this logical precision that makes operations exceptionally well-suited for systematic improvement and AI automation. Unlike the nuanced relationship-building of sales or the creative aspects of marketing, operational processes follow patterns that can be analyzed, optimized, and automated. When you see business operations as information flowing through predictable pathways, inefficiencies become visible and opportunities for improvement emerge naturally.

The challenge is that many business leaders don't think this way. Customer data lives in three different places. The procurement process requires too many emails. Project status is tracked in ad hoc spreadsheets that differ between PMs. Each problem seems isolated, but they're actually symptoms of information flow issues that compound across the organization. And the costs of underestimating the impact of operations can be very real: The Bloomfire Value of Enterprise Intelligence Report in 2025 found that operational inefficiency costs the average business 25% of annual revenue.²

Why Companies Don't Prioritize Operations

In our experience working with businesses across industries, leaders typically want to spend money on generating more revenue rather than decreasing expenses. It's a natural bias. Revenue growth feels proactive and exciting. Operational improvement feels necessary but unglamorous.

This creates a paradox. The fastest path to improved profitability often comes from operational efficiency rather than top-line growth because growth without the underlying support actually increases your risk of failure. Adding sales capacity means hiring salespeople, providing leads, managing pipelines, and waiting for deals to close. But without solid operational systems, that extra demand will lead to errors, work that needs to be redone, missed commitments, and unhappy customers. Improving operations, on the other hand, means eliminating waste that's happening right now, reducing failure points, and creating a reliable foundation for the growth that you want.

João Paulo da Silva, Regional President at Coupa, emphasizes that in the new AI era, the real levers of business success are operational stability and efficiency. He argues that companies need to embrace a kind of “resilience economics,” where healthy margins are protected through meaningful cost savings, even if those savings don’t immediately show up as rapid bottom-line growth. After years of seeing the damage caused by underestimating uncertainty, he suggests that now is the moment for businesses to double down on smarter investments and a disciplined focus on efficiency.³ 

Beyond the revenue bias, there's another reason operations get overlooked: companies often aren't even aware of their inefficiencies. They're not looking at operations systematically, so bottlenecks and time sinks remain invisible. A team might spend three hours a week manually consolidating data from multiple sources, but because it works, nobody questions whether it could be automated or eliminated entirely.

This awareness gap creates a common reaction when operational inefficiencies are identified: "Oh wow, I didn't even realize that was a bottleneck" or "I had no idea we were spending so much time on that particular process." The problems weren't hidden; they just weren't being examined.

The Automation Opportunity Beyond CRMs and ERPs

When businesses think about operational automation, they typically think about the obvious systems: customer relationship management software, enterprise resource planning solutions, accounting platforms. These are critically important, and they're just the beginning.

Powerful automation opportunities exist in the less visible aspects of business: the processes that happen between the major systems, the manual steps that connect different tools, the repetitive tasks that seem too small to deserve attention individually but consume substantial time collectively.

Consider data reconciliation between systems. Information entry that happens in one place and needs to be manually transferred to another. Report generation that requires pulling data from multiple sources. Approval workflows that happen over email. Status updates that require checking multiple platforms. These aren't the headline-grabbing automation projects, but they're where businesses often find the most immediate value.

According to the Eptura 2025 Workplace Index, 37% of surveyed enterprises now require 11 or more full-time employees just to collate, analyze, and report on operational data across separate systems, highlighting the excessive time lost to manual data and administrative processes.​⁴

Kevin Howard Goldberg, CEO of iS2 Digital offers that

"...the real breakthroughs come from marrying an understanding of client business operations with technology and AI automation. When you're clear on what a business needs and what AI and software can do, you begin to see how information flows through an organization and where real efficiencies can be created." 

This dual perspective reveals automation opportunities in places that weren't previously considered candidates.  And what surfaces are not the headline-grabbing enterprise systems, but rather, the connecting tissue between them -- that's where businesses often find the most immediate value.

