Written By: David Carneal - Digital Efficiency Consulting Group
Read time: 8 minutes

Why apparent performance issues often start as workflow issues, not people issues.

Opening: The Joke That Is Not Really a Joke

Every manager has watched a task take too long and silently wondered if the employee doing it had somehow been replaced by dial-up internet.

Nobody says that out loud, of course. We dress it up in professional language. We say there may be a training issue, an accountability gap, a prioritization concern, or a need for better ownership. Very fancy. Very corporate. Very good at avoiding the harder question.

What if the employee is not slow? What if the workflow is?

After more than two decades inside operations, manufacturing, distribution, service environments, and administrative workflows, I have learned to be careful with the first explanation that shows up in the room. When output slows down, leaders often start by looking at the person closest to the work. That is understandable. People are visible. Process friction is not. But visible does not always mean responsible.

I have seen strong employees look inefficient because the process around them was a mess. I have seen capable teams get blamed for delays created by unclear handoffs, disconnected systems, approval layers, and undocumented exceptions. I have seen managers push for more urgency when the real issue was that the employee needed three systems, two follow-up emails, one spreadsheet, and a small act of witchcraft just to finish a normal task.

The Easy Explanation Is Usually a People Explanation

When work slows down, many organizations move quickly toward people-based explanations. The employee needs more training. The supervisor needs to hold the team accountable. The department lacks urgency. Someone is not following the process. These explanations are convenient because they produce familiar remedies: coaching, retraining, performance plans, new metrics, or another meeting that somehow creates more work while claiming to reduce it.

There are certainly times when performance problems are real. Some employees do need training. Some roles need clearer expectations. Some teams need stronger management. Pretending otherwise would be naive, and operations has no shortage of moments where accountability matters.

But in my experience, many apparent performance problems are actually workflow design problems wearing a fake mustache. The person looks inefficient because the path they must follow is inefficient. They are not failing to execute. They are spending too much of their day navigating obstacles that leadership no longer sees.

That distinction matters because the wrong diagnosis creates the wrong solution. If the workflow is broken, training people to tolerate it more skillfully does not solve the problem. It just makes the dysfunction look more organized.

The Hidden Work Employees Perform Every Day

Most performance metrics show leaders the start and finish of work. A customer order was entered. A quote was completed. A file was approved. A ticket was closed. What those metrics rarely show is the hidden effort between those points.

Employees chase missing information. They confirm whether a previous step was completed. They reenter the same data into multiple systems. They wait for approvals from people who are busy with twelve other approval chains. They correct errors created upstream, translate unclear instructions, reconcile reports, and maintain side spreadsheets because the official system is not trusted enough to stand alone.

This invisible work is one of the main reasons good employees appear slower than they are. The task itself may not be difficult. The route to completing it is difficult. I have watched employees spend ten minutes doing the actual value-added work and forty minutes fighting the workflow around it. From the dashboard, that looks like low productivity. From the employee's desk, it looks like Tuesday.

MIT Sloan Management Review captured this issue cleanly when it observed that digital tools often cannot fix the root causes of overload: 'poor work design and entrenched organizational behaviors.' [1] That sentence lands because it separates tool availability from workflow quality. A company can have modern software and still operate with poor work design. In fact, many do.

When Systems Multiply Instead of Integrate

Technology is supposed to make work easier. Sometimes it does. A well-designed system can remove manual steps, improve visibility, and reduce the amount of mental energy employees spend figuring out where things stand.

But many companies do not end up with one clean operating system. They end up with a software archaeology site. A CRM bought during one phase of growth. An accounting system implemented years earlier. A project management tool added by one department. A spreadsheet that survived because it knew too much. Each piece may make sense by itself, but the total workflow becomes fragmented.

McKinsey described this problem directly in its work on operating models, noting that in many organizations 'data lives in silos and spreadsheets,' which prevents scalable efficiency. [2] That is exactly what I see in the field. Employees become the connective tissue between systems that do not communicate well. They copy, paste, check, reconcile, and follow up. Then leadership wonders why everything takes longer than expected.

When employees become the integration layer, productivity depends less on talent and more on stamina. The best people can make a bad workflow look functional for a while, but eventually the cost shows up in delays, errors, frustration, or payroll.

