Leaders are solving the wrong labor cost problem: Industry experts

When labor costs rise, many leadership teams respond the same way. They cut hours, freeze hiring, reduce headcount, push harder on automation, tighten local approvals, and demand efficiency. The logic feels sound. Labor is one of the largest costs on the P&L, so controlling labor should improve profitability.

But that logic breaks down more often than leaders want to admit.

In a recent Dayforce Virtual Summit conversation, Andrew Garcia, Vice President of Product Management at Dayforce, joined Workforce Futurist Alex Levit and PwC Partner Dominick Paradiso, who leads the Dayforce practice for PwC, to unpack a difficult truth:

In many organizations, what looks like a labor cost problem is actually a workforce visibility problem.

That distinction matters because it changes the solution. If labor inflation is the problem, the answer seems simple: spend less on it. But if poor visibility is the real issue, cutting labor before improving insight is one of the fastest ways to make performance worse.

That’s the trap many organizations are still falling into. They’re treating labor as a cost to compress when they should be treating workforce performance as a system to understand.

Why cost-cutting often creates new costs

Most companies don’t cut labor out of carelessness. They do it because labor cost is visible, measurable, and easy to explain. Payroll costs show up clearly. Pressure from finance is real. The demand for productivity gains is constant. And AI has only intensified the expectation that organizations should do more with less.

The problem is that the most visible costs aren’t the only ones that matter.

Watch the Dayforce Virtual Summit session featuring Andrew Garcia, Alexandra Levit, and Dominick Paradiso to hear the full conversation on workforce visibility, optimization, and the hidden costs leaders often miss.

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During the summit, Levit warned against what she called blunt force automation. Her point wasn’t that automation or AI are inherently flawed. It was that many organizations are applying them too broadly and too quickly, without enough thought given to where human expertise, judgment, and oversight still carry outsized value.

That kind of move can reduce visible spend in the short term, but it can also create customer frustration, compliance exposure, weaker service delivery, and poor operational decisions that cost far more over time. The issue isn’t simply that labor gets reduced. It’s that capability gets reduced with it.

And when organizations treat labor purely as expense, they often fail to ask a more strategic question: What role is this labor playing in the economic performance of the business?

That’s where the mental model has to change, says Levit.

The hidden labor economy leaders rarely see

Paradiso sharpened the issue further. In his framing, labor cost isn’t an isolated line item. It behaves as part of a broader economic system. That means reducing spend in one area can quietly create new costs somewhere else.

This is where many businesses get into trouble. They measure the dollars saved from reducing labor. They don’t measure, with the same rigor, the downstream impact on turnover, rework, service quality, overtime, compliance risk, customer attrition, or manager burnout. Those costs are more distributed. They show up across functions. They often sit in different systems. They rarely arrive in the same reporting cadence as payroll.

But they’re real, and in many organizations, they’re large.

Gallup’s 2026 State of the Global Workplace reporting underscores the scale of that hidden drag: last year, low engagement cost the global economy an estimated $10 trillion in lost productivity, or 9% of global GDP. That kind of loss reinforces the panel’s point — when leaders can’t see the real conditions shaping performance, labor decisions made purely to reduce visible cost can end up compounding much larger productivity problems.

The panelists also pointed to key HCM issues that compound beneath the surface:
 

• Overtime leakage that looks minor in one instance but becomes material at scale
• Fragmented systems that make it difficult to connect schedules, time, pay, and contingent labor
• Frontline workarounds that solve a local problem while creating hidden financial drag
• Turnover costs spread across recruiting, onboarding, and training budgets
• Lagging, aggregated reporting that obscures what’s actually happening at the point of work

In other words, many organizations are trying to optimize their use of labor without seeing the full labor economy of the enterprise. That’s why so many cost actions disappoint. Leaders cut where they can see spend, not where they can see value destruction.

And those aren’t always the same place.

The real problem isn’t labor vs. performance

Many executive teams still talk about labor and performance as if they’re opposing forces. Reduce labor and performance suffers. Increase labor and margins suffer. It sounds like an unavoidable tradeoff.

The summit discussion challenged that framing.

Andrew Garcia’s questions highlighted a core tension: when leadership tries to optimize their use of labor from the top, what’s it missing on the frontline? Levit and Paradiso’s answer was consistent:

The biggest disconnect isn’t philosophical. It’s operational.

Executives often make decisions using incomplete, delayed, or fragmented information. Frontline managers see the reality of demand shifts, understaffed time periods, overtime habits, and local service strain, but that knowledge doesn’t always translate into trusted, connected, enterprise-level insight.

