The Five Biggest Challenges in Fleet Planning

Explore five key challenges in aviation fleet planning and how connected digital twin systems help improve forecasting, maintenance, and visibility.

Complete Guide to Challenges in Fleet Planning and Their Solutions

Fleet planners face constant pressure to keep aircraft available, follow maintenance trends, and control costs. A delayed check or part shortage can ground assets and disrupt operations.

Even with advanced systems, coordination between engineering, maintenance, and operations is difficult. Data sits in separate tools, and by the time reports align, conditions have changed. These gaps lead to reactive fixes instead of long-term planning.

A connected approach is helping operators close these gaps. It gives planners a clear view of fleet health, maintenance capacity, and future demand for faster, more accurate decisions.

This article explores the five biggest pain points in fleet planning and how aviation organisations are solving them with digital twin integrated solutions.

Key Insights

• Fleet planners struggle with disconnected systems and reactive processes.

• Digital twins create one accurate, connected view of operations.

• Predictive modelling identifies risks before they cause delays.

• Shared visibility improves coordination across teams.

• Scalable deployment makes adoption faster and measurable.

Understanding Fleet Planning in Aviation

Fleet planning in aviation is more than choosing which aircraft to buy or retire. It’s coordinating maintenance, operations, finance, and regulatory compliance, so each plane in your network is used optimally.

A planner must balance daily demands (scheduling, crew, maintenance) with long-term goals (fleet growth, aircraft lifecycle, cost control). A small delay, like a missing part or engine issue, can quickly affect routes and schedules.

Modern fleets span regions, aircraft types, and regulatory environments. Many airlines still manage this using separate tools and silos of data, which slows decisions, hides risks, and forces reactive responses instead of proactive planning.

Operators are now turning toward integrated planning systems that combine all fleet inputs like maintenance status, capacity, routes, and financial constraints, and allow teams to model scenarios confidently.

This model sets the stage for the five core challenges we’ll discuss next.

The Five Biggest Challenges in Fleet Planning

Every aviation organisation faces its own mix of planning challenges. Factors like fleet size, route structure, and maintenance capacity all add layers of complexity. Yet, some issues appear repeatedly across the industry.

Bridging Short- and Long-Term Planning Gaps

When short-term and long-term planning operate separately, aviation teams spend more time reacting than preparing. Daily scheduling decisions are made without understanding their impact on future maintenance, fleet readiness, or asset value.

This disconnect leads to overlapping schedules, redundant work, and limited resilience when conditions change.

As Thomas Godfrey, modelling specialist at Aerogility, explained, “It’s all about having one system that’s able to do both.” A single, connected system lets planners react to daily issues while improving long-term efficiency and resilience.

• Short-term: Real-time data helps identify and resolve operational issues before they cause delays.

• Long-term: Simulations test strategies to improve performance, reduce redundancy, and build resilience.

Traditional spreadsheet-based methods can’t manage this complexity. Modeling an entire operation manually becomes unsustainable.

Aerogility’s domain-specific AI handles that complexity automatically, using aviation-focused logic to reflect real operational conditions. This allows teams to focus on domain-level decisions while the system manages data and calculations.

Shifting from Reactive to Proactive Maintenance Planning

When maintenance planning is reactive, small problems turn into major disruptions. Unplanned aircraft downtime, schedule delays, and higher repair costs quickly become routine.

Reactive planning happens because decisions focus on what went wrong yesterday instead of what’s coming next. Many legacy systems can’t process the data needed to predict maintenance demand, so teams end up fixing issues after they occur rather than preventing them.

A proactive approach uses data-driven forecasting. By combining real-time operational data with predictive modelling, planners can test outcomes before acting. This helps:

• Spot maintenance bottlenecks early
• Adjust schedules to prevent costly overlap
• Plan realistic fleet growth without overloading resources.

Simplifying Scenario Planning and Forecasting

Scenario planning plays a major role in fleet management, but it’s often one of the most time-consuming tasks for planners.

Testing even a few “what if” situations, such as changing flight rates, adding aircraft, or adjusting maintenance intervals, can take days of manual work. Traditional tools make it difficult to manage this level of detail, limiting how accurately teams can forecast outcomes.

Without reliable forecasting, operators are forced to make cautious or reactive decisions. Small assumptions, like extending maintenance intervals or shifting capacity, can have a major impact months later.

Simulation-based planning simplifies this process by allowing planners to test thousands of scenarios in parallel.

Once data is integrated, teams can:

• Run multiple “what if” analyses at once

• See how changes affect performance, maintenance, or availability

• Experiment safely before implementing changes in real operations

By automating scenario analysis, planners no longer need to gather stakeholders for manual reviews or rely on static models.

Today’s fleet operations generate vast amounts of data across multiple systems, yet much of it remains siloed. Maintenance data sits in platforms like TRAX or AMOS, financial records are stored in procurement and billing systems, and performance metrics live within KPI dashboards. Meanwhile, operations data is often scattered across multiple regional databases and legacy systems, creating fragmented visibility.

These silos make it difficult to gain a unified view of aircraft performance, maintenance trends, and cost drivers. As a result, decision-making is slowed, reporting becomes inconsistent, and opportunities for optimisation are missed.

When information is scattered, planners lose real-time visibility. Reports must be compiled manually from several sources, and by the time the data is complete, it’s already outdated. This forces teams to make decisions based on yesterday’s operation instead of today’s reality.

When planners can see maintenance capacity, operational performance, and financial impact in one view, decisions become faster and more reliable. It helps teams:

• Detect risks or delays early

• Coordinate maintenance and operations efficiently

• Save time spent gathering and checking data.

