US Airlines: XLR and MAX 8 Disruption Rates Lead the Pack

We developed a new model, based on U.S. DOT data, focused on U.S. Airline Operational Performance. It generates a data-rich output with actionable insights. We will update the model monthly, and although DOT data is delayed, we are confident users will get excellent value. The model uses internally developed KPIs and currently has 15 pages. We fully expect this to grow. Feedback is encouraging. The Data It may help readers to download the PDF version of the current model, which provides an overview. This is the current base model, and it is likely to evolve as our other models do. This deliverable aims to give airlines, lessors, banks, and the supply chain a way to see how the US airline fleet actually operates. As we've said before, data has no opinion. The data source is what airlines actually file with the US DOT. Although this is US data, US airlines have such critical mass that what we see here is almost certainly a benchmark for other airlines operating elsewhere. Consequently, airlines operating outside the US benefit from observing these KPIs and using them as benchmarks. US DOT; AirInsight Carrier-Controlled Disruption Rate measures the percentage of an airline's scheduled operations that suffer primary operational failures within the carrier's control, excluding external shocks like severe weather, air traffic control (ATC) ground stops, or airport infrastructure delays. In the model, you might notice that when we break down the data by OEM (we track at the tail-number level), the numbers don't add up. This is because DOT reports canceled flights before an aircraft has been assigned. To see what tail-level granularity delivers, here's what a chart for single-aisle aircraft for 2026 looks like. The model allows you to select my airline and the aircraft model. You can spend hours on this page. 2026 10 11 08 32 33 Fleet Utilization Index (FUI) quantifies the proportion of theoretical maximum capacity that an airline’s active fleet actually spends in operation (active) versus sitting idle. The formula does not automatically filter out broken-down aircraft; instead, it treats unreliability as a drop in productive output relative to total theoretical capacity. Because of how DOT reports its data, we cannot infer whether an aircraft has broken down. US DOT; AirInsight Clicking the + sign in the table opens it to show OEM. For Alaska, it shows Airbus with a higher FUI than Boeing. But then this chart provides the context that explains the reality. US DOT; AirInsight The A321neo fleet (Hawaiian) gets an excellent FUI score, but the fleet is small and has low active hours by comparison. The bigger surprise is Alaska's MAX 8 being in the underutilized quadrant. Schedule Recovery Index (SRI) tracks data showing that for every 100 minutes of initial carrier delay an airline experiences, its network buffers absorb the shock, resulting in only X minutes of downstream ripple. So, higher SRI is worse. We rank SRI as follows: SRI > 1.50 (Critical Fragility): The disruption is magnifying. A single delay triggers an exponential wave of late aircraft arrivals across the network. SRI 1.00 – 1.49 (Linear Ripple):The disruption matches the shock. One minute of trouble equals roughly one minute of late-stage ripple across the fleet day. SRI < 0.70 (High Resilience):The disruption is actively suppressed. The airline's schedule padding, hub station capacity, or spare aircraft routing isolates the problem immediately. Here's an example of Delta's SRI over the past 18 months. This is appreciably better than its peer group. US DOT; AirInsight Delay Amplification Factor (DAF) is the ratio of network delay volatility (Standard Deviation) to average delay performance. It measures how minor initial disruptions magnify into severe, erratic schedule friction across the fleet. Here's how we rank this: Ratio > 1.0: Arrival delay exceeds departure delay. The flight lost more time en route or during turns—the network compounded the delay. Ratio < 1.0: Arrival delay is less than departure delay. Flight crews made up time in the air, or schedule padding successfully absorbed the initial shock. With the caveat that the data reports only US domestic flights, this chart shows how this KPI uncovers something interesting. Delta and United show distinctly different performance on the 767s. DAF helps identify aging models and their impact on networks. US DOT; AirInsight Departure delay is what the aircraft starts its leg with (pushed back late from the gate). Operational Buffer Erosion (OBE) measures whether that delay grew or shrank by arrival (or across the turn). High Departure Delay + High Buffer Erosion: The flight pushed back late and lost even more time (or failed to recover), meaning the incoming delay passed straight through the turn and compounded into the next leg. Low Departure Delay / High Recovery (Low Erosion): Ground crews and schedule padding successfully compressed the turnaround or made up time in the air, "healing" the network. Here is an example of how the 717 is doing at Alaska (Hawaiian) and Delta. The difference is stark. Alaska has replaced its 717s with 737-800s, and Delta is doing the same with A220s. US DOT; AirInsight Ground Padded-Time Utilization (often referred to in airline ops as block-pad or turn-pad consumption) measures how much of the scheduled ground "cushion" built into the timetable is eaten up by operational friction. Airlines build padding into scheduled turn times to prevent a 10-minute arrival delay from cascading into the next leg. Tracking how much of that cushion is consumed tells you exactly where your schedule is too tight—or where you are wasting asset utilization with excess padding. With US airlines' average cost around $110/minute, this is an important number. Here's jetBlue's data. This airline reports the highest pad time. The data suggests it's the A321 that is problem #1. US DOT; AirInsight The charts are part of the deliverable. For some KPIs, there may be more than one chart. Here's an example of a summary, rather than a KPI. US DOT; AirInsight And when we dig into the fleet by type, we see this. The XLR at the top isn't what Airbus wants to see. Then again, Boeing won't like seeing the MAX 8 in second place either. US DOT; AirInsight If you're interested in a tour of the model, please contact us. Every demo we run helps us improve our deliverable.

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