The Approval Chain Problem

Another pattern I see often is the slow growth of approval layers. One approval gets added after a mistake. Another gets added after a customer complaint. Another appears because a manager wants visibility. Nobody is trying to create bureaucracy. Everyone is trying to prevent risk. That is how the approval jungle grows one responsible-sounding vine at a time.

The problem is that every approval has a cost. It creates waiting time. It interrupts momentum. It pushes work into someone else's queue. It increases the number of points where a task can stall, get reprioritized, or quietly disappear into the inbox swamp.

This is where good employees can look especially inefficient. They finish their part of the task, but the work cannot move forward. They follow up. They wait. They switch to something else. Later they return to the original task and spend more time rebuilding context. None of that looks dramatic from the outside, but it creates a constant stop-and-start rhythm that slows the entire organization.

MIT Sloan's article on knowledge work describes the danger of overloaded push systems, where work is pushed forward whether the next person is ready or not. The authors note that when work is managed this way, tasks become hard to track because they are scattered across 'individual email in-boxes, project files, and to-do lists.' [1] That is not a people problem. That is a workflow visibility problem.

The Broad Institute Case Study: Capable People, Poor Flow

One of the best case studies I have found for this issue comes from the Broad Institute of MIT and Harvard, described in MIT Sloan Management Review. The organization had highly educated, capable people working in genomic sequencing. This was not a case of lazy employees or a weak team. The people were talented, committed, and operating in an advanced research environment.

Yet the workflow had become overloaded. Samples piled up between steps. Staff were constantly reprioritizing. Important work was expedited, which pushed other work further behind. Over time, expediting became part of the process instead of an exception to it. Many business workflows operate the same way, only with invoices, orders, quotes, service tickets, or customer onboarding tasks instead of lab samples.

The article reports that in 2012, the cycle time for processing samples exceeded 120 days, and some samples took six months or more to move through the system. The problem was not a lack of effort. The team was working hard, but the system was making reliable flow nearly impossible. MIT Sloan noted that despite longer hours, the lab was falling further behind, and morale suffered. [1] There is the lesson in plain clothes: hard work cannot fully compensate for bad flow.

When the Broad Institute shifted from a push system to a pull-based workflow with clearer limits, visibility, and line balancing, cycle time eventually fell by more than 85%. [1] That improvement did not come from declaring everyone more accountable. It came from redesigning how work moved.

The Morale Cost of Bad Workflow

Workflow problems do not only reduce output. They also drain morale. Talented employees usually want to do good work. They want progress. They want clarity. They want to know that when they apply effort, something moves forward. A bad workflow breaks that relationship between effort and progress.

Over time, employees stop volunteering ideas because they assume nothing will change. They stop pushing for better methods because the system punishes initiative with more cleanup work. They become careful, quiet, and transactional. Leadership may interpret that as disengagement, but often it is process fatigue.

Harvard Business Review Analytic Services, in a report on workflow digitization, quoted an expert saying, 'Taking time to find things is a massive waste of time and erodes the employee experience.' [3] That may sound obvious, but obvious things are surprisingly good at hiding in plain sight. When employees spend their day searching, checking, and reconciling, the work becomes heavier than it should be.

The same report later makes the leadership responsibility even clearer: 'Happy employees do better work and provide customers with better experiences.' [3] I would add one practical point from my own experience: employees are much more likely to do better work when the workflow is not actively mugging them in the hallway.

The Leadership Blind Spot

The hardest part of this problem is that senior leaders often do not see the workflow itself. They see reports, dashboards, customer complaints, margin pressure, cycle time, payroll, and output. They see the smoke. They do not always see the little process fires burning underneath it.

This creates a dangerous blind spot. A leader may see that work is slow and assume the team needs to move faster. But the employee may be dealing with incomplete information, unclear ownership, duplicate entry, approval delays, and system gaps that were never designed together.

McKinsey's organizational health research reinforces why this matters. The firm states that healthy organizations focus on practices such as empowering employees, using technology to create value, and updating leadership styles. [4] Those practices require leaders to look beyond individual effort and examine the operating environment around the employee.

