In 3 steps to sustainable aviation catering with data-driven innovation

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It is no secret that aviation must undergo significant improvements to become drastically more sustainable. This applies not only to airlines, but also to other organizations that play a role in this industry. As a Data Scientist, I analyze the vast amount of data in the supply chain and develop prediction models that contribute to diverse sustainability initiatives. In this blog I would like to take you through a practical example within the aviation sector that illustrates how data-driven innovation can pave the way towards a more sustainable future: Catering on Board within Aviation.

Step 1: Predictive Catering planning

The process starts, before loading the catering, with accurately predicting the number of passengers on board. Through analysis of different phases in catering preparation, we can currently estimate exactly how many meals are needed. This prediction system is now available for both national and international caterers, which greatly aid in preventing overproduction worldwide. The resulting data from this system is then collected, analyzed, and can then be used to further develop efficient catering services. The next step is to broaden the system to estimate more specific beverage loads.

Step 2: Food Consumption Analytics

Once on board, it is crucial to accurately understand passengers’ food consumption behavior. By analyzing data, we tailor both the content and quantity of meals to suit the passengers’ requirements. This not only ensures higher customer satisfaction, but also less waste and therefore a reduction in excess weight on board. Furthermore, insights into food consumption behavior provide valuable input for assessing the range of available products as well as and developing new ones.

Step 3: Waste detection system with AI

After a plane lands, the leftover food is removed, along with the waste. Although a proportion of waste is recycled, it remains a challenge to understand exactly what the waste consists of. Only when you have a better understanding of the waste composition can you take effective measures to reduce it. Manually taking samples and analyzing waste is a time-consuming and difficult job. Moreover, this method is not systematic, as the waste stream is constantly changing.

A very nice solution for this is Computer Vision. With this specific AI technique, you can automatically identify waste into categories. The output of a Computer Vision System can then be used for in-depth analysis of the waste. And these analyses are then a good starting point for formulating actions that further reduce waste.

The benefits and implementation of data-driven innovation

The examples above provides a simple picture of the role that data-driven innovation plays in sustainability. However, implementing them is a more complex process. It not only requires collecting and analyzing data, but also applying advanced techniques and specific expertise. Nonetheless, with the right approach, you as an organization can achieve enormous benefits, such as more efficient use of resources, less waste, lower costs, higher customer satisfaction and smarter solutions. And therefore, make an important contribution to a better world and a sustainable future.

Have you been inspired, and would you like to know more about how your organization can make processes more sustainable with the help of data-driven innovation? Please feel free to contact us. We would be happy to brainstorm with you without obligation.