Creating a Shared Operational Picture for Engineering and Leadership

When visibility is limited, engineering, planning, and leadership optimise for their own goals. Engineering protects airworthiness, planning chases schedule stability, and leadership focuses on cost and risk. Without a shared view, priorities riorities of clash, issues surface late, and decisions stall.

This gap exists because data and decisions live in different systems and forums. Teams see partial truth:

• Engineers cannot see the schedule or budget impact of deferring a task.

• Leadership cannot see the technical risk behind a smooth headline metric.

The right approach is to bring all teams into one model that offers a “top-down view of the entire enterprise.” In aviation, a top-down view means seeing every part of the operation together. It includes maintenance, fleet readiness, and financial impact.

Integrated planning tools and digital twin models already make this possible in aviation. They replace manual reconciliations with one accurate, shared view that helps teams plan together and make faster decisions.

How Aerogility Supports Modern Aviation Operations

Aerogility is a digital twin platform built for aviation fleet planning. It helps operators bring maintenance, operations, and performance data into one connected model. By combining short-term and long-term planning in the same system, Aerogility gives teams a single, accurate view of their entire fleet.

The platform helps planners simulate outcomes, adjust schedules, and make confident decisions without switching between tools or losing data accuracy.

Viewing and Managing Maintenance Plans

Planners can view the complete maintenance plan across depots, aircraft, or components. Each event appears visually, giving teams a clear view of schedules and priorities.

If a delay occurs, Aerogility immediately shows how it affects the rest of the plan. Quick-view indicators highlight late or upcoming tasks, helping teams act before small issues cause disruptions.

Adjusting Schedules with Drag-and-Drop Tools

Aerogility’s drag-and-drop tools make it simple to adjust maintenance events. When a change is made, the system recalculates feasibility and flags any conflicts, such as overlapping work or missing capacity.

This replaces time-consuming spreadsheet work, cutting planning time from days to minutes while reducing the chance of human error.

Tracking Maintenance Yield and Readiness

Aerogility tracks maintenance yield to show how much useful life remains for each aircraft or component. Colour indicators highlight when items are nearing limits, allowing planners to prioritise maintenance and keep aircraft ready for service.

This helps teams avoid over-maintenance, reduce waste, and maximise availability.

Seeing Real-Time Impact of Schedule Changes

Every schedule change updates across Aerogility instantly. Planners can see how adjustments affect readiness, cost, and capacity before finalising decisions.

This instant feedback helps teams make decisions faster and with greater confidence.

Getting Started with Connected Fleet Planning

Here are the key steps to follow when building a connected, data-driven planning process:

Step 1: Identify Current Planning Challenges

Start by reviewing where planning slows down. In most fleets, the main issues are unplanned maintenance, mismatched schedules, and poor visibility across teams.

• Audit where decisions rely on manual data collection.

• Look at how long it takes to update plans after a change.

• Ask planners and engineers which tasks consume the most time.

Visibility into pain points helps define where connected tools can deliver the fastest improvement.

Step 2: Define What Success Looks Like

Set practical goals that reflect how your organisation measures success. Some focus on improving aircraft availability during peak seasons. Others aim to reduce maintenance costs or shorten planning cycles.

Whatever the metric, clarity helps teams align priorities and track results that show real operational value.

Step 3: Map Your Existing Data Sources

Fleet data sits across multiple systems, including maintenance management, flight operations, and financial tools.

• Document where each dataset lives and how often it’s updated.

• Identify which systems hold the most accurate, current information.

• Plan how to connect those sources into one shared model.

This mapping creates a foundation for digital twin planning and avoids duplicate work later.

Step 4: Start Small with Pilot Projects

A pilot project makes digital transformation manageable. Choose one fleet segment or maintenance base for testing.

Run a connected model in parallel with existing processes and track improvements in time saved, accuracy, or decision speed. Early pilots show clear value and make it easier to gain buy-in for broader adoption.

Step 5: Focus on People and Change Management

Connected planning only works when people understand how it helps them. Involve planners, engineers, and analysts early so they can shape how the system fits into real workflows.

Provide short, role-specific training sessions and share quick wins to build confidence. When teams see that the system supports their expertise instead of replacing it, adoption becomes natural and long-lasting.

To see how this works in real-world environments, explore projects completed by Aerogility.

The Future of Fleet Planning

As aviation operations grow more complex, the future of fleet planning lies in connected, intelligent models. Digital twin platforms like Aerogility help organisations move from manual planning to strategic foresight.

Looking ahead, three factors will shape the future of fleet planning:

• Data Quality and Integration: Reliable, unified data is the base for every digital twin. Accurate recordkeeping and regular updates are essential before scaling.

• Knowledge Retention: As skilled engineers retire, digital twins capture their expertise and preserve domain knowledge for future teams.

• Human-Centred AI: Digital twins support decision-makers. They automate manual tasks so planners can focus on strategy and critical choices.

The future of fleet planning will depend on collaboration between people, data, and intelligent models. Operators that invest early in connected planning will improve coordination and build more resilient fleets.

Proven Results with Aerogility

💰$3 million in savings on aircraft parts – A leading airline reduced its spares pool by just one set of landing gear, cutting costs significantly.

📊 Consistent 95%+ planning yield – Another carrier improved efficiency in heavy base maintenance, achieving over 95% planning yield.

🔄 Streamlined planning in just 15 minutes – A major airline reduced its maintenance planning process from weeks to just 15 minutes, transforming operations.

“Aerogility has given us the ability to look into the long-term maintenance planning of our fleet with the capability to not only make a late change to the plan but at the same time understand the impact of that decision operationally and economically.” – Head of Fleet Technical Management, easyJet.