Navigating the Skies of Change: A Roadmap for Cultivating a Data-Driven Future in Aviation
9/1/23
Transitioning to a data-driven aviation culture is a complex journey. This article provides key steps for change, use cases, and guidance on choosing the right analytics partner to maximize the promise of data-driven decision making.
To fully leverage data analytics, aviation companies must undergo a cultural shift. Developing data-driven operations, changing mindsets, and selecting the right partners are crucial steps for harnessing data insights. Though challenging, this transition enables sustainable gains in efficiency, safety, and strategy across aviation sectors. Transitioning to a data-driven culture involves several essential steps, applicable to organizations of all sizes within the aviation industry.
Embrace Advanced Analytics
An air ambulance operation can use advanced analytics to analyze patient data, flight times, and medical supply inventory to optimize response times and ensure efficient medical care. By utilizing data-driven insights, the operation can make better decisions in real-time, improving patient outcomes and operational effectiveness.
Create a Culture of Data-Driven Decision-Making
A small air cargo company can leverage data to optimize its logistics operations. By analyzing historical shipment data, weather patterns, and transportation routes, the company can make data-driven decisions on cargo consolidation, route planning, and scheduling. This ensures efficient transportation, minimizes costs, and improves delivery timelines.
Apply Data Insights
An example for small to mid-sized companies is utilizing data insights to optimize maintenance schedules. By monitoring equipment performance data, conducting predictive maintenance analysis, and tracking maintenance histories, companies can schedule maintenance proactively. This approach reduces costly equipment failures, ensures operational readiness, and extends the lifespan of critical assets.
Leverage Automation and AI Tools
Small to mid-sized companies can benefit from automation and AI tools to streamline operations. For instance, an executive transport company can automate crew scheduling, route planning, and aircraft maintenance processes using AI algorithms. This frees up valuable resources, reduces manual errors, and enhances operational efficiency.
Harness Predictive Analytics
A non-airline aviation operator, such as a charter flight service, can leverage predictive analytics to optimize flight scheduling and pricing. By analyzing customer demand patterns, historical pricing data, and market trends, the company can adjust pricing dynamically, optimize flight schedules, and offer competitive rates to attract more clients.
Choosing the Right Partner
Selecting the right partner to navigate the complexities of data-driven decision making is crucial for aviation companies. While the terminology may often revolve around AI and ML, it's important to note that companies at various stages of digital transformation may have different data capabilities. The right partner should understand the unique needs and limitations of each company and provide tailored solutions.
Embracing data analytics requires cultural change, investment in technology and careful partner selection. But for forward-looking aviation companies, this shift unlocks immense opportunities for enhanced efficiency, safety, and strategy. With the right guidance and strategic vision, even smaller operators can tap into the promise of data-driven decision making.
Learn more about ESP’s Aviation Solution
AUTHOR
Jay Bynum, Retired Rear Admiral
Jay has decades of operational leadership, aviation expertise, government finance, data analytics, and congressional relations experience. He has served as the Navy enterprise lead for strategic planning & investment, operational analysis, and data analytics & knowledge management. Operationally, his commands included the USS THEODORE ROOSEVELT aircraft carrier strike group, piloting F/A-18 Super Hornets, and leading the Naval Aviation Training enterprise.
About ESP
ESP was created by combining over 20 years of supply chain and logistics expertise with technologists that have focused on the science of location and location analytics, the practice of layering geographic data along with business data to extract valuable insights. The advantage that our customers have with ESP is the ability to access and capitalize on a continuously growing infrastructure that enables more focused location-based analytics, helping the supply chain become smarter. ESP has designed a Space and Time Network which enables data (real-time, historic and near real-time) to be consumed, analyzed, viewed, and translated into action. Critical to our customers’ success, our network enables the analyzation of data sets that are beyond typical supply chain data, resulting in more accurate and actionable information.