April 3, 2025
How to Predict Market Demand for Strategic Aircraft Parts Pricing
Managing strategic aircraft parts is vital to aerospace businesses. There’s continuous pressure to maintain optimal stock levels to anticipate demand, maintain profitability, and remain competitive.
The delicate balancing act is fraught with challenges. With fluctuating demand for air travel and seismic shifts in the industry (due to ESG governance, technology advances, geopolitical events, climate change, and increased demand), companies must leverage new-wave technologies and data analysis to forecast demand, optimize inventory, and align their pricing strategies “just so”.
This article will explore the factors influencing aircraft parts demand, the role of advanced forecasting technologies, and how companies can improve their forecasting methods for major competitive wins in pricing optimization.
Understanding the aircraft parts market demand
Several key factors drive demand for aircraft parts, including technological advancements, evolving airline trends, and persistent supply chain challenges.
Technology advancements
As the aviation industry continues to adopt new technologies, companies are leveraging advanced tools like artificial intelligence (AI) and machine learning to enhance demand forecasting for aircraft parts. AI platforms and predictive analytics tools analyze large datasets from historical trends, fleet data, and market shifts to predict future parts requirements with greater accuracy than older ERP systems and software models.
For example, companies analyzing historical usage patterns with AI can forecast future demand with much greater confidence, stocking the right parts in advance and reducing wait times and stockouts.
AI-based solutions, such as ePlaneAI, predict part needs based on a relentless influx of data, pulling from current trends and past fleet trends, helping companies plan for the future with unrivaled accuracy.
Airline industry trends
Broader airline trends impact the demand for specific parts and advanced inventory systems to manage them.
One growing trend is the demand for automation, particularly in the form of auto-GCAS, or automatic ground collision avoidance systems (Fortune Business Insights: Airborne Collision Avoidance Market).
As airlines adopt more advanced technologies and improve their fuel efficiency, the demand for specific parts related to these innovations has increased. Additionally, the airline industry's push for sustainability is driving the demand for lighter, more fuel-efficient aircraft. This trend, alongside a broader shift toward eco-friendly technologies and components, is shaping the market for aircraft parts. As airlines and their customers prioritize sustainability, parts manufacturers must adapt to meet these new demands, forecasting which parts will be needed in response to these “clean” technological advancements (Fortune Business Insights: Aftermarket Parts Market).
Supply chain challenges
Supply chain disruptions are impacting industries everywhere, with aviation businesses especially being hit hard. The global supply chain has faced challenges such as material shortages, parts shortages, production delays, and logistical bottlenecks—all of which have highlighted the importance of accurate demand forecasting that can proactively identify and address external threats.
One recent report from McKinsey outlines how the aerospace sector has had to adapt to supply chain constraints, which have compounded the difficulties in parts availability.
With delays in production and limited access to certain components, the ability to predict demand accurately becomes even more critical. Companies that can leverage forecasting technologies to anticipate demand and optimize inventory will be better equipped to manage these challenges (McKinsey & Company: To improve your supply chain, modernize your supply-chain IT).
Advanced tools and technologies for forecasting
Today’s aerospace market is fast-paced and, arguably, extremely volatile. Companies are turning to advanced technologies like artificial intelligence and machine learning to better respond to the market’s irrationalities. These latest-wave technologies enable businesses to analyze vast amounts of data (previously dark), identify once-missed trends, and make confident forecasts that improve parts pricing strategies.
Here are some of the key tools and technologies driving demand forecasting in the aircraft parts market.
AI and machine learning
Artificial intelligence and machine learning are transforming the way businesses predict aircraft parts demand. These solutions analyze historical data, current market conditions, and predictive trends to offer real-time insights into parts requirements. Companies using machine learning algorithms can continuously adjust their forecasts as new data comes in, constantly improving the precision of predictions.
ePlaneAI is one such AI platform that allows businesses to predict future demand with unprecedented accuracy—not only for spare parts but also for other procurement activities and company-wide operations. These technologies also assist in automating tasks that would traditionally require human input, such as demand planning and forecasting. Through reduced manual intervention, companies can minimize human error and streamline their operations.
