Artificial Intelligence Puts Airlines & MROs in Control of Their Inventory
This article was featured in the April 2023 edition of MRO Business Today magazine which focuses on the importance of MRO inventory planning.
Inaccurate Information Leading to Massive Lead Times
MRO and airlines are currently experiencing massive lead times when it comes to procuring needed aircraft parts. This means that forecasting and planning are now more important than ever.
On average, airlines face part delays of 60-90 days. Even routine parts are experiencing significant delays leading to AOG and Urgent situations. Some airlines have told us as much as 40% of the AOG team’s demand stems from routine parts demand that couldn’t be delivered on time.
The natural reaction to these long lead times and huge backlogs is for an airline to overstock parts and keep them on hand in the hangar. While this might be considered a means of hedging operational risk, in essence, all you are doing is trading one potential problem for another.
The issue with overstocking parts is that the strategy requires a large upfront amount of capital spend, which is very dangerous considering the razor-thin margins airlines are historically up against when running their business.
Most of the industry is still recovering from the effects of Covid and now navigating through an economic downturn, and airlines either cannot risk spending so much capital or simply don’t have the capital needed to properly overstock parts.
Stay ahead of the game with AI
At the crux of this is artificial intelligence (AI). AI ensures that routine parts are delivered on time and at a good price point by running advanced algorithms in the background while also providing solutions for complex situations that arise.
In order to do this, the maximum number of quotes are collected automatically, ensuring that all business requirements are met, including lead times, part conditions, locations, shipping costs, and any other parameters that must be taken into account.
This technology can help airlines and maintenance organizations to monitor lead times and manage the flow of parts and components through the supply chain. By using real-time data and analytics, they can identify and mitigate potential delays and prioritize the delivery of critical components.
And when problems do arise, this is when the real magic of AI happens. When issues pop up that could cause order delays, the AI is programmed to resource a number of resolutions. For example, switching an order to urgent to ensure timely delivery.
When coupling AI with appropriate data models, powerful forecasting features can be leveraged that enable airlines to see the trends of which parts are drying up in the market or have longer lead times and pre-stock the parts before the parts can impact the operations.
Within these models, many data points are ingested to build an accurate forecast, including historical consumption figures and current market metrics such as parts availability and costs. This way, airlines can implement or improve MRO inventory planning and stay ahead of the curve.
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