In my experience, the conversation changes when leaders watch the work happen directly. Not review the dashboard. Not read the report. Watch the work. Sit with the employee. Follow the handoffs. Count the systems. Look at how many times the same information gets touched. Suddenly the performance conversation becomes much more honest.

A Better Diagnostic Question

Before assuming an employee is inefficient, I believe leaders should ask one question: is this person slow, or is the workflow slow?

That question does not excuse poor performance. It improves diagnosis. A business still needs standards, accountability, and follow-through. But those tools work best when the process itself is capable of supporting good performance.

A practical review does not have to be complicated. Look at one workflow and ask: How many systems are involved? How many handoffs occur? Where does work wait? Which steps exist only because another step is unreliable? Where do employees use side spreadsheets or personal tracking methods? Which tasks depend on one person knowing the hidden rules?

If the answers reveal friction, the next move should not be another training session. It should be workflow repair. Training people on a flawed process may improve consistency, but it also preserves the flaw.

What Efficient Workflows Usually Have in Common

In the strongest operations I have seen, the workflow does not require heroic employees to function. That is the point. Good systems should not need daily rescue missions from the most experienced person in the department.

Efficient workflows usually have clear ownership at each step. They reduce unnecessary handoffs. Systems share information where possible. Approvals are tied to actual decision value, not historical fear. Documentation reflects how the work really happens, not how someone imagined it happened during a meeting three years ago.

Harvard Business Review Analytic Services found that 94% of surveyed respondents considered digitizing workflows important to their organization, yet only 31% said their organization was very effective at doing it. [3] That gap is important. Many companies know workflow quality matters. Far fewer have built the discipline to make it real.

That is why I tend to favor diagnostics before solutions. You cannot fix what you have not seen clearly. And you cannot see it clearly if the first assumption is that the employee must be the issue.

Closing Thought

Good employees can make a weak workflow survive longer than it should. That is both useful and dangerous. Useful because the business keeps moving. Dangerous because leadership may never feel enough pain to examine the process honestly.

When capable people look inefficient, the answer is not always more pressure. Sometimes the answer is a better path for the work to follow.

Before replacing people, retraining people, or adding another accountability layer, leaders should pause and ask the harder question: are we measuring employee performance, or are we measuring the drag created by our own workflow?

Because in many organizations, the employee is not the bottleneck. The workflow is. And unlike blaming the employee, fixing the workflow can actually make the business better. Wild concept, I know.

Footnotes

[1] Dodge, Sheila, Don Kieffer, and Nelson P. Repenning. "Breaking Logjams in Knowledge Work." MIT Sloan Management Review. September 6, 2018. https://sloanreview.mit.edu/article/breaking-logjams-in-knowledge-work/. Accessed April 27, 2026. Used for discussion of poor work design, push versus pull workflows, the Broad Institute case study, and reported cycle-time improvement.

[2] Maor, Dana, Patrick Guggenberger, and Alina Holzer. "Want to Break the Productivity Ceiling? Rethink the Way Work Gets Done." McKinsey & Company. August 27, 2025. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/want-to-break-the-productivity-ceiling-rethink-the-way-work-gets-done. Accessed April 27, 2026. Used for operating model complexity, data silos, spreadsheets, and process simplification.

[3] Harvard Business Review Analytic Services. "Improving Employee and Customer Experiences Through Workflow Digitization." Sponsored by Adobe and Microsoft. November 2023. https://business.adobe.com/assets/pdfs/resources/reports/hbr-improving-ex-cx/improving-employee-and-customer-experiences-through-workflow-digitisation.pdf. Accessed April 27, 2026. Used for workflow digitization survey data, employee experience quotes, and adoption effectiveness data.

[4] De Smet, Aaron, Arne Gast, Drew Goldstein, and Richard Steele. "Healthy Organizations Keep Winning, but the Rules Are Changing Fast." McKinsey Quarterly. August 2, 2024. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/healthy-organizations-keep-winning-but-the-rules-are-changing-fast. Accessed April 27, 2026. Used for organizational health practices and leadership context.

[5] Newport, Cal. "Why Do We Work Too Much?" The New Yorker. August 30, 2021. https://www.newyorker.com/culture/office-space/why-do-we-work-too-much. Accessed April 27, 2026. Used as supporting commentary on overload, push-based knowledge work, and the MIT Sloan research discussion.