Predictive analytics and big data
Another critical component in demand forecasting is predictive analytics. Armed with big data and expert analytics tools, companies unlock valuable insights into demand patterns and potential market shifts.
These solutions enable businesses to process and analyze large volumes of operational data more than ever before—and from all business sources. Companies can look at customer behavior, market trends, weather patterns, market demand, and past order histories when managing spare parts procurement. With this wealth of information, companies can generate more accurate forecasts and negotiate better cost savings.
Additionally, companies can use these analytics to optimize other facets of their supply chain. Insulating from the risks of over- and understocking, these businesses can leverage predictive analytics and AI to prepare for seismic demand shifts that grind their competitors’ operations to a halt (Fortune Business Insights: Aftermarket Parts Market).
Benefits of advanced forecasting tools
The integration of AI, machine learning, and predictive analytics brings numerous benefits to businesses in the aircraft parts market:
- Improved forecast accuracy: Predictive analytics enables businesses to forecast demand with higher precision, reducing the chances of overstocking or stockouts.
- Cost optimization: With accurate demand forecasts, companies can optimize inventory management and reduce unnecessary storage costs, resulting in better cost efficiency.
- Faster decision-making: AI and machine learning tools allow for real-time analysis of market data, enabling companies to make faster, more informed decisions about parts pricing and inventory management.
- Increased operational efficiency: Automated forecasting tools reduce manual labor and human error, allowing companies to focus on more strategic tasks, such as addressing customer needs and improving product offerings.
With the growing complexity of the aerospace supply chain and increasing demand for aircraft, aircraft parts, and air travel, businesses that utilize these advanced technologies are competitively positioned for operational resilience and market dominance.
Key players and their strategies for pricing
The aircraft parts market is shaped by key players, including original equipment manufacturers (OEMs) and parts suppliers. These companies must collaborate closely to ensure the efficient delivery of parts.
Let’s take a look at how industry giant Boeing and smaller OEMs and suppliers are working together to shape demand-based pricing strategies.
Boeing and its role in pricing frameworks
Boeing plays a central role in setting pricing trends for the aerospace industry, both for new aircraft and for aftermarket parts.
The company’s market outlook and demand forecasts are critical for pricing decisions made by all other airlines and suppliers alike. Boeing regularly publishes its Commercial Market Outlook, which outlines demand for new aircraft and parts over a 20-year horizon, helping to guide pricing expectations for the aerospace sector.
As the largest manufacturer of commercial aircraft, Boeing’s pricing decisions significantly impact the pricing of parts. For example, Boeing’s projections on future aircraft deliveries and demand for specific parts influence how pricing models are developed by parts suppliers and manufacturers. These models are based on a deep understanding of the parts’ usage, lifecycle, and replacement rate (McKinsey & Company: Demand for efficient airplanes remains: An interview with Darren Hulst).
OEM partnerships and supply chain networks
Strong partnerships with OEMs are crucial in setting competitive pricing strategies. Companies like STS Component Solutions leverage OEM relationships to ensure access to high-quality parts while maintaining predictable pricing models. These partnerships help keep high-quality parts available at competitive prices (STS Aviation Group).
Suppliers collaborating closely with OEMs can anticipate more accurate, demand-based production schedules and adjust pricing strategies to reflect market conditions. These collaborations also help minimize stockouts and overstocking issues, leading to more accurate forecasts and stable pricing.
The role of market segmentation in pricing strategy
When forecasting demand for aircraft parts, market segmentation plays a critical role in setting pricing strategies that cater to different types of aircraft, operations, and customers.
Civil aviation vs military aviation
The demand for aircraft parts differs significantly between the civil and military aviation sectors.
Civil aviation typically requires a broad range of parts for commercial airliners, including everything from engines to cabin components. These parts are subject to demand fluctuations based on global travel patterns and economic factors. For instance, air travel disruptions such as the COVID-19 pandemic or geopolitical events impact the demand for replacement parts, as airlines extend the lifespan of their existing fleets to cope with decreased travel demand.
