The Real Cost of Expedited Freight in Your Supply Chain

Are Your Emergency Orders a Logistics Problem—or a Planning One?

Key Takeaways

• Emergency orders aren’t a cost of doing business—they’re a planning signal. The frequency of your expedited freight and emergency supplier orders tells you exactly how reactive your supply chain is.
• Top-performing supply chains spend 3% of freight budget on expediting. Bottom performers spend 10%. That gap, multiplied by your annual logistics spend, is your freight cost reduction opportunity—and it’s entirely recoverable.
• 49% of expedite events are caused by inaccurate demand forecasts. That means nearly half your emergency orders are a direct result of a planning problem, not a logistics one.
• Disruptions cost 3–5% of annual EBITDA per event. For a manufacturer or distributor with healthy margins, a single significant supply disruption can represent millions in exposure—and reactive planning makes disruptions more frequent, not less.
• Stockout frequency is the most honest indicator of planning maturity. If your team is dealing with stockouts monthly or more, the root cause almost certainly lives upstream in the planning process.

Your Expedited Orders Are Telling You Something About Your Planning

Five emergency freight orders last quarter. Eight. Twelve. Whatever your number is, there’s a good chance your team has started treating it as background noise. An unfortunate but inevitable cost of operating in a volatile market. Suppliers are unpredictable. Demand shifts without warning. Sometimes you just have to move fast and pay the premium.

Here’s the thing: the frequency of your emergency orders isn’t primarily a logistics problem. It’s a planning problem. And treating it as background noise means you’re paying a recurring tax on a root cause you haven’t addressed.

That tax has a specific dollar value. One that most operations teams haven’t calculated. This column walks through how to quantify your expedite overrun and disruption risk exposure, and what the number typically reveals about the state of your planning process.

The Expedited Freight Benchmark That Should Reframe Your Thinking

APQC’s Open Standards Benchmarking data draws a clear line between top-performing supply chains and bottom performers on expedited freight. Top performers keep expedite spend to 3% of total logistics costs. Bottom performers spend 10%.

That seven-point gap might sound modest. Against real freight spend, it isn’t.

For an operation with $9 million in annual logistics costs, the difference between a 3% expedite rate and a 7% rate is $360,000 per year. At $18 million in freight spend, common for a manufacturer or distributor in a growth phase, the same gap represents more than $700,000 annually.

The spread between your current expedite rate and the top-performer benchmark is your freight cost reduction opportunity. Unlike many supply chain improvements, it’s directly calculable, fully recoverable, and almost entirely within your control to address through better planning.

The Logility Cost Optimizer assessment calculates your expedite overrun by comparing your estimated expedite rate to the APQC top-performer benchmark. The resulting number isn’t hypothetical. It’s a direct calculation of what your operation is paying above and beyond what a well-run supply chain at your scale and freight volume would spend.

Why Demand Forecasting Is Behind Most of Your Emergency Orders

The APQC research includes a data point that should shift how you think about your expedite spend: 49% of expedite events are caused directly by inaccurate demand forecasts.

That means nearly half of your emergency orders aren’t a response to genuine supplier lead time variability, logistics disruptions, or unpredictable demand spikes. They’re a response to a planning signal that arrived too late. A forecast that didn’t anticipate demand accurately enough to trigger replenishment at the right time, leaving your team scrambling to close the gap with premium freight.

If your team handles eight emergency orders per quarter, roughly four of those are preventable with better demand planning. The freight cost is recoverable. More importantly, the signal is clear: your planning system isn’t giving your procurement and logistics teams enough lead time to respond through normal channels.

This is the upstream-downstream connection that gets missed when supply chain problems are diagnosed departmentally. Your logistics team sees an expedite problem. Finance sees a cost overrun. Planning sees a forecast miss. They’re looking at the same failure from different angles. The fix lives in the planning process, not in logistics execution.

Supply Chain Disruption Risk: The Exposure Most Operations Underestimate

Emergency freight is the visible cost of reactive planning. Disruption risk is the latent cost, the exposure you’re carrying whether or not it materializes in any given quarter.

