boosting forecasting precision through machine learning

gateretail is the world’s leading inflight retailer, serving more than 20 airlines and over 300 million passengers annually. Our team has propelled gateretail on its data-driven journey with advanced machine-learning solutions, resulting in a double-digit improvement in forecasting accuracy.

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Inflight retailer's journey into advanced forecasting

gateretail is recognised as a world-leading airline retailer, renowned for its extensive expertise in food & beverage and travel retail. The company is committed to enhancing the flight experience for over 300 million passengers annually with its exceptional offerings on board. Their customer portfolio, which includes Wizz Air, Air Canada, Iberia, and Norwegian, spans four continents and supports a fleet of over 1,000 aircraft.

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gateretail is committed to enhancing both its operational efficiency and customer offerings with cutting-edge digital solutions. To achieve this goal, Supercharge delivered a proof of concept (PoC) for a machine-learning forecasting solution.

Built upon years of sales data to fully understand passengers' preferences, this solution aims to improve forecast accuracy, optimise stock levels, and mitigate business challenges. By implementing this advanced digital solution, gateretail aims to elevate its service quality, operational efficiency, and overall customer satisfaction.

services
data strategy
technology and architecture
data and AI development
deliverables
thorough exploratory data analyses to understand customer behaviour, uncover hidden patterns, and test hypotheses
PoC for a machine-learning forecasting solution

Navigating new horizons with machine-learning solutions

While gateretail had several years of sales history – foundational for machine-learning projects – they lacked a data platform necessary for the implementation. 

To get started, we needed to dive deep into the unique intersection of retail and aviation industries, which involves specific customer purchasing behaviours influenced by many aspects, like the travel purpose or the seasonality of demand. The first step was to analyse the available data to establish a baseline understanding for building the forecasting solution.

Gateratail workflow

Our primary goal was to provide an accurate and easily automated forecasting model seamlessly integrated into the daily operations of the supply chain team.

Our innovative solution introduces a fresh approach to forecasting and leverages a state-of-the-art cloud environment for deployment. This unique combination not only enhances accuracy but also marks a new era of efficiency and adaptability for businesses in modern data-driven landscapes.

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Shaping the future of operations with next-level forecasting 

Transitioning from traditional rule-based forecasting to a machine learning-driven paradigm was a game-changing shift with significant impact. 

The implementation of our solution has led to a double-digit improvement in forecasting accuracy and to a remarkable 10x return on investment, while also directly benefiting operational excellence and customer satisfaction.

gateretail's dedication to a data-driven approach extends beyond short-term gains. We aim to lay the foundation for a sustainable, long-term data strategy. Leveraging data efficiently ensures sustained competitiveness, guaranteeing exceptional service not just today, but well into the future.

This success propels us into the next phase: scaling up the supply chain forecasting PoC solution that will replace outdated methods, ensuring sustained innovation and enhanced performance in the dynamic landscape of data-driven business operations.

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