On the other hand, military aviation parts tend to have a more predictable demand, driven by defense budgets, procurement cycles, and geopolitical factors. The parts required by military aircraft often need to meet stricter standards, and supply chains may be more robust in terms of meeting the needs of defense operations. However, military aviation may experience unique challenges, such as the need for highly specialized parts or the rapid introduction of new aircraft models driven by evolving defense requirements (Fortune Business Insights: Aircraft Aftermarket Parts Market).
Technological trends and their segmentation impact
Emerging technologies continue to influence demand in both civil and military aviation.
In the civil aviation sector, airlines are increasingly focusing on fuel-efficient, eco-friendly technologies, such as electric vertical take-off and landing (eVTOL) aircraft and sustainable aviation fuel (McKinsey & Company: Demand for efficient airplanes remains: An interview with Darren Hulst). These advancements are influencing the types of parts that are needed and how those parts are priced. For example, the growing adoption of eVTOLs may require new types of parts that were previously not in demand, opening up opportunities for parts suppliers.
In military aviation, technological trends such as the development of advanced avionics, radar systems, and propulsion technologies are also driving changes in parts demand. Military aircraft often require parts designed for high performance, high durability, and more rigorous safety features. As defense contractors develop new systems, parts suppliers must adapt to these technology shifts and plan for demand accordingly (Deloitte).
Methods for assessing the accuracy of demand forecasts.
There are several methods businesses use to validate the accuracy of their forecasts. Let’s explore more.
Using historical data
One of the most important tools is existing historical data. By analyzing past demand trends, companies can gauge the effectiveness of their forecasting models and make adjustments for future predictions.
While historical facts and figures alone are not enough, if your forecasts vary wildly from past historical trends, something is almost certainly amiss. Historical data is a solid bellwether telling you which way the winds of supply and demand are blowing.
For example, looking at the historical performance of certain aircraft during peak travel seasons or in response to specific global events (like the pandemic) can help refine demand forecasts for similar future events.
Historical data also allows businesses to broadly understand the lifecycles of different parts, how often they need replacement, and how their demand correlates with external factors like airline operations, economic conditions, or fuel price fluctuations (Fortune Business Insights: Aftermarket Parts Market).
Collaborating with OEMs for more precise data
In addition to historical data, collaboration with OEMs (original equipment manufacturers) is key to improving forecast accuracy. Sharing data with suppliers, airlines, and parts manufacturers allows companies to gain more accurate insights into upcoming needs.
OEMs typically have access to detailed information about aircraft production schedules, maintenance requirements, and parts longevity. Incorporating this data into forecasting models helps businesses reduce uncertainty surrounding demand for specific parts and better align their pricing strategies with the actual market need (STS Aviation Group).
Challenges in accuracy and overcoming them
Despite the best efforts to use historical data and collaborate with OEMs, there are challenges. For example, unpredictable global events, such as the COVID-19 pandemic or geopolitical crises, can drastically alter demand patterns. Similarly, shifts in air travel habits—such as the rise of low-cost carriers or the increased demand for cargo flights—can impact parts demand.
To overcome these challenges, companies need agile forecasting methods that can quickly adapt and flex to changing conditions. Real-time data analysis and continuous updates to forecasting models can help businesses stay ahead of market trends and adjust their pricing strategies accordingly (McKinsey & Company: To improve your supply chain, modernize your supply-chain IT).
The future of aircraft parts pricing and demand prediction
For a lasting competitive edge, companies must continually embrace new technologies that allow smarter, leaner operations and demand forecasting. When a large competitor wades in and adopts a new technology, it forces the industry to follow or risk operational obsolescence.
AI and connected real-time data systems are upping the game for everyone in the aviation space. Demand for parts is driven by a range of internal and external factors, which are constantly shifting.
Businesses leveraging AI and machine learning solutions for smarter insights are leading the way and are positioned to remain ahead.
In a high-precision industry, aviation companies that constantly improve their forecasting processes for small (and big) gains day over day can reliably meet customer and market expectations.
Looking to stay ahead of the competition in forecasting and aircraft parts pricing? Partner with ePlaneAI today and take advantage of our cutting-edge predictive analytics tools to optimize your pricing strategy. Don’t miss out—make data-driven decisions that can elevate your business in the evolving aerospace market.