That gap creates a dangerous dynamic. Corporate leaders think they’re making rational cost decisions. Frontline teams experience those decisions as workload increases, capability gaps, rising frustration, and degraded service. Over time, the business absorbs the consequences in places leadership wasn’t monitoring closely enough.

That’s not just a labor tradeoff problem. It’s a cross-functional decision-making problem.

More technology doesn’t fix fragmented thinking

This is where many organizations make a second mistake. Once they realize visibility is weak, they assume the answer is simply more technology: more dashboards, more point solutions, more pilots, more AI.

But the panel made clear that piling technology on top of fragmentation doesn’t create better decisions. It often creates more noise.

Paradiso emphasized that what matters isn’t just producing data. It’s having confidence that the data is accurate, connected, timely, and usable in the flow of operational decision-making. If scheduling lives in one place, time in another, payroll somewhere else, contingent labor in yet another environment, and analytics are treated as a back-end reporting task, the business is still operating from partial truth.

That architecture doesn’t just slow insight. It undermines confidence. And when leaders don’t trust the data, they go back to blunt controls: freeze spend, tighten approvals, reduce labor, push harder on efficiency.

The underappreciated problem here isn’t that labor is too expensive. It’s that most organizations are still trying to manage workforce economics through disconnected systems, lagging insight, and incomplete visibility.

That’s what produces bad optimization.

The better question leaders should be asking

One of the strongest shifts in the conversation came when Levit argued that leaders need to stop asking, “How do we spend less on labor?” That question is too blunt to produce a smart answer.

A better question is: What is the right level of labor for this volume, in this location, at this time, given the workforce conditions, operational realities, and performance outcome we need?

That’s a materially different frame. It treats labor as something to optimize, not simply minimize. It moves the conversation from backward-looking explanations to forward-looking decisions.

It also creates a more disciplined foundation for AI. Instead of using AI as a broad replacement mechanism, organizations can use it to strengthen forecasting, improve visibility, detect issues sooner, support better operational choices, and augment their existing workforce. But that only works when AI is embedded into a connected operating environment, supported by reliable data, and applied to clear use cases with measurable outcomes.

That point came through clearly from Paradiso as well. Organizations get stronger outcomes when AI moves from isolated experimentation into integrated operational workflows. Innovation alone isn’t enough. Strategy, confidence, and integration matter just as much.

What leading organizations will do differently

The companies that navigate labor pressure best won’t be the ones that cut fastest. They’ll be the ones that see fastest, learn fastest, and adapt fastest.

That requires a different approach to workforce decision-making. It requires leaders to think beyond payroll as the only meaningful labor number. It requires operations and finance leaders to see labor cost in context, as part of a broader system of performance, service, compliance, and adaptability. It requires organizations to surface the hidden costs that fragmented systems and delayed reporting tend to bury.

Most of all, it requires a new operating foundation:
 

• A single view across workforce data
• Real-time insight into schedules, time, pay, and labor trends
• People analytics leaders trust enough to act on
• Continuous payroll visibility instead of retrospective surprises
• AI applied inside workflows, not hovering above them
• A shared data model that lets the business operate from one version of reality

In short, the labor cost problem leaders are trying to solve is often a symptom of something deeper: a fragmented people and operations model that makes true optimization incredibly challenging. Until that changes, many organizations will keep mistaking cuts for discipline and visibility gaps for productivity problems.

Where the conversation should go next

If this diagnosis is right, the next question becomes unavoidable: What kind of workforce foundation helps HR, finance, and operations make labor decisions with more visibility, confidence, and alignment?

That’s where the conversation needs to go next. Leaders need a trusted HCM platform they can use alongside operational and financial context — not fragmented workforce data that makes labor decisions harder than they need to be. And there’s a meaningful difference between stitching together a “unified” experience across separate systems and operating on a truly single, AI-powered people platform with one data model, real-time people analytics, and continuous payroll calculation.

That difference isn’t just technical. It shapes how quickly leaders can see workforce risk, how confidently they can act on labor signals, and how effectively HR can partner with finance and operations around business outcomes.

In an environment where labor pressure, workforce expectations, and operational volatility are all rising at once, the underlying platform matters more than ever. No HCM platform captures every operational or financial signal a business needs. But it should give leaders one trusted, real-time workforce foundation for making stronger decisions about time, pay, scheduling, labor trends, and workforce risk. That’s what helps HR step into the conversation with finance and operations as a more strategic partner. And that’s why the difference between a “unified” experience and a truly single platform deserves a closer look.

If fragmented systems are making labor decisions harder, the next question is what kind of workforce foundation helps HR, finance, and operations work from the same reality.

Read our next blog on the difference between a single HCM platform and an integrated one, and why that distinction matters when leaders need more confidence in workforce decisions.

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