The Critical Window: Transitions

There are predictable inflection points where operational investment delivers outsized returns: moving from startup to a going concern, from $100K to $1M in revenue, from $10M to $100M, and so on. The exact numbers vary, but the pattern is the same. At each stage, the existing processes are working for the current level of customers, employees, and transactions. People can still coordinate, issues get handled, and speed and flexibility often feel more important than formalizing the processes.

But as the business grows with more customers, more employees, more complexity, those processes start breaking. Maybe in subtle ways at first, but then it's clear. Files get lost or misfiled because there are now three “latest” versions floating around. Unwritten essential knowledge lives in someone’s head, and they’re on vacation, in a different time zone, or no longer at the company when it’s needed. Simple approval steps that used to take minutes now require three people, two systems, and a Slack thread. Reporting that used to be “good enough” becomes unreliable because data is manually copied between tools and spreadsheets. The workarounds that were clever solutions turn into massive inefficiencies and failure points.

This is where many growing businesses hit a wall. They're trying to scale on infrastructure designed for a completely different size organization. Every new customer or employee adds friction instead of momentum. Only 4% of U.S. businesses ever reach $1 million in revenue, and just 0.4% surpass $10 million. Most falter in this transitional "valley of death" because operational structure and process discipline aren't adapted or upgraded.​⁵

The organizations that navigate this transition successfully are those that invest in operational structure before they desperately need it. They build error detection into processes. They establish guardrails that prevent common mistakes. They automate the repetitive work that will compound as volume increases. They create systems that can scale without requiring proportional increases in headcount or management attention.

This isn't about over-engineering solutions or building infrastructure for a company ten times your current size. It's about systematizing what you're already doing so that growth strengthens rather than strains your operations. When the processes supporting your business are solid, you can focus leadership attention on growth rather than constantly putting out operational fires.

What Operational Debt Actually Costs You

The real cost of operational inefficiency isn’t just wasted time; it’s what your team could be doing instead. Every minute spent wrestling with broken processes is a minute not spent serving clients, improving products, or pursuing new opportunities. That shows up as degraded customer experience when things slip through the cracks, growing frustration when employees feel blocked by the system, and strategic decisions that stall because people are still hunting for basic information. Operational debt compounds like financial debt: every inefficient process adds downstream work, every manual workaround becomes someone else’s dependency, and every undocumented fact creates a hidden risk. 

Companies that win long-term treat operations as a strategic advantage. They deliberately build systems that support growth without requiring a matching increase in headcount or overhead. How information moves, how work is routed, and how commitments are fulfilled are given as much attention as the outward-facing brand. The question isn’t whether operational improvement delivers value; it does. The question is whether you address it proactively before, or at least during, a growth phase, or reactively in a crisis when the old system finally fails.

Where to Start

Addressing operational debt doesn’t require a massive transformation initiative. Start by mapping how information actually flows through your organization: where it originates, how it moves, who touches it, and where decisions get made. As you do, look for friction points, places where information gets stuck, where there are manual handoffs between systems, or where people spend surprising amounts of time on repetitive tasks.

Then focus on the processes that aren’t working at your current scale, especially those that made sense when you were smaller but are breaking now: shared spreadsheets, single-person approvals, status reporting that requires checking five different tools. Consider automation not just for your major systems, but for the “connecting tissue” between them including reports built by hand, data entered in multiple places, approvals managed through email chains.

Finally, treat operational improvement as an ongoing discipline, not a one-time project. As your business evolves, your operational needs will change. The goal is to build systems that can scale with you—systems with clear ownership, error detection, and guardrails that prevent problems instead of relying on constant heroic effort to catch them. That’s how you free leadership to focus on strategy while operations run smoothly in the background.

In our next article, we’ll explore how AI is changing the operational automation landscape, and why building AI-forward processes looks fundamentally different from both traditional software development and standard operating procedures.

References

1. Rachel Woods, Founder, DiviUp - Presentation at Tony Robbins’ AI Advantage Summit
2. How Knowledge Mismanagement is Costing Your Company Millions - HBR
3. Profit Margins are as important as Revenue growth in 2025 - Enterprise Times
4. Rethinking productivity: 2025 Workplace statistics - Eptura
5. Scaling Up: Why 96% of firms fail? - Crossmentors