Managing supply chain disruptions

The aerospace & defense (A&D) supply chain is under high stress due to the ongoing shortages of labor, materials, and parts. Additionally, major airframers continue to increase production rates with further ambitious rate increases planned. In a recent announcement, Boeing set record 737 production goals to at least 57 planes per month for July 2025, which is a 42% increase compared to the aircraft maker’s December 2023 schedule. The truth is all players are struggling daily to cope with production schedules and the stress is very real. The critical question is how will the supply chain withstand this ever-increasing manufacturing demand while on-time delivery (OTD) performance is slowly decreasing across the industry?

It’s necessary to assess the impact on quality this situation creates as safety production margins erode. Safety production margins are small buffer stock in one’s assembly line that can help prevent disruption if a part is delivered late. It can also be a time buffer in a delivery schedule that can absorb a transportation event, a cargo delay, or customs delay. Late deliveries will likely lead to lower quality levels at the final assembly stage.

A&D executives must continue to create a resilient supply chain with minimal safety margin and no risk of stalling. For quality and OTD for aircraft manufacturing, anything below 100% is critical, even more so if there’s no buffer stock and the supply chain is under stress.

Balancing OTD, OQD

TRIGO’s daily work is to improve supply chain performance and to grow OTD and on-quality delivery (OQD) performance indicators. We manage OTD and OQD for 200-plus large customers, addressing a portfolio of more than 2,000 aerospace suppliers. Access to a wealth of supply chain data offers intriguing insights into original equipment manufacturers (OEMs) and their supply chains that aren’t readily available otherwise.

• OQD represents the percentage of parts delivered in a time period with no quality issues compared to the total number of parts delivered. A 99% OQD means 1% of the parts have a known quality issue.
• OTD is the number of parts delivered on time versus the total number of parts in a given period. A 99% OTD means that 1% of parts are delivered late.

To better understand supply chain disruptions in the U.S. aerospace industry, we extracted and analyzed 18 months of OTD performance (Jan. 22, 2022 to July 23, 2023) from about 500 suppliers in the U.S., pinpointing purchasing orders, items, delays, root causes for each late delivery, and lines of the corrective action plan. Then we created a simple overview.

Overall, the data show suppliers and external forces aren’t the only inhibitors to OTD; the end customer can also be a significant factor. When a supplier is late to supply its end customer, the responsibilities for this perturbation are much more balanced than one would believe. As an industry average, TRIGO observes two-thirds of late delivery events are the responsibility of the supplier in the U.S., while an average one-third (33%) of late deliveries are the responsibility of the end customer. The root causes of these 33% are, by rank in our statistics:

• Change of schedule
• Engineering changes, i.e., product definition maturity
• Manufacturing process changes requested by customer
• Configuration issues
• Late arrival of customer provided material or equipment
• Missing purchase orders
• Zero delay or no date purchase orders
• Late payments

Surprisingly, none of the well-known disruptions (such as manpower, material, machining) are noted. We also found there was always a combination of these root causes, i.e., they don’t appear alone but must be understood as the various symptoms of a larger issue in the supply chain operation. It also shows they can’t be tackled independently.

Breaking the OTD sound barrier

TRIGO’s OTD analysis also shows a noteworthy correlation between supplier performance and customer discipline, as represented in the graph. Each blue dot represents a monthly dataset of a specific supply chain for one customer (usually around 100 suppliers). The blue dot is positioned in (X, Y) coordinates with the following rule, coming from the dataset reduction:

• X axis being the share of late deliveries that are the responsibilities of the customer in percentage for a given month.
• Y axis being the OTD performance, monthly, of the supply chain subset.

We clearly see two clouds of dots:

• Cloud 1 (upper left) shows where the end customer is within the industry average for late deliveries, and OTD are up to 99%.
• Cloud 2 (at right) shows under 85% OTD with customer-induced issues the cause above 70%.

We conclude:

• For customers and suppliers exhibiting a standard industry share of late deliveries around 30%, good to very good OTD is achievable.
• For customers and suppliers having a higher level of customer-induced late deliveries, OTD is average and never exceeds 85%. We named it the “OTD sound barrier” as a reference to the speed of sound as a limit that can’t be exceeded without specific technology.

The following sound barrier rule emerges: If a supply chain experiences more than 30% of delays caused by the end customer, OTD will never exceed 85%.

The major takeaway is the customer’s behavior has a cumulative influence on the supply chain.

The path to better OTD, OQD

The OTD performance of a global supply chain correlates directly with the behavior and timely performance of the end customer. Breaking the OTD sound barrier is possible. By simply improving a customer’s discipline, accountability, and program management, there’s an opportunity to reduce customer-induced late deliveries. The OTD goal is achievable with the existing suppliers, products, and programs.

Although these suggestions may easily be applicable, change management is required to show how internally induced, low performance is a massive problem. Using external experts can be a strong lever to transform the way customers and suppliers behave, to greatly improve partnership performance and better match OTD and OQD to end-customer requirements.

Secondly, OEMs should invest in and embed predictive analytics into their operations with the use of artificial intelligence (AI) and machine learning (ML). If they have a limited number of engineers to manage a large portfolio of suppliers, predictive analytics can help them detect which suppliers will be the most problematic, and then allocate resources accordingly. Without predictive information, OEMs are blocked into a corrective mode, reacting to suppliers’ failures after issues are detected and unable to deploy sustainable improvements because the focus becomes fixing the latest events.

These tech enhancements enable A&D manufacturers to be a step ahead of quality issues and inventory management. The fear, of course, is digital programs may replace workers. The sweet spot is to combine human expertise and deep tech tools to boost production outcomes. In an example from the auto sector, FleetPride, a U.S.-based distributor of heavy-duty truck parts, used data analytics to plan inventory by analyzing past shipping orders, enabling the distributor to set appropriate supply thresholds based on demand. Another advantage is the potential cost savings from eliminating corrective actions.

Given the high improvement potential and the ever-increasing pressure on production rates, OEMs should consider starting with a new situation-awareness paradigm. The power of predictive analytics is evident, no matter the industry or region.

TRIGO Group

About the author: Emmanuel Marquis is executive vice president of Aerospace, Defense, & Rail of TRIGO Group. He can be reached at emmanuel.marquis@trigo-group.com.