McKinsey’s supply chain disruption research puts a number on it: a supply disruption lasting 30 days or less costs the affected company 3-5% of annual earnings before interest, taxes, depreciation, and amortization (EBITDA). For a manufacturer generating $375 million in revenue at a 12% EBITDA margin, roughly $45 million in EBITDA, a single significant disruption carries a potential exposure of $1.35 million to $2.25 million.

That’s per event.

The Logility Cost Optimizer assessment maps your disruption exposure using your revenue, EBITDA margin, and the frequency of your service failures (stockouts). Operations that report monthly or more frequent stockouts are assigned the higher disruption multiplier because high stockout frequency indicates a supply chain regularly operating at the edge of its capacity to respond, which is exactly the profile that makes disruptions more costly and more likely.

Frequency matters more than severity. The McKinsey framework applies to individual events, but what’s operationally significant is how often your supply chain is in conditions where disruptions become expensive. A reactive operation doesn’t just suffer when disruptions happen. It operates in a permanent state of reduced resilience that makes every disruption more severe.

Stockout Frequency as a Planning Maturity Signal

Of all the inputs in the Cost Optimizer assessment, stockout frequency may be the most honest indicator of where your planning process actually stands.

Quarterly or less frequent stockouts suggest a supply chain largely in control. Exceptions happen, but they’re managed before they cascade. Monthly stockouts indicate a chronic planning gap: your demand signal or replenishment process isn’t reliable enough to keep pace with actual demand variation. Weekly stockouts signal that the planning process is structurally struggling. The supply chain is perpetually reacting to a demand signal it can’t get ahead of.

Running a full stockout cost calculation, one that captures not just lost revenue from the immediate transaction, but downstream customer reallocation and potential share loss, consistently reveals an impact larger than the initial stockout volume suggests. Customers who experience repeated stockouts don’t typically complain, they reallocate. In B2B and retail supply chains, a missed fill creates a downstream allocation decision at the customer level that may not reverse when you’re back in stock. The revenue impact is longer-tailed than a single transaction.

Proactive vs. Reactive Supply Chain Planning: The Financial Case for Change

What ties expedite overrun and disruption risk together is that they both measure the same underlying condition: a supply chain operating reactively rather than proactively.

A proactive supply chain isn’t one that eliminates surprises. It’s one where the planning process is sophisticated enough to anticipate demand variation, flag exceptions before they become crises, and give procurement and logistics teams enough lead time to respond through normal channels rather than emergency ones.

When forecast accuracy improves, safety stock optimization becomes possible. You can right-size buffers based on actual demand variability rather than padding against a model you don’t fully trust. When replenishment triggers are based on accurate demand signals rather than historical averages, you’re less likely to be caught short. When exception management surfaces the right problems to the right people at the right time, your team is resolving issues before they become expedites, not after.

That shift, from reactive to proactive, is what the Logility platform is designed to enable. Connecting demand signals to replenishment and inventory decisions reduces the frequency of situations that generate emergency orders and service failures. This isn’t the result of enterprise-scale transformation that takes years and requires a large consulting team. Most deployments require minimal IT involvement, primarily around data connectivity and user authentication.

Red Wing Shoes experienced this shift firsthand. Facing spreadsheet limitations, forecasting challenges, and lower fill rates, they moved to Logility and reduced inventory across their network, increased fill rates, shortened lead times, and cut their S&OP process time in half. The improvement wasn’t incremental. It was a structural shift from reactive firefighting to confident, forward-looking planning.

Calculate Your Supply Chain Expedite Exposure Before You Discount It

The natural instinct when reviewing expedite costs is to normalize them; compare this quarter to last quarter, note that things are roughly similar, and move on. The comparison that matters is different: how does your expedite rate stack up against what top-performing operations at your freight spend level are achieving?

That’s the calculation the Logility Cost Optimizer assessment runs. Input your quarterly expedite volume, annual freight spend, stockout frequency, and revenue and EBITDA margin—and the assessment returns your expedite overrun against the APQC benchmark and your disruption risk exposure based on the McKinsey framework, specific to your operation rather than an industry average.

Most operations find the number larger than expected. That’s the point.